Power Aware On-Demand Multicast Routing Protocol
Power Aware On-Demand Multicast Routing Protocol 1
B. Venkatalakshmi and S. Manjula
RFID & Sensors Lab TIFAC CORE, VEC 2 E- mail: [email protected]
, [email protected]
ABSTRACT: This paper proposes a new routing algorithm called Power Aware On-Demand Multicast Routing protocol which maximizes the lifetime of an adhoc network. The algorithm is based on the routing discovery phase and establish a resilient path. At routing discovery phase, the forwarding members are identified with suitable energy capacity. The optimal route confirms the resilience with respect to energy capacity of the load. The Join Query message compares the required power with the available power. The simulated result confirms the improvement in traffic load. Keywords— Ad-hoc Networks, ODMRP, Power - Aware.
dhoc networks  are infrastructure less wireless networks. Here, mobile nodes communicate directly with each other. If two nodes are not within radio range of each other, they can use the forwarding functionality of another node to establish a connection, i.e., the message travels from one node to another until it reaches its destination. All nodes need to implement at least simple medium access mechanisms and need to detect collisions themselves. Therefore, nodes of ad hoc networks are much more complex than those of infrastructure based networks. However, ad hoc networks are easy to manage and establish. Since they do not require an infrastructure network, they are much more flexible and their use is possible in a broader range of scenarios, e.g. for disaster relief. Depending on the frequency of structural changes in the network, ad hoc networks can be subdivided into mobile ad hoc networks, or MANETs, and sensor networks. The MANET  is decentralized, where network organization and message delivery must be executed by the nodes themselves, i.e., routing functionality will be incorporated into mobile nodes. Nodes must also contend with the effects of radio communication, including multiuser interference, multipath fading, and shadowing. A MANET may operate in a stand-alone manner, or be connected to a larger network, e.g., the fixed Internet. The majority of applications for the MANET technology  are in areas where rapid deployment and dynamic reconfiguration are necessary and the wireline network is not available. These include military battlefields, emergency search and rescue sites, classrooms, and conventions where participants share information dynamically using their mobile devices. These applications lend themselves well to multicast operation. In addition, within a wireless medium, it is even more crucial to reduce
the transmission overhead and power consumption. Multicasting can improve the efficiency of the wireless link when sending multiple copies of messages by exploiting the inherent broadcast property of wireless transmission. Routing plays a very important role in MANET which has been done by routing protocols. Routing protocols are used to route the packets depending on the path conditions. The design of network protocols for MANETs is a complex issue. These networks need efficient distributed algorithms to determine network organization (connectivity), link scheduling, and routing. An efficient approach is to consider routing algorithms in which network connectivity is determined in the process of establishing routes. Message routing in a decentralized environment where network topology fluctuates is not a well-defined problem. While the shortest path (based on a given cost function) from a source to a destination in a static network is usually the optimal route, this idea is not easily extended to MANETs. Factors such as power expended, variable wireless link quality, propagation path loss, fading, multi-user interference, and topological changes, become relevant issues. The network should be able to adaptively alter routing paths to alleviate any of these effects.
RELATED WORKS Energy Efficient Routing Protocol in MANETs The network lifetime  is a key design factor of mobile adhoc networks (MANETs). To prolong the lifetime of MANETs, one is forced to attain the tradeoff of minimizing the energy consumption and load balancing. In MANETs, energy waste resulting from retransmission due to high frame error rate (FER) of wireless channel is significant. In this paper, we propose a novel protocol termed error-aware candidate set routing protocol (ECSRP). ECSRP chooses a route in a candidate subset in the route cache in which all the nodes have enough residual battery power. This
Power Aware On-Demand Multicast Routing Protocol approach avoids overusing certain routes. If multiple routes exist in the candidate set, ECSRP employs a metric achieving the tradeoff between energy -efficiency and load balancing to select the optimal route. It also takes channel condition into consideration by incorporating packet loss probability in the computation of energy consumption. This helps to reduce the number of retransmissions and save energy.
Power Management Based Grid Routing Protocol for IEEE 802.11 Based MANET MANET  (Mobile Ad Hoc Network) is a collection of wireless mobile nodes forming a temporary communication network without the aid of any established infrastructure or centralized administration. The lifetime of a MANET depends on the battery resources of the mobile nodes. So energy consumption may be one of important design criterions for MANET. With changing the idle model to sleep model, a new energy-aware grid routing protocol was discussed.
node id of one of the entries in Join-Reply table matches its own id. If it is does, the node realizes that it is on the path to the source and becomes the part of the forwarding group by setting the FG_FLAG (Forwarding Group flag). When receiving a multicast data packet, a node forwards it only when it is not a duplicate, hence minimizing traffic overhead. Because the nodes maintain soft state, finding the optimal flooding interval is critical to ODMRP performance. ODMRP uses location and movement information to predict the duration of time that routes will remain valid. With the predicted time of route disconnection, a “join data” packet is flooded when route breaks of ongoing data sessions are imminent. It reveals that ODMRP is better suited for ad hoc networks in terms of bandwidth utilization.
AODV-Based Power-Aware Routing Protocol A mobile adhoc network which does not use a wired network and base station system is composed of a group of mobile and wireless nodes. There are various types of restrictions. The biggest restriction is the confined energy of the batteries . If the network is divided into more than two, and one of the nodes consumes all the energy, that node can no longer participate in the network. In recent years, much research has been undertaken to not only improve the energy storage but also to lengthen the networks lifetime. In this , we propose an enhanced AODV (Ad-hoc On-demand Distance Vector) routing protocol which is modified to improve the networks lifetime by applying an Energy Mean Value Algorithm which considerate node energy aware.
ODMRP OVERVIEW ODMRP  is a mesh based rather than a conventional tree based scheme and uses a forwarding group concept (only a subset of nodes forwards the multicast packets via scoped flooding). By maintaining a mesh instead of a tree, the drawbacks of multicast trees in ad hoc networks like frequent tree reconfiguration and non-shortest path in a shared tree are avoided. In ODMRP, group membership and multicast routes are established by the source on demand when a multicast source has packets to send, but no route to the multicast group, it broadcasts a Join-Query control packets to the entire network. This control packet is periodically broadcast to refresh the membership information and updates routes as shown in the fig. When the Join-Query packet reaches a multicast receiver, it creates and broadcasts Join-Reply to its neighbours. When it has been received by the node, it checks if the next hop
ALGORITHM An energy efficient flooding algorithm proposed in  proved that the lifetime of the network is increased. Our algorithm basically depends on such an energy efficient algorithm. We explore this property, in the routing discovery phase for ODMRP. E th represents the energy of each node. The initial required energy (E th) level is calculated dependent on the number of data packets which will send by each node. Here we assume that, the maximum number of data packets as 100 which will be transmitted in CBR (constant bit rate) Eth = (N0 packets) * Pcs Pcs – Power required to transmit one packet (eg: 1 mW) When a node wants to multicast the packets the required energy Ea v for the transmission is calculated at the source node. This value is carried by the join query message in the ODMRP protocol. Each intermediate node updates this Eav by one hop energy value. In each intermediate node, energy in the join query message is compared with energy available in each corresponding node. If the node doesn’t have enough available energy (i.e., if Eav < Eth), the corresponding packets are dropped without forwarding. If the node have enough available energy (Eav >= Eth), the node continue to forward the packets.
Mobile and Pervasive Computing (CoMPC–2008)
The above simulation parameters are set in the input file and CBR values are set in the application file (app.config). The group members are mentioned in the member file (member.config). We are included power parameter in two places into ODMRP protocol. First, in the routing table of each node, power (E th ) required to transmit the data packets is set to 100 mW because the maximum number of data packets which are transmitted in simulation process is set to 100 packets. Here we assume that each packet requires 1 mW power. Second, within the join query message structure, the available energy (Eav ) is fixed at 100 mW. This energy is decremented for each transmission by one unit value. If Eav < Eth., the intermediate node can’t forward the packets. In this condition, t he FG_FLAG is not set. If Eav > = Eth, the FG_FLAG is set i.e., the intermediate node transmit the packets. Using this algorithm, we reduce the number of packets routed for another node. These settings are done into ODMRP protocol (i.e., ODMRP.h & ODMRP.PC). We take the reading from the network protocol statistics to measure the traffic load in routing discovery phase. Here, we provide the results of the network performance with and without algorithm for different seed values.
Layers Mobility Radio Propagation Radio Model Packet Reception Models Data Link (MAC)
Protocols Random waypoint, Random drunken, Trace based Two ray and Free space
Noise Accumulating SNR bounded, BER based with BPSK/QPSK modulation CSMA, IEEE 802.11 and MACA IP with AODV, Bellman- Ford, DSR, Fisheye, LAR scheme 1, ODMRP, WRP TCP and UDP
CBR, FTP, HTTP and Telnet
PERFORMANCE OF ENERGY AWARE ROUTING ALGORITHM TRAFFIC LOAD DURING ROUTING DISCOVERY PHASE
Glomosim is suitable for MANET.Global Mobile Information System Simulator (GloMoSim)  a scalable simulation environment for large wireless and wire line communication networks. GloMoSim uses a parallel discrete-event simulation capability provided by Parsec. GloMoSim simulates networks with up to thousand nodes linked by a heterogeneous communications capability that includes multicast, asymmetric communications using direct satellite broadcasts, multi- hop wireless communications using adhoc networking, and traditional Internet protocols. GloMoSim currently supports protocols for a purely wireless network. Most network systems are currently built using a layered approach that is similar to the OSI seven layer network architecture. The plan is to build GloMoSim using a similar layered approach. Standard APIs will be used between the different simulation layers. This will allow the rapid integration of models developed at different layers by different people. The following t able lists the GloMoSim models currently available at each of the major layers :
160 140 120 100 80 60 40 20 0
WITH ALGORITHM WITHOUT ALGORITHM
SIMULATION PARAMETER S
The some of the simulation parameters are mentioned below: Parameter Simulation Time Terrain Dimensions Number of Nodes Node- Placement Mobility Model Propagation-Pathloss Radio- Type Radio- Frequency Radio- Bandwidth Radio- Rx-Type MAC Protocol Network Protocol Routing Protocol
Value 200S (1000,1000) 20 Uniform Mobility Rando m- Waypoint Tw o-Ray Radio-Accnoise 2.4e9 2000000 SNR- Bounded 802.11 IP ODMRP
SIMULATION RESULT Simulation parameters mentioned above are set in GloMoSim. We compare the performance of energy aware routing algorithm with existing algorithm. The simulation result at routing discovery phase shows that the traffic loads during routing discovery phase. Therefore the proposed algorithm confirms the reduction in traffic load of the network.
CONCLUSION The algorithm is implemented in ODMRP routing protocol. Performance of algorithm is compared with general ODMRP routing algorithm. In future we will verify the
Power Aware On-Demand Multicast Routing Protocol lifetime increase of an Ad Hoc Network using the power aware information.
REFERENCES  Performance of Routing Protocols for Mobile AdHoc Networks by Subbarao, Madhavi W., Wireless Communication Technologies Group, National Institute of Standards and Technology.  On-Demand Multicasting in Adhoc Networks: Comparing AODV and ODMRP by Thomas Kunz and Ed Cheng, Carleton University.  An Error-aware and Energy Efficient Routing Protocol in MANETs Liansheng Tan; Peng Yang; Chan,S. Computer Communications and Networks, 2007, ICCCN 2007.  Power Management Based Grid Routing Protocol for IEEE 802.11 Based MANET by Li X u1,2 and Bao-y u Zheng2 , Dept. of Computer Science, Fujian Normal University, Fuzhou, China and Dept. of Info. Eng., Nanjing University of Post and Telecommunication, Nanjing, China.
 Performance Evaluation of AODV-based Power-Aware Routing Protocol in Mobile Ad Hoc Networks by Kim, J.M. and Jang, J.W. (Korea), Scientific and Technical Publishing Company.  A Comparative and Performance Study of On Demand Multicast Routing Protocols for Ad Hoc Networks by Mohan, P. Madhan, Johnson, J. James, Murugan, K. and Ramachandran, V., College of Engineering,Guindy(CEG), Anna University.  Mobility Prediction and Routing in Ad Hoc Wireless Networks by William Su, Sung-Ju Lee, and Mario Gerla, Wireless Adaptive Mobility Laboratory, Computer Science Department, University of California.  ERA: Energy - Saving Routing Algorithm for Ad Hoc Networks, School of engineering-Information Communication University (ICU).  Global Mobile Information Systems Simulation Library.  A Comprehensible GloMoSim Tutorial compilation by Jorge Nuevo, INRS—Universite du Quebec.