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Ring Mesh Based Multicast Routing Scheme in MANET Using Bandwidth Delay Product Rajashekhar C. Biradar & Sunilkumar S. Manvi

Wireless Personal Communications An International Journal ISSN 0929-6212 Volume 66 Number 1 Wireless Pers Commun (2012) 66:117-146 DOI 10.1007/s11277-011-0329-0

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Author's personal copy Wireless Pers Commun (2012) 66:117–146 DOI 10.1007/s11277-011-0329-0

Ring Mesh Based Multicast Routing Scheme in MANET Using Bandwidth Delay Product Rajashekhar C. Biradar · Sunilkumar S. Manvi

Published online: 6 May 2011 © Springer Science+Business Media, LLC. 2011

Abstract Quality of Service (QoS) support in Mobile Ad Hoc Networks (MANETs) for group communication necessitates design of reliable networks with multicast support mechanisms. Reliable network connectivity among MANET nodes require high quality links that have much less packet drops and reliable nodes considering node mobility and failures. Reliability of a network can be enhanced by designing an end-to-end network pipe that satisfies the required QoS in terms of in-flight packets from source to a destination as well as by using a path comprising of reliable nodes. In-flight packets may be computed by using bandwidth delay product (BDP) of a network pipe. To meet the QoS requirements of an application, BDP should be maintained stable irrespective of vibrant network conditions. In this paper, we propose a BDP based multicast routing scheme in MANET using reliable ring mesh backbone. The scheme operates in the following sequence. (1) Reliable node pairs are computed based on mobility, remaining battery power and differential signal strength. The node pairs also compute BDP between them. BDP of a reliability pair is assessed using available bandwidth and delay experienced by a packet between them. (2) Backbone ring mesh is constructed using reliable pair nodes and convex hull algorithm. Reliable ring mesh is constructed at an arbitrary distance from the centroid of the MANET area. (3) Multicast paths are found by discovering a path from source to each destination of the group with concatenated set of reliability pairs that satisfy the BDP requirement. (4) The ring mesh maintains high BDP on ring links and can recover in case of node mobility and failures. Results show that there is an improvement in terms of end-to-end delay, packet delivery ratio, control overhead, memory overhead and application rejection ratio as compared to the Enhanced On Demand Multicast Routing Protocol.

R. C. Biradar (B) · S. S. Manvi Department of Electronics and Communication Engineering, Wireless Information Systems Research Laboratory, Reva Institute of Technology and Management, Bangalore 560 064, India e-mail: [email protected] S. S. Manvi e-mail: [email protected]

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R. C. Biradar, S. S. Manvi

Keywords MANET · Multicast routing · Bandwidth delay product · Reliable ring mesh · Reliability pair

1 Introduction Mobile Ad hoc Networks (MANETs) do not have fixed infrastructure which makes difficult for nodes in MANET to be connected among themselves for longer duration unless robust mechanisms are available to maintain connectivity. Some of the major problems in MANETs arise due to limited battery power, mobility, unpredictable behaviour of nodes that join and leave the network without any prior information, unreliable and bottleneck bandwidth links and long delays (both propagation and node delays). These problems not only create volatile environment to establish routes but also make existing routes more vulnerable so that either route maintenance cost increases or all the routes are destroyed such that the route recovery is possible through the route re-establishment procedure. The situation aggravates when one thinks of establishing QoS based routes for group communication among its members since required parameters such as bandwidth, delay, jitter and packet loss can not be guaranteed. Thus, stable and robust backbone is essential for routing in MANET to meet the user satisfied QoS guarantees. In recent years, group communication services (such as audio/video conferences, battlefield scenarios and disaster recovery) are gaining significance in societal and emergency needs. MANETs are emerging as a promising commodity in supporting group communication services through multicast techniques in several scenarios where the network infrastructure is either costlier affair to deploy or if deployed, it has been made inoperative by natural disasters (such as earthquakes, tsunami and tempest) or man made activities (such as enemies in battlefields, terrorists, or spies). In such situations, nodes in MANETs communicate to group members by establishing multicast routes that satisfy QoS guarantees. Multicast route establishment and maintenance can be realized through a robust backbone. In this paper, we propose QoS based multicast routing in MANETs with a robust ring mesh backbone. Backbone helps in establishing QoS satisfied multicast routes that use bandwidth delay product (BDP) as QoS metric. BDP is an important parameter in evaluation of MANET routing efficiency since it provides a measure of end-to-end network pipe in multihop networks and is well understood concept in wire-line systems. It helps us to find a sufficient number of in-flight packets to fill the network pipe. However, wireless connectivity in MANETs instigate fluctuating end-to-end network pipe, wherein, it becomes difficult to establish and maintain routes if the routes constructed are not based upon any type of reliability criteria resulting in reduced routing efficiency. The goal of designing BDP based multicast routing in MANET are as follows. (1) For a given number of hops from source to destination, number of in-flight packets is a function of BDP for every hop. (2) Less overheads for recovery of routes if the hop BDP is monitored continuously as compared to re-routing, retransmission and other TCP mechanisms that are based on end-to-end BDP mechanism. (3) Buffer allocation can be made at network level hop-by-hop that reduce losses. (4) BDP based multicast routing along with reliable ring mesh structure provides a robust backbone to achieve the aforesaid goals. 1.1 Related Works As observed from the literature, researchers have explored the possibility of enhancing routing efficiency in MANET through various techniques such as path reliability, path stability,

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route lifetime enhancement and optimum power usage techniques. In this section, we review and analyze some of the related works that throw some light on the proposed scheme. In [1], authors compute BDP and BDP upper bound (BDP-UB) in MANET where only one packet is allowed to be transmitted over a link at any given time. BDP-UB of a path in MANET is the number hops in round-trip. BDP and BDP-UB concept is used to set TCPs congestion window limit in MANET to mitigate TCPs congestion window overshooting problem. The congestion window overshooting problem is stated as follows. TCP’s congestion window should never exceed the paths BDP-UB since BDP-UB is the maximum packet carrying capacity of the path. Beyond this path capacity, no additional throughput can be obtained. The problem of voice application support in multi-hop IEEE 802.11 ad hoc networks proposed in [2] uses reactive, non-intrusive based method for calculating QoS metrics (such as bandwidth, delay and packet loss) to support voice communication. IEEE 802.11 supports voice application under light network traffic and when network traffic is heavy, delay and packet loss become significantly high due to hidden node problem. The hidden route problem (HRP) and hidden multicast route problem (HMRP) addressed in [3] are avoided in bandwidth-satisfied multicast trees for QoS applications. HRP arises when a new flow is permitted and bandwidth consumption of the hosts in the neighborhood of the route is computed and HMRP arises when multiple flows are permitted concurrently. The protocol aims at minimizing number of forwarders so as to reduce bandwidth and power consumption. Low-overhead due to node localization improves reliability of routes using link durability routing protocol (LDRP) given in [4]. LDRP selects links with highest durability estimated using local information and avoids periodic global exchange of network information. Level of reliability are found under two cases: (1) when a node localization was obtained from GPS (Global Positioning System) receivers and (2) when a sensor network having information such as location of sensors, sensor density and sensor communication patterns that may impact accuracy of the localization information. With the knowledge of packet flows, LDRP monitors existing paths and takes preventive or corrective actions to deal with the arbitrary mobility of nodes and avoid path breaks. The review article presented in [5] discusses works on resolving QoS issues in MANET focusing on common difficulties such as mobility, limited bandwidth and power consumption. The work given in [6] minimizes the control and data overhead for mesh based multicast routing. The mean link duration metric is defined to construct multicast mesh with overhearing technique that forms a fish bone structure. Each mesh member chooses its forwarding node independently in a distributed fashion based on its own perceived network conditions to provide a trade off between reducing data overhead and achieving multicast reliability. The work given in [7] proposes query packet formulation (containing source id, sequence number, next sequence number, hop count and the time interval needed to send next query packet) to reduce control overhead. The query packet is sent by multiple sources and are processed by intermediate nodes and receiver nodes. In [8], a stable and delay constrained QoS routing protocol (SDCR) for MANET is proposed that makes routing decisions according to link state and dynamic delay detection. End-to-end path stability and path lifetime are found using stable link mobility model to obtain higher link stability paths constrained by maximum delay, in the route discovery phase. A longer lifetime path is selected for data transfer. In route maintenance phase, it keeps monitoring network topology changes by delay prediction mechanism and performs rerouting before current path becomes unavailable and thus there is a significant improvement in routing performance that guarantees the required QoS. In [9], the received signal strength is continuously assessed based upon newton interpolation polynomial which selects middle values out of several sample values. Link lifetime is

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estimated with a mobility model that provides independence of link lifetime on the relative movement direction and velocity of nodes. The sampling policy is derived with reference points calculated from newton interpolation polynomial. Using this mechanism, source node discovers route hop-by-hop to calculate the maximum link lifetime and proposes On-Demand Routing Protocol based on Link Duration Estimation (ODLE). The work given in [10] proposes a routing algorithm called link failure prediction QoS routing (LFPQR) that predicts the future state of a node to decide whether the node is a good candidate as a router, i.e., downstream node decides whether the upstream node is a good candidate for selection as a router. The future prediction depends on the mobility and power level of the node. The protocol selects more stable paths and hence QoS requirements are satisfied. In [11], authors propose partial multipath routing algorithm with parallel packet redundancy mechanism in MANET in which the link lifetime estimation predicts lifetime of links in the route establishment procedure without the aid of additional positioning equipments and extra control messages. Starting and ending nodes are set as relay nodes that are responsible for sending some packets of primary path to secondary path and recording the sequence number of such packets. Parallel packet redundancy method has been employed to transmit packets along multipaths simultaneously, the relay nodes send out the redundant packets along secondary path after the redundancy threshold, which can compensate the packet loss and enhance the end-to-end path reliability. EraMobile (Epidemic-based Reliable and Adaptive Multicast for Mobile ad hoc networks) is presented in [12] that supports group applications requiring high reliability. The protocol delivers multicast data reliably with minimal network overhead under dynamic and unpredictable topology changes due to mobility. Multicast routing is created without the help of traditional approaches such as maintenance of tree or mesh-like structures with global or partial view of the network and information. It eliminates redundant data transmissions and adapts to varying node densities delivering data reliably in both sparse networks (where network connectivity is prone to interruptions) and dense networks (where congestion is likely). The work given in [15] proposes a scalable admission control framework known as Contention-aware Admission Control Protocol (CACP) to support QoS in ad hoc networks. It presents methods to achieve contention aware admission control on a single channel that includes node information inside carrier-sensing range and outside transmission range during admission control process. Friend Management Algorithm (FMA) given in [16] selects stable neighbors in urban areas that exploits the knowledge of urban mobility. The link metrics are determined by residence time of neighbors within the wireless range to find stable nodes and filters out unreliable nodes considering the characteristics of urban mobility, thereby friends could sustain friendship for a long time. Friendship of nodes leads to better QoS information sharing among neighbors in improving stability of networks by applying FMA to the OLSR multi-point relay (MPR) generation. Reliable multicast transport protocol for MANETs presented in [17] recovers data from various types of losses using Reliable Adaptive Congestion controlled Transport protocol (ReACT) which combines source-based congestion-and error control with receiver-initiated localized recovery. The work given in [18] proposes a mesh-based multicast routing scheme that finds stable multicast path from source to receivers. The multicast mesh is constructed by selecting stable forwarding nodes (SFN) using route request and route reply packets with help of multicast routing information cache (MRIC) and link stability database (LSD) maintained at every node.

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The signal stability-based adaptive routing (SSA) is proposed in [19] that monitors the signal strength of neighbour nodes. When a node receives a packet, the regulated value of the signal strength is stored in the signal strength table. If signal strength value of the neighbour node exceeds a predefined threshold, the link from the neighbour is considered as stable link. The work given in [20] proposes advanced signal strength-based link stability estimation model (ASBM) that utilises the differentiated signal strength of a neighbor node to assess link stability with that node. It also compares ASBM with two link stability estimation models: (i) signal strength-based link stability estimation model (SBM) that uses received signal strength model of a neighbor node proposed in SSA and (ii) pilot signal-based link stability estimation model (PBM) that is presented in ABR [21]. ABR maintains pilot signal counter table at each node. The counter table is updated whenever a node receives pilot signal. All nodes periodically broadcast pilot signals with the senders ID. The node that receives the pilot signal from a link increases the pilot signal counter of the link. The pilot signal counter is reset if no signal is received for a certain time period. If the number of consecutive pilot signals for a link exceeds certain limit, the link is considered as stable. Among three models, ASBM finds a route that has the longest lifetime with link increase in hop length. The work given in [22] characterizes the performance of multicast protocols over a wide range of MANET scenarios. In [23], each node in MANET determines the trustworthiness of the other nodes with respect to reliable packet forwarding by combining first-hand trust information obtained independently of other nodes and second-hand trust information obtained via recommendations from other nodes. In on-demand multicast routing protocol (ODMRP) [24], a source floods request packets periodically and receiver responds to the packet by using backward learning. The nodes on the path from the receiver to source form a mesh of forwarding nodes. Advantage of ODMRP is that it produces high packet delivery ratio under mobility conditions since it reduces the overhead due to re-establishment of routes under route failures. Disadvantage of ODMRP is the growth of control overhead with network size. Enhanced ODMRP with Motion Adaptive Refresh (EODMRP) given in [25] presents an enhancement of ODMRP with refresh rate dynamically adapted to the environment. An additional enhancement is the inclusion of unified local recovery and receiver joining. On joining or upon detection of a broken route, a node performs an expanding ring search to graft to the forwarding mesh. Other mesh-based protocols include forwarding group multicast protocol (FGMP) [26], core assisted mesh protocol (CAMP) [27], location-based multicast protocol [28], and dynamic core-based multicast protocol (DCMP) [29]), Dynamic Counter-Based Forwarding Scheme for ODMRP (CODMRP) [30] and Resilient On Demand Multicast Routing Protocol (RODMRP) [31]. The works mentioned above do not consider QoS metric as BDP for multicast routing in MANETs based upon backbone ring mesh designed with reliability pair concepts. The proposed scheme employs the number of in-flight packets in end-to-end network pipe through stable ring mesh backbone to estimate multicast routing efficiency, hence satisfies the QoS requirement of a multicast group. 1.2 Our Contributions The proposed BDP based multicast routing scheme using reliable ring and reliability pair is motivated by observing the inherent drawbacks of existing multicast routing schemes since they do not support QoS and are less robust to link failures, node failures, node mobility, low reliability and scalability. The work given in this paper is an extension of our previous work given in [32] which was not supported with validation of the scheme and performance analysis and also it lacked detailed formulation of components of the scheme. This paper

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provides an extension to the work by providing detailed functioning of the scheme, examples and simulation based performance analysis. The scheme operates in the following sequence. (1) Reliable node pairs are computed based on mobility, remaining battery power and differential signal strength. The node pairs also compute BDP between them. BDP of a reliability pair is assessed using available bandwidth and the delay experienced by a packet between them. (2) Backbone ring mesh is constructed using reliable pair nodes and convex hull algorithm. Reliable ring mesh is constructed at an arbitrary distance from the centroid of the MANET area. (3) Multicast paths are found by discovering a path from source to each destination of the group with concatenated set of reliability pairs that satisfy the BDP requirement, and (4) The ring mesh maintains high BDP on ring links and also it has the capability of recovering from node mobility and failures. Our contributions in this paper are as follows. (1) Defining reliability pair and constructing reliable ring mesh (that acts as backbone for multicast routing) at an arbitrary distance from the centroid of network area using convex hull algorithm and reliability pair concept. (2) Developing a bandwidth model to compute the total available bandwidth between reliability pair using probabilistic model. (3) Developing delay model to compute total delay a packet experiences between reliability pair using Little’s theorem [33]. (4) Developing bandwidth and delay models to find bandwidth delay product of a reliability pair. (5) Establishing multicast routes from source to destinations through the reliable ring mesh backbone and bandwidth delay product of each link. Multicast routes are discovered using concatenated set of reliability pairs from source to destinations through the ring mesh backbone, and (6) Designing a route maintenance procedure to handle node and link failures.

2 Reliable Ring Mesh Backbone Construction Reliable ring mesh acts as backbone for multicast routing in MANET. Reliable ring mesh is defined as the mesh structure of connected nodes in a MANET, constructed at an arbitrary radial distance from the centroid of a given area, within which, all the MANET nodes are assumed to be located. The arbitrary radial distance is chosen as 23 rd of an average distance from the centroid since a ring drawn at this radial distance approximately divides the total area into two equal halves such that one half of the area is within the ring and the other half of the area lies outside the ring but within the convex hull boundary. This assumption is made for the random distributed topology where one half of the nodes are probably distributed within the radial distance and the other half of the nodes are distributed outside the ring. In this section, we begin with the construction of reliable ring using convex hull algorithm and the computation of reliability pair factor. The construction of reliable ring mesh backbone using reliability pair factor is discussed in Sect. 2.2.2. 2.1 Reliable Ring Construction Using Convex Hull In order to create a reliable backbone, we need complete topological knowledge of a MANET. The complete topological information can be obtained only if we know the boundary formed by all the nodes of a MANET. The boundary of MANET area is found by using Jarvi’s March Gift Wrapping convex hull algorithm from computational geometry [14]. Once the boundary of the MANET is known, the area and centroid of the MANET can be found which helps in construction of reliable ring backbone. To decide an arbitrary distance from the centroid, we use convex hull algorithm and reliable node pair concept. The boundary of the nodes of MANET and its centroid is found by using similar concepts used in works [34,35]. The

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Fig. 1 Angle calculation to create convex hull

R(x2,y2)

Q(x1,y1)

T S P(x0,y0)

connectivity among the ring mesh nodes forms a mesh structure that lie in a narrow strip of the ring at an arbitrary distance from the centroid. Ring mesh reduces the overhead of route establishment since a group member is connected to ring mesh nodes with few number of hops; whether a node is located either inside or outside the ring. Ring mesh backbone helps in establishing the routes with stable link connectivity using reliable pair. In this section, we discuss a preliminary idea of forming a reliable ring using reliability pair that is designed with the knowledge of battery power of nodes, euclidean distance between the nodes and differential received signal strength. The reliability pair with better value of reliability pair factor (denoted as FR P , discussed in Sect. 2.2) is used to construct the reliable ring mesh backbone. To understand the topology and thus to find the boundary covered by MANET nodes, we assume that the nodes on the boundary are in each other’s transmission range. Jarvi’s March Gift Wrapping convex hull construction algorithm begins at any extreme node. On this extreme node, the algorithm either selects a neighbor node that makes minimum angle with negative x-axis if it traces in clockwise direction or selects a neighbor node that makes a maximum angle with negative x-axis if it traces in anti-clockwise direction. Since every node is assumed to be aware of its location information through GPS (Global Positioning System), the algorithm begins at one of the extreme nodes with the knowledge of its location information (found through its coordinate values). For example, let us consider an extreme boundary node P(x0 , y0 ) that has two neighbor nodes Q(x1 , y1 ) and R(x2 , y2 ) as shown in Fig. 1 for the construction of a convex hull. The angles S and T at node P(x0 , y0 ) on the bottom line is shown with respect to negative x-axis and the angles are calculated by Eqs. 1 and 2, respectively. |y1 − y0 | |x1 − x0 | |y2 − y0 | T = tan −1 |x2 − x0 | S = tan −1

(1) (2)

The angles correspond to two extreme neighbors on negative x-axis. Suppose we wish to calculate an angle at node P(x0 , y0 ) that is assumed to be a beginning node to initiate convex hull formation on all the boundary nodes. The angle at P(x 0 , y0 ) selects a neighbor node Q(x1 , y1 ) as it makes minimum angle S rather than neighbor node R(x 2 , y2 ) which makes an angle T with the condition that S < T if traced in clockwise direction. This procedure is repeated at node Q and its next boundary node (tracing all the boundary nodes) till it reaches to the original node P(x0 , y0 ) through opposite direction. Thus, the convex hull is created. The convex hull for an arbitrary topology of nodes is shown in Fig. 2. The convex hull algorithm does not terminate even if nodes form a concave shape. This may happen due to node distribution and range of transmission of each node.

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Fig. 2 Convex hull and reliable ring for random node topology

Convex Hull Non−Group Nodes

Fig. 3 Area and centroid calculation

Group Nodes

(x2,y2) (x1,y1)

(x3,y3) Centroid

(x0,y0)

(x5,y5)

(x4,y4)

Once the convex hull is created, reliable ring is constructed that serves as a backbone for multicast routing. Reliable ring creation is initiated based on two assumptions, (a) establishing a reliable ring that should be located at 23 rd of an average radius from the centroid so as to be reached by all the nodes with minimum hop distance (may be two or three or depends on node population and node spreading), whether they are either towards the centroid or towards the boundary nodes on the convex hull, (b) this ring is established by connecting links formed by reliability pairs that have non-zero FR P estimated by Eqs. 22 and 23 given in Sect. 2.2.1. The reliable ring creation process includes the following, (a) calculation of an arbitrary centroid for convex hull, (b) finding an average distance from extreme nodes to the centroid, (c) fixing a node (reliable ring node) nearer to 23 rd of an average distance between the centroid and boundary nodes and finding its neighbor with non-zero FR P located at a distance from the centroid and extreme node, and (d) joining all such reliable ring nodes. The process of calculating the area and centroid of convex hull is as follows. Arbitrary centroid is calculated by finding the area of convex hull [13]. For example, let us consider a convex hull polynomial formed by six nodes with their coordinate values given by (x0 , y0 ), (x1 , y1 ), (x2 , y2 ), (x3 , y3 ), (x4 , y4 ) and (x5 , y5 ) as shown in Fig. 3.

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Fig. 4 Reliable ring formation

Centroid

2/3 of

d av Reliable ring

Convex Hull

Non−Group Nodes

Group Nodes

The area A and centroid C of the convex hull with N number of nodes are respectively given by Eqs. 3 and 4. A=

N −1 1 (xi × yi − xi+1 × yi ) 2

(3)

i=1

C = (x , y ),

(4)

where x =

N −1 1 (xi + xi+1 )(xi × yi+1 − xi+1 × yi ) 6A

(5)

N −1 1 (yi + yi+1 )(xi × yi+1 − xi+1 × yi ) 6A

(6)

i=1

y =

i=1

Once the centroid C is obtained, the average value of radius Av.Radius is given by Eq. 7. Av.Radius =

N 1 (xi − x )2 + (yi − y )2 N

(7)

i=1

We find the average radius (Av.Radius) of a convex hull and construct reliable ring at an arbitrary distance (dav ) measured from centroid of the convex hull. It is given by dav = 23 × Av.Radius. All the nodes at dav are joined together to form a reliable ring as shown in Fig. 4. 2.2 Reliability Pair Reliability pair is defined as a set of two nodes and a link connected between them. Link connectivity is a function of power level of two nodes involved in communication, distance between them, mobility status of nodes and differential signal strength. Reliability pair helps

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us to design the reliable ring and BDP based paths. Reliable ring helps us to create a reliable backbone through which we can establish BDP based multicast routes in MANET. The neighbor node selection is achieved by a reliability pair by computing reliability pair factor. In this section, we explain the procedure for neighbor node selection to form a reliability pair that helps in construction of reliable ring backbone in MANETs. 2.2.1 Computation of Reliability Pair Factor We use reliability pair factor (FR P ) which is proportional to the ratio of differential power received at a node and minimum battery power of nodes in reliability pair to the distance between them. In this section, we discuss the procedure to compute the FR P in order to select neighbor node and construct a reliability pair in MANET. The procedure involves following sequence of operations: (1) Power model of nodes to form reliability pair for neighbor node selection is defined. (2) Mobility model is augmented by noting the change in each node’s location along with the initial and final velocities. (3) Differential signal strength received at a node is calculated using received signal strength of neighboring node and (4) Reliability pair factor is calculated based on the models created in steps 1–3. Power Model In order to compute FR P , we need the knowledge of remaining battery power of a node. The battery power model is as follows. If F is the full battery capacity of a node, then the remaining battery power of a node i at time t (Wi r em (t)) is given by Eq. 8, Wi r em (t) = Wi r em (t − 1) − P × B(t − 1, t) − PI (t − 1, t)

(8)

where P is the power required to transmit a bit, B(t − 1, t) is the number of bits transmitted from time t − 1 to t and PI (t − 1, t) is the power required to perform node i’s internal operations for the duration t − 1 to t. At t = 0, Wi r em (t) = F. It is assumed that the remaining power of a battery lies in two ranges based on power ratio defined by Eq. 9. Power ratio =

Wi r em (t) F

(9)

such that Wi r em (t) of node i is either in Low range or in H igh r ange, as given in Eq. 10. Low range if 0 < Power ratio < 0.1 Wi r em (t) = (10) H igh r ange if 0.1 < Power ratio ≤ 1 The ranges of Wi r em (t) of node i helps us to decide transmission power and connectivity status of reliability pair nodes. For example, if the node power is in low range, there may be less possibility of connection to its neighbor node and thus the node does not qualify to be a part of reliability pair. The transmission power will be adjusted to keep the node power (battery power) draining to minimum so as to provide longer network life time. On the other hand, if the node power is in high range, transmission power of the node may be increased to cover far away nodes. Mobility Model Let initial positions of nodes i and j have coordinate values (x1 , y1 ) and (x2 , y2 ), respectively. Nodes i and j move with variable velocities in a particular direction making angles

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(x1’,y1’) d1

d (ij, t)

j

(x2’,y2’)

i

d2

v2

v1

2

j

(x2,y2)

1

(x1,y1) i

d (ij,0)

Fig. 6 Finding new coordinates after mobility

(x1’, y1’)

d1

d1sin

1

1 (x1, y1)

d1cos

1

φ1 and φ2 with respect to positive x-axis respectively, i.e., node i moves a distance d1 and node j moves a distance d2 in duration from T = 0 to T = t. At time T = t, after mobility, nodes i and j move to new positions (x1 , y1 ) and (x2 , y2 ), respectively as shown in Fig. 5. Initially, at time T = 0, nodes i and j are at positions (x1 , y1 ) and (x2 , y2 ) with an euclidean distance, d(i j,0) , between them as given in Eq. 11. d(i j,0) =

|x1 − x2 |2 + |y1 − y2 |2

(11)

In realistic scenario, a node may not move with constant speed, instead, it moves with a variable speed in a particular duration. Distances traversed by nodes i and j are functions of their initial and final velocities for a given duration. This is necessary to account acceleration and deceleration of nodes at the beginning and end of mobility. Let vi s , vi f , v j s and v j f be the initial and final velocities of nodes i and j, respectively. The distances d1 and d2 traversed by two nodes at time T = t are given by Eqs. 12 and 13, respectively. (vi s + vi f ) × t 2 (v j s + v j f ) × t d2 = 2 d1 =

(12) (13)

At time T = t, node i moves a distance d1 in direction φ1 to a new location (x1 , y1 ) as shown in Fig. 6. In terms of velocities (vi s , vi f , v j i and v j f ) and time (t), the values x1 and y1 are given by Eqs. 14 and 15, respectively. (vi s + vi f ) × t cosφ1 2 (vi s + vi f ) × t y1 = y1 + sinφ1 2

x1 = x1 +

(14) (15)

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Similarly, when the node j moves a distance d2 in direction φ2 to a new location (x2 , y2 ), the coordinate values of new position x2 and y2 are given by Eqs. 16 and 17, respectively. (v j s + v j f ) × t cosφ2 2 (v j s + v j f ) × t sinφ2 y2 = y2 + 2

x2 = x2 +

(16) (17)

At time T = t, nodes i and j move to new locations (x1 , y1 ) and (x2 , y2 ), respectively, and the new distance between two nodes (d(i j,t) ) is given by Eq. 18. d(i j,t) = |x1 − x2 |2 + |y1 − y2 |2 (18) Differential Signal Strength Model Differential signal strength [7] is the difference of two signal strengths received at a node by its neighbor node in two different times. This signal is measured at a receiving node. Let S( j,0) and S( j,t) be the signal strengths of node j received at node i at two different times, T = 0 and T = t, respectively. The differential signal strength, D iS( j,t) , measured at node i at T = t is given by Eq. 19. D iS( j,t) = S( j,0) − S( j,t)

(19) j

Similarly, the differential signal strength of node i, D S(i,t) , measured at node j at time T = t is given by Eq. 20. j

D S(i,t) = S(i,0) − S(i,t)

(20)

Intuitively, from Eqs. 19 and 20, we can define a single measure D S for differential signal j strength D iS( j,t) and D S(i,t) assuming full duplex symmetrical link between nodes i and j. D S gives a measure of node mobility, i.e., if the nodes are moving away from each other, D S is negative and if the nodes are moving towards each other, D S is positive as given in Eq. 21. ⎧ if S(i,0) < S(i,t) ⎨ −ve if S(i,0) > S(i,t) D S = +ve (21) ⎩ unchanged if S(i,0) = S(i,t) Reliability Pair Factor The successful transmission of packets is directly proportional to the minimum power level of either of the node pair and inversely proportional to the distance between them and differential signal calculated at either of the node pair. We define FR P to account successful transmission between the nodes using above discussed models. FR P at time T = 0 and T = t is given by Eqs. 22 and 23, respectively. Min(Wi r em , W j r em ) + D S d(i j,0) r em Min(Wi , W j r em ) + D S =K d(i j,t)

FR P = K

(22)

FR P

(23)

where K is a proportionality constant.

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From Eqs. 22 and 23, we make following observations. Observations assuming node power remain constant: (1) FR P is maximum when the nodes are stationary and reduces with node’s mobility. (2) When one of the nodes moves out of its coverage area, distance measure d(i j,0) or d(i j,t) becomes ∞ and thus FR P = 0. (3) When both nodes remain stationary for a period of time T = 0 to time T = t, then FR P remains same since d(i j,0) = d(i j,t) . (4) When any one of the node is moving and other one is stationary, FR P reduces. (5) D S becomes negative and decreases FR P when nodes are moving away from each other and D S becomes positive and increases FR P when the nodes are moving towards each other. Observations assuming nodes are sending packets while moving: (1) FR P is an equilibrium function of three parameters: minimum power level of nodes, the number of packets transmitted and the distance covered by nodes. (2) For every packet transmission, the remaining battery power of a node reduces. (3) The average differential signal strength decreases with increase in distance and node movement. (4) When a node moves away while sending packets, the node power is decreased. Equations 22 and 23 are used to find FR P between neighbor nodes that are employed in establishing BDP based multicast routes through reliable ring mesh as discussed in Sect. 2.1. 2.2.2 Reliable Ring Mesh A node (located at an approximate distance dav from the centroid of the convex hull) identifies its neighbors to initiate ring mesh construction. Neighbor node parameters collected from this node are: remaining battery power W r em , distance between the node and each of its neighbors and received differential signal strength from each of the neighbors. Reliability pair nodes with non zero FR P that lie in a narrow strip (one hop) of ring structure nearer to higher FR P node form a ring mesh structure. The ring mesh is formed under following two conditions. (1) There exists more than one parallel reliability pair (parallel reliability pair means the pair formed with either two distinct nodes or with one of them as a common node) at an approximate distance of dav from the centroid with non-zero FR P , then all such pairs become valid ring mesh links. (2) Existence of more than one reliability pairs formed with a same node located at dav from the centroid and (3) when a node moves towards the ring having non-zero FR P with ring nodes, the node gets connected with ring node and thus forms a ring mesh. The ring mesh construction using reliability pair operates in the following phases: (1) define and augment reliability pair, (2) compute reliability pair factor of reliability pair using power model, mobility model and differential signal strength model, (3) use convex hull algorithm to find the boundary covering all MANET nodes in an area, (4) find centroid and average distance between centroid and boundary nodes of a convex hull, (5) on a node located at approximately 23 rd of average distance from centroid (where the strip of ring mesh is going to be constructed), find reliability pair factor with those neighbors that are located in the strip of a ring mesh, (6) repeat step 5 at selected neighbor, (7) repeat steps 5 and 6 till it forms a ring structure at 23 rd of average distance from the centroid of convex hull, (8) repeat steps 5 to 7 for varying values of reliability pair factors so that a reliable ring mesh is formed as backbone. For example, Fig. 7 shows the ring mesh formation. The ring node i identifies its neighboring ring node among nodes [ j, k, l, m, n, o] with reference to the centroid C. At node i, the FR P values corresponding to each neighbor are [3.42, 1.65, 3.17, 0.39, 3.36, 2.07]. Among two nodes n and o at an approximate distance of dav from centroid, node n is selected as one of the reliability pair nodes since it has FR P = 3.36. The reliability pair [i, o] is also located

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Fig. 7 Reliable ring construction using reliability pair

k

FRP=1.65

l FRP=3.17

Reliability Pair

F

RP

i

FRP=0.39

= 3.42

j

m FRP=3.36

FRP=2.07

C Centroid

o

n

Fig. 8 Reliability pair: after mobility

k

FRP=1.65

l FRP=3.17

FRP=3.27

FRP=3.42

i

FRP=0.39

j’

j

m

n

FRP=2.07

FRP=3.36

C Centroid

o

near to reliability pair [i, n] and it becomes another reliability pair since FR P = 2.07 and the two reliability pairs form a ring mesh structure. On the other side of node i, a node pair i and k with FR P = 1.65 becomes a part of reliable ring since node k lies at an approximate distance of dav . Even though the reliability pair [i, j] has higher value of FR P (i.e., 3.42), it is not a part of ring mesh since node j is not located at an approximate distance of dav from the centroid. Suppose, node j moves in a direction towards the node k and after certain time, node j moves to a new position j where FR P reduces to 3.27 for a pair [i, j ] as shown in Fig. 8. Since node j moves nearer to node k and now it is at an approximate distance of dav from the centroid, the reliability pair [ j , i] becomes a part of reliable ring along with existing reliability pair [k, i] for that section of reliable ring, thus forming a ring mesh. Finally, the node pairs [i, n], [i, o], [i, k] and [i, j ] become part of a ring mesh. Typical reliable ring mesh is shown in Fig. 10 (discussed in Sect. 3).

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3 BDP Based Multicast Routing Using Ring Mesh Backbone The bandwidth delay product (BDP) is an important parameter in the evaluation of MANET routing efficiency. The BDP is a well understood concept in wire-line systems since BDP provides a measure of number of packets in end-to-end network pipe in multi-hop networks. It helps to define a sufficient number of in-flight packets to fill the network pipe. However, the wireless connectivity in MANETs instigate fluctuating end-to-end network pipe, wherein, it becomes difficult to establish and maintain the routes, if the routes constructed are not based upon any type of reliability criterion resulting in reduced routing efficiency. Since wired network infrastructure provides reliable connectivity between the nodes, the BDP based routing design becomes simple to allocate enough number of resources that maintains required number of end-to-end in-flight packets in a virtual network pipe. This requires the design of transport layer protocols that only do look into optimizing the sending and receiving windows to improve number of in-flight packets in end-to-end network pipe. Because of very nature of network node stability, the protocols in wired networks need to pay less attention towards various vulnerabilities in terms of node instability, node mobility, unstable link conditions, sudden appearance and disappearance of nodes, limited battery life and limited resources. However, the vulnerabilities become prominent and are common phenomena in MANETs. To enhance the routing efficiency in MANETs, apart from looking into the end-to-end behavior as in wired networks, one has to think of node level and link level mechanisms to reduce the vulnerabilities that imposes a condition to design protocols at routing layer and provide the stable backbone. In order to maintain an end-to-end network pipe and to enhance the routing efficiency in MANETs, we design BDP based efficient routing structure that uses robust ring mesh backbone discussed in Sect. 2. In this section, we discuss BDP based multicast routing scheme using reliable ring mesh, in which we define models for bandwidth and delay to define BDP of every link in a path and hence to find end-to-end path BDP.

Bandwidth Model The available bandwidth of end-to-end path in MANET is influenced by the bandwidth available at a reliability pair. After assessment of reliability pair factor, the available bandwidth for selected reliability pair is obtained with the help of a cluster formed by one of the nodes of a reliability pair and all neighbors. Available bandwidth of a reliability pair is arrived in following three steps: (1) assessment of cluster available bandwidth (a cluster is defined as the set of nodes consisting of a node and all its one hop neighbors), (2) assessment of individual node available bandwidth in a cluster and (3) available bandwidth of reliability pair. A cluster is defined as a node and its one hop neighbors as shown in Fig. 9, where we wish to find available bandwidth between the node and each of its neighbor. Available bandwidth of a cluster provides the measure of overall bandwidth available for all the nodes within a cluster at time t that helps to compute the available bandwidth of individual nodes within a cluster. An application that arrives at this node consumes part of total available bandwidth of a cluster and when there are no applications at a node, the cluster will have maximum available C L . At time t, suppose the available bandwidth of a clusbandwidth represented by M AX BWav C L ter is BWav and there are k number of nodes in a cluster. Let the average number of arrivals at this cluster follows a Poisson process with the arrival rate of λC L and the probability of n number of arrivals to a cluster up to time t is given by Eq. 24.

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Fig. 9 Cluster of a node with its neighbors 2 1 3

8 7

Reliability pair 6 4 5

PC L =

λt n × e−λt n!

(24)

C L , using non-arrival probability We can estimate the available bandwidth of a cluster BWav C L (1 − PC L ) and M AX BWav given by Eq. 25. CL CL = (1 − PC L ) × M AX BWav BWav

(25)

Available bandwidth of a cluster, BW C L , provides a measure of overall bandwidth available for all the nodes within a cluster at time t. We are looking for estimating the available bandwidth of pair of nodes that are connected with statistical measure defined as reliability pair factor, which is a significant parameter to assess the depth of connectedness between the two nodes. With reference to every neighbor in a cluster, a node finds reliability pair factor and calculates available bandwidth of reliability pair for which FR P > 0. If the probability that FR P ≤ 0 is represented as PFLR P , then the probability that FR P > 0 for which a reliability pair is connected is represented by PFHR P = 1 − PFLR P . Let the probability of available bandwidth of individual node in a cluster is Pind , which excludes the influence of reliability pair factor with its neighbors within a cluster. It is measured based on the average number of arrivals at r th individual node in a cluster, where r = 1, 2, 3, . . . , k − 1, with an arrival rate of λr . The probability of r th individual node is Pr within a cluster that includes the influence of FR P and is given by Pr = Pind × PFHR P . The bandwidth available at s th node, represented s , is given by Eq. 26 with all its possible neighbors for which F as BWav R P > 0. s = BWav

r =k−1

CL (1 − Pr ) × BWav

(26)

r =1,r =s

It is assumed that the nodes which are nearer to the edge of a cluster will not have any influence of bandwidth consumption due to the nodes outside the cluster (i.e., the nodes that are neighbors of edge nodes of a cluster). The available bandwidth of any two neighbor nodes in a cluster is given by the sum of individual node’s available bandwidth. If we select two neighbor nodes r and s as the reliability pair, then available bandwidth of a pair, (BWav ) R P , is given by Eq. 27. r s (BWav ) R P = BWav + BWav .

(27)

Among many other parameters, (BWav ) R P depends upon the number of arrivals to each node, the FR P value between the pair nodes and their neighbors and the time of occupancy

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of each user. Our objective is to find the available bandwidth of a reliability pair (BWav ) R P assuming FR P of that pair is non-zero. Delay Model The delay incurred in transmission of a packet between the nodes of a reliability pair depends on the parameters such as (1) processing delay and output queueing delay at sender of a reliability pair, (2) propagation delay between reliability pair nodes and (3) processing delay and input queueing delay at receiver of reliability pair. We are interested in estimating overall delay performance of reliability pair in terms of following quantities (a) the average number of arrivals α(t) (up to time t) in the system of reliability pair with the arrival rate λ = α(t) t , (b) average delay the packet experiences while it is in reliability pair which is given by α(t)

D

i=0 i D = α(t) and average number of packets (N ) in a reliability pair system at time t is given by t → ∞. (N is the sum of packets in both node’s queue of reliability pair and the number of packets in transit between the reliability pair nodes). These quantities will be estimated in terms of known parameters of λ and the packet service rate. We assume that the reliability pair as a system, in which the total delay experienced by a packet depends upon two parameters: average input queueing delay and the average time the packet need to wait while there are many other packets getting serviced by the system. We use Little’s Theorem [33] to compute an average delay that a packet experiences in a reliability pair system and is estimated as the sum of waiting time and service time in a system. Average delay experienced by a packet, D R P , is obtained as the ratio of average packet arrival rate λ to N , given by Eq. 28.

DR P =

λ N

(28)

Bandwidth Delay Product From Eqs. 27 and 28, we can get the bandwidth delay product of a reliability pair, B D P R P , given by Eq. 29. B D P R P = (Bav ) R P × D R P

(29)

BDP of a path from source to a destination is a sum of BDP’s of concatenated set of reliability pairs. If a path is formed by K concatenated set of reliability pairs, then the path BDP is given by Eq. 30. BDP =

K (B D P R P )k.

(30)

k=1

BDP gives a measure of in-flight packets in an assumed network pipe from source to multicast destinations. 3.1 Database Structure for Routing Every node stores some useful information to establish multicast routes. The information is stored in two types of database maintained at every node, namely the node database and the neighbor node database. The database stores most recent information necessary for routing and this information is related to various aspects such as BDP based information, reliability pair information and flag information. At certain time, the stored information in node database and neighbor node database are shown in Tables 1 and 2, respectively.

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Table 1 Node database

Sl. no. 1

Parameter M AX BW av

Value 2 Mbps

2

Bav

1.2 Mbps

3

RNF

1

4

GMF

0

5

PF

0

6

dav

489 m

7

Location info

N24 54 32 W45 76 34

8

Centroid

E42 12 03 N22 37 45

9

W r em

320 mW

Table 2 Neighbor node database (BWav )RP

Neighbor node

FRP

DRP

B D PRP

128.23.68.1

3.42

64.34.40.21

–

0.9 Mbps

240 ms

0.216 Mb

–

–

128.87.0.7

–

–

–

–

–

Information stored in node database are as follows. Maximum available bandwidth (M AX BW av ), current available bandwidth (Bav ), remaining battery power of a node (W r em ) and three flags (ring mesh node flag (R N F)—to indicate whether the node is a part of ring mesh node, group membership flag (G M F)—to indicate whether the node belongs to group member and path flag (P F)—to indicate whether the node is on the path from source to destination). Other parameters are related to the current location of a node (Location Info), centroid of MANET area and the distance between the centroid and the node’s current location (dav ). Neighbor node database information is shown in Table 2. They are: reliability pair factor (FR P ), delay required to transmit a packet between the pair nodes (D R P ), available bandwidth of reliability pair ((BWav ) R P ) and bandwidth delay product of a pair (B D PR P ) stored corresponding to every neighbor. 3.2 Multicast Routing with Ring Mesh The ring mesh serves as robust backbone to establish multicast routes from source to multicast destinations. By the very nature of reliability pair on which the ring mesh is constructed, the FR P of every pair has non-zero value so that BDP of each pair can be estimated since there exists a well defined connectivity between the pair nodes. Given the reliable ring mesh backbone, the problem of route establishment from source to multicast destination reduces to the establishment of paths from source to the nearest ring mesh node and from the nearest ring mesh node to the destination. In this section, we discuss BDP based end-to-end path set up procedure that uses two types of reliability pair links: ring mesh reliability pair links and non-ring mesh reliability pair links. Non-ring mesh reliability pair links are used to setup a path from source to source’s nearest ring mesh node and destination to destinations’s nearest ring mesh node, whereas ring mesh backbone itself is used to set up end-to-end path.

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135

S

31 5

2

7

12

3

4

8

6

11

30

29

9

28 10

27

13 14

15 22

18

26

23

16 17

24

21

19

25

Ring mesh Ring mesh node

20 29 Non−group member

Group member

Fig. 10 Ring mesh topology and routing

For example, Fig. 10 shows an arbitrary ring mesh topology, wherein source S establishes multicast routes to group members through a ring mesh. 3.2.1 Route Establishment Through Ring Mesh We have two entities (FR P and BDP R P ) of a reliability pair that are used to set up a path from source to the nearest ring mesh node and from nearest ring mesh node to the destination nodes. There may be multiple paths available from source to the nearest ring mesh node and from nearest ring mesh node to the destination node. Similarly, there may be multiple paths between two ring mesh nodes that are nearest to the source node and nearest to destination node respectively. In summary, we have multiple end-to-end paths existing between every source-destination pairs. For example, in Fig. 10, we see that there are two paths from source S to the nearest ring mesh node (Node number 4) and likewise, there are two paths from nearest ring mesh node (Node number 16) to one of the destination nodes (Node number 18). As the ring mesh provides a robust backbone, the only effort needed is to establish a path from source to the ring mesh node and from ring mesh node to a destination node. The following sequence of operations are performed to establish a route. (1) Source node calculates (FR P ) with each one of its neighbor and broadcasts a request message to all neighbors that have FR P ≥ 0. (2) After receiving a request message, every neighbor checks whether it is a ring mesh node using R N F flag in its node database. (3) If the neighbor node happen to be a ring mesh node (R N F = 1), the source sets a path through that node. (4) If the neighbor node is not a ring mesh node (R N F = 0), repeat steps (1) to (3). (5) Ring mesh node receiving the request message sends it to all the remaining ring mesh nodes. (6) Ring mesh nodes broadcast request message to their non-ring mesh neighbors which have FR P ≥ 0. (7) If the neighbor node is not a group member, it rebroadcasts request message. (8) If the neighbor is a group member (i.e., G M F = 1 in its node database), it generates reply message and broadcasts. (9) When a node receives reply message through which the request message is sent, it sets P F = 1 and calculates the B D P R P with the node sending a reply message. (10) If the node receives a reply message and if it is on the return path from

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destination to source, then it calculates B D P R P with its previous node, updates (i.e., earlier B D P R P is added to new value) and rebroadcasts reply message along with updated B D P R P . (11) Any node that receives duplicate request or reply message, message is discarded. (12) Repeat steps 8 to 11 until the reply reaches to source. Through the reply messages from all group members, source has total B D P that is estimated using Eq. 30 for individual path to every group member. There may be multiple alternate paths from source to each group member node having varying value of B D P with each path. This is because, the multiple paths may contain different number of hops, different reliability pair parameters (i.e., B D P R P , D R P and FR P of each reliability pair), varying values of number of packet transmission and varying Wi r em of every node. If there are multiple routes to a destination, source uses a route that has higher value of B D P to send data packets to that destination so as to satisfy the objective of having maximum number of in-flight packets on end-to-end path. 3.2.2 Route Maintenance There are many situations under which existing route may break leading to loss of packets. We need to monitor route breaks and find appropriate action to be triggered to either avoid route break or recover from failure so that the end-to-end path has minimal packet losses. Occasions under which such situation may happen are listed as following cases. (1) Power drain and mobility of ring mesh node, (2) Power drain and mobility of non-ring mesh node, (3) Node failure (either ring mesh node or non-ring mesh node), (4) Reduction of FR P beyond 0 of any reliability pair existing on end-to-end path, and (5) Reduction of end-to-end path B D P. Case I: Mobility of ring mesh node Ring mesh node is chosen only when it has higher values of FR P and B D PR P with its neighbor ring mesh node. These values may get disturbed if a node starts moving and such disturbance is due to several reasons: distance between reliability pair nodes may increase, power level of nodes may decrease and propagation delay may decrease. All the effects are reflected in reduction of B D PR P , if one of the nodes of a reliability pair starts moving. In such a situation, the other node of a reliability pair selects an alternate reliability pair to transmit remaining data packets that satisfies required B D PR P . For example, in Fig. 10 if ring mesh node 5 starts moving, the node towards the source (node number 4) makes above listed observations and constantly monitors B D P R P with node number 5 and selects alternate node (node number 6) as its next pair node. Thus, the traffic is routed through node number 6 instead of node number 5, whose B D P R P remains invariably constant. The procedure is repeated at node number 6 to provide a connectivity to node number 7. The recovery procedure from ring mesh node mobility will have little overhead since there is no new path to be set up as there exists robust ring mesh backbone. Case II: Mobility of non-ring mesh node Non-ring mesh nodes help in connecting either source or destination to nearest ring mesh node. Since FR P of non-ring mesh node pair is less compared to the ring mesh node pair, whenever a non-ring mesh node starts moving, FR P and B D PR P tend to reduce drastically. The drastic variation is monitored by the node towards the source on the path and further

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packets are diverted to alternate pair node that remain static for sufficient amount of time and thus avoiding sending of packets through the moving node. For example, in Fig. 10 if node number 2 is moving, source S that is monitoring its B D PR P , diverts next packets to node number 31, which is non-moving to establish a connection with node number 3. If many non-ring mesh nodes are moving, the source has to initiate new route set up mechanism.

Case III: Node failure (either ring mesh node or non-ring mesh node) Node failure is defined as malfunctioning of a node due to several reasons: power level of a node goes down drastically, a node gets overloaded because of heavy traffic (congestion) and a node may be hacked (by malware, since ad hoc nodes are more susceptible to such attacks). Under such conditions, the neighboring node of a failed node finds appropriate actions (as stated in above cases) to find alternate paths and route the packets to a destination. When such a node recovers from failure, it notifies its reappearance to the neighbors by hello message advertising its Bav , which helps its neighbors to consider the node and thus become a part of routing function. Notification of reappearance message by a node is also used in case a new node wishes to join the group.

Case IV: Vanishing of reliability pair (when FR P ≤ 0) Reliability pair on end-to-end path may get vanish once FR P becomes negative. This may happen due to several reasons: both nodes of a reliability pair are moving at very high speed, both of them are transmitting data at a faster rate, battery power of both the nodes is reducing (i.e., it goes below Low range) and both nodes are attacked by malware and they start behaving unpredictably. This situation causes a fatal condition of a route and the recovery of route may become very difficult since the path should be set up afresh avoiding misbehaving reliability pair nodes.

Case V: Reduction of end-to-end path BDP End-to-end path BDP may reduce because of two types of reasons that are listed in cases I to IV. First type of reasons might be due to reduction of number of hops since a node on the path moves away and alternate recovery path may contain less number of hops. In this case, it is simply ignored since path BDP is proportional to the number of hops on a path. Second type of reasons are due to decrease in (BWav ) R P of reliability pair, packet occupancy time in a reliability pair and thus reducing in-flight number of packets in a reliability pair and other channel condition. In this case, the e B D P of reliability pair reduces and constructs alternate path bypassing the affected reliability pair whether an affected pair belongs to either ring mesh or non-ring mesh. Our routing scheme effectively manages to recover routes with the help of reliability pair and reliable ring to maximize the B D P of existing route. This produces best possible multicast routing efficiency under certain level of node mobility and node failures. If large number of node’s mobility is chaotic and unpredictable, then entire ring mesh is to be reconstructed and routes to be re-established frequently.

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4 Simulation Model Multicast routing scheme is simulated in various network scenarios to assess the performance and effectiveness of the approach. We used C language on Pentium IV machine as a simulation environment. The warm-up period in the simulation is varied between 100 to 200 observations for different parameters. We considered an average of 1,000 observations after warm-up period to compute each performance parameter. Simulation environment for the proposed work consists of five models: (1) Network model, (2) Power model, (3) Propagation model, (4) Mobility model and (5) Traffic model. The details of the models are as follows. • Network Model: An ad hoc network is generated in an area of l × b square meters, with an approximate centroid C. It consists of N number of mobile nodes that are placed randomly within the given area. Total delay experienced by a packet at every node is the sum of input queueing delay diq , output queueing delay doq and processing delay d pr . • Power Model: Every node is assumed to have its remaining battery power W r em in two ranges, (1) Low range and (2) High range. Differential received signal strength D S is calculated as the difference of signal levels S( j,0) and S( j,t) from node j before and after its mobility, respectively. • Propagation Model: Free space propagation model is used with propagation constant β. Transmission range of MANET node is r for a one-hop distance d and propagation delay incurred by a packet is d pg , which is a function of speed of propagation and the distance between two neighboring nodes. • Mobility Model: We use a random way-point (RWP) mobility model based upon three parameters; speed of movement, direction of mobility and time of mobility. Each node picks a random destination uniformly within an underlying geographical space and travels with a speed v whose values are decided by initial velocity v s and final velocity v f . Upon reaching a destination a node pauses for a time period Z , and the process repeats itself afterwords. Eight directions are considered for movement of nodes: east, west, north, south, north-east, north-west, south-east and south-west. • Traffic Model: Constant bit rate model is used to transmit certain number of fixed size packets, T r pkts . The maximum available bandwidth M AX BWav of a node is shared among its neighbors. The current available bandwidth of a node is BWav and transmission rate is Trate . 4.1 Simulation Inputs The proposed scheme is simulated using the following simulation inputs. l = 1,000 m, b = 1,000 m, N = 50–250, diq = doq = random values in the range 0.1–0.5 ms, d pr = random values in the range 0.3–0.7 ms. Low range = 0 to 0.1, H igh r ange = 0.1 to 1, D S = 0 to 5 mW, β = 2.5, r = 350 meters, d pg = random values in the range 0.8–1.5 ms, v s = 0 m/s, v f = 10 m/s, Z = 0.1 ms. T r pkts are in multiples of 1,000. M AX BWav = 10 Mbps, BWav ≤ 10 Mbps and Trate = 200 Kbps. Simulation procedure involves following steps. 1. Generate ad hoc network and traffic across the network. 2. Form a reliability pair factor for pair of one hop neighbors. 3. Compute the centroid and average distance at which the reliable ring mesh is to be constructed. 4. Use reliability pair factor to create ring mesh structure. 5. Compute BDP of reliability pair using bandwidth and delay model.

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139

6. Establish multicast routes that satisfy the BDP through ring mesh. 7. Compute performance parameters. The following performance parameters are assessed. • Average end-to-end delay: It is the average time taken by a packet to reach to all multicast destinations. It is defined by Eq. 31. G [di ] Average end-to-end delay = i=1 (31) G where G is the group member size, di is the delay incurred by a packet to reach to ith group member. • Packet delivery ratio: It is defined as the ratio of number of packets received at each group member to the total number of packets sent at sender. • Control overhead: It is defined as the total number of control packets needed to establish multicast routes from source to all destinations. It is the sum of control packets used for creating reliability ring mesh using reliability pair and establishing routes. • Application rejection ratio: It is defined as the ratio of number of applications rejected due to lack of required BDP to the total number of applications generated in an interval. It is defined by Eq. 32. Application rejection ratio =

Number of applications rejected Number of applications generated

(32)

• Memory overhead: It is the average number of bytes required to set up multicast routes in neighbor node database of all neighbors of ring mesh nodes, non-ring mesh nodes and group member nodes at any given time.

5 Results Simulation results of Reliable ring Mesh based multicast Routing scheme using Bandwidth Delay Product (RMRBDP) and EODMRP are compared in this section. 5.1 Analysis of Average End-to-End Delay The average end-to-end delay fluctuates for various group sizes for a fixed total number of nodes in a network as shown in Fig. 11 (for static nodes) for RMRBDP scheme since it depends upon the number of hops in each path from source to multicast destination. The average end-to-end delay is slightly less for EODMRP compared to RMRBDP since EODMRP does not use a ring mesh backbone and the end-to-end path may consist of less number links compared to RMRBDP. However, larger delay is the price paid for acheiving higher reliability in RMRBDP since it uses reliable ring backbone. However, the delay increases as the number of nodes in a network increase. This is because, as the number of network nodes increase, the number of hops to reach destination on each path increase thereby increasing average end-to-end delay for the network sizes of 50, 100 and 150 nodes. Another observation is made with RMRBDP when nodes are moving with different speeds of 5–20 m/s as shown in Fig. 12. Due to node mobility, the delay drastically increases as there will be frequent local repairs. For high speed mobility of nodes (above 10 m/s), there is a drastic increase in delay since node mobility causes route breaks.

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Average end−to−end delay (in seconds)

Average end−to−end delay Vs. group size 0.08 0.07 0.06 0.05 0.04 0.03 Nodes = 050, RMRBDP Nodes= 100, RMRBDP Nodes = 150, RMRBDP Nodes = 050, EODMRP Nodes = 100, EODMRP Nodes = 150, EODMRP

0.02 0.01 0

5

10

15

20

25

Group size Fig. 11 Average end-to-end delay versus group size, no mobility (comparison to EODMRP)

Average end−to−end delay (in seconds)

Average end−to−end delay Vs. Mobility 0.3

0.25

0.2

0.15

0.1

0.05

No. of nodes = 50 No. of nodes = 100 No. of nodes = 150

0 0

5

10

15

20

Mobility (in m/s) Fig. 12 Average end-to-end delay versus mobility, group size = 5

5.2 Analysis of Packet Delivery Ratio Packet delivery ratio (PDR) is plotted against group size in Fig. 13 for RMRBDP and EODMRP. In both cases, we find that there is an enhancement in PDR with more number of nodes in a network but PDR is less for small group sizes. As the number of nodes in the network increase, there are less packet losses because of higher reliable paths built upon reliable ring mesh backbone in RMRBDP that ensures better end-to-end BDP and hence there will be an increase in PDR. As EODMRP does not use a relaible backbone due to which there may be more number of packet drops in EODMRP compared RMRBDP and the PDR is less in EODMRP. With increase in group size, the PDR improves in both RMRBDP and

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PDR (%) Vs. Group size 100

PDR (%)

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Group size Fig. 13 PDR% versus group size, no mobility (comparison to EODMRP)

PDR(%) Vs. Mobility, Group Size=5 100

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Mobility, m/s Fig. 14 PDR% versus mobility for RMRBDP

EODMRP since the chance of packet delivery to a destination increases if many multicast destinations are located nearer to each other. PDR with node mobility for RMRBDP is shown in Fig. 14, where PDR is plotted with fixed group size of 5 with varying number of nodes in a network (i.e., number of nodes are 50, 100 and 150). PDR drops heavily with increase in node mobility. End-to-end BDP on each path gets affected if there are less number of nodes in a network where as connectivity increases with the increase in number of nodes and hence PDR is higher with 100 and 150 nodes in a network as compared to 50 nodes.

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Control overhead (# of control packets)

Control overhead Vs. number of nodes 1400 1200 1000 800 600 400

RMRBDP, Mobility = 0 m/s RMRBDP, Mobility = 05 m/s RMRBDP, Mobility = 10 m/s EODMRP, Mobility = 0 m/s EODMRP, Mobility = 05 m/s EODMRP, Mobility = 10 m/s

200 0

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Number of nodes Fig. 15 Number of control packets versus number of nodes (comparison to EODMRP)

5.3 Analysis of Control Overhead Number of control packets needed to establish multicast routes in RMRBDP and EODMRP are shown in Fig. 15 for three cases: no mobility, mobility = 5 m/s and mobility = 10 m/s. To construct the reliable ring mesh and to establish routes through ring mesh, the control packets increase with increase in number of nodes in network in RMRBDP whereas in EODMRP, the control packets required is more since EODMRP route establishment takes more number of packets. Once the reliable ring is constructed, the mobility and link failures are locally recovered in RMRBDP whereas in EODMRP, such events are handled by creating temporary clusters and recovery is made within clusters that needs more number of control packets. As mobility increases, the increase in number of control packets is more steeper in EODMRP than in RMRBDP. 5.4 Analysis of Application Rejections The percentage of applications rejected with increase in node mobility for RMRBDP and EODMRP is shown in Fig. 16. Applications rejected in RMRBDP is due to the lack of enough BDP available for a path out of total number of applications generated at the source. In both cases, many applications are rejected with increase in node mobility. The increase in application rejection ratio with node mobility is due to the incapability of path BDP to provide the required BDP because of random mobility of nodes. Increase in node mobility triggers the local recovery of ring mesh and non-ring mesh nodes. With higher mobility of nodes, recovery of large number of links increases the overhead as discussed in Sect. 3.2.2 that increases number of application rejections. In EODMRP, the application rejection ratio is higher compared to RMRBDP for all the cases since there is no backbone ring to prevent from many application drops at higher mobility. Thus, EODMRP fails in adopting local refreshing mechanism and mesh routes are to be established afresh that triggers many application rejections.

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Application rejection ratio Vs. mobility Application rejection ratio (%)

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Mobility, m/s Fig. 16 Application rejection ratio versus mobility (comparison to EODMRP)

Memory overhead Vs. simulation time, Group size = 05 450

Memory overhead (bytes)

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Simualtion time (seconds) Fig. 17 Memory overhead versus simulation time

5.5 Analysis of Memory Overhead The memory requirement at each node for route establishment depends upon the number of control packets to be stored for routing. For group size of 5, Fig. 17 shows the average number bytes to be stored in the memory of each node with respect to simulation time for both RMRBDP and EODMRP. EODMRP needs more control memory storage since fresh routes are established every time nodes are moving with higher mobility. With increase in number of nodes in the network, we observe that the average number of bytes stored in memory is 17.1% more in 100 node topology compared to 50 node topology.

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6 Conclusions In this paper, we proposed BDP based multicast routing scheme in MANETs that uses reliable ring mesh backbone. Since BDP provides the number of in-flight packets in a network pipe established from source to destination, it helps in establishing QoS satisfied routing that creates stable multicast routes. Reliable ring mesh is constructed at a an arbitrary distance between centroid and boundary of MANET area using convex hull algorithm. Stable links are identified to form reliable ring mesh with the concept of reliability pair. Selection of reliability pair is based upon remaining battery power of nodes, differential signal strength between the nodes and distance. Simulation results for packet delivery ratio, application rejections, memory and control overheads and end-to-end delay show an improved performance over EODMRP for various group sizes and node mobility conditions.

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Author Biographies Rajashekhar C. Biradar completed his B.E. (Electronics and Communication Engineering) and M.E. (Digital Electronics) from Karnataka University Dharwad, India. He is working as faculty in the Department of ECE, Reva Institute of Technology and Management, Bangalore, India. He has submitted his Ph.D. thesis to Visvesvaraya Technological University (VTU), Belgaum, India. He has many publications in national/international journals and conferences. His research interests include multicast routing in mobile ad hoc networks, wireless Internet, group communication in MANETs, softwrae agent technology, network security, etc. He is a member IETE (MIETE) India, member IE (MIE) India, member ISTE (MISTE) India, member of IEEE (USA) and member of ACM (USA). He has been listed in Marqui’s Who’s Who in the World (2011).

Sunilkumar S. Manvi received M.E. degree in Electronics from the University of Visweshwariah College of Engineering, Bangalore, Ph.D. degree in Electrical Communication Engineering, Indian Institute of Science, Bangalore, India. He is currently working as a Professor and Head of Department of Electronics and Communication Engineering, Reva Institute of Technology and Management, Bangalore, India. He is involved in research of Agent based applications in Multimedia Communications, Grid computing, Ad-hoc networks, E-commerce and Mobile computing. He has published over 110 papers at national and international conferences and 35 papers for national and international journals. He is a Fellow IETE (FIETE, India), Fellow IE (FIE, India) and member ISTE (MISTE, India), member of IEEE (MIEEE, USA), He has been listed in Marqui’s Who’s Who in the World.

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