Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and          Applications (IJERA)    ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and           Applications (IJERA)   ...
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  1. 1. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390 Modified Ultra Smart Counter Based Broadcast Using Neighborhood Information in MANETS 1 Ms. Nutan Julka1, Prof. Dr. J.W Bakal2 Dept. of Computer Science , Pillais Institute of Information Technology, Navi Mumbai, India. 2 PHD, Principal, S.S Jondhale College of Engineering , Dombivali-west,IndiaABSTRACT Broadcasting protocol heavily affects transmission is directed toward only one neighborperformance of Mobile Ad Hoc Networks (using narrow beam directional antennas or separate(MANET). Counter-based scheme can reduce the frequencies for each node) [3]. Broadcasting hasnumber of rebroadcasts, and as a result reduce been studied in the literature mainly for the one to-Broadcast Storm Problem. Previously fixed all models, and most of this study is devoted to thatcounter-based broadcasting was used irrespective model.of node/network status; this researchdemonstrates that dynamically adjusting the A counter bases approach to flooding hascounter-based to take into account neighborhood been suggested in [4, 5, 6] as a means of reducinginformation over 1- hop improves network redundant rebroadcasts and alleviating the broadcastperformance in terms of both saved rebroadcasts storm problem. The counter-Based is based on aand degree of Reachability. This paper presents counter c that is used to keep track of the number ofModified Ultra Smart Counter Based Broadcast times the broadcast packet is received, whenAlgorithm [MUSCBA] where the threshold value receiving a broadcast message for the first time theat the nodes is dynamically adjusted using one- counter c that records the number of times a host hashop neighborhood information. received the same broadcast packet and is We have conducted simulation experiments to maintained by each host for each broadcast packet.characterize node neighborhood in MANETs When c reaches a predefined threshold c, we inhibitusing ‘Hello’ packet exchange. This research the host from rebroadcasting this packet because theargues that neighboring information could be benefit (the additional coverage) could be low [3].used to better estimate the counter-basedthreshold value at a given node. Additionally Studies [3, 4, 5] have shown that counterresults of extensive simulation experiments based broadcasts incur significantly lower overheadperformed in order to determine the minimum compared to blind flooding while maintaining a highand maximum number of neighbors for a given degree of propagation for the broadcast messages.node is shown. This is done based on locally This paper proposes the Modified Ultra Smartavailable information using AODV protocol and counter-based broadcast algorithm is based on awithout requiring any assistance of distance counter c that is used to keep track of the number ofmeasurements or exact location determination times the broadcast packet is received. A counterdevices. threshold is decided based on neighboring information. That is a sparse network has a differentKeywords- MANET, Counter-Based, Flooding, threshold than a medium sparse, medium, mediumReachability, Neighborhood Information, dense or dense network, we call them c1, c2, c3, c4,Broadcast Storm Problem, c5 respectively. Whenever c is greater than or equal to the threshold, the rebroadcast is inhibited.I. INTRODUCTION The self-configuring nature of MANETs This paper proposes Modified Ultra Smartmakes them suitable for a wide variety of counter-based broadcast algorithm that dynamicallyapplications [2]. One of the applications of this type adjust the rebroadcasting threshold value as per theof networks is communication within groups of node’s neighborhood distribution over one hopspeople with laptops and other hand-held devices. In neighborhood. This is done based on locallyaddition to that communication in battlefield and available information and without requiring anyhome networking [1, 2, 10]. assistance of distance measurements or exact location determination devices. The proposed Broadcasting is a fundamental operation in algorithm, referred to as the smart counter-basedad hoc networks whereby a source node sends the broadcast, only information on one-hop neighbors issame packet to all the nodes in the network. In the required. Short ‘Hello’ packets, containing the ID ofone to- all model, transmission by each node can the senders only, are used to collect suchreach all nodes that are within its transmission information. Furthermore, the algorithm does notradius, while in the one-to-one model, each require a positioning system, because a node 384 | P a g e
  2. 2. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390compares the neighbor lists to deduce counter based cluster heads and gateways. However, the overheadthreshold information. In the algorithm, the counter of cluster formation and maintenance cannot bebased threshold in nodes located in sparse regions is ignored [3, 11].set lower than those located in dense regions. Therest of this paper is organized as follows: In Section The counter-based scheme is a simple way2, we introduce the related work of broadcasting in of controlling message floods. Counter-basedMANETs. In Section 3, we describe our Modified broadcast was first proposed in [4, 5, 6] as a fixedUltra smart counter based approach. In Section 4, we Counter-based broadcast. It has a counter c thatevaluate our approach and present the simulation records the number of times a host has received theresults. Section 5, concludes the paper and offers same broadcast packet and is maintained by eachsuggestions for future work. host for each broadcast packet. When c reaches a predefined threshold c, we inhibit the host fromII. RELATED WORK rebroadcasting this packet because the benefit (the One of the earliest broadcast mechanisms is additional coverage) could below. After that anflooding, where every node in the network adaptive Counter-based scheme was proposed in [4,retransmits a message to its neighbors upon 5 ,6] as it extended the fixed threshold C into areceiving it for the first time. Although flooding is function C(n), where n is the number of neighbors ofvery simple and easy to implement, it can be very the host under consideration. Thus, each host willcostly and may lead to a serious problem, often use a threshold C(n) depending on its current valueknown as the broadcast storm problem [4, 5, 6, 8] of n to determine whether to rebroadcast or not. Tothat is characterized by high redundant packet this point the function C(n) is undefined yet [8].retransmissions, network contention and collision.Ni et. al. [4, 5, 6] have studied the flooding protocol A straightforward method for gatheringanalytically and experimentally. Their obtained neighborhood information at a given node involvesresults have indicated that rebroadcasts could the periodic exchange of ‘Hello’ packets betweenprovide at most 61% additional coverage and only neighbors to construct a 1-hop neighbor list at the41% additional coverage on average over that nodes. A high (low) a number of neighbors impliesalready covered by previous transmissions. that the node in a dense (sparse) area. The higher isTherefore, rebroadcasts are very costly and should the number of neighbors, the denser the networkbe used with caution [4, 5]. area is. The lower the number of neighbors is sparser the network area is. We will show in the subsequent Williams and Camp [3] have classified the paper that neighborhood information such as thebroadcast protocols into flooding, probability-based, average number of neighbors of the node can becounter-based, distance-based, location-based and used to efficiently estimate the counter basedneighbor knowledge schemes. Similarly, neighbor threshold value at the network nodes. In this paper,knowledge schemes can be divided into selecting we report results from Ns-2 as the simulationforwarding neighbors and clustering-based. In platform [12]. Ns-2 is a popular discrete eventcounter-based scheme inhibits the rebroadcast if the simulator which has originally been designed forpacket has already been received for more than a wired networks and has been subsequently extendedgiven number of times. In the probabilistic scheme to support simulations in MANET settings in order[7, 9], when receiving a broadcast packet for the first to characterise neighborhood information, such astime, a node rebroadcasts the packet with a the average number of neighbors of a given node byprobability p; when p=1, this scheme reduces to means of ‘Hello’ packet exchanges. We alsoblind flooding. In the distance-based scheme a node investigate the effects of node mobility and networkrebroadcasts the packet only if the distance between density on such gathered information. Our study isthe sender and the receiver is larger than a given motivated by the fact the periodic ‘Hello’ packet forthreshold. In the location-based scheme, a node ad-hoc networks stems from the hello protocol ofrebroadcasts a packet only when the additional AODV [10]. Such a protocol and its utility havecoverage due to the new emission is larger than a been explicitly studied by Chakeres et al. [10]. Thecertain bound. In the selecting forwarding neighbors authors have studied the hello protocol in 802.11 ad-a broadcasting node selects some of its 1-hop hoc networks but have focused on a limited type ofneighbors as rebroadcasting nodes. Finally, the information (i.e., connectivity or forward a packet).cluster structure is a simple backbone infrastructure We will show in the subsequent sections how we usewhereby the network is partitioned into a group of the findings of this paper to introduce new andclusters. Each cluster has one cluster head that efficient class of counter based broadcast floodingdominates all other members in the cluster. A node algorithm for MANETs.is called a gateway if it lies within the transmissionrange of two or more cluster heads.Gateway nodes are generally used for routingbetween clusters. The rebroadcast is performed by 385 | P a g e
  3. 3. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390III. MODIFIED ULTRA SMART COUNTER neighbours of node X is less than the minimumBASED BROADCAST ALGORITHM [MUSCBA] numbers of neighbours, n1 . Alternatively, if the The counter based scheme [4, 5, 6, 8] is one number of neighbours of the node X is greater orof the alternative approaches to simple flooding that equal the minimum number of neighbours, n1 , andaims to reduce redundancy through rebroadcast the number of neighbours less than or equal thetiming control in an attempt to alleviate the numbers of neighbours, n2 , X has a sparse mediumbroadcast storm problem. In this scheme, when degree and the counter based threshold value is set atreceiving a broadcast message for the first time it c2 such that c1 <c 2 . If the number of neighbours ofhas a counter c that records the number of times a the node X is greater or equal the neighbours, n2 ,host has received the same broadcast packet and is and the number of neighbours less than or equal themaintained by each host for each broadcast packet. numbers of neighbours, n3 , X has a medium degreeWhen c reaches a predefined threshold c, we inhibit and the counter based threshold value is set at c3.the host from rebroadcasting this packet. If the number of neighbours of the node X is greater or equal the neighbours, n3 , and the number of In dense networks, multiple nodes share neighbours less than or equal the numbers ofsimilar transmission range. Therefore, these neighbours, n4 , X has a medium dense degree andthresholds control the frequency of rebroadcasts and the counter based threshold value is set at c4.thus might save network resources without affecting Otherwise, if the number of neighbours of the nodedelivery ratios. Note that in sparse networks there is X is greater than maximum number of neighbours,much less shared coverage; thus some nodes will not n4 , then the counter based threshold value is setreceive all the broadcast packets unless the threshold high, c5, where c1 <c 2c <c 3<c4<c5 . A briefparameter is low. So if the threshold c is set to a far outline of the new algorithm is presented belowsmaller value, Reachability will be poor. On theother hand, if c is set far large, many redundant 1. On hearing a broadcast packet m at node Xrebroadcasts will be generated.The need for dynamic 2. Get the Broadcast ID from the packet;adjustment, thus, rises. ◦ n1 = 20 % number of neighbours ◦ n2 = 40 % number of neighbours The counter based threshold value should ◦ n3 = 60 % number of neighboursbe set low at the hosts in sparser areas and high at ◦ n4 = 80 % number of neighbours;the hosts in denser areas. Our simple method for 3. Get degree n of node X (number ofdensity estimation requires mobile hosts to neighbors of node X);periodically exchange HELLO messages betweenneighbours to construct a 1-hop neighbour list at 4. If n ≤n1 theneach host. A high a number of neighbours impliesthat the hosts in denser areas, a low number of 4.1 Sparse networkneighbors imply that the host is in sparser areas. We 4.2 Node X has a low degree: the lowincrease the counter based threshold value if the threshold value (threshold = c1 );value of the number of neighbours is too high (orsimilarly if the current node is located in a dense 5. Else If n > n1 and n ≤ n2 thenneighbourhood), which indirectly causes thethreshold value at neighbouring hosts to be 5.1 Medium Sparse networkdecremented. Similarly, we decrease the counter 5.2 Node X has a Sparse medium degree: thebased threshold value if the value of number of Sparse medium threshold value (threshold =neighbours is too low. c2 ); The Modified Ultra Smart counter-Based 6. Else If n > n2 and n ≤ n3 thenbroadcast algorithm is based on a counter c that isused to keep track of the number of times the 6.1 Medium networkbroadcast packet is received. A counter threshold is 6.2 Node X has a medium degree: thedecided based on neighboring information. That is a medium threshold value (threshold = c3 );sparse network has a different threshold than amedium or dense network, we call them c1 ,c 2, c3 7. Else If n > n3 and n ≤ n4 then,c4, and c5 respectively. Whenever c is greater thanor equal to the threshold, the rebroadcast is inhibited. 7.1 Medium Dense networkThe algorithm works as follows 7.2 Node X has a Medium high degree: the high threshold value (threshold = c4 ); On hearing a broadcast packet m at node X, 8. Else If n > n4 thenthe node rebroadcasts the packet according to a lowcounter based threshold value, say c1 , if the packet 8.1 Dense networkis received for the first time, and the number of 386 | P a g e
  4. 4. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390 8.2 Node X has a high degree: the high minimum and maximum number of neighbours over threshold value (threshold = c5); the whole nodes in the network. For each configuration, we have gathered statistics for 309. End if arbitrary topologies where nodes are initially placed10. counter = 1 randomly over the terrain. The results represent the11. The Packet is Broadcasted average over the 30 different topologies in order to12. Increment c achieve a 95% confidence interval in the collected13. If (c < threshold) statistics. For a given number of nodes, three terrain 13.1 Goto step 11 sizes have been considered: 600m × 600m, 800m × 800m and 1000m ×1000m.14. Else 14.1 exit algorithm Table1. Summary of the parameters used in the simulation experiments.15. End if EndFig. 1: Modified Ultra Smart counter-Basedbroadcast algorithm [MUSCBA] We will show in the subsequent sectionsthat neighbourhood information such as theminimum and maximum number of neighbours ofthe node can be used to efficiently estimate thecounter based threshold values at the network nodes.In this paper, we report results from ns-2 [4]simulations in order to characterise neighbourhoodinformation, such as the minimum and maximumnumber of neighbours of a given node by means of‘Hello’ packet exchanges. We also investigate theeffects of node mobility and network density on suchgathered information. Figures 2 and 3 depict the minimum and maximum number of neighbours after averaging over theIV. PERFORMANCE EVALUATION whole network nodes when the nodes move at the We have used ns-2 as the simulation max. speed of 2m/s. Various network densitiesplatform [4]. Ns-2 is a popular discrete-event resulting from a combination of different networksimulator which has originally been designed for sizes (from 25 to 125 nodes) and terrain sizeswired networks and has been subsequently extended (600m×600m, 800m×800m, and 1000m×1000m)to support simulations in MANET settings. The have been examined. A summary of the minimumdensity of the nodes is sufficient to maintain good and maximum number of neighbours is listed innetwork connectivity levels, with each node Table 2. Also a summary of confidence intervals,engaging in communication transmitting within 250 margin errors for the minimum and maximummeter radius and having bandwidth of 2Mbps. The number of neighbours of a given node (averagedparameters used in the following simulation over the whole network) is shown in Table 3. Theexperiments are listed in Table 1. The MAC layer results show that as expected the denser the networkscheme follows the IEEE 802.11 MAC specification. is, the higher the maximum number of neighbours isWe have used the broadcast mode with no at a given node. On the other hand, the sparser theRTS/CTS/ACK mechanisms for all packet network is, the lower is the minimum number oftransmissions, including Hello, DATA and ACK neighbours at a given node. As the network sizepackets. The interface queue length has been increases so does the minimum and maximumselected because it has been used in many previous number of neighbours. For example, in a terrain sizesimilar studies [5, 6]. Moreover, this has been found of 1000m × 1000m when the network size is 50to reduce the number of drop packets at the link nodes, a typical node has the minimum number oflayer protocol due to increased packet collisions. neighbours equals to 6, the maximum number ofThe movement pattern of each node follows the neighbour to 24. When the network size is doubledrandom way-point model. Each node moves to a to 100 nodes, a typical node has the minimumrandomly selected destination with a constant speed number of neighbours equals to 6, the maximumbetween 0 and the maximum speed. When it reaches number of neighbour to 47. Figures 4 and 5 providesthe destination, it stays there for a random period further results on the minimum and maximumand starts moving to a new destination. We have number of neighbours (averaged over the wholevaried the network density (i.e., the number of nodeson a given terrain size) and have measured the 387 | P a g e
  5. 5. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390network) after repeating the above simulation Table 3. Summary of confidence intervals andexperiments where the node speed is set at 20 m/s. margin of errors of minimum number of neighbors of given node Table 4 Summary of confidence intervals and margin of errors of maxmum number ofFig. 2. Minimum numbers of neighbours vs. neighbors of given nodenetwork size with a node speed of 2 m/s.Fig. 3. Maximum number of neighbours vs.network size with a node speed of 2 m/s.Table 2. Summary of the minimum andmaximum number of neighbours of given node Fig. 4. Minimum numbers of neighbours vs. network size with a node speed of 20 m/s 388 | P a g e
  6. 6. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-390Figure 5. Maximum number of neighbours vs. Fig. 6: The SRB vs. the rebroadcast counternetwork size with a node speed of 20 m/s. based with node speed 10m/s. The performance of broadcast protocols canbe measured by a variety of metrics [1 ,5, 6] Acommonly used metric is the number of message re-transmissions with respect to the number of nodes inthe network [6]. In this work, we use rebroadcastsavings, which is a complementary measure and isprecisely defined below. The next important metricis reachability, which is defined in terms of the ratioof nodes that received the broadcast message out ofall the nodes in the network. The formal definitionsof these two metrics are given as follows [4, 6].Saved ReBroadcasts (SRB): Let r be the number ofnodes that received the broadcast message and letand t be the number of nodes that actuallytransmitted the message. The saved rebroadcast is Fig. 7: SRB of three broadcast schemes againstthen defined by (r – t)/r. network density with node speed 10m/s.Reachability (RE): is the percentage of nodes thatreceived the broadcast message to the total numberof nodes in the network. For useful information, thetotal number of nodes should include those nodesthat are part of a connected component in thenetwork. For disconnected networks this measureshould be applied to each of the componentsseparately. We have compared the saved broadcast(SRB) in Ultra Smart counter-Based[15] and ouralgorithm Modified Ultra Smart counter Based. Fig.6 shows our algorithm can significantly reduce thenumber of saved rebroadcast.Fig. 7 shows the saved rebroadcast (SRB) of thefixed counter-Based, Ultra smart counter based andour Algorithm Modified Ultra Smart counter- Based. Fig. 8: RE of three broadcast schemes againstThe SRB of our algorithm Modified Ultra Smart network density with node speed 10m/scounter Based is 45% in low-density networks andsignificantly high in high-density network. Finally, Fig. 8 shows that reachability increases whenwe can see that our algorithm performs the best in network density increases, regardless of what kind ofvarious network densities. the algorithms is used. The flooding algorithm has the best performance in reachability, reaching nearly 389 | P a g e
  7. 7. Ms. Nutan Julka, Prof. Dr. J.W Bakal / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.384-3901. The performance of Ultra Smart counter-Based Proceedings of the 21st Internationalalgorithm Conference on DistributedComputing Systems, pages 481-488, 2001.shows that the reachability is above 45% in any [7] M. Bani-Yassein, M. Ould-Khaoua, L. M.density of the network. The performance of Mackenzie, S. Papanastasiou and A. Jamal,Modified Ultra Smart counter-Based algorithm Improving route discovery in on demandshows that the reachability is above 50% in any routing protocols using local topologydensity of the network .In all network densities, the information in MANETs, Proceedings ofreachability of our Algorithm performs better than the Ninth ACM/IEEE Internationalthe Ultra smart counter based counter-Based Symposium on Modeling, Analysis andalgorithm. Simulation of Wireless and Mobile Systems (MSWIM 06), pages 95- 99, October 2006.V. CONCLUSION [8] Y.-C. Tseng, S.-Y. Ni, and En-YU Shih. In MANETs, due to node mobility, Adaptive approaches to relieving broadcastneighborhood relationship changes frequently. In storm in a wireless multihop mobile ad hocorder to cope with mobility and have up-to-date network. IEEE Transactions on Computers,neighborhood information, nodes advertise ‘Hello’ volume 52(5), pages 545-557, May 2003.packets periodically. simulation experiments are [9] M. Bani-Yassein, M. Ould-Khaoua, L. M.done in order to characterize node neighborhood in Mackenzie and S. Papanastasiou,MANETs using ‘Hello’ packet exchange Simulation Performance Analysis of Adjustedresults have shown how neighborhood information, Probabilistic Broadcasting in Mobile Adthat includes minimum and maximum number of Hoc Networks , International Journal ofneighbors of a given node, have been used to devise Wireless Information Networks, Pages 1-14,a new class of efficient modified ultra smart counter Springer Netherlands, Mar 2006.based broadcast algorithms for MANETs. These [10] C. Perkins and E. M. Royer, Ad-hocalgorithms enable a given node to dynamically ondemand distance vector routing.adjust its counter based threshold values depending Proceedings of 2nd IEEE Workshop onon whether it is located in a sparse, medium sparse, Mobile Computing Systems andmedium, medium dense or dense network region. Applications (WMCSA’99), pages 90–100,Also we investigated the performance merits of the 1999.counter-based flooding algorithm. [11] J. Wu and W. Lou. Forward-node-set-based broadcast in clustered mobile ad hocREFERENCES networks, special issue on Algorithmic, [1] W. Peng, X.C. Lu, on the reduction of Geometric, Graph, Combinatorial, and broadcast redundancy in mobile ad hoc Vectors. Wireless Networks and Mobile networks, in Proceedings of the First Computing, volume 3(2), pages 155-173, Annual Workshop on Mobile Ad Hoc 2003. Networking & Computing (MobiHOC , [12] K. Fall and K. Varadhan. The ns manual, 2000), Boston, Massachusetts, USA, pp. the VINT project 129–130, 2000. http://www.isi.edu/nsnam/ns/ns-man.html. [2] C-K. Toh, Ad Hoc Mobile Wireless [13] M. Chatterjee, S.K. Das, and D. Turgut. Networks: Protocols and Systems WCA: A weighted clustering algorithm for (Prentice- Hall, New York, 2002). mobile ad hoc networks. Journal of Cluster [3] B. Williams, T. Camp, Comparison of Computing, volume 5(2), pages 193–204, broadcasting techniques for mobile adhoc 2002. networks. (MOBIHOC 2002), pages. 194– [14] S. Kurkowski, T. Camp, and M. 205, 2002. Colagrosso. MANET simulation studies. [4] S.-Y. Ni, Y.-C. Tseng, Y.-S. Chen and J.-P. ACM SIGMOBILE Mobile Computing and Sheu. The broadcast storm problem in a Communication Review, volume 9(4), mobile ad hoc network. Proceedings Of pages 50-61, 2005. ACM/IEEE Mobicom’99, pages 151-162, [15] M. Bani-Yassein, M. Ould-Khaoua, A. Al- August 1999. DubaiOmar M. Al-jarrah New Adaptive [5] S.-Y. Ni, Y.-C. Tseng, Y.-S. Chen, J.-P. Counter Based Broadcast Using Sheu, The broadcast storm problem in a Neighborhood Information in MANETS, mobile ad hoc network, Wireless Networks, IEEE Transactions on Computers, volume volume 8(2), pages.153-167, 2002. 52(5), pages 545-557, May 2009. [6] Y.-C. Tseng, S.-Y. Ni, and E.-Y. Shih. Adaptive Approaches to Relieving Broadcast Storms in a wireless multihop mobile ad hoc network. ICDCS 01, 390 | P a g e

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