A Cross-Layer Approach to Enhance the Call Setup ...

2014 2014 Eighth Eighth International International Conference Conference on Next on Next Generation Generation Mobile Mobile Applications, Apps, Services Services and and Technologies Technologies

A Cross-Layer Approach to Enhance the Call Setup Performance of SIP-Based VoIP over AODV MANET Mazin Alshamrani, Haitham Cruickshank, and Zhili Sun Centre for Communication Systems Research (CCSR), University of Surrey, Guildford, Surrey, UK {m.alshamrani, h.cruickshank, z.sun}@surrey.ac.uk

and call duration. The aim of this research was to study a simple, closed, AODV-based MANET scenario with a high density of mobile nodes using SIP-based VoIP to communicate together, as represented in Fig. 1. The study assumed a single SIP server in this network system that provides the SIP registration, initiation, and termination mechanism for SIP calls. It was also assumed that node A is the caller and node B is the callee. Nodes A and B both need to be registered with the SIP server to identify their existence and IP addresses. When node A wants to call node B, the SIP initiation messages for call setup start flooding between the two nodes through the SIP server, as shown in Fig. 2. When the call ends, the SIP termination message is sent through the SIP server to terminate the call. This scenario takes advantage of applying SIP-based VoIP applications as an alternative or backup communication system over mobile nodes that support the MANET network system. This system could be used for disaster and emergency recovery schemes when other communication systems are lost or break down. This study considered a MANET with moderate node capacity and different types of mobility models. In addition, IEEE 802.11n was considered the WLAN technology representing the physical layer technology for the implemented MANET.

Abstract— The implementation of SIP signaling over MANET is still a challenging issue, as many routing factors affect SIP performance. Node mobility and dynamic hop number changes between nodes are considered the main routing problems within MANET routing protocols. RFC 6076 proposed end-to-end performance metrics for SIP signaling to provide a standardized method of evaluating SIP performance over different platforms; however, no benchmarking values for these metrics have been proposed yet. In this paper, a cross-layer system designed to enhance the call setup performance of SIP-based VoIP over AODV-based MANET is proposed. The approach used is to employ the SIP performance metric to enhance the call setup time by adjusting the Time-To-Live (TTL) parameter and the Route Request (RREQ) message retries for the AODV route request messages to support the reachability ratio of SIP INVITE and reINVITE messages to reduce the call setup time of SIP-based VoIP. The study investigated the Session Request Delay performance metric of SIP signaling as part of the SIP over MANET simulation efforts. Both the call setup time and the number of SIP calls over random waypoint mobility models were enhanced by applying instantaneous modifications to the TTL parameter and RREQ retries, increasing the delivery ratio of route discovery messages to about 35-40% compared with the classic AODV routing protocol. Keywords- SIP; AOVD; Performance Metrics; OPNET

SIP Server

I. INTRODUCTION Mobile Ad Hoc Network (MANET) is one of the most common wireless network systems that provide dynamic simple wireless connectivity for mobile devices over different mobility systems. MANET has different routing protocols, and each protocol has its own characteristics over different applications and mobility models. MANET has reactive and proactive routing protocols. The most common reactive routing protocol is the Ad Hoc on Demand Distance Vector (AODV). Implementing Session Initiation Protocol (SIP) signaling over MANET has many challenges over all SIP call stages. Voice over Internet Protocol (VoIP) is considered one of the most common applications over different types of network systems. Different factors affect the Quality of Service (QoS) of VoIP over MANET’s routing protocols, such as mobility model, voice codec, physical distance between calling parties, number of hops, node capacity, Wireless Local Area Network (WLAN) technology, 978-1-4799-5073-7/14 $31.00 © 2014 IEEE DOI 10.1109/NGMAST.2014.14

A

B

Figure 1. SIP-based VoIP implementation over closed MANET

II. SIP PERFORMANCE METRICS SIP is a signaling protocol defined by the SIP Working Group within the Internet Engineering Task Force (IETF). The protocol was published as IETF Request for Comments (RFC) 3261 [1]. SIP is commonly used for controlling multimedia communication sessions such as voice and video calls over IP. A SIP session can include one or more participants/applications, and it can be used to create, modify, and terminate two or more participant sessions consisting of one or more media streams. SIP is a text 241

encoded protocol with a built-in code that allows different types of modifications as well as extensions. The modifications can be applied in addresses, ports, participant invitations, and adding/deleting media streams. SIP is an application layer protocol designed to be independent of the existing transport layer, and it depends on the supported Internet protocols. SIP can run on top of Transmission Control Protocol/IP (TCP/IP), or user datagram protocol/IP (UDP/IP). SIP-based VoIP implementations depend on three main stages: registration, call initiation, and call termination. These stages depend on the SIP proxy server to relay the connectivity between different callers. Delays in SIP signaling at all stages affect the performance of VoIP calls. SIP signaling performance has an important role in the overall QoS of next-generation networks. SIP signaling delays relate to the connectivity status between the call parties, which are the caller, the callee, and the SIP proxy. These delays occur mainly during the caller’s registration process, call initiation, call termination, and/or call management. SIP signaling is also affected by the behavior of the transportation protocol that the SIP relies on during the different connectivity processes of SIP calls. Many standards for evaluating the performance of telephony signaling protocols have been proposed; however, none of those metrics were used to address SIP signaling performance until the IETF proposed RFC 6076, Basic Telephony SIP end-toend Performance Metrics [2]. However, no numerical values or benchmark objectives for the RFC 6076 SIP performance metrics have been proposed yet.

setup requests, where the durations of success and failure responses vary. A simple representation of SRD related to SIP flow is shown in Fig. 2. SRD is calculated using the following formula: SRD = Time of Status Indicative Response - Time of INVITE

(2)

3) Session Disconnect Delay (SDD) SDD is designed to calculate the time interval between the time at which the session completion (BYE) message is sent and the last subsequent acknowledgement of the session completion response is received (2xx). SDD is used to detect failures or impairments that cause delays in ending the session. SDD measures both successful and failed session disconnects, and the output values are in milliseconds (ms). SDD is calculated using the following formula: SDD = Time of (2xx) or Timeout - Time of Completion Message (BYE)

(3)

A. RFC 6076: SIP End-to-End Performance Metrics The IETF adopted standardized end-to-end performance metrics for basic SIP-based signaling systems as defined in RFC 6076 [2]. These metrics provide key performance indicators and Service Level Agreement (SLA) indicators to support SIP-based telephony systems and enhance network utilization. The main RFC 6076 metrics are as follows: 1) Registration Request Delay (RRD) RRD is used to determine the response delay time for the user agent REGISTER request. RRD helps to measure and analyze successful registration requests at the originating user agent, as represented in Fig. 2. The RRD output values should be in milliseconds (ms). This metric is calculated using (1): RRD = Time of Final Response - Time of REGISTER Request

(1)

RRD is calculated only for successful registrations. When the SIP call load in the network system increases, the RRD value also increases. Conversely, when there is a low load in the network system, the RRD value is also low.

Figure 2. SIP signaling flow and RRD,SRD, and SDD SIP performance metrics based on RFC 6076 [2]

2) Session Request Delay (SRD)

B. Research Efforts Related to RFC 6076

SRD is a metric designed to detect the faults or defects that cause delays in responding to INVITE requests. SRDs are considered for both successful and unsuccessful session

A limited number of research efforts have been undertaken to study the RFC 6076 SIP performance metrics for VoIP applications. An early effort to identify a specific

242

set of performance metrics to evaluate SIP signaling performance was proposed in [3]. This method measured the overall performance of the SIP server by defining the parameters and methodology for benchmarking the SIPbased VoIP infrastructure. This method was designed to investigate the performance of the SIP server Back-To-Back User Agent (B2BUA) for VoIP applications. The study proposed and examined two parameters: RRD and SRD. The study was updated in [4] and proposed new approach to manage and control high SIP-based traffic depends on traffic stress testing. The efforts later extended to a study of the SIP proxy server B2BUA that proposed a stress test of SIP signaling and benchmarking the performance metrics based on the behavior analysis of the SIP environment [5]. The SIP registration burst load of SIP servers was examined in [6]. The research studied the RRD performance metric for SIP server by investigating the effectiveness of handling the burst loads for SIP registration requests in an Asterisk PBX system. In [7], a simulation-based optimization algorithm of SIP signaling procedures in IP Multimedia Subsystem (IMS) was presented to improve SIP signaling performance by assigning high priority values to SIP messages to reduce network congestion and improve the overall QoS. The simulation efforts were conducted with ns-2, and the results were analyzed in terms of RRD, SRD, and SDD. The results were not compared with other related published results because the measurements used were implemented under different conditions and environments. In [8], the SIP performance metrics were used to evaluate the implementation of the Rich Communication Suite services in IMS platforms. The study used RRD, SRD, SDD, and session duration time as timing parameters to optimize the SIP signaling services for the proposed system during its implementation. In [9], the SIP performance metrics were used to measure the overhead of using Transport Layer Security (TLS) compared with TCP and UDP for secure SIP implementation. The experimental results showed a noticeable decrease in the performance of VoIP services based on RRD and SRD when using SIP over a TLS-based signaling system.

networks. In addition, it provided some theoretical analysis of SIP setup delays and provided results indicating that call setup delay values were greater when using IPv6 than when using IPv4 for radio access links with a bit rate less than 128 kbps. In [12], call setup delay was represented by using the RFC 6076 performance metrics. The research considered both RRD and SRD values to evaluate the call setup delays for SIP-based VoIP services in terms of high loss, high latency, and bandwidth-constrained airborne network environment using an OPNET simulation tool. III. AODV MECHANISM AODV is one of the most efficient MANET routing protocols which is widely implemented over different applications and services. AODV, defined by the IETF MANET working group in RFC 3561 [13], is an efficient reactive routing protocol that computes routes on an ondemand basis when a node wants to send data to another node. It maintains only one active route per destination inside the routing table between nodes that need to communicate. AODV provides fast adaptation for dynamic links, low network utilization, and low processing and memory overhead [14]. AODV depends on per-node sequence numbers to avoid loops and to select the most updated routing path. It is a hop-by-hop routing system that depends on simple route request and reply messages to determine the routes of the requested connectivity. Each route has its own lifetime, which is renewed once it is used; the route is discarded if it is not used during this lifetime interval. The routing table maintains information about the destination node IP address and sequence number, the next hop, the route lifetime, and the required routing flags. AODV provides multicast and unicast connectivity, and it supports the QoS of MANET connections. AODV depends on Route Request (RREQ) messages to determine and find the required route. RREQ packets flood to the next nodes in the network until the best route is found from the routing table of network nodes. The node’s route table entry is at least as fresh as the source node’s last known route to the destination node, and it can create a Route Reply (RREP) message. The most recent route to the destination is selected, and it concurrently ensures loop freedom. AODV behavior affects the routing performance of different applications and data transmission processes. AODV does not retransmit lost data packets, nor does it guarantee packet delivery; however, the delivery percentage is nearly 100% for MANET with few nodes [15]. The packet delivery ratio drops with the increased mobility ratio of nodes. On the other hand, the overhead in AODV packets needs to be at the least possible level, as it is related to the behavior of RREQ, RREP, and route error messages. The amount of overhead for the packets increase with the increase ratio of nodes mobility as the probability of frequent links break will growth and the route discovery time will increase. For route optimization in AODV, RREQ messages are initially sent with small TTL fields to limit

C. Call Setup Delay Call setup delay is defined as the elapsed time between sending the initial INVITE request and receiving a 180 RINGING response [10]. Also known as Post Dial Delay (PDD), it is considered one of the required parameters for Quality of Experience (QoE) evaluation. A number of studies have evaluated the call setup time for SIP-based network systems. The International Telecommunication Union–Telecommunication recommendations defined considerable constraints for SIP call setup delay, with a mean value of 800 ms and a maximum value of 1500 ms [11]. In [10], SIP call setup delay was investigated based on the values in [11] by using different QoS and QoE factors for SIP signaling evaluation over IPv4 and IPv6 IMS

243

their propagation. If no RREP is received, a larger TTL value will be used to increase the chances of reaching the distance node (B). Using larger TTL values increases the probability of reaching the destination node (B); however, there will be longer delays if the route if not found immediately [16]. In addition, AODV gives the nodes the ability to repair broken active links locally instead of notifying the source node (A), resulting in less overhead, delay, and packet loss; however, longer delays and greater packet loss may occur in cases of unsuccessful repairs.

systems with moderate to high node capacity, variable hop numbers, and node mobility, SIP performance metrics can be used to enhance the performance by adjusting the routing parameters to the required level. In this approach, SRD is calculated for all calls initiated by the caller node UA(A). As the call initiation signaling pass through the SIP server, all messages and parameters for INVITE messages are recognized by the SIP server and the caller to evaluate the SIP signaling performance, as represented in Fig. 3. The call setup time is the time difference between TIn1 and TA3, where TA3 is the time of receiving the call acceptance acknowledgment 200 OK by the callee UA(B). The SRD in this implementation is the time difference between the INVITE message, sent at time TIn1, and Tx3, the time at which the callee’s response message was received by the UA(A) for the call invitation, as represented in Formula (1). In this approach, the three-way handshake system is applied for the call setup, as it represents the basic SIP signaling flow between the call entities, and the SRD SIP performance metric can applied. The proposed approach is applied to both the SIP server side and the caller node side. When the caller node UA(A) or the SIP server UAS recognizes a delay, the CLAODV approach, triggered to enhance the routing performance using cross-layer messages with the network layer to modify the AODV routing parameters based on the on the analyzed data in the application layer, as represented in Fig. 4.

IV. CROSS-LAYER IMPLEMENTATIONS A number of studies have proposed different approaches to the Cross-Layer AODV (CLAODV) routing system to enhance its application performance over MANET. There is no optimal cross-layer solution for AODV-based MANET that can solve all the challenging performance issues; however, these proposed mechanisms provide performance enhancement approaches to specific problems. Most of the proposed cross-layer approaches to AODV deal with the lower layers of OSI, between the network layer and the physical layer, to provide an efficient enhancement level for AODV connectivity and data transmissions. A limited number of cross-layer approaches use SIP signaling to enhance the performance of the network system. Most of the implementation has focused on the IMS systems to support the QoS and performance efficiency of SIP-based applications. An example of a CLAODV implementation is presented in [17] where a cross-layer algorithm was proposed to calculate channel availability at the link layer of an AODVbased vehicular network to improve its communication reliability and reduce its latency for vehicle safety applications. In that study the distance change rate between related nodes was calculated by investigating the AODV path discovery process regarding the forwarded RREQ packets to increase the route lifetime, decrease the route delays, and increase the transmission reliability. Another example is represented in [18], wherein a cross-layer handover management architecture (CHM-SIP) was proposed to shorten the service interruption time of frequent mobile node handovers between WLAN subnets. The study aimed to enhance the handover performance of SIP-based Voice over WLAN (VoWLAN) by using the mobile’s speed and the handover signaling delay information to decrease the handover delays. The theoretical analysis and simulation results of this approach show that CHM-SIP improved the VoWLAN handover performance. All the proposed approaches are related to different platforms that can be applied for MANET. In addition, it does not provide dynamic performance enhancement system for SIP call setup processes.

Figure 3. Call setup signaling flow for the proposed CLAODV

Application Layer

SIP

Transport Layer

TCP

Network Layer

AODV

Examine: SRD, INVITE, 200 OK Adjust: RREQ, TTL

Data Link Layer Physical Layer Figure 4. CLAODV representation of MANET OSI for the proposed call setup performance enhancement algorithm

V. PROPOSED METHODOLOGY Call setup performance depends on the SIP initiation messages sent and received by the call entities. For MANET

The proposed algorithm depends on SRD_BenchM, which is the benchmark value for SRD that determines and evaluates the call setup time performance over MANET. The

244

SRD_BenchM value can even be used as a specific input value, or it can be found during the run time of the system. Because there are no approved benchmark values for the RFC 6076 performance metrics in general and for MANET specifically, this research study set out to evaluate and find the SRD value. During the call setup session, the SRD values of caller UA(A) was compared with a determined SRD_BenchM. If the SRD was greater than SRD_BenchM, then CLAODV was triggered to update the routing table by resending the RREQ messages with longer a TTL period, as represented in Algorithm 1. This process was triggered for a short time until a RREP was received to provide the call setup message with the ability to reach its destination with an active updated route. When the RREP was received, a reINVITE message was resent, and the TTL for the RREQ value degraded to save both the CPU cycles and the bandwidth. T is the simulation time at second n, T_Waite is the maximum specified time in seconds before sending the re-INVITE message, and T_End is the time that the simulation ends. The UAS uses the signaling timers for INVITE messages and responses that are forwarded by the UAS between the call ends during the call setup process. The UAS can observe the call setup performance for INVITE messages between both UA(A) and UA(B) by investigating TIn2, TR2, Tx2, and TA2. The UAS can determine the SRD values for the UA(A) call setup process from the sequence numbers and time stamps of the INVITE messages and its acknowledgments. When a delay is detected, the UAS initiates the CLAODV process to adjust the routing parameters with the required level that allows the routing table to be updated with active routes.

The CLAODV algorithm provides a reliable real-time detection system for the call setup delays and undeliverable SIP messages as it relays the SRD performance metric to adjust the level of the routing update values. In addition, it provides a self-adjustment mechanism for SIP signaling instead of feeding the system with the required actions to enhance the call setup performance over MANET. The SRD values can be determined by the caller node with continuous investigations to obtain self-evaluation records for SRD values during the application running time. This method can enhance the call setup performance with the dynamic reachability process to other nodes to reduce the connectivity delays, save the CPU cycles, and reduce the bandwidth. If the RREP message is not received during this approach, the call setup performance is not enhanced, as additional delays may result because the algorithm needs to reuse the last known routing to send the re-INVITE message. The CPU cycles increase as the level of RREQ messages increases in order to update the routing tables, which also increases the nodes’ consumed power for routing purposes; bandwidth consumption also increases. VI. SIMULATION SETUP In this research effort, we used IEEE 802.11n as the wireless network standard for MANET, due to its enhanced features and wide usage over WLAN devices. The simulations were carried out in OPNET Modeler v17.1 over four types of mobility models: Static, Uniform, Random Waypoint (RWP), and RWP All. Table I presents the simulation parameters that were identified, depending on the features and capabilities of the MANET and VoIP applications. This design and implementation were used to investigate and evaluate the QoS for SIP-based MANET over different mobility systems in [19]. The SIP server was a Registration, Redirect, and Proxy server for SIP-based applications. Fig. 1 shows the scenario implementation in OPNET with regard to the identified simulation parameters given in Table I. This design was implemented in all of the mobility models used in this study. Fig. 1 shows the implementation of the RWP mobility model in OPNET for the MANET scenario. In the Uniform model, all nodes move in the same direction, with different speed ranges, including the SIP server. In the RWP model, the nodes move in different directions, but the SIP server is stable in the center of the simulation area. In the RWP mobility model, every node in the simulation, except the SIP server, has its own mobility direction and speed, depending on the identified random functionality of the node parameters. In the RWP All model, all nodes move in different directions, including the SIP server. The reason for examining random mobility using two different models is to study and evaluate the effect of SIP server mobility for VoIP applications and the signaling QoS. The study considered both IPv4 and IPv6 MANET in order to identify the difference in route overhead between the two IP systems. IPv6 did not apply the QoS features over MANET applications in this research study and simulation efforts, as it is not supported over MANET.

Algorithm 1: Cross-Layer AODV in the UAC(A) and UAS

Input: SRD_BenchM, T_Wait, T_End Call Setup T(n) if ( 200 OK (n) for TInv1(n) is Received) SRD = Tx3 (n) - TInv1(n) if ( SRD > SRD_BenchM) and (T(n) != T_End) TTL_Current = TTL (n) TTL = TTL + 1 Resend RREQ if ( RREP received) Resend INVITE TTL = TTL_Current n=n+1 Go to Call Setup T(n+1) Return else Loop Loop else if ( wait time at T(n) is > T_Wait ) Resend INVITE Go to Call Setup T(n+1) end else if else if (T(n) == T_End) End else Go to Call Setup T(n+1)

245

TABLE I.

SIMULATION PARAMETERS IN OPNET

RWP and RWP All scenarios; the shortest SRD was about 0.485 seconds, and the longest was 13.276 seconds. These results indicate very long delays in the call setup times of VoIP over AODV MANET. The call setup mechanism needs to be improved to meet the SRD ideal values for Uniform models and the best cases of the RWP mobility model.

A. MANET 8

Number of Simulations

Simulation Seed Number

128

30 Minutes = 1800 Seconds

Simulation Duration:

Static, Uniform, RWP, and RWP All

Mobility Models:

Number of 25 nodes 1 km x 1 km Area Dimension: nodes: Uniform Speed between 5.57 m/s (20 km/hr) and Node Speed 12.5 m/s (45 km/hr) Range: WLAN Physical 802.11 n 13 Mbps Data Rate: Characteristic: MANET Reactive Background AODV 40% Routing Protocols Traffic Maximum Transmission 100 -250 meters Range between Nodes: 0.001 W Frequency Band: 2.4 GHz Transmission Power: Packet Size:

512 Bytes

Buffer Size:

TABLE II.

32 Kbytes

B. AODV Active Route Timeout (Seconds) Net Transversal Time (Seconds)

3

2

Allowed Hello Loss

Node Transversal Time (Seconds) Path Discovery Time 3 RREQ Retries (Seconds) C. Applications: SIP Based VoIP 2.8

Number of Proposed Calls in 1800 Seconds

Average 16.32 189.48 1028.29 2142.74

Static Uniform RWP RWP All

IPv6 AODV: SRD in msec Minimum Maximum 5.11 41.03 7.42 469.27 684.36 3322.79 1408.15 13276.16

Average 18.76 265.23 1643.57 3255.35

B. Call Setup Perforamce The Call Setup performance for both IPv4 and IPv6 AODV MANET is shown in Fig. 5. The Call setup time has larger values than SRD as SRD is included in the total call setup time values. The call setup values for Static and Uniform scenarios are values for the best effort case, and the RWP and RWP All values are not meeting with the best effort values. In these scenarios we used the normal values for TTL which is 2 seconds with a three RREQ retries where the call setup time was relatively long. In further evaluations, we used to increase the TTL value to 3 seconds and the RREQ retries value to five.

5.6

175 calls

Call Duration

Caller

Callee

10 Sec

Node 24

Maximum Simultaneo us Calls

SIP Server

Node 1 User Agent (Caller/Callee) 1 Call at time

Static Uniform RWP RWP All

IPv4 AODV: SRD in msec Minimum Maximum 3.08 28.56 5.42 317.67 485.04 2141.25 1179.46 6147.81

0.04

VoIP Calls (Unlimited)

Unlimited Call/ Second

SRD VALUES FOR SIP OVER AODV MANET

Voice Codec: GSM 13 Kbps

VII. MEASUREMENT RESULTS A. SIP End-to-End Performance Metrics In this research study, the SRD performance metric of RFC 6076 was evaluated for the same AODV scenarios for IPv4 and IPv6 as shown in Table II. As no benchmarking values were proposed for the RFC 6076 metrics in general and for MANET in specific, this study implemented and evaluated the SRD performance metric on the simulation works to determine a reference values that can be compared for SIP signaling performance over MANET. Both the Static and Uniform mobility models represented the best implemented scenarios, as node mobility did not affect the overall performance of SIP signaling over MANET. The number of initiated calls and the calls setup times were at the optimum level, and the average SRD values were 16.32– 18.76 ms for Static and 189.48-265.23 ms for Uniform. However, with node mobility, the number of successfully initiated calls decreased and the call setup time increased. The average SRD values for RWP were 1028.29–1643.57 ms and 2142.74-3255.35 ms for RWP All. The results shows that when the SIP server moved, the call setup performance was the worst, and only a few calls were initiated, depending on the routing performance at the time of the call’s initiation. In general, there were very long call initiation delays in the

Figure 5. Average SIP call setup time in seconds

246

REFERENCES

The results shown that the performance of the call setup process over both IPv4 and IPv6 had enhanced with about 35-40% as shown in Fig. 6. This indicate that SIP signaling performance affected by the routing behavior of MANET and the call setup time could reduce with the adjustments of TTL values for RREQ and RREP routing parameters.

[1] [2]

[3]

[4]

[5]

[6] Figure 6. Average SIP call setup time in seconds with enhanced TTL and RREQ

[7]

[8]

VIII. CONCLUSION AND FUTURE WORKS In this paper, an investigation of the call setup performance of SIP-based VoIP over MANET AODV implementations was presented. A cross-layer AODV MANET design was proposed to enhance the performance of SIP signaling in the call setup process. The proposed approach used the SRD SIP performance metric of RFC 6076 to provide a reference value of time spent between the caller sending the initial call invitation message and receiving the acceptance message from the callee. As the SIP end-to-end performance metrics have yet to be determined with approved benchmark values, the initial simulation efforts of this research study used the SRD performance metric to evaluate the values of the best efforts scenarios in the Static and Uniform models. This value will be used as reference value to compare the values of the RWP mobility models. In addition, the simulation implementations with enhanced AODV routing parameters that used longer TTL values for RREQ messages shown good performance for the SIP call setup process compared with the implementations with normal default routing values. The performance results demonstrate that the proposed approach will enhance the performance of SIP signaling by about 35-40% over the default values of AODV MANET. Future works will implement the proposed CLAODV approach for call setup performance and will evaluate enhancement levels with different network saturation ratios in terms of UAS performance, bandwidth consumption, and CPU efficiency. In addition, the trade-off between SIP call setup performance and both; CPU performance and power consumptions will be considered.

[9]

[10]

[11] [12]

[13]

[14]

[15]

[16]

[17]

[18]

ACKNOWLEDGMENT [19]

The use of OPNET Modeler® version 17.1 in this research was facilitated through OPNET’s University Program.

247

J. Rosenberg, and et al, “RFC 3261: SIP: Session Initiation Protocol,” (2003). D. Malas and A. Morton, “Basic Telephony SIP End-to-End Performance Metrics,” Technical Report RFC 6076, Internet Engineering Task Force (IETF), 2011, URL: http://tools.ietf.org/html/rfc6076. M. Voznak, and J. Rozhon, “SIP back to back user benchmarking,” In Wireless and Mobile Communications (ICWMC), 2010 6th International Conference on, pp. 92-96. IEEE, 2010. J. Rozhon, Jan, M. Voznak, K.Tomala, and J. Vychodil, “Updated approach to SIP benchmarking,” In Telecommunications and Signal Processing (TSP), 2012 35th International Conference on, pp. 251254. IEEE, 2012. M. Voznak, and J. Rozhon, “Approach to stress tests in SIP environment based on marginal analysis,” Telecommunication Systems 52, no. 3 (2013): 1583-1593. J. Rozhon, and M. Voznak, “SIP Registration Burst Load Test,” In Digital Information Processing and Communications, pp. 329-336. Springer Berlin Heidelberg, 2011. J. Husic, A. Hidic, M. Hadzialic, and S. Barakovic, “Simulation-based Optimization of Signaling Procedures in IP Multimedia Subsystem,” 2014. V. Grasic, and A. Kos, “Structuring the RCS services on the IMS application layer Part I: Description and comparison parameters,” Elektrotehniski vestnik 79, no. 3 (2012). M. Kulin, T. Kazaz, and S. Mrdovic, “SIP Server Security with TLS: Relative Performance Evaluation,” In Telecommunications (BIHTEL), 2012 IX International Symposium on, pp. 1-6. IEEE, 2012. Mohamed Boumezzough, N. Idboufker, and A. Ouahman. “Evaluation of SIP Call Setup Delay for VoIP in IMS,” In Advanced Infocomm Technology, pp. 16-24. Springer Berlin Heidelberg, 2013. ITU-T TR Q-series supplements 51 signaling requirements for IPQoS (December 2004). Tuong Le, S. Cook, G. Kuthethoor, P. Sesha, G. Hadynski, D. Kiwior, and D. Parker. “Performance analysis for SIP based VoIP services over airborne tactical networks,” In Aerospace Conference, 2010 IEEE, pp. 1-8. IEEE, 2010. C. Perkins, E. Belding-Royer, and S. Das. "Ad hoc on demand distance vector (AODV) routing (RFC 3561)." IETF MANET Working Group (August. 2003) (2003). Z. Ren, J. Su, and W. Guo, “A Cross-Layer AODV routing protocol,” In Mechatronics and Automation, 2005 IEEE International Conference, vol. 4, pp. 2150-2155. IEEE, 2005. A. Pirzada, and M. Portmann, “High performance AODV routing protocol for hybrid wireless mesh networks,” In Mobile and Ubiquitous Systems: Networking & Services, 2007. MobiQuitous 2007. Fourth Annual International Conference on, pp. 1-5. IEEE, 2007. E. Borgia, and F. Delmastro, “Effects of unstable links on AODV performance in real testbeds,” EURASIP Journal on Wireless Communications and Networking 2007, no. 1 (2007): 32-32. N. Yawan, and P. Keeratiwintakorn, “AODV Improvement for Vehicular Networks with Cross Layer Technique And Mobility Prediction,” In Intelligent Signal Processing and Communications Systems (ISPACS), 2011 International Symposium on, pp. 1-6. IEEE, 2011. Y. Tang, J. Li, and Y. Yao, “A Cross-Layer Handover Management Scheme for SIP-based VoWLAN,” In Computer Science & Education, 2009. ICCSE'09. 4th International Conference on, pp. 425428. IEEE, 2009. M. Alshamrani, H. Cruickshank, Z. Sun, V. Fami, B. Elmasri, and E. Danish, “Signaling Performance for SIP over IPv6 Mobile Ad-Hoc Network (MANET),” In Multimedia (ISM), 2013 IEEE International Symposium on, pp. 231-236. IEEE, 2013.