Your SlideShare is downloading. ×
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
20120140504027
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

20120140504027

98

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
98
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 247 NETWORK CODING BASED MULTICAST FOR VANET Jitendra Bhatia 1 , Zunnun Narmawala 2 1 Assistant Professor, CSE Department, Institute of Technology, Nirma University, Ahmedabad - 382 481, Gujarat, India. 2 Assistant Professor, CSE Department, Institute of Technology, Nirma University, Ahmedabad - 382 481, Gujarat, India. ABSTRACT A Vehicular Ad-Hoc Network, or VANET, is a delay Tolerant network in which no contemporaneous path exists between source and destination most of the time. So, routing protocols proposed for VANET follow ‘store-carry-forward’ paradigm in which two nodes exchange messages with each other only when they come into contact. Multicast can be used to perform the regional multicasting to deliver safety related, commercials and advertisements messages. The challenging problem in multicasting is how to deliver packets to all the nodes within the particular region with high efficiency but low overhead. Network coding with Multi-Generation-Mixing is a special in- network data-processing technique that can potentially increase the network capacity and packet throughput in wireless networking environments. In this paper, a network coding with MGM based Multicast algorithm for transmitting multicast packets over VANET is proposed. The proposed algorithm can increase packet delivered ratio at each mobile node. As a result, the safety and transmission efficiency can be achieved simultaneously. We developed multi-copy routing protocol for multicasting in VANET which uses ‘Network coding with MGM’ to reduce this overhead. Simulation results shows that proposed multicasting protocol outperforms the conventional network coding based protocol in terms of throughput and delay Key words: Network Coding, Vanet, Multicasting. 1. INTRODUCTION Network coding is considered as a generalization of conventional store and forward techniques and it’s a tool for optimization which can improve the chances of delivery in a spontaneous network, and also it was originally proposed in order to achieve multicast data delivery INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET) ISSN 0976 - 6480 (Print) ISSN 0976 - 6499 (Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME: www.iaeme.com/ijaret.asp Journal Impact Factor (2014): 7.8273 (Calculated by GISI) www.jifactor.com IJARET © I A E M E
  • 2. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 248 at the maximum data transfer in single source multicast [1].Network coding need to use algebraic nature of data. There are three well known application of network coding in overlay networks: distributed storage system, content distribution and layered multicast. There are two types of network coding, Deterministic Linear Network Coding (LNC) and Random Linear Network Coding (RLNC). In traditional network, relay node or router simply forward the information packets destined to other node. In LNC, source node or intermediate node or router allows to combine number of packets it has received or generated into one or several outgoing packets. With linear network coding, outgoing packets are linear combinations of the original packets, where addition and multiplication are performed over the field GF2 s [2]. Linear combination is not concatenation, if we linearly combine packets of length L, the resulting encoded packet also has size L. The rest of the paper is organized as follows. Section 2 describes the working of MGM. In section 4, a new network coding with MGM based multicast algorithm for VANET is presented. Section 7 demonstrates the simulation scenario provides results and analysis. Finally, in section 8 some concluding remarks and scope for future work is presented. 2. NETWORK CODING WITH MULTI GENERATION MIXING(MGM) Network Coding with Multi-generation mixing (MGM) is a RLNC approach which improves the performance without increasing buffer size. In MGM mixing set of size m generations can be coded together. A new set of generation packet is mixed with previously transmitted generations. Results show that MGM reduces overhead for are covery of packets. In MGM, N packets are grouped into generations where the size of each generation is k packets. Each generation is assigned a sequence number from 0 to N/k. In G-by-G Network coding encoding is allowed amongst packet belonging to the one generation. While in MGM generations are grouped into mixing sets where the size of mixing set is m generations. Each mixing set has an index M. Generation i belongs to mixing set with index M=i/m. Each generation in mixing set has a position index. Position index (l) of generation i in a mixing set of size m is i mod m. G-by-G Network coding is a special case of MGM where m=1. In MGM packets of different generations are encoded together. When node sends a packet belonging to generation i with position index l in mixing set, that node encode all packets that are associated with the generations of same mixing set and have the position indices less than or equal to l as shown in Figure 1[3]. Size of encoding vector depends on the number of packets encoded together at sender node. Number of packets that are encoded together depends on the position index of the generation with which packet is associated. Packet in generation with position index l have the size of encoding vector is (l+1)k. So sender will generate (l+1)k independent packets. In Network Coding with MGM goal is to enhance decodable rates in situation where losses prevent efficient propagation of sender packets. MGM allows the cooperative decoding among the different generations of a mixing set which enhances decodablity. Compare to G-by-G Network coding with MGM extra encoded packets associated with generation protect more than one generation. Computation overhead is incurred at intermediate node to check the usefulness of received packets and at receiver node to decode received packets[4]. In g-by-g Network coding computation are performed on packets within the generation so it is fixed due to fixed generation size. But in MGM encoding/decoding is performed on packets belonging to at least one generation in mixing set and so computational overhead is not fixed. In MGM in case generation is unrecoverable due to the reception of insufficient encodings, it is still possible to recover that generation collectively as a subset of mixing set generations. Packets received with generation of higher position indices have information from generations of lower position indices and hence contribute in recovery of unrecovered generations of lower position indices in the same mixing set. Redundant encoded packets enhance the reliability of communication. With MGM extra packets protects all
  • 3. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 249 generations with lower position indices. While inG-by-G Network coding extra packets protects that generation only. Figure 1: Network Coding with MGM, each generation is encoded with previous generations in mixing set[3] In MGM there are different options for sending extra packets. One option is distribute the packets over all generations of mixing set. Another option is to send extra encodings with the last generation of mixing set. So, extra encodings protects all mixing set generations. Figure 2: Generation’s partitioning with MGM into different layers of priority. Mixing set size is m, generation size is k[5] 3. MULTICASTING IN VANET Many VANET applications need multicast service. For example, vehicle on road may send the packet regarding accident to one of the server(ambulance or emergency service providers). However, conventional multicast methods proposed for ad hoc networks are not suitable for VANET, due to frequently disconnectivity in the network. Data transmissions suffer from large end- to-end delays along the tree because of the repeated partitions due to frequent disconnections. Also the conventional approaches may fail to deliver a message when the possibility of link unavailability becomes high. 3.1 Multicasting in wireless networks Network coding is potentially applicable to many forms of network communications. Up to now, the best understood scenario where network coding offers unique advantages is multicasting in a wireless communication network.
  • 4. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 250 Throughput enhancement is one of the application of network coding to wireless networks. Wireless networks are suitable for network coding because wireless links inherently have the broadcast nature. Network coding scheme for multi-hop wireless networks improves throughput performance with the following simple example shown in figure. [6]. Network coding could be more helpful for improve delay, reliability and robustness, rather than improving throughput enhancement only for multicasting. 3.2 Characteristics of VANET Scenarios Nodes move at very high speed. Highly dynamic topology. Vehicles are equipped with long lived batteries, so the energy consumption due to communication is negligible. Mobility patterns are constrained. Vehicle can have digital maps of the geographic zone they are travelling around. Positioning information may be acquired via geographic positioning system like GPS or Galileo. [7] Interaction with onboard sensors. 3.3 Common services used for VANET • Safety information • Advanced driver assistance systems • Traffic management • Infotainment 3.4 ISSUES Due to the unpredictability of network connectivity and delay, and limited buffer, Multicasting in VANETs is a quite unique and challenging problem. It requires both re-definition of Multicasting semantics and new routing algorithms. But these approaches cannot be applicable to VANETs since for Multicasting routing it cannot assume the connectivity is guaranteed, and the uncertainty of both the path to a destination group member and the destination of the Multicasting message during the routing makes the problem more challenging. One of the challenges in designing a Multicasting routing protocol is to maintain the group membership efficiently. Due to the long delivery delay in VANETs, group membership may already change during the delivery of a message, introducing ambiguity in Multicasting semantics. 4. THE PROPOSED PROTOCOL Procedure mgm_processing(node Id) 1. if Id = Source_node then (a) Create n generations of k packets in to each mixing set m (b) Encode the generation using multi-generation mixing concept for each mixing set. (c) send the packets 2. if Id = Intermediate_node then (a) Calculate the rank of received packets for each generation of particular mixing set (b) if the rank of received packets is sufficient then do collectively decoding (i.e. generation size*generation ID) else "decoding not possible" and wait for new node to become neighbor
  • 5. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 251 (c) Do re-encoding of the received packets. (d) Send the encoded packets with their respective effective co-efficient vector to its neighbor nodes. 3. if Id = Destination_node then (a) Calculate the rank of received packets foreach generation of particular mixing set (b) Decode it if rank is sufficient i.e. rank>=gen_size * gen_ID (c) send anti-packets to its neighboring nodes End Procedure 5. OVERVIEW 5.1 Opportunistic Routing VANET, which is Delay Tolerant Networks or Intermittently Connected Networks in which end-to-end connectivity is not present most of the time. In such a network, conventional approach of finding route or source-rooted multicast tree before data transmission is not feasible. So, in our protocol, data transfer takes place whenever two nodes come into communication range of each other. 5.2 MultiCopy Scheme We assume that no prior information about the network to pology or connection pattern is available, as it is the case in mobile ad hoc networks most of the time. Single copy schemes generally rely heavily on such information and these schemes have very high delivery delay and low delivery ratio. Further, Multi-copy schemes are very robust. So, we choose our protocol to be a Multi-copy protocol 5.3 Network coding In existing routing schemes for VANET, whenever a transmission opportunity arrives, ideally, a node should forward packets such that the destination node gets all the required packets without getting any redundant packet. However, a forwarding node has no such precise knowledge in VANET. So, it is difficult to select the best suitable packet for transmission. On the other hand, in the network coding based protocol, a node can transmit any of the coded packets since all of them can contribute the same to the eventual delivery of all data packets to the destination with high probability. Similarly, the network coding based protocol has the advantage in proper utilizing limited buffer resource since dropping any coded packet has the same effect. So, our protocol uses network coding to exploit these and other benefits mentioned earlier. 5.4 Purging Scheme For efficient buffer usage, copies of already delivered packets have to be purged from the nodes in the network. 5.5 Estimation of Protocol Parameters Following are the two configurable parameters in our protocol: 1. Generation size (G): It denotes the size of the generation. For the reasons explained earlier, packets are grouped into generations and only the packets in the same generation can be mixed. 2. Mixing set size (MSS): It denotes the number of generations of size G in particular mixing set.
  • 6. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 252 The network parameter of interest is Meeting rate. Of the network is the average number of times a node meets with any other node in the network per second. It depends on the area within which the network nodes move (field area), their velocities and communication range and the mobility pattern. 6. PROTOCOL DESCRIPTION In this section, we describe working of our protocol. Data packets are grouped into generations. Nodes store independent packets along with their coefficients according to RLC scheme. Main components of our protocol are explained in following sections. Figure 3: Diagram representing protocol components 6.1 Neighbor Management Every node in the network transmits ‘HELLO’ packet at fixed interval called as ‘HELLO Timer’. Duration of the interval is pre-configured parameter which is decided depending on speed of the nodes and their communication range. e.g., if we consider the case of neighbour nodes moving with 6 m/s speed in opposite directions having communication range of 100 m, they will remain in contact for approximately 34 seconds. If we keep the HELLO Timer value to be 10 seconds, the neighbour node will be detected at most after 10 seconds from the actual time of first contact between two nodes and the node will not be able to make use of approximately 1/3rd of total contact period. If we decrease HELLO Timer value, then number of HELLO packets in the network will increase but neighbour will be detected early. So there is a tradeoff. Whenever a node receives HELLO packet from another node, it adds that node into its neighbour list if that node is not in the list already. If any node does not receive any HELLO packet for the interval equal to three times ‘HELLO Timer’ from its neighbour node, that node is purged from the neighbour list. This interval is called as ‘Neighbour Purge Timer’. 6.2 Purging After adding a node into the neighbour list, the node shares accumulated delivery information with its neighbour for purging. Apart from these schemes, remaining packets of generation are purged from all the buffers after a timeout period ‘TTL’. This timeout mechanism ensures that, if a generation is not delivered to all the destinations or delivery information from all destinations are not
  • 7. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 253 received by a node even after TTL delay, it will be purged. So value of TTL is to be kept sufficiently large such that generations are received by most of the destinations most of the time. 6.3 Packet Mixing and Forwarding After intelligent beaconing, the initiator node sends encoded data packets to the neighbour till it is within communication range. The generation of which next encoded packet is to be forwarded, along with its coefficients, is decided based on some forwarding policy 6.4 Packet Reception When the neighbour node receives the packet and the buffer is full, it makes room in the buffer as per the buffer management policy mentioned below and it stores the coefficients of the packet in the corresponding coefficient matrix 6.5 Packet Decoding When the sufficient number of packets from all the generation of particular mixing set at the destination node is equal to (mixing set size * generation size) 7. SIMULATION We have simulated the proposed protocol in NS2 simulator and The network contains 50 wireless nodes which move according to mobility models generated by MOVE simulator. The minimum speed of a node is 10 m/s. The communication range of a node is 100 m and band width of the channel is 1 Mbps. Meeting rate (γ) is changed by varying field area of the network. There is source in the network and there are different number of destinations i.e. Group Size. For network coding, randomly chosen coefficients and addition and multiplication operations for encoding and decoding are over the Galois field F2 8 . 7.1 Simulation Results Our performance parameter of interest is percentile delay(δ) which we define as time taken to deliver given percentage of total packets by the network. Please note that it captures two performance parameters namely delivery ratio and delivery delay. The protocol parameters are generation size (G) and number of generations in one mixing set (MSS). The network parameter of interest is meeting rate (γ). 7.2 Infinite Buffer Case In this section, we present the performance of the protocol when buffers are infinite. i.e., each node has enough buffer to store all the generations of each mixing set from all sources. Once average speed of the nodes in the network achieves steady state, all the source nodes generate given number of data packets which are grouped into generations for a particular mixing set i.e., data packets are generated in a pulse and there is no new traffic generated after that. For the results shown, number of data packets per source are 64. We run the simulation for sufficient time period such that all the generations of particular mixing set are received by all intended destination nodes. For infinite buffer case, anti-packets are generated only when all generations of particular mixing set is delivered. A node purges entire generation when the node has accumulated all the destinations in its destination list for that generation of particular mixing set. We observe from Fig. 4, that as we increases the meeting rate block delivery delay(δ) will decreases because as more and more number of nodes comes in contact chances of delivery is going to be increase but it will increases the redundancy also. For the value of γ = between 0.8 and 0.9,
  • 8. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 254 decreasing in value of δ is almost nearer, but for lower value of γ, MGM outperforms in delivery delay. As shown in Fig. 5, as mixing set size increases delay decreases. For decoding entire mixing set we need sufficient rank i.e. sufficient number of packets to decode particular mixing set. for example in our MGM case G=8 and MSS=8 so total number of packets are 64 but after applying MGM based network coding, we will have 288 packets out of which if we get total number of 64 packets from different generation of that mixing set then destination node is able to decode all the packets as rank is sufficient. Note rank indicates the sufficient innovative packets to decode entire generation/Mixing set. Our result implies that if we increase our mixing set up to some extent it will out performs in case of delay over conventional and G-by-G scheme. For conventional scheme i.e. MSS=1 and G=1 Delay is higher with compare to the case where MSS=1 for different value of G= 2, 4 and 8 but for MGM case where MSS=8 and G=8, δ decreases drastically. Figure 4: Delay v/s Meeting rate Figure 6: Packet delivery ratio v/s Mixing set size Figure 5: Delay v/s Mixing set size Figure 7: Packet delivery ratio v/s Meeting rate As shown in Fig. 6, packet delivery ratio increases, as we increase the mixing set size for meeting rate (γ =0.43). For conventional scheme, it is less with compare to G-by-G case (i.e. MSS=1 and G=2, 4, 8). MGM case where MSS=8 and G=8 have higher value of α. As shown in Fig. 7, value of α increases as γ increases. MGM outperforms over conventional and G-by-G scheme for lower values of γ but it become somewhat stable after γ=0.73. From Fig.8, it is clear that number total number of packets received increases as time goes on. MGM out performs over both the scheme.
  • 9. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 255 Figure 8: Throughput v/s Time 8. CONCLUSION AND FUTURE SCOPE VANET which is an example of Delay Tolerant Networks require different routing strategy than conventional networks because of frequent and long partitions in the network. To improve chances of delivery, Single or Multicopy schemes are used. However, communication overhead and buffer occupancy increases as we increase number copies per packet. To reduce this overhead without impacting performance, we use network coding based single-copy scheme. 9. FUTURE WORK We will work on multi-copy approach that will generate redundant copies of the same packet for increasing the probability of delivery for finite buffer with probabilistic purging mechanism to utilize optimal use of buffer which takes advantage of network coding and also binary spray and wait [8] mechanism to reduce the number of copies in the network for optimal usage of buffer and bandwidth. We will work on cross layer optimization in which speed and direction parameters from physical layer can be used at network layer for intelligent routing. REFERENCES 1. R. Ahlswede, N. Cai, S.-Y. R. Li, and R. W. Yeung, “Network Information Flow,” In IEEE Transactions on Information Theory, Vol. 46, Pp. 1204-1216, July 2000. 2. C. Fragouli and E. Soljanin, “Network Coding Applications,” Tech. Rep., Foundations and Trends in Networking Vol. No.2, 2007. 3. H. R. Mohammed Halloush, “Network Coding with Multi-Generation Mixing: A Generalized Framework for Practical Network Coding,” Tech. Rep., IEEE Transactions on Wireless Communications, Vol. 10, No. 2., February 2011. 4. H. R. M. Halloush, “A Case Study of: Sender Transmission Reliability and Complexity Using Network Coding with Multi-Generation Mixing,” Tech. Rep., 2009. 5. H. R. Mohammed Halloush, “Performance Evaluation: Priority Transmission using Network Coding with Multi-Generation Mixing,” Tech. Rep., ICC Proceedings, 2009. 6. S. Katti, H. Rahul, W. Hu, D. Katabi, M. Mèdard, And J. Crowcroft, “Xors in the Air: Practical Wireless Network Coding,” In SIGCOMM, September 2006. 7. S.O..M.C.Weigle, “Vehicular Networks From Theory to Practice,” Tech. Rep. 8. S. S. Narmawala, Z., “Midtone: Multicast in Delay Tolerant Net- Works,” In Fourth International Conference on Communications and Networking in China, Pages. 1 - 8, 2009.
  • 10. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 247-256 © IAEME 256 9. N. A. Laiq Khan And A. Saeed, “Any Cast Based Routing in Vehicular Adhoc Networks (Vanets)”, Using VANET Mobisim, Tech. Rep., World Applied Sciences Journal 7 (11): 1341-1352, 2009. 10. M. A. A. Ghassan M. T. Abdalla and S. M. Senouci, “Current Trends in Vehicular Ad Hoc Networks”, Tech. Rep. 11. J. Z. Hao Kun and W. Ying, “Partial Network Coding for Wireless Opportunistic Routing, Tech. Rep.”, Iet Conference Publications, 2006. 12. Y. Q. Shengli Fu, Kejie Lu and M. Varanasi, “Cooperative Network Coding for Wireless Ad- Hoc Networks”, Tech. Rep., IEEE GLOBECOM Proceedings, 2007. 13. K. B. L. Wei Chen and Z. Cao, “Opportunistic Network Coding for Wireless Networks, Tech. Rep., Icc Proceedings, 2007. 14. M. S. L. R. G. W. S. L. Lu Lu, Ming Xiao, “Efficient Network Coding for Wireless Broadcasting, Tech. Rep., WCNC Proceedings, 2010. 15. J.-Y. L. B. Christina Fragouli, “Network Coding: An Instant Primer”, Tech. Rep., ACM SIGCOMM Computer Communication Review, Volume 36, January 2006. 16. R. S. Rodica Stoian, Lucian Andrei Perisoara, “Random Network Coding for Wireless Ad- Hoc Networks”, Tech. Rep., Wireless Communications And Networking Conference, 2010. 17. R. K. D. R. K. M. E. J. S. Tracey Ho, Muriel Medard And B. Leong, “A Random Linear Network Coding Approach To Multicast” Tech. Rep., IEEE Trans. Information Theory, Oct 2006. 18. K. J. Philip Chou, Yunnan Wu, “Practical Network Coding” Tech. Rep., In Proc. Allerton Conf. Commun., 2003. 19. Jitendra Bhatia, Bhumit Shah “Review on Various Security Threats and Network Coding Based Security Approach for VANET”, International Journal of Advances in Engineering and Technology, March 2013, Issn No. 2231-1963. 20. Prakash Patel, Jitendra Bhatia, “Review on Variants of Reliable and Security Aware Peer to Peer Content Distribution using Network Coding Technique”, IEEE Conf. NUiCONE, 2012 Nirma University International Conference. 21. A. Rhattoy and A. Zatni, “Impact of Mobility and Maps Size on the Performances of VANETS in Urban Area”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 2, 2013, Pp. 556 - 568, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 22. P.A. Kamble and Dr. M.M. Kshirsagar, “Improvement Over Aodv Routing Protocol in VANET”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 4, 2013, pp. 315 - 320, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 23. Poonam Pahuja and Dr. Tarun Shrimali, “Routing Management for Mobile Ad-Hoc Networks”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 3, 2013, pp. 464 - 468, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 24. Mitul K. Patel, “Study of Localization Techniques in Vehicular Ad-Hoc Networks”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 4, 2013, pp. 194 - 202, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.

×