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Coalitional game theoretic approach for ieee 802
1.
International INTERNATIONAL Journal
of Computer JOURNAL Engineering OF and COMPUTER Technology (IJCET), ENGINEERING ISSN 0976-6367(Print), & ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME: www.iaeme.com/IJCET.asp Journal Impact Factor (2014): 8.5328 (Calculated by GISI) www.jifactor.com IJCET © I A E M E COALITIONAL GAME THEORETIC APPROACH FOR IEEE 802.11E STANDARD BASED ON INCENTIVE AND CREDIT Dr. Sanjay Tejbahadur Singh Department of Computer Engineering, P K Technical Campus, Chakan, Pune 50 ABSTRACT Vehicular ad hoc network (IEEE 802.11e) is dynamic network where independent identity node helps each other to forward the message. But some time node may not be interested in forwarding the message. Thus it is essential to give node some incentive to participate in message forwarding game on the basis of credit based system. Our approach based on credit based system as well as coalitional game theory proposes an hybrid approach to solve this issue. Existing message forwarding technique like proportional, receipt counting and Frame have not addressed load balancing issue. We have further extended our system by applying load balancing on credits since we don’t want credit to be concentrated on limited number of nodes. Our proposed approach outperforms all above existing approaches by increasing delivery ratio with 16 to 20% and reducing Virtual Currency Center (Vcc) credit time computation by 46 to 48%. Index terms: Coalitional Game Theory, Credit Base System, IEEE 802.11e Standard, Incentive Scheme, Load Balancing. I. INTRODUCTION Vehicular ad hoc networks (VANETs) consist of smart vehicles and roadside equipment to support communication between vehicles. The assumption is that in VANETs, each vehicle has OBU (On Board Unit) for optimized message delivery among vehicles. To solve the problem of intermittent connectivity between vehicles under certain circumstances like night time or rural area one solution point of view is store-carry and- forward message switching in VANETs. Thus depend on type how message get delivered different routing protocols (e.g., [1]–[5]) have been proposed to
2.
International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME increase the success rate of message delivery. Availability of good protocol doesn't guarantee the utilization of protocol in the application. The question related to node behavior for cooperating in VANET arises due to two reasons. First an individual user can be selfish for its VANET node. Therefore that individual may not be in scène where it will help other node to forward their message due to its limited resources like its own storage space. Second reason is that depend on protocol conformability probability of selecting special kind of vehicle is more as compared to normal vehicle. In [6] proposed system routing protocols, nodes from same community always get preference as compared to normal vehicle to forward the message. Another situation is that where many nodes are interested in forwarding the message but most of their resources like wireless bandwidth or storage space get consumed during communication. Therefore to save their resources they have to deviate from predefined protocol unwillingly. Hence it is highly important to involve more number of nodes to cooperate in forwarding messages. Today the automotive industry controls the vehicle manufacture. However, after the vehicles are sold, they are under the full control of the users. So if user wants, he can consult with some expert hackers to change the VANET protocols running in the vehicles and to make themselves the “free riders” in the network without contributing anything. Hence, we believe that rather than making forceful interaction in VANETs which is not easy to achieve, try to design system will take advantage of user selfish nature. Currently there are two types of existing incentive mechanisms for stimulating cooperation in 51 wireless networks: Reputation based approaches (e.g., [7],[8]) In Reputation-based approaches behavior of nodes gets observed by neighbor nodes and to stimulate cooperation among uncooperative nature nodes punishment is given. But in VANETs to observe whether node has deviating behavior of a selfish node is very difficult. Since the guarantee of node neighbor will remain same is very less. Today’s work on incentive-aware routing in delay-tolerant networks [10] tit-for-tat mechanism has been used where neighbor punish or give reward to node based on history they have observed. However, in VANETs the probability of two nodes will be meet is very low if compare it with history data that can be store within node memory. But this scenario will be different for centralized controller authority. Credit-based approaches Credit-based mechanism motivates nodes to cooperate among themselves to get proper reward. In existing works like traditional multi hop networks many question related to credit based system had got asked and based on that solution was suggested. The question like how many credit node should receive, how the end to end connection will set the credit based mechanisms. In this paper, we have use coalitional game theory to solve the forwarding cooperation problem in VANETs with its vulnerability problem of load balancing. We propose an incentive and credit based scheme for VANETs and analysis of it for coalitional games theory. In addition, we extend our approach to take the limited number of credits of each node for load balancing. In particular, we say that in coalitional game theory VANET nodes act as players and they cooperate in forwarding message if they run the routing protocol. In game theory when the players in a subset decide to cooperate within the subset, the subset is called a coalition. In particular, we are creating scenario of grand coalition where all nodes will receive incentives to develop a grand coalition.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME 52 II. RELATED WORK A number of DTN routing protocols have been proposed, out of which most of can roughly be classified into two categories depend on their strategies: • Flooding (replication)-based protocols (e.g., [16] and [17]) and • Forwarding-based protocols (e.g., [18], and [19]) Flooding-based protocols give guarantee of message to reach destination by making replica of message and thus messages will reach to destinations with higher probability. For example, in epidemic routing [9], node with copy will give copy to all the nodes to whom he meet. In [6] to forward message evolutionary game has proposed where community of vehicles (like bus community, taxi community) are created from sample space of vehicles. But in this approach as number of community increases success probability decreases. Again in [11] Broadcast storm problem has been solved using the volunteer’s dilemma Game but as amount of Vehicle increases Percentage of performance stability decreases. On other hand in [12] reputation-based cooperative game has been played but then in that also player participate in the game by the force of neighbor to deduct its credit if it does not forward the message rather interest of its own. Another secure incentive framework related to commercial ad dissemination has been suggested in [13]. In this protocol mapping nature of node message sending is one to many only. But in case of single or selective number of destination this protocol is not applicable. Again in [14] routing scheme proposed where protocol ensures that node follows the protocol for routing decision. While our objective is motivating nodes participate in message forwarding game and at same time make routing decision to balance number of credits on the nodes. III. PROBLEM STATEMENT A. Need of Load balancing in Credit Based System In credit based system there are some node with large no of credit point and some node with less number of credit point since there is no constraint on participation of node in the game. There would be situation occur where node want to send data may not succeed due to lack of credit. Hence probability of participation is inversely proportional to number of credit in node. Therefore with improved approach in coalitional game theory for message forwarding there is need of way to preserve same number of credit on most of node. B. Coalitional Game and the Core Formally, a coalitional game formation processes same as defined in [20] as follows: Definition 1: In this coalitional game we are considering ordered pair (N, v), where N is the set of players and subset of N will be called as coalition, and v is a characteristic function which will assign a real number to each coalition for which ranger varies from 2N to R such that v() = 0. Whenever all subset of N coalition will come together they will form grand coalition and v will payoff of that coalition. For example coalition S, v(S) is the amount of overall benefit when all nodes within coalition S will cooperate with each other.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME Definition 2: In this a coalitional game the core C(v) is the set of payoff allocation vectors x RN, s.t. 53 (1) where xi is the payoff allocation to player i. Each player will get benefitted in same way in this game if they work as part of coalition game or do same work individually. C. Coalitional Game Formation in VANET Message Forwarding We consider a VANET with a set of mobile nodes where message will get forwarded if two nodes come within the transmission range of each other. Therefore at basic level we are considering general routing protocol R. In this model, we are redefining routing protocol and assuming that every node will follow only this routing protocol. In the VANET, directly messages are delivered to the destination if destination node is within range of source node else forwarded by intermediate nodes before reaching to their destinations. When we say message has been forwarded at that time node may or may not keep copy of message before forwarding. In VANET the forwarding coalitional game (N, v) starts when the message is generated by source (src) and ends when message (or its copy) successfully received by the destination (dest) or discarded by an intermediate nodes during communication. We can say two nodes are in coalition if communication between these two nodes occurs the way defined in R protocol. IV. SYSTEM ARCHITECTURE Fig 1: System Architecture
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME The VANET proposed system architecture consist of smart vehicle equipped with OBU and virtual currency center (Vcc) which act as central authority. Vcc can be nearby some infrastructure like petrol pump or gas station. When vehicle pass nearby Vcc then communication between Vcc and node occur. During that meeting period information about credit gets exchanged. In many other incentive scheme Vcc has been proposed like (e.g., [13]). Some system proposed Vcc consists of nodes virtual account which keeps the information about node virtual currency in form of credits. Credits are unit of virtual currency and it gets distributed among node account by Vcc. It is not compulsory for node to connect to Vcc all the time. Initially Vcc will put equal amount of currency in each node account. If a node wants to send message then that node become source node and where that message wants to be get deliver that node become destination node. All other nodes which help source node to forward message to destination node are called as intermediate nodes. If any node helped another node in forwarding the message then for that work credit will be get putted into node and whenever node come in contact with Vcc its account status get updated. When source node want to send message to destination, it will predict number of intermediate node will take part in forwarding the message and it will put that much credit in message packet. Buttyan and Hubaux in [15] proposed stimulation approach where nuglets act as virtual currency. They also proposed two payment models which are the Packet Purse Model and the Packet Trade Model. In the Packet Purse Model, the sender send message packet with nuglet in it. As message get forwarded node to node nuglets share by intermediate node. But in this method if packet runs out of nuglet then packet drops occur. In case of Packet Trade Model, packet get buy from source node to intermediate node and get sold to next node. Such process get repeated until packet received by destination node that means indirectly destination node pays for message forwarding. But in our case we are trying to avoid issue of both models. In our case when message packet run out of credit then instead of dropping that packet it will get store in intermediate node until Vcc arrive. In Vcc message packet get refill from source node account and continue with its journey. If number of intermediate require is less as compared to predicted intermediate node then message packet arrives at destination side with remain credit. At that time destination will add those extra credits into source account whenever it comes in contact with Vcc. Once destination node receive message next thing is acknowledgement (ACK). Destination will send ACK to source node same way as that of message but only difference is number of credits get share. The number of credit get node from message is always greater than ACK credit. To implement this system smart vehicle equipped with OBU as well as a tamper-proof hardware. Tamper-proof hardware help node in correcting the amount of message packet for addition or deduction of credit. Credit distribution during message forwarding also divided into 3 types. First is normal message which will get forwarded by intermediate node and appropriate credit will be get putted into node. Second is ACK message for which process will be same but amount of credit earn by node by forwarding ACK is less as compared to normal message. Third is emergency message where no credit will involve. Emergency message are higher priority message which will be get used in case of emergency situation like accident, bridge collapse etc. Normal message and ACK will be forwarded in end to end terminal way while emergency message will be get forwarded in flooding based way. The work of VCC has been divided into 3 categories as follow 54 • update credit status of node: Vcc will check node current status and update that status within its virtual account whenever node passes nearby it.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME 55 • refill message packet: If during message forwarding message packet credit becomes zero and when such message packet node pass Vcc area at that time message packet get refill from source node account. • Sell credit to node: It is also possible to buy credit from Vcc using money. A. Allocation of Payoff We are trying to design Grand Coalition game where payoff allocation will be different for different player node and message type. Like in case of emergency message situation priority will be given to message rather than credit allocation. In this game all node will get different credit allocation according to their work. Therefore, we consider payoff should be given differently for different node as follow: • Payoff Allocation to the Source Node: Credit for message forwarding will get deducted from source node since its source node who wants to send the message. • Payoff Allocation to Intermediate Nodes: Intermediate nodes are nodes who actually doing the work of forwarding the message. Therefore credit distribution will actually happen in between intermediate nodes and message packets only. • Payoff Allocation to Destination Nodes: Destination node will not get any credit since it is doing any work like forwarding the message and again it is not node who initiated the message forwarding. It is just accepting message which addressed by source node. B. Mathematical model At start all node will be credited by same amount by Vcc. If (SaccMinbal) then Obtain iddestination and set source node as idcurrent While message not reach to destination { Check If (Msgcredit 0) then { If iddestination within range of idcurrent then send message directly to it Update the Sacc for remaining credit Else check Qlist for nodes with credit within range. { If Qlist nodes credit are same then send message from idcurrent to idperimeter ,drop credit share to node and set idperimeter idcurrent Else send message from idcurrent to idthreshold drop credit share to node and set idthreshold idcurrent } } } Fig 2: Protocol to balance load of Credits
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME In this model Sacc is Credit of source account. Minbal is minimum balance node should have to forward message. In some cases this balance could be minimum credit required to reach message to destination by considering predicted intermediate node. Destination address is denoted by iddestination and current node is denoted by idcurrent . How much credit has been left in message packet is denoted by Msgcredit. Current node will maintain Qlist which will contain list of all nodes present within range it with their credit information. Qlist will also contain two node information which are idperimeter and idthreshold. idperimeter is node reside on perimeter range line of current node and towards direction of destination node and it get selected if all nodes within range of current node having same credits. idthreshold is node with minimum number of credit in Qlist of current node. . In [20] credits given to node on the basis of number of receipt (meeting records) they are having. Those receipts get submitted to Vcc and at that time node gets credits. That means node credits information for itself cannot be updated unless and until it come in contact with Vcc. During two Vcc connection period, node travel with its old information of credits obtained by previous Vcc. Thus if we consider this approach for our improved LB protocol then node selection will be based on its old credits information. But in our game each time message get forwarded by intermediate node credits get putted into node at that time only. Therefore every time message get forwarded node itself get updated on that time only even if does not come in contact with Vcc. Hence next time when another node makes the decision to select node for forwarding the message, it always gets freshly updated credit information. Another point in [20] is that every intermediate node will get credits iff message successfully delivered to destination. That means if message does not reach to destination all efforts made by intermediate node to forward it get wasted. But in our system if node utilizing their resources to forward message they will get credit for that. Therefore every node knows each time they will forward the message, they will definitely get credits rather than indefiniteness of successful message delivery credits allocation. Hence it leads more number of nodes to participate in game. 56 V. ANALYSIS In analysis section we compare result of existing game theory system with our proposed system. We use the ns-2 simulator to evaluate the performance of our algorithm in terms of the message loss ratio, delivery rate, etc. We simulated a traffic scenario with a high vehicle density. The VCC is located at roadside and vehicles can associate with the VCC when they come in contact with it. The NS-2 simulation parameters are the following: 15 nodes placed at random in an area of 700m x 500m. We utilize the VANET mobility model [20], together with real data from the Malaga, Spain database to generate the vehicles’ mobility traces. The default transmission range is 50m. The inter-vehicular distance varied from 5 m to 50 m to simulate the scenarios with different traffic densities. We assume each vehicle contain interface queue capable of storing maximum 60 packets in it and packets will be deleted when the buffer is full. In all of the simulations, packets are 100 KB in size, and each signature is 128 bits. Inter-vehicle Messages are sent by vehicle 100kbps CBR data rate at each vehicle. IEEE 802.11a is used to simulate the medium access control layer transmission protocol as was done by [5]. The bandwidth of the channel is 6 Mb/s. A. Credit Load Balancing The first aim our experiment to verify whether our incentive scheme with help of Improved LB can balance Credits on more number of nodes or not. In this experiment we formed coalition and assume that every node is going to follow Improved LB protocol only. We vary size of coalition according to node behavior and to testify different scenario.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME Fig. 3: Average Credits on Each node Fig. 4: Credits on Each Node at Time 42.811324 In one of the scenario we include 15 active nodes to form five coalitions, out of which three coalitions consist of 3 nodes while other two consisting of four and two nodes respectively. We have recorded the average number of credits on each node after 180 minutes and shown in Fig. 3. We observe that credit has been distributed in such way that credits balance would not be concentrated to limited number of nodes Credit balancing among node does not occur after some periodic time. Instead every time before message forwarding dynamic node selection occur which based on node credits condition. To verify our system we took result of different scenario with same number of active nodes after 42.811324 minutes. Fig. 4 shows credits available on each node. From Fig. 4 it is observed that number of credits balance has been achieved. Therefore from result we can say we are trying to eliminate situation where interested node cannot send message due to lack of credits. 57 B. Packet Loss ratio Fig. 5: Packet Loss Ratio vs Node per Km Fig. 6: Average Reward Vs Contribution In application of message forwarding packet loss on the network could lead to serious problem. In case of weighted Graph 60% message loss observe for light traffic while in other hand
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME for blind flooding message loss is 55%. For forwarding dilemma game message loss percentage is low as compared other two which is 45% as shown in fig, 5. 58 C. Nodes Contribution Reward In fig. 6 we have compare different scheme for rewarding the node according to its contribution. Each node gets credit according to its contribution in the game. Most of scheme gets less average credits due their scheme rule. The rules such as node will get credits if and only if message successfully delivered to destination. But if some intermediate node helps another node to forward message and after some time that message gets loss. As its not intermediate node fault since intermediate node has done its work therefore there is no any reason to waste its efforts by not giving credits to it. But in our system as contribution of node increases average rewards also increases since we are giving credits during message forward process only. D. Success Probability Fig. 7: Success Probability VS Rewards Fig. 8: Delivery Ratio for different scheme Fig. 7 shows success probability of Evolutionary Game [6] and Improved LB. The Success probability for single species in evolutionary game keeps increasing when rewards increased and when reward (G) become 2.4 its success probability reach to 1. That means as rewards increases, number of nodes quantity to acquire credits also increases. On other hand success probability for improved LB from very start almost 1 because in Improved LB protocol we are selecting needy node (node with less number of credits) out of interested node. Therefore to get credits, chances of needy node to forward that message become very high. E. Delivery Ratio Now for next experiment of delivery rate percentage we changed message forwarding methods such as Frame, receipt counting and proportional and compare those result with Improved LB. From fig. 8 the delivery ratio is higher in Improved LB as compared to other three methods. This proves the applicability of the Improved LB scheme.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME Fig. 9: Delivery Ratio for different protocol Fig. 10: Time to compute credit on Vcc In Fig. 9 we have compared delivery ratio of Improved LB protocol with existing DSR and AODV protocols. By observing Fig .11 we can say that Due to proper selection for message forwarding in Improved LB its performance increase dramatically. 59 F. Credit Computation on VCC Fig. 10 shows time required to compute credits on VCC. In [20] receipt get submitted to VCC and after calculating number of receipts node gets credits. Therefore more time get wasted on calculating receipt and then distribute credits to each cooperative node. On other hand in our system VCC does not have overhead of receipt calculation or credits distribution. Since most of Credits distribution happens during communication only. Thus time required to process credits information on VCC in our Improved LB coalition Game is very low as compared to normal coalition. VI. CONCLUSION In our proposed algorithm we are overcoming drawback of receipt depend credit based system where node get credit iff message successfully deliver to destination. If due to some reason message gets drop then all effort done by intermediate node just go to waste. Again receipt credit based system node store receipt and when Vcc come in contact then account gets updated. But in load balancing forwarding message to node with less number of credits, this decision has done at dynamic time. Therefore this decision cannot wait Vcc availability and its updation. In our proposed system we are motivating more nodes to participate in the game by their own will to gain credits. But at same time we are restricting more selfish natured nodes from getting more credits to achieve credit load balancing. Again our system performance does not reduce even if quantity of number of nodes increases. VII. REFERENCES [1] E. Jones, L. Li, and P. Ward, “Practical routing in delay-tolerant networks,” in Proc. ACM Chants Workshop, Aug. 2005, pp. 237–243. [2] S. Jain, K. Fall, and R. Patra, “Routing in a delay tolerant network,” in Proc. SIGCOMM, 2004, pp. 145–158. [3] A. Vahdat and D. Becker, “Epidemic routing for partially connected ad hoc networks,” Duke Univ., Durham, NC, Tech. Rep. CS-200006, Apr. 2000.
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International Journal of
Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 9, September (2014), pp. 50-60 © IAEME [4] B. Burns, O. Brock, and B. N. Levine, “MV routing and capacity building in disruption tolerant networks,” in Proc. INFOCOM, Mar. 2005, pp. 398–408. [5] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, “Spray and wait: An efficient routing scheme for intermittently connected mobile networks,” in Proc. WDTN, Aug. 2005, pp. 252–259. [6] Di Wu, Jing Cao, Yan Ling, Jiang chuan Liu, Limin Sun. ‘Routing algorithm based on multi community evolutionary game for VANET’ in JOURNAL OF NETWORKS, VOL. 7, NO. 7, JULY 2012 [7] S. Marti, T. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” in Proc. MOBICOM, Boston, MA, Aug. 2000, pp. 255–265. [8] P. Michiardi and R. Molva, “CORE: A collaborative reputation mechanism to enforce node cooperation in mobile ad hoc networks,” in Proc. CMS, Portoroz, Slovenia, Sep. 2002, pp. 107–121. [9] A. Vahdat and D. Becker, “Epidemic routing for partially connected ad hoc networks,” Duke Univ., Durham, NC, Tech. Rep. CS-200006, Apr. 2000. [10] U. Shevade, H. H. Song, L. Qiu, and Y. Zhang, “Incentive-aware routing in DTNs,” in Proc. 60 ICNP, Oct. 2008, pp. 238–247. [11] Filipe Maciel Roberto, Joaquim Celestino J´unior, Henning Schulzrinne “Using a symmetric game based in volunteer’s dilemma to improve Vanets multihop broadcast communication”. 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications [12] J. J. Jaramillo and R. Srikant, “DARWIN: Distributed and adaptive reputation mechanism for wireless ad-hoc networks,” in Proc. MOBICOM, Montreal, QC, Canada, Sep. 2008, pp. 87–98P. [13] S. Lee, G. Pan, J. Park, M. Gerla, and S. Lu, “Secure incentives for commercial ad dissemination in vehicular networks,” in Proc. MOBIHOC, Sep. 2007, pp. 150–159. [14] F. Wu, T. Chen, S. Zhong, L. Li, and Y. R. Yang, “Incentive-compatible opportunistic routing for wireless networks,” in Proc. MOBICOM, San Francisco, CA, Sep. 2008, pp. 303–314. [15] L. Buttyan and J. P. Hubaux, “Enforcing service availability in mobile ad-hoc WANs,” IEEE/ACM Workshop on Mobile Ad Hoc Networking and Computing (MobiHOC), Boston, MA, August 2000. [Online]. Available: http://icawww.epfl.ch/Publications/Buttyan/ButtyanH00.ps [16] J. Burgess, B. Gallagher, D. Jensen, and B. N. Levine, “MaxProp: Routing for vehicle-based disruption-tolerant networks,” in Proc. INFOCOM, Apr. 2006, pp. 1–11. [17] A. Vahdat and D. Becker, “Epidemic routing for partially connected ad hoc networks,” Duke Univ., Durham, NC, Tech. Rep. CS-200006, Apr. 2000. [18] S. Jain, K. Fall, and R. Patra, “Routing in a delay tolerant network,” in Proc. SIGCOMM, 2004, pp. 145–158. [19] E. Jones, L. Li, and P. Ward, “Practical routing in delay-tolerant networks,” in Proc. ACM Chants Workshop, Aug. 2005, pp. 237–243. [20] Tingting Chen, Liehuang Zhu, Fan Wu,Sheng Zhong, “Stimulating Cooperation in Vehicular Ad Hoc Networks: A Coalitional Game Theoretic Approach”, IEEE Transactions on Vehicular Technology, Vol. 60, No. 2, February 2011. [21] Priti Bhardwaj and Rahul Johari, “Routing in Delay Tolerant Network using Genetic Algorithm”, International Journal of Computer Engineering Technology (IJCET), Volume 4, Issue 2, 2013, pp. 590 - 597, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
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