Performance Testing of OLSR using Mobility Predictions
|
|
- Lenard Higgins
- 2 years ago
- Views:
Transcription
1 Institut Eurécom Department of Mobile Communications 2229, route des Crêtes B.P Sophia-Antipolis FRANCE Research Report RR Performance Testing of OLSR using Mobility Predictions March 5 th, 2006 Jérôme Härri, Fethi Filali and Christian Bonnet Tel : (+33) Fax : (+33) Institut Eurécom s research is partially supported by its industrial members: BMW Group Research & Technology - BMW Group Company, Bouygues Télécom, Cisco Systems, France Télécom, Hitachi Europe, SFR, Sharp, STMicroelectronics, Swisscom, Thales.
2
3 Performance Testing of OLSR using Mobility Predictions Jérôme Härri, Fethi Filali and Christian Bonnet Abstract OLSR (Optimized Link State Routing) protocol routing is a proactive routing protocol presented by the IETF MANET (Mobile Ad-hoc NETwork) working group for ad-hoc networks. The common drawback of all tabledriven protocols in MANETs is the large routing overhead for the creation of routing tables. In order to tackle this issue, OLSR uses the Multipoint Relaying protocol (MPR), which main use is to limit the flooding of OLSR routing packets. In a previous study, we illustrated how MPR could benefit from mobility predictions. We introduced the Kinetic Multipoint Relaying (KMPR) protocol which selects kinetic multipoint relays based on the overall nodes predicted degree in the absence of trajectory changes. In this paper, we propose to study the application of the KMPR protocol for OLSR. We show that thanks to KMPR s improved topology knowledge, the route error ratio (RER) and packet delivery ratio (PDR) are consequently improved. OLSR is also able to benefit from the low fraction of messages required my KMPR in order to maintain its topology. The emphasis of this paper is to show that thanks to the use of mobility prediction, OLSR s performances may be significantly improved, at virtually no extra cost in term of routing overhead. Experiments demonstrate a cut by 6 of the RER, while an increase of the PDR of 60% compared to the regular OLSR. Index Terms Performance, Kinetic Multipoint Relay, Mobility Prediction,OLSR, Mobile Ad Hoc Networks.
4
5 Contents 1 Introduction 1 2 Preliminaries OLSR and MPR Multipoint Relays (MPR) OLSR Link State Information Mobility Predictions in MANETs Related Work 4 4 KMPR Kinetic Nodal Degree in MANETs Kinetic Multipoint Relaying (KMPR) KMPR applied to OLSR Simulation Results 9 6 Conclusion and Future Works 11 v
6 List of Figures 1 Illustration of flooding reduction using MPR Double sigmoid function modeling a link lifetime between node i and node j Illustration of nodes kinetic degrees Illustration of the fowarding decision of KMPR vi
7 1 Introduction Mobile Ad Hoc Networks (MANETs) consist of a collection of mobile nodes forming a dynamic autonomous network through a fully mobile infrastructure. Nodes communicate with each other without the intervention of centralized access points or base stations. In such a network, each node acts as a host and may act as a router. Due to limited transmission range of wireless network interfaces, multiple hops may be needed to exchange data between nodes in the network, which is why the literature often uses the term of multi-hop network in MANETs. With the lack of infrastructures and coordinators, MANETs routing protocols have to be robust in order to maintain a connected network, limit the waste of network resources, and optimize the performance of the transfer of data traffic. Several such routing protocols for ad hoc networks have been developed and evaluated [1 3]. These evaluations mainly focus their performance evaluations upon determining the throughput, packet delivery ratio and overhead of the different protocols. The Optimized Link State routing protocol provides an interesting throughput and packet delivery ratio, yet at an important routing overhead, mostly due to the flooding of its periodical topology control messages. In order to improve it, OLSR ( [4]) uses the MPR ( [5]) protocol. Multipoint relaying (MPR) provides a localized way of flooding reduction in a mobile ad hoc network. Using 2-hops neighborhood information, each node determines a small set of forward neighbors for message relaying, which avoids multiple retransmissions and blind flooding. In [6], authors introduced a novel heuristic, called Kinetic Multipoint Relaying (KMPR) protocol, to select kinetic multipoint relays based on nodes overall predicted degree in the absence of trajectory changes. Consequently, thanks to mobility prediction, topology maintenance messages are limited to the instant when unpredicted topology changes happen. The authors illustrated how a significant reduction of the number of messages was then experienced, yet still keeping a coherent and fully connected backbone. In this paper, we propose to study the benefits OLSR may have from the use of KMPR. More precisely, we show that thanks to KMPR s improved topology knowledge, OLSR s Packet Delivery Ratio (PDR) and the Route Error Ratio (RER) are significantly improved. By the low topology maintenance overhead induced by KMPR, OLSR also obtains a better channel access for packet routing. However, as results will show, the collaboration of OLSR and KMPR is also victim of its own success. Indeed, since the packet dropped rate is reduced, a significantly larger number of packets are buffered for transmission after channel access. And it is of public notoriety that the b MAC protocol does not scale either with the number of nodes or the size of uncoordinated traffic. However, the channel access and contention is not in the scope of this work and we will only consider the routing features in this paper. Our objective is to show that after being under study for MPR, mobility prediction is also able to improve OLSR. The rest of the paper is organized as follows. In Section 2, we shortly define our motivations for using mobility predictions with OLSR-KMPR, while in Section 3, 1
8 we provide some related work on performance evaluation for OLSR. Section 4 describes KMPR and OLSR deployment on top of KMPR. Finally, in Section 5, we provide simulation results justifying our approach, while in Section 6 we draw some concluding remarks and describes our future works. 2 Preliminaries In this section, we give a short summary of OLSR functionality, followed by a description of mobility predictions and our motivation for using this concept in MANETs. 2.1 OLSR and MPR The Optimized Link State Routing (OLSR) is a proactive link state routing protocol for mobile ad hoc networks. OLSR contructs and maintain routing tables by diffusing partial link state information to all nodes in the network with the help of an optimized flooding control protocol, called Multi-Point Relaying (MPR) Multipoint Relays (MPR) In order to reduce the effect of flooding messages to all nodes in the network, OLSR selects a subset of nodes, called Multipoint Relays (MPR), to be part of a relaying backbone. In order to build this structure, each node gathers 2-hops neighborhood information and elects the smallest number of relays such that all 2-hops neighbors are covered by at least one relay. Nodes notifies the respective relays of their decision such that each relay maintain a list of nodes, called Multipoint Relaying Selectors (MPR Selector), which has elected it as MPR. Finally, the relaying decision is made on the basis of last-hop address according to the following rule: Definition 1 (MPR flooding) A node retransmits a packet only once after having received the packet the first time from a MPR selector. Figure 1 shows a node with its set of 1-hop and 2-hops neighbors. Fig. 1(a) depicts the initial full topology, while Fig. 1(b) illustrates the MPR topology, where solide circles are MPRs to the central nodes. Accordingly, the central node is part of the MPR Selector list of each solide cirlces nodes OLSR Link State Information In order to create and maintain routing tables, OLSR generates two kinds of control traffic: HELLO packets and TC packets. Hello packets are periodically sent by each node and are never forwarded by any node. The main purpose of this packets is to gather and transmit up to 2-hops neighborhood information. Basically, a HELLO packet contains the list of a node s 2
9 (a) All neighbors retransmit broadcast (b) Only MPR nodes relay broadcast Figure 1: Illustration of flooding reduction using MPR 1-hop neighbor. When received by a neighboring node, that node is able to acquire a view of its 2-hops neighborhood at no extra cost. OLSR however requires transmission over bi-directional links only. Therefore, the set of 1-hop neighbors sent by a HELLO message is slipt up into 4 categories: a list of neighbor nodes from which control traffic has been heard, a list of neighbors with which bi-directional communication are possible, a list of neighbors that has been elected MPR, and finally a list of neighbor nodes which link has been lost. Upon receiving a HELLO message, a node examines the list of addresses. If its own address is included in the MPR list, this mean that the sender elected it as MPR node. Accordinlgly, the sender in added to the list of MPR Selector nodes. In the future, if the node receives traffic from that neighbor, it will forward it. Topology Control (TC) messages are also periodically emitted. The purpose of TC messages is to transmit partial link state information on the network. A TC message can only be generated by a MPR node and contains the MPR Selector list. TC messages are transmitted in the network and uses the MPR protocol in order to reduce redundant transmissions. Upon reception of a TC message, a node knows that the sender is the next hop node to reach all nodes listed in the TC packet. If similar destination are obtained, the route with the fewest hops is chosen. Further details on OLSR are discussed in [4]. 2.2 Mobility Predictions in MANETs In mobility predictions, a mobile node continuously or periodically samples its own location and constructs a model of its own movement. The model can be first order, which provides nodes velocities, but higher and more complex models providing nodes accelerations are also possible. The node disseminates its cur- 3
10 rent model s parameters 1 in the network. Any change to the model s parameters is reactively announced by the respective nodes. Each neighbor node uses this information to track the location of this node. Very little location update cost is incurred if the model s prediction is accurate. A basic assumption in mobility prediction-based techniques is to assume that nodes move following a linear trajectory, then predict to update the neighborhood information when a trajectory change occurs. Therefore, scalability is highly dependent to the number of trajectory changes (or transitions) per unit of time, thereafter called β. Authors in [7] provided a lower bound on the average trajectory duration, that is 1 β 10s using extreme values for the configuration parameters of the mobility models. In more realistic situations, this value is rather 1 β 30s. Accordingly, it becomes conceivable to consider predictions to improve ad-hoc protocol the way we will do in this paper. 3 Related Work Since its creation, OLSR has been widely tested and compared with other proactive and reactive routing protocol in Manets. For example, in [3], authors performed a comparative study of AODV, DSR and OLSR in variying mobility or density conditions, as well as variying traffic types and conditions. They concluded that OLSR performed comparatively to reactive protocols. However, their most interesting result was that none of them outperform the others in every domain. It is important to keep both solutions available to each kind of network configuration, such as WSN, SANETs, or VANETs. This result has been confirmed in [8], where the authors analyzed control traffic overhead based on varying mobility and data traffic activities for the same three protocols. There objective was to predict in which configurations a particualr protocol outperforms the others.they provided a model predicting which protocol yields the lowest overhead depending on properties of the desired targeted network. The author of [9] took a different approach and explored the effect of different traffic loads and varying node density on network performance. They concluded that for meaningful comparisons of routing protocols, traffic and node density have their fair amount of influence and should be wisely chosen. Finally, in [10] tested the peformance of OLSR for real networks. They introduced an interesting Route Change Latency, the time needed to determined a new route after a link failure. They illustrated that control traffic sending rate was essential to increase the end-to-end path connectivity in real networks, at a cost of higher energy consumption and lower reliable data traffic rates. 1 The model s parameters are assumed to be valid over a relative short period of time depending on the model s complexity 4
11 Although deeply interleaved together (see [11]), OLSR and MPR have two independant tasks. The role of MPR is to provide a optimized flooding control mechanism, while OLSR s task is to create routing tables. Both protocols have their own comparision criteria and can be independently compared and improved. We can imagine to use OLSR with a different flooding reduction algorithms, or make AODV benefit from MPR to reduce the diffusion of RREQ messages. As a matter of fact, the research community interested in improving OLSR already successfully tested it with different flooding reduction algorithms, such as NS-MPR, S-MPR, MPR-CDS, and E-CDS [12 14]. They all reached the same conclusion that although creating a larger set of relays, the original MPR protocol reachs a higher broadcast throughput than other tested flooding control algorithm and is better suited for OLSR. This was the motivation of the authors in [6] for using MPR in order to adapt the mobility prediction technique and also a justification for testing KMPR with OLSR as we will do in this paper. 4 KMPR In the first part of this section, we explain the method for modeling kinetic degrees in MANETs. We model nodes positions as a piece-wise linear trajectory and, as showed in [7], the corresponding trajectory durations are lengthy enough to become a valuable cost for computing kinetic degrees. In the second part, we formally describe the Kinetic Multipoint Relaying (KMPR) protocol. Finally, in the last part, we shortly describe how OLSR is implemented on top of KMPR. 4.1 Kinetic Nodal Degree in MANETs The term Kinetic in KMPR reflects the motion aspect of our algorithm, which computes a node s trajectory based on its Location Information [18]. Such location information may be provided by the Global Positioning System (GPS) or other solutions exposed in [24] or [25]. Velocity may be derived through successive location samples at close time instants. Therefore, we assume a global time synchronization between nodes in the network and define x, y, dx, dy as the four parameters describing a node s position and instant velocity 2, thereafter called mobility. Over a relatively short period of time 3, one can assume that each such node, say i, follows a linear trajectory. Its position as a function of time is then described by Pos i (t) = [ xi + dx i t y i + dy i t ], (1) 2 We are considered moving in a two-dimensional plane. 3 The time required to transmit a data packet is orders of magnitude shorter than the time the node is moving along a fixed trajectory. 5
12 where Pos i (t) represents the position of node i at time t, the vector [x i,y i ] T denotes the initial position of node i, and vector [dx i,dy i ] T its initial instantaneous velocity. Let us consider node j as a neighbor of i. In order to let node i compute node j s trajectory, let us define the squared distance between nodes i and j as Dij(t) 2 = Dji(t) 2 = Pos j (t) Pos i (t) 2 2 ([ ] [ ] xj x = i dxj dx + i y j y i dy j dy i ) 2 t = a ij t 2 + b ij t + c ij, (2) where a ij 0, c ij 0. Consequently, a ij,b ij,c ij are defined as the three parameters describing nodes i and j mutual trajectories, and D 2 ij (t) =a ijt 2 + b ij t + c ij, representing j s relative distance to node i, is denoted as j s linear relative trajectory to i. Consequently, thanks to (1), a node is able to compute the future position of its neighbors, and by using (2), it is able to extract any neighboring nodes future relative distance. Considering r as nodes maximum transmission range, as long as D 2 ij (t) r2, nodes i and j are neighbors. Therefore, solving Dij 2 (t) r2 = 0 a ij t 2 + b ij t + c ij r 2 = 0, (3) gives t from ij and t to ij as the time intervals during which nodes i and j remain neighbors. Consequently, we can model nodes kinetic degree as two successive sigmoid functions, where the first one jumps to one when a node enters another node s neighborhood, and the second one drops to zero when that node effectively leaves that neighborhood (see Fig. 2). 1 from t ij to t ij t Figure 2: Double sigmoid function modeling a link lifetime between node i and node j Considering nbrs i as the total number of neighbors detected in node i s neighborhood at time t, we define 6
13 Deg i (t) = ( nbrs i 1 k=0 1+exp( a (t t from k )) ) 1 1+exp(a (t t to k )) (4) as node i s kinetic degree function, where t from k and t to k represent respectively the time a node k enters and leaves i s neighborhood. Thanks to (4), each node is able to predict its actual and future degree and thus is able to proactively adapt its coverage capacity. Fig. 3(a) illustrates the situation for three nodes. Node k enters i s neighborhood at time t =4s and leave it at time t =16s. Meanwhile, node j leaves i s neighborhood at time t =20s. Consequently, Fig. 3(b) illustrates the evolution of the kinetic degree function over t. t=16 ¾ Ö i r ½ k t=4 j t=20 Ø Ø ½ Ø ¾¼ Ø (a) Node i kinetic neighborhood (b) Node i kinetic nodal degree Figure 3: Illustration of nodes kinetic degrees Finally, the kinetic degree is obtained by integrating Eq. 4 Deg i (t) = ( k=nbrsi t k=0 1 1+exp(a (t t to k ))) 1 ( 1+exp( a (t t from k )) ) For example, in Fig. 3(b), node i kinetic degree is 32. (5) 4.2 Kinetic Multipoint Relaying (KMPR) In this section, we describe the Kinetic Multipoint Relaying (KMPR) protocol. It is mainly extracted from the regular MPR protocol. Yet, it has been adapted to deal with kinetic degrees. ½ 7
14 To select the kinetic multipoint relays for node i, let us call the set of 1-hop neighbors of node i as N(i), and the set of its 2-hops neighbors as N 2 (i). We first start by giving some definitions. Definition 2 (Covering Interval) The covering interval is a time interval during which a node in N 2 (i) is covered by a node in N(i). Each node in N 2 (i) has a covering interval per node i, which is initially equal to the connection interval between its covering node in N(i) and node i. Then, each time a node in N 2 (i) is covered by a node in N(i) during a given time interval, this covering interval is properly reduced. When the covering interval is reduced to, we say that the node is fully covered. Definition 3 (Logical Kinetic Degree) The logical kinetic degree is the nodal degree obtained with (5) but considering covering intervals instead of connection intervals. In that case, t from k and t to k will then represent the time interval during which a node k N 2 (i) starts and stops being covered by some node in N(i). The basic difference between MPR and KMPR is that unlike MPR, KMPR does not work on time instants but on time intervals. Therefore, a node is not periodically elected, but is instead designated KMPR for a time interval. During this interval, we say that the KMPR node is active and the time interval is called its activation. The KMPR protocol elects a node as KMPR a node in N(i) with the largest logical kinetic degree. The activation of this KMPR node is the largest covering interval of its nodes in N 2 (i). Kinetic Multipoint Relaying Protocol (KMPR): The KMPR protocol applied to an initiator node i is defined as follows: Begin with an empty KMPR set. First Step: Compute the logical kinetic degree of each node in N(i). Second Step: Add in the KMPR set the node in N(i) that has the maximum logical kinetic degree. Compute the activation of the KMPR node as the maximum covering interval this node can provide. Update all other covering intervals of nodes in N 2 (i) considering the activation of the elected KMPR, then recompute all logical kinetic degrees. Finally, repeat this step until all nodes in N 2 (i) are fully covered. Then, each node having elected a node KMPR for some activations is then a KMPR Selector during the same activation. Finally, KMPR flooding is defines as follows: Definition 4 (KMPR flooding) A node retransmits a packet only once after having received the packet the first time from an active KMPR selector. 8
15 4.3 KMPR applied to OLSR In order to construct and maintain its routing tables, OLSR periodically sends link state information in the network. The interaction between OLSR and MPR is therefore that OLSR benefits from MPR flooding to reduce the redundant transmission of identical TC packets (also known as the Broadcast Storm Problem). Although sharing some common properties and mutual requirements (see [11]), it can be mentioned that OLSR and MPR are functionaly independent. OLSR sends link state packets and MPR relays only if the packet has come from a MPR selector. As a matter of fact, the research community interested in improving OLSR already successfully tested it with different flooding reduction algorithms, such as NS-MPR, S-MPR, MPR-CDS, and E-CDS. KMPR creates a set of KMPR selectors and their respective activations. Compared to MPR, the difference is that KMPR has computed actual and future KMPR selectors. Each KMPR selector and its relaying capability will be activated when its activation becomes valid. Accordingly, we can see that OLSR can be easily adapted to use KMPR instead of MPR. It will still periodically send topology messages and the forwading decision is simply kept transparent to it. Indeed, each OLSR TC message is forwarded by KMPR according to Definition 1. Although KMPR uses activations in order to maintain its set of KMPR selectors, each forwarding decision will be taken by each node based on Fig 4. Reception of a TC Packet KMPR Selector? Yes No Ready No Active? No Yes Forwards Packet Yes First Copy? Figure 4: Illustration of the fowarding decision of KMPR 5 Simulation Results We implemented the OLSR-KMPR protocol under ns-2 and compared it with OLSR-MPR. The global parameters we used for the simulations are given in Table 1. We measured several significant metrics for MANETs routing: 9
16 Packet Delivery Ratio (PDR) It is the ratio between the number of packets delivered to the receiver and the expected number of packet sent. Route Error Ratio (RER) It represents the ratio between the number of packets dropped due to the lack of valid routes, and the total number of packet sent. Routing Overhead Ratio (ROR) It represents the ratio between the number of routing bytes and total number of bytes correctly received. Delay- It mesures the average end-to-end transmision delay. Finally, we decomposed our performance analysis in three different scenarios, were we fixed the parameters according to Table 2. In the first scenario, we want to see the influence of an increased data rate, whereas in the second scenario, the objective is to test the influence of network mobility. The last scenario aims at observing the effect of the network density on both OLSR-KMPR and OLSR-MPR. Network Simulator ns-2 OLSR Implementation NRLOLSR [26] Simulation time 100s Simulation Area 1500m x 300m grid Tx Range 250m Mobility Model Steady State RWM Node Speed Uniform Network Density π range #nodes X dim Y dim Data Type CBR Data Packet Size 512 bytes MAC Protocol IEEE DCF MAC Rate 2 Mbits/s Confidence Interval 95% Table 1: Simulation parameters Scenarios Data Rate Network Mobility Nodes Density Data Rate 0.08 Mbits/s to 8 0, 10, 20 m/s 8.7 Mbits/s Network Mobility 0.8 Mbits/s 0m/s to 20m/s 8.7 Network Density 0.8 Mbits/s 10m/s 4.3 to Table 2: Simulation Scenarios 10
17 6 Conclusion and Future Works In this paper, we presented a study of the application of Mobility Predictions to the OLSR protocol. We showed that OLSR packet delivery ratio may be improved by a factor of 50% to60%, while the route error can be between 2 and 6 times smaller. More interesting, these improvements are obtained at virtually no extra cost since OLSR-KMPR routing overhead ratio is smaller that OLSR. We consequently illustrated that, after having been studied in other fields of mobile ad hoc networking, mobility predictions are also an interesting technique to improve proactive routing protocols, and that more specifically, OLSR performances may be significantly improved by the use of KMPR and mobility predictions. As we mentioned before when analyzing the increase of the routing overhead ratio, KMPR managed to reduce the number of neighborhood discovery messages. However, when using OLSR, the periodical broadcast of TC packets becomes prohibitive and even increases its influence on OLSR routing overhead as the number of nodes increases. Accordingly, similarly with KMPR and mobility prediction, our next step would be to use the KMPR Selector election intervals as a mean to suppress the need for periodic broadcasts of TC messages in the network. 11
18
19 References [1] J. Broch, D.A. Maltz, David B. Johnson, Y. Hu, and J. Jetcheva, A performance comparison of multihop wireless ad hoc networking protocols, in Proc. of the Fourth Annual ACM/IEEE Internation Conference on Mobile Networking (Mobi- Com 98), pp 25-30, October [2] S.R. Das, C.E. Perkins, and E.M. Royer, Performance comparison of two on-demand routing protocols for ad hoc networks, in Procs of the IEEE Infocom, pp. 3-12, March [3] T. Clausen, P. Jacquet, and L. Viennot, Comparative study of routing protocols for mobile ad hoc networks, in Proc. of the 1st IFIP Annual Mediterranean Ad Hoc Networking Workshop (MedHocNet 02), September, [4] T. Clausen and P. Jacquet, Optimised Link State Routing Protocol (OLSR), October 2003, IETF RFC 3626, Experimental. [5] A. Laouiti et al., Multipoint Relaying: An Efficient Technique for Flooding in Mobile Wireless Networks, 35th Annual Hawaii International Conference on System Sciences (HICSS 2001), Hawaii, USA, [6] J. Haerri, F. Filali, and C. Bonnet, On the Application of Mobility Predictions to Multipoint Relaying in MANETs: Kinetic Multipoint Relays, in Eurecom Technical Report, Institut Eurecom, France, [7] J. Haerri and Christian Bonnet, A Lower Bound for Vehicles Trajectory Duration, in Proc. of the IEEE VTC Fall 2005, Dallas, USA, September [8] P. Jacquet, L. Viennot, T.-H. Clausen Analyzing Control Traffic Overhead in Mobile Ad-hoc Network Protocols versus Mobility and Data Traffic Activity, in Proc of the 1st IFIP Annual Mediterranean Ad Hoc Networking Workshop (MedHocNet 02), September [9] Aders Nilsson, Performance Analysis of Traffic Load and Node Density in Ad Hoc Networks, in Proc. of European Wireless 2004, February [10] C. Gomez,D. Garcia, and J. Paradells, Improving Performance of a Real Ad Hoc Network by Tuning OLSR Parameters in Proc. of the 10th IEEE Symposium on Computers and Communications (ISCC 05), June [11] J. Haerri, and Christian Bonnet, and Fethi Filali, OLSR and MPR: Mutual Dependences and Performances, in Proc. of the 2005 IFIP Med-Hoc-Net Conference, Porquerolles, France, June [12] J.P. Macker and Justin Dean, Simplified Multicast Forwarding in Mobile Ad hoc Networks in Proc. of the IEEE Military Communications Conference (MILCOM 04, November
20 [13] Philippe Jacquet, Performance of Conneced Dominating Set in OLSR protocol in INRIA Tecnical Report N. 5098, February [14] Brian Adamson, Justin Dean, Simplified Multicast Forwarding (SMF) Update, in 64th IETF Meeting November [15] B. Liang and Z. Haas, Predictive distance-based mobility management for pcs networks, in Proc. IEEE Infocom Conference, pp , [16] L. Blazevic et al., Self-Organization in Mobile Ad-Hoc Networks: the Approach of Terminodes, in IEEE Communications Magazine, June [17] William Su, Sung-Ju Lee, and Mario Gerla, Mobility Prediction in Wireless Networks, in Proc. of the IEEE Military Communications Conference (Milcom 05), pp , Vol. 1, October [18] C. Gentile, J. Haerri, and R. E. Van Dyck, Kinetic minimum-power routing and clustering in mobile ad-hoc networks, in IEEE Proc. Vehicular Technology Conf. Fall 2002, pp , Sept [19] Aarti Agarwal and Samir R. Das, Dead Reckoning in Mobile Ad-Hoc Networks, Proc. of the 2003 IEEE Wireless Communications and Networking Conference (WCNC 2003), New Orleans, March [20] V. Kumar and S. R. Das, Performance of Dead Reckoning-Based Location Service for Mobile Ad Hoc Networks, Wireless Communications and Mobile Computing Journal, pp , Vol. 4 Issue 2, Mar [21] J. Haerri, and Navid Nikaein, and Christian Bonnet, Trajectory knowledge for improving topology management in mobile ad-hoc networks, in Proc. of ACM CoNext Conference 2005, Toulouse, France, October [22] D. Son, A. Helmy and B. Krishnamachari, The Effect of Mobility-induced Location Errors on Geographic Routing in Mobile Ad Hoc and Sensor Networks: Analysis and Improvement using Mobility Prediction, IEEE Transactions on Mobile Computing, Special Issue on Mobile Sensor Networks, To appear 3rd Quarter, [23] Jian Tang, Guoliang Xue and Weiyi Zhang, Reliable routing in mobile ad hoc networks based on mobility prediction in MASS 04: IEEE International Conference on Mobile, Ad-Hoc and Sensor Systems, October 25-27, 2004, Fort Lauderdale, Florida, USA. [24] R.J. Fontana and S.J. Gunderson, Ultra-wideband precision asset location system, IEEE Conf. on Ultra Wideband Systems and Technologies, pp ,
Performance Evaluation of AODV, OLSR Routing Protocol in VOIP Over Ad Hoc
(International Journal of Computer Science & Management Studies) Vol. 17, Issue 01 Performance Evaluation of AODV, OLSR Routing Protocol in VOIP Over Ad Hoc Dr. Khalid Hamid Bilal Khartoum, Sudan dr.khalidbilal@hotmail.com
Scenario based Performance Analysis of AODV and OLSR in Mobile Ad hoc Networks
Scenario based Performance Analysis of AODV and OLSR in Mobile Ad hoc Networks Scenario based Performance Analysis of AODV and OLSR in Mobile Ad hoc Networks S. Gowrishankar, T.G. Basavaraju, M. Singh,
A Link-state QoS Routing Protocol for Ad Hoc Networks
A Link-state QoS Routing Protocol for Ad Hoc Networks Anelise Munaretto 1 Hakim Badis 2 Khaldoun Al Agha 2 Guy Pujolle 1 1 LIP6 Laboratory, University of Paris VI, 8, rue du Capitaine Scott, 75015, Paris,
Performance comparison and analysis of routing strategies in Mobile ad hoc networks
2008 International Conference on Computer Science and Software Engineering Performance comparison and analysis of routing strategies in Mobile ad hoc networks Fu Yongsheng, Wang Xinyu, Li Shanping Department
VoIP over MANET (VoMAN): QoS & Performance Analysis of Routing Protocols for Different Audio Codecs
VoIP over MANET (VoMAN): QoS & Performance Analysis of Routing Protocols for Different Audio Codecs Said El brak Mohammed Bouhorma Anouar A.Boudhir ABSTRACT Voice over IP (VoIP) has become a popular Internet
Formal Measure of the Effect of MANET size over the Performance of Various Routing Protocols
Formal Measure of the Effect of MANET size over the Performance of Various Routing Protocols Er. Pooja Kamboj Research Scholar, CSE Department Guru Nanak Dev Engineering College, Ludhiana (Punjab) Er.
NetworkPathDiscoveryMechanismforFailuresinMobileAdhocNetworks
Global Journal of Computer Science and Technology: E Network, Web & Security Volume 14 Issue 3 Version 1.0 Year 2014 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals
Analysis of Application Level Traffics and Routing Protocols in Mobile Ad Hoc Network
Analysis of Application Level Traffics and Routing Protocols in Mobile Ad Hoc Network Rawendra Pratap Singh 1, Savita Shiwani 2 1 Master of Technology (Scholar), Suresh Gyan Vihar University, Jaipur, India
PERFORMANCE ANALYSIS OF AD-HOC ON DEMAND DISTANCE VECTOR FOR MOBILE AD- HOC NETWORK
http:// PERFORMANCE ANALYSIS OF AD-HOC ON DEMAND DISTANCE VECTOR FOR MOBILE AD- HOC NETWORK Anjali Sahni 1, Ajay Kumar Yadav 2 1, 2 Department of Electronics and Communication Engineering, Mewar Institute,
Security Scheme for Distributed DoS in Mobile Ad Hoc Networks
Security Scheme for Distributed DoS in Mobile Ad Hoc Networks Sugata Sanyal 1, Ajith Abraham 2, Dhaval Gada 3, Rajat Gogri 3, Punit Rathod 3, Zalak Dedhia 3 and Nirali Mody 3 1 School of Technology and
Energy Efficiency of Load Balancing in MANET Routing Protocols
Energy Efficiency of Load Balancing in MANET Routing Protocols Sunsook Jung, Nisar Hundewale, Alex Zelikovsky Abstract This paper considers energy constrained routing protocols and workload balancing techniques
Behavior Analysis of TCP Traffic in Mobile Ad Hoc Network using Reactive Routing Protocols
Behavior Analysis of TCP Traffic in Mobile Ad Hoc Network using Reactive Routing Protocols Purvi N. Ramanuj Department of Computer Engineering L.D. College of Engineering Ahmedabad Hiteishi M. Diwanji
An Efficient QoS Routing Protocol for Mobile Ad-Hoc Networks *
An Efficient QoS Routing Protocol for Mobile Ad-Hoc Networks * Inwhee Joe College of Information and Communications Hanyang University Seoul, Korea iwj oeshanyang.ac.kr Abstract. To satisfy the user requirements
Keywords- manet, routing protocols, aodv, olsr, grp,data drop parameter.
Volume 5, Issue 3, March 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Evaluation of
Simulation of Internet Connectivity for Mobile Ad Hoc Networks in Network Simulator-2
Simulation of Internet Connectivity for Mobile Ad Hoc Networks in Network Simulator-2 Sulaiman Khalifa Yakhlef, Ismail Shrena, Nasaraldian Ambark Shashoa Azzaytuna University, Faculty of Engineering Tarhuna
An Extended AODV Protocol to Support Mobility in Hybrid Networks
An Extended AODV Protocol to Support Mobility in Hybrid Networks Sèmiyou A. Adédjouma* Polytechnic School of Abomey-Calavi (EPAC) University of Abomey-Calavi (UAC) Cotonou, Benin *semiyou.adedjouma {at}
Study of Different Types of Attacks on Multicast in Mobile Ad Hoc Networks
Study of Different Types of Attacks on Multicast in Mobile Ad Hoc Networks Hoang Lan Nguyen and Uyen Trang Nguyen Department of Computer Science and Engineering, York University 47 Keele Street, Toronto,
Security and Scalability of MANET Routing Protocols in Homogeneous & Heterogeneous Networks
Security and Scalability of MANET Routing Protocols in Homogeneous & Heterogeneous Networks T.V.P. Sundararajan 1, Karthik 2, A. Shanmugam 3 1. Assistant Professor, Bannari Amman Institute Of Technology,
IJMIE Volume 2, Issue 7 ISSN: 2249-0558
Evaluating Performance of Audio conferencing on Reactive Routing Protocols for MANET Alak Kumar Sarkar* Md. Ibrahim Abdullah* Md. Shamim Hossain* Ahsan-ul-Ambia* Abstract Mobile ad hoc network (MANET)
DESIGN AND DEVELOPMENT OF LOAD SHARING MULTIPATH ROUTING PROTCOL FOR MOBILE AD HOC NETWORKS
DESIGN AND DEVELOPMENT OF LOAD SHARING MULTIPATH ROUTING PROTCOL FOR MOBILE AD HOC NETWORKS K.V. Narayanaswamy 1, C.H. Subbarao 2 1 Professor, Head Division of TLL, MSRUAS, Bangalore, INDIA, 2 Associate
A Comparison Study of Qos Using Different Routing Algorithms In Mobile Ad Hoc Networks
A Comparison Study of Qos Using Different Routing Algorithms In Mobile Ad Hoc Networks T.Chandrasekhar 1, J.S.Chakravarthi 2, K.Sravya 3 Professor, Dept. of Electronics and Communication Engg., GIET Engg.
Performance Comparison and Analysis of Three Gateway Discovery. Protocols of Internet Connectivity for Ad Hoc Networks
Jan. 2006, Volume 3, No.1 (Serial No.14) Journal of Communication and Computer, ISSN1548-7709, USA Performance Comparison and Analysis of Three Gateway Discovery Protocols of Internet Connectivity for
COMPARATIVE ANALYSIS OF ON -DEMAND MOBILE AD-HOC NETWORK
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 2 Issue 5 May, 2013 Page No. 1680-1684 COMPARATIVE ANALYSIS OF ON -DEMAND MOBILE AD-HOC NETWORK ABSTRACT: Mr.Upendra
VOL. 2, NO. 3, March 2012 ISSN ARPN Journal of Systems and Software AJSS Journal. All rights reserved
Performance Comparison and Improvement of Broadcasting Protocols in Mobile Ad-hoc Network 1 Md. Saifur Rahman, 2 Md. Bellal Hossain, 3 Md. Javed Hossain, 4 Mrinal Kanti Baowaly 1,2,3,4 Department of Computer
Optimization of AODV routing protocol in mobile ad-hoc network by introducing features of the protocol LBAR
Optimization of AODV routing protocol in mobile ad-hoc network by introducing features of the protocol LBAR GUIDOUM AMINA University of SIDI BEL ABBES Department of Electronics Communication Networks,
CROSS LAYER BASED MULTIPATH ROUTING FOR LOAD BALANCING
CHAPTER 6 CROSS LAYER BASED MULTIPATH ROUTING FOR LOAD BALANCING 6.1 INTRODUCTION The technical challenges in WMNs are load balancing, optimal routing, fairness, network auto-configuration and mobility
Security Threats in Mobile Ad Hoc Networks
Security Threats in Mobile Ad Hoc Networks Hande Bakiler, Aysel Şafak Department of Electrical & Electronics Engineering Baskent University Ankara, Turkey 21020013@baskent.edu.tr, asafak@baskent.edu.tr
Load-balancing Approach for AOMDV in Ad-hoc Networks R. Vinod Kumar, Dr.R.S.D.Wahida Banu
Load-balancing Approach for AOMDV in Ad-hoc Networks R. Vinod Kumar, Dr.R.S.D.Wahida Banu AP/ECE HOD/ECE Sona College of Technology, GCE, Salem. Salem. ABSTRACT Routing protocol is a challenging issue
The Monitoring of Ad Hoc Networks Based on Routing
The Monitoring of Ad Hoc Networks Based on Routing Sana Ghannay, Sonia Mettali Gammar, Farouk Kamoun CRISTAL Laboratory ENSI, University of Manouba 21 Manouba - Tunisia {chnnysn,sonia.gammar}@ensi.rnu.tn,
Routing with Load Balancing in Wireless Ad hoc Networks
Routing with Load Balancing in Wireless Ad hoc Networks Hossam Hassanein and Audrey Zhou Department of Computing and Information Science Queen's University Kingston, Ontario, Canada, K7L 3N6 {hossam, zhou}@cs.queensu.ca
EXTENDING NETWORK KNOWLEDGE: MAKING OLSR A QUALITY OF SERVICE CONDUCIVE PROTOCOL
EXTENDING NETWORK KNOWLEDGE: MAKING OLSR A QUALITY OF SERVICE CONDUCIVE PROTOCOL by Pedro Eduardo Villanueva-Pena, Thomas Kunz Carleton University January, 2006 This report examines mechanisms to gradually
II RELATED PROTOCOLS. Dynamic Source Routing (DSR)
ENERGY AWEAR LOAD BALANCING IN MOBILE AD HOC NETWORK Prof. Uma Nagaraj Computer Engineering Maharashtra Academy of Engg. Alandi (D) Pune, India Shwetal Patil (Student) Computer Engineering Maharashtra
Intelligent Agents for Routing on Mobile Ad-Hoc Networks
Intelligent Agents for Routing on Mobile Ad-Hoc Networks Y. Zhou Dalhousie University yzhou@cs.dal.ca A. N. Zincir-Heywood Dalhousie University zincir@cs.dal.ca Abstract This paper introduces a new agent-based
PERFORMANCE OF MOBILE AD HOC NETWORKING ROUTING PROTOCOLS IN REALISTIC SCENARIOS
PERFORMANCE OF MOBILE AD HOC NETWORKING ROUTING PROTOCOLS IN REALISTIC SCENARIOS Julian Hsu, Sameer Bhatia, Mineo Takai, Rajive Bagrodia, Scalable Network Technologies, Inc., Culver City, CA, and Michael
Enhanced routing performance and overhead in Mobile Ad-hoc network for big data Transmission in Telemedicine using computer communication network
ISSN (Online) : 2278-1021 Enhanced routing performance and overhead in Mobile Ad-hoc network for big data Transmission in Telemedicine using computer communication network D. Rajasekaran 1, S.Saravanan
A Workload-Based Adaptive Load-Balancing Technique for Mobile Ad Hoc Networks
A Workload-Based Adaptive Load-Balancing Technique for Mobile Ad Hoc Networks Young J. Lee and George F. Riley School of Electrical & Computer Engineering Georgia Institute of Technology, Atlanta, GA 30332
Towards Efficient Routing in Vehicular Ad Hoc Networks
Towards Efficient Routing in Vehicular Ad Hoc Networks Moez Jerbi*, Sidi-Mohammed Senouci* and Yacine Ghamri-Doudane** *France Telecom R&D, Core Network Laboratories, Lannion, France **Networks and Multimedia
Optimized Load Balancing Mechanism Using Carry Forward Distance
Optimized Load Balancing Mechanism Using Carry Forward Distance Ramandeep Kaur 1, Gagandeep Singh 2, Sahil 3 1 M. Tech Research Scholar, Chandigarh Engineering College, Punjab, India 2 Assistant Professor,
ADAPTIVE LINK TIMEOUT WITH ENERGY AWARE MECHANISM FOR ON-DEMAND ROUTING IN MANETS
ADAPTIVE LINK TIMEOUT WITH ENERGY AWARE MECHANISM FOR ON-DEMAND ROUTING IN MANETS M. Tamilarasi 1, T.G. Palanivelu 2, 1, 2 Department of ECE, Pondicherry Engineering College, Puducherry-605014. Email:
SIMULATION STUDY OF BLACKHOLE ATTACK IN THE MOBILE AD HOC NETWORKS
Journal of Engineering Science and Technology Vol. 4, No. 2 (2009) 243-250 School of Engineering, Taylor s University College SIMULATION STUDY OF BLACKHOLE ATTACK IN THE MOBILE AD HOC NETWORKS SHEENU SHARMA
Study of Network Characteristics Incorporating Different Routing Protocols
Study of Network Characteristics Incorporating Different Routing Protocols Sumitpal Kaur #, Hardeep S Ryait *, Manpreet Kaur # # M. Tech Student, Department of Electronics and Comm. Engineering, Punjab
Delay aware Reactive Routing Protocols for QoS in MANETs: a Review
Delay aware Reactive Routing Protocols for QoS in MANETs: a Review Saad M. Adam*, Rosilah Hassan Network and Communication Technology Research Group, Faculty of Information Science and Technology, Universiti
Natarajan Meghanathan Assistant Professor of Computer Science Jackson State University Jackson, MS 39217, USA nmeghanathan@jsums.
A Simulation Based Performance Comparison Study of Stability-Based Routing, Power-Aware Routing and Load-Balancing On-Demand Routing Protocols for Mobile Ad hoc Networks Natarajan Meghanathan Assistant
PERFORMANCE STUDY AND SIMULATION OF AN ANYCAST PROTOCOL FOR WIRELESS MOBILE AD HOC NETWORKS
PERFORMANCE STUDY AND SIMULATION OF AN ANYCAST PROTOCOL FOR WIRELESS MOBILE AD HOC NETWORKS Reza Azizi Engineering Department, Bojnourd Branch, Islamic Azad University, Bojnourd, Iran reza.azizi@bojnourdiau.ac.ir
Adaptive Multiple Metrics Routing Protocols for Heterogeneous Multi-Hop Wireless Networks
Adaptive Multiple Metrics Routing Protocols for Heterogeneous Multi-Hop Wireless Networks Lijuan Cao Kashif Sharif Yu Wang Teresa Dahlberg Department of Computer Science, University of North Carolina at
A Survey: High Speed TCP Variants in Wireless Networks
ISSN: 2321-7782 (Online) Volume 1, Issue 7, December 2013 International Journal of Advance Research in Computer Science and Management Studies Research Paper Available online at: www.ijarcsms.com A Survey:
Position and Velocity Aided Routing Protocol in Mobile Ad Hoc Networks
Position and Velocity Aided Routing Protocol in Mobile Ad Hoc Networks 1 Taifei Zhao, 2 Xizheng Ke, 3 Peilin Yang *1,Corresponding Author Department of Electronics Engineering, Xi an University of Technology,
Simulation vs. Emulation: Evaluating Mobile Ad Hoc Network Routing Protocols
Simulation vs. Emulation: Evaluating Mobile Ad Hoc Network Routing Protocols Furqan Haq and Thomas Kunz Systems and Computer Engineering Carleton University Ottawa, Ont., Canada K1S 5B haq_furqan@hotmail.com,
Implementation of a Lightweight Service Advertisement and Discovery Protocol for Mobile Ad hoc Networks
Implementation of a Lightweight Advertisement and Discovery Protocol for Mobile Ad hoc Networks Wenbin Ma * Department of Electrical and Computer Engineering 19 Memorial Drive West, Lehigh University Bethlehem,
PERFORMANCE ANALYSIS OF AODV, DSR AND ZRP ROUTING PROTOCOLS IN MANET USING DIRECTIONAL ANTENNA
International Research Journal of Engineering and Technology (IRJET) e-issn: -00 Volume: 0 Issue: 0 Oct-01 www.irjet.net p-issn: -00 PERFORMANCE ANALYSIS OF AODV, DSR AND ZRP ROUTING PROTOCOLS IN MANET
Performance Analysis of Load Balancing in MANET using On-demand Multipath Routing Protocol
ISSN: 2278 1323 All Rights Reserved 2014 IJARCET 2106 Performance Analysis of Load Balancing in MANET using On-demand Multipath Routing Protocol Monika Malik, Partibha Yadav, Ajay Dureja Abstract A collection
Comparative Study of Routing Protocols for Mobile Ad-hoc NETworks
Comparative Study of Routing Protocols for Mobile Ad-hoc NETworks Thomas Heide Clausen *, Philippe Jacquet and Laurent Viennot INRIA Rocquencourt, Projet Hipercom, Domaine de Voluceau, B.P.5, 7853 Le Chesnay
Load-Balanced Routing through Virtual Paths: Highly Adaptive and Efficient Routing Scheme for Ad Hoc Wireless Networks
Load-Balanced Routing through Virtual Paths: Highly Adaptive and Efficient Routing Scheme for Ad Hoc Wireless Networks Abdulrahman H. Altalhi Computer Science Department University of New Orleans New Orleans,
Performance Comparison of AODV, DSDV, DSR and TORA Routing Protocols in MANETs
International Research Journal of Applied and Basic Sciences. Vol., 3 (7), 1429-1436, 2012 Available online at http:// www. irjabs.com ISSN 2251-838X 2012 Performance Comparison of AODV, DSDV, DSR and
Advanced Computer Networks
Introduction to Mobile Ad hoc Networks (MANETs) Advanced Computer Networks Outline Ad hoc networks Differences to other networks Applications Research areas Routing Other research areas Enabling Technologies
Secured Data Transmissions In Manet Using Neighbor Position Verfication Protocol
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 3 Issue3 March, 2014 Page No. 5067-5071 Secured Data Transmissions In Manet Using Neighbor Position Verfication
Performance Evaluation and Investigation of Energy in AODV, OLSR Protocols through Simulation
Performance Evaluation and Investigation of Energy in AODV, OLSR Protocols through Simulation Dharam Vir 1, S.K Agarwal 2 and S.A. Imam 3 1 Research Scholar, Department of Electronics Engg. YMCA UST, Faridabad,
Load balanced routing in mobile ad hoc networks
Computer Communications 27 (2004) 295 305 www.elsevier.com/locate/comcom Load balanced routing in mobile ad hoc networks Vikrant Saigal a, Ajit K. Nayak b, *, Sateesh K. Pradhan c, R. Mall a a Department
Energy Consumption analysis under Random Mobility Model
DOI: 10.7763/IPEDR. 2012. V49. 24 Energy Consumption analysis under Random Mobility Model Tong Wang a,b, ChuanHe Huang a a School of Computer, Wuhan University Wuhan 430072, China b Department of Network
Performance Evaluation of Mobility Speed over MANET Routing Protocols
International Journal of Network Security, Vol., No.3, PP.28 38, Nov. 2 28 Performance Evaluation of Mobility Speed over MANET Routing Protocols Yasser Kamal Hassan, Mohamed Hashim Abd El-Aziz 2, and Ahmed
AIR FORCE INSTITUTE OF TECHNOLOGY
Voice Traffic over Mobile Ad Hoc Networks: A Performance Analysis of the Optimized Link State Routing Protocol THESIS Lady Noreen P. Santos, Captain, USAF AFIT/GCE/ENG/09-09 DEPARTMENT OF THE AIR FORCE
Internet Connectivity for Ad hoc Mobile Networks
Internet Connectivity for Ad hoc Mobile Networks Yuan Sun Elizabeth M. Belding-Royer Department of Computer Science University of California, Santa Barbara suny, ebelding @cs.ucsb.edu Charles E. Perkins
Performance Evaluation of Aodv and Dsr Routing Protocols for Vbr Traffic for 150 Nodes in Manets
Performance Evaluation of Aodv and Dsr Routing Protocols for Vbr Traffic for 150 Nodes in Manets Gurpreet Singh, 1 Atinderpal Singh 2, 1, 2 Department of CSE & IT, BBSBEC, Fatehgarh Sahib, Punjab, India
Comprehensive Evaluation of AODV, DSR, GRP, OLSR and TORA Routing Protocols with varying number of nodes and traffic applications over MANETs
IOSR Journal of Computer Engineering (IOSR-JCE) e-issn: 2278-0661, p- ISSN: 2278-8727Volume 9, Issue 3 (Mar. - Apr. 2013), PP 54-61 Comprehensive Evaluation of AODV, DSR, GRP, OLSR and TORA Routing Protocols
LOAD BALANCING AND EFFICIENT CLUSTERING FOR IMPROVING NETWORK PERFORMANCE IN AD-HOC NETWORKS
LOAD BALANCING AND EFFICIENT CLUSTERING FOR IMPROVING NETWORK PERFORMANCE IN AD-HOC NETWORKS Saranya.S 1, Menakambal.S 2 1 M.E., Embedded System Technologies, Nandha Engineering College (Autonomous), (India)
2. Related protocols. 1. Introduction
Virtual Cellular Infrastructure For Mobile Ad hoc Network Muthu Chidambaranathan.P, Sundaresan S muthuc@nitt.edu Department of electronics and communication engineering National institute of technology,
Step by Step Procedural Comparison of DSR, AODV and DSDV Routing protocol
th International Conference on Computer Engineering and Technology (ICCET ) IPCSIT vol. () () IACSIT Press, Singapore Step by Step Procedural Comparison of DSR, AODV and DSDV Routing protocol Amith Khandakar
Abstract. 1 Introduction. Aleksandr Huhtonen Helsinki University of Technology Telecommunication Software and Multimedia Laboratory ahuhtone@cc.hut.
Comparing AODV and OLSR Routing Protocols Aleksandr Huhtonen Helsinki University of Technology Telecommunication Software and Multimedia Laboratory ahuhtone@cc.hut.fi Abstract An ad hoc wireless network
Realistic Mobility for Mobile Ad Hoc Network Simulation
Realistic Mobility for Mobile Ad Hoc Network Simulation Michael Feeley, Norman Hutchinson, and Suprio Ray Computer Science Department, University of British Columbia, Vancouver, Canada Abstract. In order
A Performance Comparison of Stability, Load-Balancing and Power-Aware Routing Protocols for Mobile Ad Hoc Networks
A Performance Comparison of Stability, Load-Balancing and Power-Aware Routing Protocols for Mobile Ad Hoc Networks Natarajan Meghanathan 1 and Leslie C. Milton 2 1 Jackson State University, 1400 John Lynch
1 M.Tech, 2 HOD. Computer Engineering Department, Govt. Engineering College, Ajmer, Rajasthan, India
Volume 5, Issue 5, May 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Dynamic Performance
Node Mobility Tracking In Mobile Ad-Hoc Networks in their Geographical Position (Dynamic Networks)
Node Mobility Tracking In Mobile Ad-Hoc Networks in their Geographical Position (Dynamic Networks) A. Subramani, A. Krishnan Abstract In mobile ad-hoc network, nodes of position change due to dynamic nature.
Robust Routing in Wireless Ad Hoc Networks
Robust Routing in Wireless Ad Hoc Networks Seungjoon Lee, Bohyung Han, Minho Shin {slee, bhhan, mhshin}@cs.umd.edu Computer Science Department University of Maryland College Park, MD 2742 USA Abstract
ROUTE MECHANISMS FOR WIRELESS ADHOC NETWORKS: -CLASSIFICATIONS AND COMPARISON ANALYSIS
International Journal of Science, Environment and Technology, Vol. 1, No 2, 2012, 72-79 ROUTE MECHANISMS FOR WIRELESS ADHOC NETWORKS: -CLASSIFICATIONS AND COMPARISON ANALYSIS Ramesh Kait 1, R. K. Chauhan
SJBIT, Bangalore, KARNATAKA
A Comparison of the TCP Variants Performance over different Routing Protocols on Mobile Ad Hoc Networks S. R. Biradar 1, Subir Kumar Sarkar 2, Puttamadappa C 3 1 Sikkim Manipal Institute of Technology,
Study And Comparison Of Mobile Ad-Hoc Networks Using Ant Colony Optimization
Study And Comparison Of Mobile Ad-Hoc Networks Using Ant Colony Optimization 1 Neha Ujala Tirkey, 2 Navendu Nitin, 3 Neelesh Agrawal, 4 Arvind Kumar Jaiswal 1 M. Tech student, 2&3 Assistant Professor,
A UBIQUITOUS PROTOCOL FOR ADDRESS DYNAMICALLY AUTO CONFIGURATION FOR MOBILE AD HOC NETWORKS
A UBIQUITOUS PROTOCOL FOR ADDRESS DYNAMICALLY AUTO CONFIGURATION FOR MOBILE AD HOC NETWORKS Chandanpreet Kaur Global Institute of Management and Emerging Technologies, Amritsar, Punjab, India, lpu_chandan@yahoo.co.in
INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY
INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK AN OVERVIEW OF MOBILE ADHOC NETWORK: INTRUSION DETECTION, TYPES OF ATTACKS AND
Figure 1. The Example of ZigBee AODV Algorithm
TELKOMNIKA Indonesian Journal of Electrical Engineering Vol.12, No.2, February 2014, pp. 1528 ~ 1535 DOI: http://dx.doi.org/10.11591/telkomnika.v12i2.3576 1528 Improving ZigBee AODV Mesh Routing Algorithm
AntHocNet: an Ant-Based Hybrid Routing Algorithm for Mobile Ad Hoc Networks
: an Ant-Based Hybrid Routing Algorithm for Mobile Ad Hoc Networks Gianni Di Caro, Frederick Ducatelle and Luca Maria Gambardella Istituto Dalle Molle sull Intelligenza Artificiale (IDSIA) Galleria 2,
CAODV: Routing in Mobile Ad-hoc Cognitive Radio Networks
: Routing in Mobile Ad-hoc Cognitive Radio Networks Angela Sara Cacciapuoti, Cosimo Calcagno, Marcello Caleffi Department of Biomedical, Electronics and Telecommunications Engineering University of Naples
Comparative Study of Performance Evaluation for Mobile Ad hoc networks using a proxy node
Comparative Study of Performance Evaluation for Mobile Ad hoc networks using a proxy node G. E. RIZOS georizos@teiep.gr D. C. VASILIADIS dvas@teiep.gr E. STERGIOU ster@teiep.gr Abstract: In this paper,
Location-Aided Routing (LAR) in mobile ad hoc networks
Wireless Networks 6 (2000) 307 321 307 Location-Aided Routing (LAR) in mobile ad hoc networks Young-Bae Ko and Nitin H. Vaidya Department of Computer Science, Texas A&M University, College Station, TX
International Journal of Advanced Research in Computer Science and Software Engineering
Volume 2, Issue 9, September 2012 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Power Aware
Simulation Analysis of Different Routing Protocols Using Directional Antenna in Qualnet 6.1
Simulation Analysis of Different Routing Protocols Using Directional Antenna in Qualnet 6.1 Ankit Jindal 1, Charanjeet Singh 2, Dharam Vir 3 PG Student [ECE], Dept. of ECE, DCR University of Science &
Achieving Energy Efficiency in MANETs by Using Load Balancing Approach
International Journal of Computer Networks and Communications Security VOL. 3, NO. 3, MARCH 2015, 88 94 Available online at: www.ijcncs.org E-ISSN 2308-9830 (Online) / ISSN 2410-0595 (Print) Achieving
ISSUES AND CHALLENGES OF QUALITY OF SERVICE IN MOBILE ADHOC NETWORK
ISSUES AND CHALLENGES OF QUALITY OF SERVICE IN MOBILE ADHOC NETWORK Mukesh Kumar Student (Ph.D) Department of Computer Engineering The Technological Institute of Textile and Science, Bhiwani-127021, Haryana
On Reliability of Dynamic Addressing Routing Protocols in Mobile Ad Hoc Networks
On Reliability of Dynamic Addressing Routing Protocols in Mobile Ad Hoc Networks Marcello Caleffi, Giancarlo Ferraiuolo, Luigi Paura Department of Electronic and Telecommunication Engineering (DIET) University
Intelligent Transportation System for Vehicular Ad-Hoc Networks
Intelligent Transportation System for Vehicular Ad-Hoc Networks T. Sujitha 1, S. Punitha Devi 2 1,2 Department of CSE, P.A College of Engineering and Technology, Coimbatore, Tamilnadu Abstract - Vehicular
OPTIMIZED SENSOR NODES BY FAULT NODE RECOVERY ALGORITHM
OPTIMIZED SENSOR NODES BY FAULT NODE RECOVERY ALGORITHM S. Sofia 1, M.Varghese 2 1 Student, Department of CSE, IJCET 2 Professor, Department of CSE, IJCET Abstract This paper proposes fault node recovery
OLSR Performance Measurement in a Military Mobile Ad-hoc Network
OLSR Performance Measurement in a Military Mobile d-hoc Network Thierry Plesse ½, Jerome Lecomte ½, Cedric djih ¾, Marc Badel ¾, Philippe Jacquet ¾, nis Laouiti ¾, Pascale Minet ¾, Paul Muhlethaler ¾,
Lecture 2.1 : The Distributed Bellman-Ford Algorithm. Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol
Lecture 2 : The DSDV Protocol Lecture 2.1 : The Distributed Bellman-Ford Algorithm Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol The Routing Problem S S D D The routing problem
Security for Ad Hoc Networks. Hang Zhao
Security for Ad Hoc Networks Hang Zhao 1 Ad Hoc Networks Ad hoc -- a Latin phrase which means "for this [purpose]". An autonomous system of mobile hosts connected by wireless links, often called Mobile
Reliable Adaptive Lightweight Multicast Protocol
Reliable Adaptive Lightweight Multicast Protocol Ken Tang Scalable Network Technologies ktang@scalable-networks.com Katia Obraczka UC Santa Cruz katia@cse.ucsc.edu Sung-Ju Lee HP Labs sjlee@hpl.hp.com
Comparison of WCA with AODV and WCA with ACO using clustering algorithm
Comparison of WCA with AODV and WCA with ACO using clustering algorithm Deepthi Hudedagaddi, Pallavi Ravishankar, Rakesh T M, Shashikanth Dengi ABSTRACT The rapidly changing topology of Mobile Ad hoc networks
Robust Security Solution to Countermeasure of Malicious Nodes for the Security of MANET
Robust Security Solution to Countermeasure of Malicious Nodes for the Security of MANET Kritika Sharma M.tech(CSE) Doon Valley Insttitute of Enggineering & Technology, Karnal Parikshit Singla Assistant
Performance Evaluation of Unicast and Broadcast Mobile Ad-hoc Networks Routing Protocols
Vol. 7, No., 200 Performance Evaluation of Unicast and Broadcast Mobile Ad-hoc Networks Routing Protocols Sumon Kumar Debnath, Foez Ahmed 2, and Nayeema Islam 3 Dept. of Computer Science and Telecommunication
A Comparison Study of Address Autoconfiguration Schemes for Mobile Ad hoc Network
A Comparison Study of Address Autoconfiguration Schemes for Mobile Ad hoc Network Soyeon Ahn, Namhoon Kim, Woohyun Kim and Younghee Lee Information and Communications University, Computer Networks Lab.,
Routing Protocols for Mobile Ad-hoc Networks: Current Development and Evaluation
Routing Protocols for Mobile Ad-hoc Networks: Current Development and Evaluation Zhijiang Chang, Georgi Gaydadjiev, Stamatis Vassiliadis Computer Engineering laboratory, EEMCS, Delft University of Technology