Adaptive Service Discovery Protocol for Mobile Ad Hoc Networks

European Journal of Scientific Research ISSN 1450-216X Vol.49 No.1 (2011), pp.6-17 © EuroJournals Publishing, Inc. 2011 http://www.eurojournals.com/ejsr.htm

Adaptive Service Discovery Protocol for Mobile Ad Hoc Networks Cynthia Jayapal Department of Information Technology, Kumaraguru College of Technology Coimbatore – 641006, India E-mail: [email protected] Sumathi Vembu Department of Electronics and Communication Engineering Government College of Technology, Coimbatore – 641013, India E-mail: [email protected] Abstract We present an adaptive service discovery protocol that enhances the performance of service discovery. The existing service discovery procedures, uses either centralized, distributed or hybrid architectures. These architectures use different methods of service registration, advertisement, selection, discovery modes and state maintenance to improve the service discovery performance, but they use the conventional methods for selecting a core node that aids in all the service discovery phases. Our main focus is to use an adaptive core node election mechanism that changes whenever the load increases and is also robust against network failures. This enhances the performance of discovery due to the reduction in frequent handoffs. We use a distributed directory based service discovery mechanism that operates in a proactive mode with service advertisements to the core node and selects a provider based both on distance and service capability of the provider. Our simulation results show that our adaptive service discovery scheme performs better in terms of service discovery success ratio, control message over head, discovery delay and the number of hand offs, when compared to conventional schemes.

Keywords: Ad hoc networks, service discovery, adaptive leader election, service advertisement, service selection

1. Introduction Mobile ad hoc networks are networks with mobile nodes that are characterized with mobility, energy limitations and uses multi hop communication. All nodes in an ad hoc network can send, receive and forward data packets. A service is any entity or resource that is provided by one node and shared by other nodes. Service discovery protocols enable resource sharing among mobile nodes dynamically. Service discovery (SD) protocols are network protocols, which allow automatic detection of devices and services offered by the devices on a computer network [1]. Services are located based on user requests. A service request may be satisfied by several providers, or a service may have several candidate providers. To enable service coordination, the service provision framework should be able to track a group of service providers (SP) and their services. The challenges in service discovery are node mobility, frequent disconnections, data management and security. With rapid proliferation of mobile

Adaptive Service Discovery Protocol for Mobile Ad Hoc Networks

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devices, service provisioning is becoming one of the fundamental operations of an ad hoc network. The function of a SP is to advertise the available services, register its service with a registry node, update the service attributes and deliver the service to the requestor. The function of a service requestor (SR) is to query the SP information and forward a request either to the registry node or directly to the provider and receive the service from the SP. There are different mechanisms to improve the performance of the discovery as described in section 2. In directory based service discovery architectures, a SP registers or advertises the service with its descriptions. The details of the descriptions and the providers are maintained by the directory node. A SR can send a request either to the directory node or to the provider. Service coordination is an important task that is performed by the directory node in the discovery process. The directory nodes are responsible for maintaining and sharing the service information and acts as an agent for the requestor and the provider. It also aids in service delivery. The geographic position-based service provisioning makes use of the position of the mobile node is vital for both service discovery and delivery. In this case, the directory node also takes the responsibility of maintaining the location of the providers and the requestors. Most of the existing discovery schemes use the conventional methods of selecting a core node that aids in all the service discovery phases. These methods result in frequent handoffs and affect the performance of service discovery. We propose an adaptive service discovery protocol (ASDP) that uses an adaptive core node election mechanism to elect a node that change whenever the load increases and is also robust to any network failures. We elect a directory node based on an eligibility factor that considers the battery power of the directory node, its distance to the center of the geographical zone and speed. This makes the directory node more stable, reducing the handoffs. We use a distributed directory based SD mechanism where the service advertisement is done proactively, state maintenance is done in a soft state and service selection is done based both on the distance and service capability of a provider. We simulate the adaptive service discovery protocol and compare its performance with two other discovery procedures that use node ID and hash value to select a directory node. The performance evaluation shows that the performance of ASDP is better than the other two schemes. The rest of the paper is organized as follows. Section 2 provides a review of literature in service provisioning domain. Section 3 describes the geographic decomposition for service provisioning. Section 4 describes the role of a leader node and the adaptive leader election mechanism. Section 5 describes the adaptive service discovery protocol. In section 6, we evaluate the performance of the adaptive service discovery protocol and Section 7 provides the concluding remarks for this paper.

2. Literature Review There are various service discovery architectures proposed in the literature that use different discovery modes, service selection strategies and state maintenance methods [1] – [5]. In the directory less architecture, the mobile nodes do not distribute their service descriptions to the other nodes in the network. A SR node sends its request message to all the neighbor nodes by broadcasting. If one or more SP nodes can satisfy the request, a response is sent back to the SR by all the SPs. Here, the broadcasting leads to high bandwidth and energy consumption and is not scalable. In directory based architecture, the SPs register their services with the directory nodes and the service information is provided to the requestors, through these directories only. The crucial issue in directory based architecture is the election of the directory node. A directory can be either centralized or distributed. In centralized directory architecture, a central directory stores the descriptions of all the services available in the network. SPs advertise their services to the central directory using a unicast message. To access a service, the SR first contacts the central directory to obtain the service description, which is then used to interact with the SP. This helps in the communication between the SPs and the SRs, but it is hard to scale and leads to bottlenecks as the centralized directory limits its scope to devices within local SD domain. Moreover the central directory nodes energy depletes as its load increases. In distributed directory architecture, instead of a single directory node, multiple nodes share the responsibility [6].

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Cynthia Jayapal and Sumathi Vembu

These directory nodes constantly communicate with each other to spread and replicate service information. The directory nodes integrate to form the backbone of the network region. The SPs register their services with the directory which is geographically closer to its location [7]. Preserving service consistency and controlling communication costs are some of the major challenges involved. In hybrid directory architecture, the SPs register their services with service directories if they locate any in their vicinity [5]. If not, they simply broadcast service advertisements to all the nodes in the network. Here the response may come both from the SPs and service directories which leads to high message overhead. A SR can obtain service information using the reactive, proactive or hybrid service discovery modes. In reactive mode [3], the SR sends a request directly to the coordinator or the SP, when needed. The request may be sent as a unicast, multicast or broadcast packet. This increases the network traffic. In proactive mode [8] [9], the SP advertises or registers its service with the coordinator or the directory nodes. The advertisement can be sent to all coordinators or to those within the SP’s domain. Service advertisement can also be multicast to a selective group of directory or backbone nodes. In hybrid mode, both proactive and reactive communication takes place. The SPs advertise their services periodically to the backbone nodes and the SRs query the backbone nodes for service information, when required. If the service is not available the request and reply are made directly. There are two service discovery strategies that can be employed in this mode – greedy strategy and conservative strategy [10]. In the greedy strategy both service advertisement and service requests are broadcast to all nodes, while in conservative strategy only a set of nodes, generally the backbone nodes receive the service advertisements and service requests. There are various service selection methodologies to select a SP. A service query may result in multiple SPs. A proper selection mechanism is needed to handle multiple responses. The technique may either be manual or automatic based on some criteria like current load of a SP, bandwidth available for the communication channel between the SP and the client, velocity of the SP. Moreover, the service selection algorithm can be run either directly by the SR or can be distributed among the backbone nodes. Service selection may either be route specific [11] or service specific [4]. In route specific service selection, the SP which is reachable with a minimum number of hop counts from the SR is chosen. Though the cost of communication is reduced, quality of service cannot be guaranteed. In service specific selection, among the multiple SPs, the SP with the highest capacity to serve is chosen. The effectiveness of service is given priority over route and cost of communication. Service state maintenance is required to maintain service information in MANETs, owing to frequent changes in service availability. Failure to do this will lead to inconsistency. Service state preservation can be done using two methods, hard state maintenance and soft state maintenance. In hard state maintenance, the SP must inform the coordinator node if it moves outside the region. This de-registration of services is not always guaranteed due to frequent node movements and disconnections. In soft state maintenance, every service is associated with a time limit, until which the mobile node offers the service. For service state maintenance, polling or notifications can be used. In polling, the SRs approach the SP to obtain service information. Polling can be performed either on demand or proactively. In notification, the SP sends notifications about service state changes to registered clients. Notifications lead to increase in the number of control messages and hence traffic [12]. Leader election is used in number of applications such as key distribution, routing coordination, sensor coordination, group communication, cluster coordination. The role of a leader is to control a group of nodes periodically and to act as an agent on behalf of them. In wired network the leader can be a static server with enormous processing capability and memory capacity. But in an ad hoc or sensor network the role of a leader and the responsibility of a node to act as a leader may vary time to time. The leader election problem is a problem of electing a unique leader periodically based on the nodes current capability [13]. In ad hoc networks, nodes with similar characteristics are often grouped to form a cluster that changes adaptively. For each cluster, a cluster head is elected periodically to act on behalf of the cluster nodes. The change in leader is essential for an ad hoc node, due to the limited battery


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power of the node. In sensor networks, the role of the leader or cluster head is even more important as it performs data aggregation, which greatly reduces the traffic [14].

3. Geographic Decomposition for Service Provisioning Scalable Geographic Service Provision Framework for MANETs (SGSP) [8] and Distributed Hashing for Scalable Multicast in Wireless Ad hoc Networks (HRPM) [15] are the two service discovery techniques; we use to compare our adaptive service discovery scheme. SGSP uses node ID, HRPM uses hash value and our adaptive algorithm uses an eligibility factor to select a core node within a geographic zone. SGSP provides a self-configuring, distributed, hierarchical structure. It uses scalable membership management to manage the dynamic collection of service nodes and their services. SGSP is based on geographic unicast routing, in which every node is aware of its position and the intermediate nodes make packet forwarding decisions based on local topology only. The entire network is divided into manageable square zones virtually. Every zone has a local coordinator (LC) for managing the nodes in that zone and one central global coordinator (GC) is chosen. The GC keeps track of aggregated information of all the zones, while the LC has information about every node within its area. Service Coordination is done by the participating LCs and the GC. In HRPM, the entire network is divided into equal sized square cells. Within each cell there is one access point (AP) and one rendezvous point (RP) for the entire network, for each of the service group. Every node has the information about two different hash functions to find the position of the AP and RP. The RP maintains information about all the service requests from different zones. The SP requests for this information from the RP and constructs a multicast tree to deliver the service. HRPM uses hierarchical routing based on greedy geographic forwarding algorithm. We use a distributed directory based architecture, where we divide the entire geographic region into zones as in [8]. We elect a Local coordinator (LC) for every geographic zone and a Global Coordinator (GC) for entire region that is common to all the multicast groups, unlike the other schemes that use one coordinator for every multicast group [15]. The LC is responsible for maintaining the position information and service details of all the requestors and providers within a zone. The service is registered by a provider with its LC and when the requestor needs a service it forwards the request to its LC. The LC finds a suitable provider with the available service information or through the GC.

4. Leader Election for Service Provisioning 4.1. Role of a Leader Node in Service Provisioning The role of a leader node is crucial in the different phases of service provisioning such as service advertisement, service discovery, service coordination and service delivery. In directory based architectures, the SPs register their services with the directory or leader node. In reactive service discovery mode, a SR forwards the service request through the leader node. The service coordination is a process of coordinating all the SPs, requestors and available services. This is done by the leader node periodically and the service details are updated. Service delivery involves distributing a service to all the requestors. Hierarchical service provisioning schemes divides the geographical area into various zones and selects a leader node for every zone. The SP then constructs a tree from itself to the zone leaders of all the requestors and then delivers the service to them. 4.2. Adaptive Leader Election We use a vote based election algorithm [16] that elects a core node (LC or GC) dynamically. A node calculates its eligibility factor (EF), based on the distance to the zone center, remaining battery power and average speed. 1. When a new SP or requestor enters a zone, it sends a hello message to learn about the core node to its neighbors.

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Cynthia Jayapal and Sumathi Vembu 2. All neighbor nodes reply with a beacon message, using which a neighbor table is constructed. 3. If there is no other core node, the new node announces itself as a leader and initiates an election procedure to elect a new core node. 4. To elect a core node, initially all the nodes in transmission range to the center of zone calculate their eligibility factor and send them to the leader. 5. The leader elects a node with the highest eligibility factor within a zone, as a new LC and amongst all zones and within a radius of r/2 from the center of the geographical region, as a new LC. 6. The node with the second highest ranking is stored as a backup node. If the core node fails or gets overloaded, the backup node becomes the core node. 7. Whenever the eligibility factor of the core node becomes less than the threshold, the election procedure is initiated to select a new core node. 8. All service records are transferred by the old core node to the new core node.

5. Adaptive Service Discovery Protocol (ASDP) Table 1, illustrates the important tables used by us for service provisioning, with their functions, descriptions and update details. Table 1: S. No.

List of tables maintained

Table name

Stored at

Function

1.

Service Provider (SP) Table

SP

To store service parameters.

2.

Member Table

SP

To record details of the service requests received.

3.

Global Core Node(GC) Table

GC

4.

Local Core Node (LC) Table

LC

5.

Service Requestor (SR) Table

LC

To maintain service requests within the zone.

6.

Neighbor Table

Nodes

To record details of the Neighbors.

To coordinate activities of all LC’s. To store details of all the SP’s and their services within the zone.

Description Service Parameters: Provider ID Provider Location Advertisement Seq. No. Service Name, Service ID, Service Life Time SR ID SR’s LC ID SR’s LC Location Service ID LC ID LC Location Service Parameters Service Parameters SR ID SR location SP ID Service ID Neighbor ID Neighbor Location Flag (=1 if coordinator)

Updated when

Updated by

Change in service parameter information.

SP

Service request is received.

SP

LC moves, Change in EF, Change in service information.

LC

SP moves, Change in service information.

SP

Service request or reply is made.

SR / SP

Change in location

Neighbor nodes

5.1. Service Registration and State Maintenance All the SP in a zone wishing to provide any service, register their service with the respective LC by sending the associated service parameters like advertisement sequence number, service name, service ID, provider ID, location and service lifetime. The LC on receiving this information updates the LC


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Table. On expiry of the lifetime of a service, the corresponding entry is deleted from the table. Any SP, willing to extend its service, can re-register with the new lifetime before expiry. A SP, that wishes to withdraw providing a service, directly informs its LC and the LC of all the SR zones. The LCs of all the zones, advertise the LC Table contents, to the GC periodically and the GC updates its GC Table. The LC Table and GC Table are used as a service cache by the coordinator nodes. The coordinator nodes overhear the service advertisement and reply messages from the service requestors and providers. The entry is refreshed on hearing an advertisement with a greater sequence number or an entry is added if not found. The entries in the table are deleted after expiry of the service lifetime. 5.2. Service Discovery and Service Selection Figure 1, illustrates the service discovery procedure. Any SR node which requires a service sends a SREQ with its NID and service details to its LC. On receiving the SREQ the LC checks the LC Table if there is a provider within the same zone, if so the SREQ is forwarded. Otherwise, the LC checks the SR Table to see if there is already a request for the same service within the zone, if so the SREP is forwarded directly to the requestor after updating the SR Table. If the SP is known to the SR’s LC, the SREQ is directly forwarded to the SR’s LC. If a SP is not within the zone and is not known to the SR’s LC, the LC forwards the SREQ to the GC. The GC checks the GC Table for a LC with a SP, providing the requested service. If found the request is forwarded to the LC of the SP. Any coordinator node that hears a SREQ forwards it directly to the provider, if it is known. On receiving a SREQ, the SP’s LC gets the position of the SP from LC Table and forwards the request to the corresponding SP. The SP on receiving the SREQ sends a SREP to the SR after updating its Member Table. If there is no match in the GC Table, the SREQ is flooded. In MANET, several SPs may provide the same service. The core node chooses the SP, before forwarding the SREQ packet to the SP. The SP is chosen by considering the distance between the SR and SP, the remaining lifetime of the service and the EF. This helps to prevent a single provider being overloaded and also avoids redundant service delivery from all the providers like in [15].

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Cynthia Jayapal and Sumathi Vembu Figure 1: Service Discovery in ASDP

5.3. Location Update Every node maintains the location of its neighbors and its LC. All LCs maintain the location of the GC and the GCs maintain the location of all the LCs. Whenever a node enters a new zone it sends a HELLO message to all its neighbors in the Neighbor Table. The neighbor nodes receiving this message send back a BEACON message, with their location and LC information. If the sender finds that it has moved to a new zone, it associates itself with the LC of that zone. If no Beacon is received, it assumes that it is the only node in that zone and hence considers itself as LC of that zone. It sends an update packet to the GC indicating its presence. Every node stores and maintains details of its neighbors in its Neighbor Table. Location update is done by a GC to all the LCs, LC to all the SRs and SPs in its zone, SR and SP to LC when it moves more than 100m. A node updates its location to all its neighbors, if it moves beyond the transmission range.


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6. Performance Evaluation 6.1. Simulation Overview The proposed scheme was implemented using NS2 [17] on LINUX platform. We have included the energy model with initial energy set as 0.5 Joules, txPower as 0.3 watt and rxPoweras 0.6 watt. We have assumed the MANET region as a square region of size 2400mX2400m. For virtual zone construction, the zone-size is taken as 800m, which resulted in 9 different zones with ZIDs (0,0),(0,1),(0,2),(1,0),(1,1),(1,2),(2,0),(2,1), (2,2). The simulations were run for varying network size with Vmax values ranging from 10 to 200 m/s and with different pause time. The simulation result was gained by averaging over 10 runs. The nodes were randomly distributed using Random Waypoint Model. We have assumed that at least 25 % of the total number of nodes in the network acts as SPs. Each of these SP provides different service types with varying lifetimes. A service of a particular type is uniquely identified by Service ID. A SP is assumed to provide a maximum of 5 different types of services. SPs are simulated to provide similar service types. For evaluating the EF of a core node, we gave 70% preference for remaining battery power, and 15% preference for both speed and distance to center. 6.2. Simulation Results We have studied the following metrics. Service discovery success ratio - It is the ratio of the number of service request message issued, to the corresponding hit message. In the simulation, the service request message was sent by the SR and the hit message was sent by the SP. To study the effect of moving speed on Service discovery success ratio, we varied the maximum speed of the nodes (V max) from 10 m/s to 200m/s. Figure 2, shows that ASDP performance is better than SGSP and HRPM. We also infer that the change in moving speed does affect the service discovery success ratio. The success ratio is more, when the provider is within the zone and when it is known to the LC. Figure 2: Effect of speed on service discovery success ratio

Control message overhead- It is the total number of control messages forwarded for service discovery and hand offs. Figure 3, shows the effect of speed, pause time and group size on control message overhead. It shows that the ASDP has less number of control message transfers because of the more stable core nodes and less number of hand offs. ASDP and SGSP use similar provider selection mechanism. Therefore the difference in overhead is only due to the stable core node of ASDP. The

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Cynthia Jayapal and Sumathi Vembu

overhead in HRPM is more because, it sends control messages to all the available SPs and has frequent handoffs. Figure 3(a): Effect of speed on control message overhead

Figure 3(b): Effect of pause time on control message overhead


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Figure 3(c): Effect of group size on control message overhead

Average discovery delay – It is the average time interval between a service request and service reply. To study the effect of request load on the discovery delay, we varied the number of SRs and observed that with increase in the number of requests the delay increased for all the three techniques. Figure 4, shows that the discovery delay is more in HRPM as the hash value is computed to find the AP and RP location and also because of the frequent change in core nodes. Performance of SGSP and ASDP are similar under light load. As the load increased the average discovery delay of SGSP increased linearly but there is marginal increase of delay for ASDP. Figure 4: Effect of number of requestors on average discovery delay

Joining delay – It is the time difference between a node joining the group and receiving its first data packet. To study the effect of the total number of nodes on the joining delay, we varied the total number of nodes in the network from 30 through 50. It is observed from Figure 5, that SGSP and HRPM has higher joining delay than ASDP and it increases with increase in number of nodes. We infer this is due to factors like increased distance between the coordinator and the new node. In ASDP the delay is almost stable owing to optimum distance between the coordinator and new node and the SP is directly intimated about the request. In HRPM, before each delivery the SP has to get the membership update from the RP and hence the joining delay is more.

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Cynthia Jayapal and Sumathi Vembu Figure 5: Effect of the number of nodes on joining delay

Election rate- It is the number of times the election procedure for coordinator selection is invoked. To study the effect of the total number of nodes on the election rate, we varied the total number of nodes in the network from 30 through 50. It is observed from Figure 6, that HRPM has the highest number of elections because whenever a new node comes near the hashed location, the core node changes and the changes are more when the mobility is more. In SGSP, the leader node is consistent until it moves out of the zone but the nodes battery power is not taken into consideration. In ASDP election happens only when EF of a node drops below the threshold limit. When the leader changes are more the control overhead is also more. Figure 6: Effect of speed on number of leader change

7. Conclusion Our adaptive leader election and service discovery procedure, selects a core node that is reliable and stable. This in turn reduces the number of hand offs and the control overhead involved in service discovery. Our simulation results shows that the performance of ASDP is better than the other algorithms that use node ID and hash value for leader election, in terms of success ratio, discovery delay and control message overhead. The ASDP protocol can be enhanced by dynamic and cooperative cache update mechanism. We also propose to advertise the popular service to all back bone nodes to improve the discovery delay.


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References [1]

[2]

[3]

[4]

[5]

[6] [7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

Seyed Amin Hosseini Seno, Rahmat Budiarto and Tat-Chee Wan, 2007. “Survey and new Approach in Service Discovery and Advertisement for Mobile Ad hoc Networks”, International Journal of Computer Science and Network Security 7, pp. 275-284. Christopher, N., Ververidis and George, C., Polyzos, 2008. “Service Discovery for Mobile Ad Hoc Networks: A Survey of Issues and Techniques”, Communications Surveys & Tutorials, IEEE Publication 10, pp. 30-45. Adnan Noor Mian, Roberto Baldoni and Roberto Beraldi. 2009. "A Survey of Service Discovery Protocols in Multihop Mobile Ad Hoc Networks", IEEE Pervasive Computing 8, pp. 66-74. Vincent Lenders, Martin May and Berhard Plattner, 2005. “Service discovery in mobile ad hoc networks: A field theoretic approach”, Elsevier Journal on Pervasive and Mobile Computing 1, pp. 343-370. S. A,. Hosseini-seno1, B., Pahlevanzadeh, T.C., wan, R., Budiart, and M.M., Kadhum, 2009. “A Distributed Resource-Management Approach in Manets”, Journal of Engineering Science and Technology 4, pp. 142 – 153. F.,Sailhan and V.,Ussarbtm, 2005. “Scalable service discovery for MANET”, IEEE conference on Pervasive Computing and Communication, pp. 235 -244. Hassan Artail, Khaleel Wafiq Mershad and Hicham Hamze, 2008. “DSDM: A Distributed Service Discovery Model for MANETs”, IEEE Transaction on Parallel and Distributed Systems 19, pp.1224 – 1236. Xiaojing Xiang and Xin Wang, 2007. “A Scalable Geographic Service Provision Framework for Mobile Ad Hoc Networks”, IEEE conference on Pervasive Computing and Communication, pp. 151-160. Xiaojing Xiang, Xin Wang and Zehua Zhou, 2006. “An Efficient Geographic Multicast Protocol for Mobile Ad hoc Networks”, IEEE World of Wireless, Mobile and Multimedia Networks, pp. 73 -82. Honghui Luo and M., Barbeau, 2004. “Performance Evaluation of Service Discovery Strategies in Ad Hoc Networks”, Second Annual Conference on Communication Networks and Services Research, pp. 61 – 68. Alex Varshavsky, Bradley Reid and Eyal de Lara, 2005. “A cross layer approach to service discovery and selection in MANETs”, IEEE International Conference on Mobile Ad hoc and Sensor Systems, pp.466. C., Dabrowski, K., Mills and J., Elder 2002. “Understanding consistency maintenance in service discovery architectures during communication failure”, Third International Workshop on Software and Performance, ACM, pp. 15 – 20. Sudarshan vasudevan, Jim Kurose and Don Towsley, 2004. “Design and Analysis of a Leader Election Algorithm for Mobile Ad Hoc Networks”, IEEE International Conference on Network Protocols, pp. 350 -360. Qi Dong and Donggang Liu, 2009. “Resilient Cluster Leader Election for Wireless Sensor Networks”, Sixth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 1 – 9. Saumitra M.Das, Himabindu Pucha, and Y., Charlie Hu, 2008. “Distributed Hashing for Scalable Multicast in Wireless Adhoc Networks”, IEEE Transactions on Parallel and Distributed Systems 19, pp.347-362. Cynthia Jayapal, Sumathi Vembu and Arul Jothi Subramanium, 2010. “Adaptive Service Provisioning for Mobile Ad Hoc Networks”, ICTACT Journal on Communication Technology 3, pp. 166-171. NS-2 Simulator, http://www.insi.edu/nsname/ns. Accessed 10 December 2008.