VIEWS: 51 PAGES: 13 CATEGORY: Emerging Technologies POSTED ON: 5/8/2010
Volume 8 No. 1 April 2010 International Journal of Computer Science - Research Series
(IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 QoS Routing For Mobile Adhoc Networks And Performance Analysis Using OLSR Protocol K.Oudidi A.Hajami M.Elkoutbi Si2M Laboratory Si2M Laboratory Si2M Laboratory National School of Computer Science National School of Computer Science National School of Computer Science and Systems Analysis, Rabat, Morocco and Systems Analysis, Rabat, Morocco and Systems Analysis, Rabat, Morocco k_oudidi@yahoo.fr Abdelmajid_hajami@yahoo.fr elkoutbi@ensias.ma categories Abstract-- This paper proposes a novel routing metrics based on of MANET routing protocols: Proactive (table-driven), the residual bandwidth, energy and mobility index of the nodes. Reactive (on-demand) and Hybrid. Proactive protocols build Metrics are designed to cope with high mobility and poor their routing tables continuously by broadcasting periodic residual energy resources in order to find optimal paths that guarantee the QoS constraints. A maximizable routing metric routing updates through the network; reactive protocols build theory has been used to develop a metric that selects, during thetheir routing tables on demand and have no prior knowledge protocol process, routes that are more stable, offer a maximum of the route they will take to get to a particular node. Hybrid throughput and prolong network life time. The OLSR protocols create reactive routing zones interconnected by (Optimized Link State Routing) protocol, which is an proactive routing links and usually adapt their routing strategy optimization of link state protocols designed for MANETs to the amount of mobility in the network. (Mobile Ad hoc Networks) is used as a test bed in this work. We prove that our proposed composite metrics (based on mobility, In this paper we reiterate our proposed mobility metric. energy and bandwidth) selects a more stable MPR set than the Based on the use of this mobility metric we propose a new QOLSR algorithm which is a well known OLSR QoS extension. composite metric, to find the optimal path given the QoS By mathematical analysis and simulations, we have shown the constraints. The objective of the composite metric is to find an efficiency of this new routing metric in term of routing load, optimal stable path with maximum available bandwidth and to packet delivery fraction, delay and prolonging the network lifetime. prolong network life time. Using the OLSR Protocol, we show that our proposed Index Terms— Mobile Ad hoc networks, quality of service, routing metric selects stable MPR Set rather than the QOLSR protocol, routing metric, mobility, residual energy. algorithm which is a well known OLSR QoS algorithm for MANETs. I. INTRODUCTION This paper is organized as follows. Section 2 gives an A Mobile Ad hoc Network (MANET) is a collection of overview of the original OLSR protocol. Section 3 summarizes mobile nodes working on a dynamic autonomous network. the state of the art dealing with QoS support in MANETs and Nodes communicate with each other over the wireless medium describes the QoS routing problems Section 4 presents our without need of a centralized access points or a base station. proposed composite metric based on mobility, residual energy Since there is no existing communication infrastructure, and bandwidth as QoS parameters. In Section 5, simulations adhoc networks cannot rely on specialised routers for path and results are discussed. The last part of this paper concludes discovery and routing. Therefore, nodes in such a network are expected to act cooperatively to establish routes instantly. and presents some future work. Such a network is also expected to route traffic, possibly over multiple hops, in distributed manner, and to adapt itself to the II. OPTIMIZED LINK STATE ROUTING PROTOCOL highly dynamic changes of its links , mobility and residual energy patterns of its constituent nodes. A. Overview OLSR (Optimized Link State Routing) protocol [2-3] is a Providing QoS in MANETs [1] is a tedious task. It’s known proactive table driven routing protocol for mobile ad hoc that combining multiple criteria in the routing process is a networks and it is fully described on RFC 3626 (Thomas Hard problem (NP-Complet) A complete QoS model in Clausen & Philippe Jacquet, (October 2003)). As a link state MANETs will span multiple layers, however the network routing protocol, OLSR periodically advertises the links layer plays a vital role in providing the required support building the network. However, OLSR optimizes the topology mechanisms. The goal of QoS routing is to obtain feasible information flooding mechanism, by reducing the amount of paths that satisfy end-system performance requirements. Most links that are advertised and by reducing the number of nodes QoS routing algorithms present an extension of existing forwarding each topology message to the set of MPRs only. classic best effort routing algorithms. There are three main Information topology is called Topology Control (TC) message 138 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 and exchanged using broadcasted into the network. TC Based on the above notations, the standard algorithm for messages are only originated by nodes selected as Multipoint MPR selection is defined as follows (figure 2-b): Relays (MPRs) by some other node in the network. MPRs are OLSR uses hop count to compute the shortest path to an selected in such a way that a minimum amount of MPRs, arbitrary destination using the topology map consisting of all located one-hop away from the node doing the selection its neighbours and of MPRs of all other nodes. Number of hop (called MPR Selector), are enough to reach every single criterion as a routing metric is not suitable for QoS support as neighbour located two-hops away of MPR selector. By a path selected based on the least number of hops may not applying this selection mechanism only a reduced amount of satisfy the required QoS constraints. nodes (depending on the network topology) will be selected as MPRs[18]. Every node in the network is aware of its one-hop and two-hop neighbours by periodically exchanging HELLO messages containing the list of its one-hop neighbours. On the other hand, TC messages will only advertise the links between the MPRs and their electors. Then, only a partial amount of the network links (the topology) will be advertised, also MPRs are the only nodes allowed to forward TC messages and only if messages come from a MPR Selector node. These forwarding constrains considerably decrease the amount of flooding retransmissions (Figure 1). This example shows the efficiency of the MPR mechanism because only eight transmissions are required to reach all the 23 nodes building the network, which is a significant saving when compared to traditional flooding mechanism where every node is asked to Figure 2-b: MPR Selection Algorithm retransmit to all neighbours. III. RELATED WORK A. Qos Support in a Manet In this section we discuss the recent work done to provide QoS functionality in Manets. INSIGNIA, [7], is an adaptation of the IntServ Model to the mobile ad hoc networks. QoS guarantee is done by per-flow Figure 1: Flooding with MPR mechanism information in each node that is set up by the B. MPR Selection Algorithm signalling/reservation protocol. The destination statistically measures QoS parameters (e.g. packet loss, delay, average The computation of the MPR set with minimal size is a NP- complet problem [14-16]. For this end, the standard MPR throughput,etc.) and periodically sends QoS reports to the selection algorithm currently used in the OLSR protocol source. Based on those reports, the source node can adapt real- time flows to avoid congestion. implementations is as follows: SWAN, [13], Service differentiation in stateless Wireless Ad-hoc Network, is an adaptation of the DiffServ Model to the mobile ad-hoc networks. Nodes do not need to keep per-flow information in order to handle packets. QoS guarantee is provided according to the class of the flow once it has been accepted. FQMM, [11], Flexible Qos Model for MANET, has been introduced to offer a better QoS guarantee to a restricted Figure 2-a- Example of MRRset calculation. number of flows whereas a class guarantee is offered to the For a node x, let N(x) be the neighborhood of x. N(x) is the set other flows. FQMM is a hybrid approach combining per-flow of nodes which are in the range of x and share with x a granularity of IntServ for high priority classes and perclass bidirectional link. We denote by N2(x) the two-neighborhood granularity of DiffServ for low priority classes. of x, i.e, the set of nodes which are neighbors of at least one G. Ying et al [8] have proposed enhancements that allow node of N(x) but that do not belong to N(x) (see Figure 2-a). OLSR to find the maximum bandwidth path. The heuristics 139 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 are based on considering only bandwidth as a QoS routing • Concave { : M(P) = min M i; j , M i;k ,..., M l;m } constraint and revisions to the MPR selection criteria. They The proof of NP-Completeness relies heavily on the identify that MPR selection is vital in optimal path selection. correlation of the link weight metrics. QoS Routing is NP- The key concept in the revised MPR selection algorithm is Complete when the QoS metrics are independent, real that a “good bandwidth” link should never be omitted. Based numbers or unbounded integers. on this three algorithms were proposed: OLSR_R1, R2 and In general, QoS routing focuses on how to find feasible and R1. optimal paths that satisfy QoS requirements of various voice, The research group at INRIA [9],[10] proposed a QoS video and data applications. However, based on maximizable routing scheme over OLSR. Their technique used delay and routing metrics theory [16], it is shown that two or more bandwidth metric for routing table computation. Such metrics routing metrics can be combined to form a composite metric if are included on each routing table entry corresponding to each the original metrics are bounded and monotonic. destination. Before we proceed to the mathematical proof, we give QOLSR [11] and work presented in [9] enhance OLSR with definitions of maximal metric tree and the properties desired QoS support. Both propose a solution providing a path such for combining metrics i.e. bounded- ness and monotonicity. that the bandwidth available at each node on the path is higher than or equal to the requested bandwidth. Furthermore, Definition 1: Routing Metric A routing metric for a network N is six-tuple (W,Wf, M, mr, met, QOLSR considers delay as a second criterion for path R ) where: selection. 1. M is a set of metric values However, all of these solutions do not take into account at 2. Wf is a function that assigns to each edge {i, j} in N a all mobility and energy parameters induced by the nature of Manet Network. weight Wf( {i, j}) in W 3. W is a set of edge weights B. Qos Routing Problems 4. mr is a metric value in M assigned to the root. One of the key issues in providing end-to-end QoS in a 5. met is a metric function whose domain is MxW and given network is how to find a feasible path that satisfies the whose range is M (it takes a metric value and an edge QoS constraints. The problem of finding a feasible path is NP- value and returns a metric value). Complete if the number of constraints is more than two, it 6. R is a binary relation over m, the set of metric values that cannot be exactly solved in polynomial time and mostly dealt satisfy the following four conditions of irreflexivity, with using heuristics and approximations. The network layer Definition 2: Maximum Metric Tree has a critical role to play in the QoS provision process. The A spanning tree of N is called a maximum metric tree with approaches used by the QoS routing algorithms follow a trade- respect to an assigned metric iff every rooted path in T is off between the optimality of paths and the complexity of maximum metric with respect to the assigned metric. In algorithms especially in computing multiconstrained path. A simple words every node obtains its maximum metric through survey on such solutions can be found in [14]. its path along a maximum metric tree. The computation complexity is primarily determined by the Definition 3: Boundedness composition rules of the metrics [16]. The three basic A routing metric (W, Wf, M, mr, met, R ) is bounded iff the composition rules are: additive (such as delay, delay jitter, following condition holds for every edge weight w in W and logarithm of successful transmission, hop count and cost), every metric value m in M. multiplicative (like reliability and probability of successful met (m,w) R m ∨ met(m,w) = m transmission) and concave/min-max (e.g. bandwidth). The additive and multiplicative metric of a path is the sum and Definition 4: Monotonicity multiplication of the metric respectively for all the links A routing metric (W,Wf, M, mr, met, R ) is monotonic iff the constituting the path. The concave metric of a path is the following condition holds hue for every edge weight w in W maximum or the minimum of the metric over all the links in and every pair of metric values m and m’ in M: the path. m R m’ ⇒ (met (m,w) R met (m’,w) Otherwise, if M i; j is the metric for link {i, j} and P is the ∨ met (m,w) = met (m’,w)) path between (i, j, k,..1,m) nodes, the QoS metric M(P) is (W,Wf, M, mr, met, R ) is called strict monotonic iff defined as [14-15]: m R m’ ⇒ met (m,w) R met (m’,w) • Additive : M(P) = M i ; j + M i;k +…+ M l ;m Theorem 1 (Necessity condition of Boundedness) • Multiplicative : M(P) = M i ; j x M i;k x…x M l ;m If a routing metric is chosen for any network N, and if N has maximal spanning tree with respect to the metric, then the 140 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 routing metric is bounded Mob QOLSR To the best of our knowledge, this work is amongst the first Theorem 2 (Necessity condition of Monotonicity) efforts to consider nodes with mobility and energy If a routing metric is chosen for any network N, and if N constraints in Manets. has maximal spanning tree with respect to the metric, then the routing metric is monotonic B. Proposed criterion Theorem 3 (sufficiency of Boundedness and Monotonicity) Our goal is to select the metric to maximize network If a routing metric is chosen for any network N, and if N throughput taking into account taking into account the key has maximal spanning tree with respect to the metric, then the constraints of MANET environment (mobility, energy). The routing metric is monotonic. idea behind the composite metric is that a cost function is computed locally at each node during the topology IV. OUR IMPROVEMENT information dissemination during the flooding process. Once the network converges, each node runs a shortest path A. Presentation of the solution algorithm based on the calculated composite metric to find the Our solution can be summarized as follows. Bandwidth is optimal route to the destination. An underlying implication of one of the most important factors required and requested by this is that each node should also be able to measure or gather customer’s applications. Mobility and energy are crucial the information required. Bandwidth, mobility and remaining problem in MANETs, and up to now, the majority of routing energy information’s are available and could simply be protocols have shown some weaknesses to face a high mobility gathered from lower layers. This paper is mainly focused on and poor energy resources in the network. solving the routing issues based on the assumption that an Our objective consists in positively manage the network underlying mechanism is there to gather the necessary bandwidth taking into account the constraints of energy and information about the individual metrics. mobility, in order to adapt and improve the performance of We suggest the simple solutions already proposed in [7] can manet routing protocol and prolog network life time. be used to get bandwidth. Mobility estimation will be based on Initially, we start by giving the results of comparing our our lightweight proposed mobility measure cited [4-6] due to approach based solely on mobility parameter. Thus we its simplicity and lightweight. Energy information is derived evaluate the modified OLSR (Mob-OLSR) that uses our from the energy model used in NS2 simulator at MAC Layer proposed mobility metric [4]. Mob-OLSR is then compared to [4]. the standard version of the OLSR protocol (without QoS Individual metrics must be combined according to the extension) and QOLSR (The well known OLSR QoS following dependencies: extension for Manets). • Nodes with no energy must be rejected in the process of Simulations results conduct us to think to use mobility route discovery and maintenance parameters to fulfil QoS requirements. So, we focus on • Nodes with a high degree of mobility should be avoided maximizing the bandwidth based on the parameters of in the process of routes construction. mobility. In this regard, two metrics are proposed. The first is • Tolerate a slight decrease in throughput in order to based on the sum criteria and the second is based on the maximize other performance parameters (delay, product criteria. collisions, NRL) We have processed in the performance comparison between • Nodes start with a maximum energy and bandwith the OLSR protocol using the MPR standard algorithm, and ressources. The residual energy decreases over time the two modified OLSR protocols: SUM-OLSR and PRD- depending on node’s states (transmitting/receiving, in OLSR protocols. The SUM-OLSR protocol is related to the idle/transition mode, etc.). sum criteria, and the PRD-OLSR protocol is related to the Based on these results, the proposed relationship for the product criteria. By the end we have eliminated the sum composite metric is given below: criteria for his hard cost in terms of PDR (comparing to product critéria). However, it is important to mention that the eliminated criteria (the sum) also perform well comparing to QOLSR protocol. In a second step, and in order to maximize bandwidth while taking into account the constraints of energy, a new generalized metric is presented. The proposed metric (EN-OLSR) will be compared to different proposed metrics so called PRD-OLSR and OLSR- 141 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 starting from root, the metric is non-increasing. The metric Where relation is given by: met {m,W(i,j)}. BW : Available Bandwidth in kilobits per second E : residual energy of node (number in range 0 to 5; 0 Given m is the metric of the root. It is evident that this refers no energy for node to perform) meets the boundedness and that monotonicity conditions hold for the selected metric. The available bandwidth is always The constants K0, K1, K2, will be set by the administrator positive, hence for any node located at distance “d” from the based on network nature. For example, in a very dynamic root W(i,j) would always be less than or equal to the metric environment, and to give more importance to the mobility of value at the root. Since the bandwidth is always positive and nodes, we can fix K0 to 0, K1 to 1 and K2 to 10. greater than zero hence it satisfies the boundedness and Constant k3 is not null and is used to indicate if the monotonicity conditions. environment takes into account the energy or not. Thus, an Mobility & energy: important value of K3 indicates that energy is important in the process of routing. The mobility metric represents the rate of changes in the Composite metric scales Bandwidth metric with following neighbouring of a node at time t compared to the previous calculations: state at time t − ∆t . In a previous work [18], We define the BW = 106 / available bandwidth mobility degree of a mobile node i at a time t by the following The proposed metric reflects a real dynamic environment formula: where nodes have limited energy resources, and bandwidth NodesOut( t ) NodesIn( t ) M iλ ( t ) = λ + (1 − λ ) (7) constraints are crucial (streaming application). The idea Nodes( t − ∆t ) Nodes( t ) behind the proposed metric is that in Manets environments, Where: durable-stable link with optimal bandwidth should never be NodesIn( t ) : The number of nodes that joined the omitted. communication range of i during the interval [t − ∆t,t ] . C. Proprieties of the proposed metrics NodesOut( t ) : The number of nodes that left the communication range of i during the interval [t − ∆t,t ] . In this subsection we prove that each of the individual metrics satisfies the conditions of houndness and monotonicity Nodes( t ) : The number of nodes in the communication conditions then we prove the proposed metric. range of i at time t. λ : The mobility coefficient between 0 and 1 defined in Node and Link Available Bandwidth: advance. For example, in an environment where the number of entrants is large relative to the number of leavers, we can The bandwidth metric represents the available bandwidth at encourage entrants taking λ = 0.25 the link. A simple technique proposed in [17], which Many simulations have been done for different values of λ computes available bandwidth based on throughput can be ( λ =0, 0.25, 0.5, 0.75, 1). Simulation result [4] shows that for used to measure the bandwidth on any given node (respect. λ =0.75 the network performs well (in term of delay, Packet link L(i,j)). delivery fraction and throughput). For this reason, we consider Available bandwith “ α ” for each node could be estimated λ =0,75 in the rest of this work. by calculating the percentage of free time TL which is then multiplied by the maximum capacity of the medium Cmax as Let Wij = M be the edge weight on the link L(i,j). The L (i, j ) follows [17]: link mobility between two nodes A and B is defined as the α = TL * C max (4) average mobility of the involved nodes (see Figure 4), as Let Bav (i,j) represent available bandwidth of the link then, showed in following equation: λ λ M A (t ) + M B (t ) Bav (i , j) = min{Bav (i ); Bav ( j )} λ (5) M L ( A,B ) = (8) 2 Where Bav (i ) is the available bandwidth of the node i Also let Wi,j be the edge weight on the link L(i,j). Wi,j can be estimated from the following relationship given below. 1 Figure 4. Link mobility estimation example: M L ( A; B ) = 45% Wi , j = (6) As node’s mobility reflects how likely it is to either corrupt Bav (i, j ) or drop data. It could be considered as reliability metrics [15]. The condition of boundness implies that along any path 142 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 Because the reliability metric is bounded and strictly By exchanging Hello messages, every node is aware of its monotonic, it may be sequenced with the partial metric while neighbor nodes and can simply compute its Cost-to-Forward preserving boundedness and monotonicity. value (i.e. to forward packet). Moreover, residual energy function is monotonic and The Cost-to-Forward function (F(i)) for each of the four bounded its value decreases (depending on the state of the models can be defined as shown in figure 6. node: transmission / reception, transition/sleep mode,etc.) To motivate the nodes to reveal their exact Cost-to-Forward from a maximum value (ex 200) to 0. it also reflects how value during the cluster head election and the MPR selection, likely it is to either corrupt or drop data. Consequently, it can a reputation-based incentive mechanism using the VCG be sequenced with the partial metric while preserving mechanism could be used [20]. The nodes participating boundedness and monotonicity. truthfully to these processes see their reputation to increase. Since the network services are offered according to the Energy consumption parameters are derived from the reputation of the nodes, they would benefit to participate energy model defined in NS2 [19] as follows : honestly. Pt_consume= 1.320 (~ 3.2W drained for packet transmission); V. SIMULATIONS AND RESULTS Pr_consume= 0.8 (2.4W drained for reception); P_idle=0.07, P_sleep =06; P_transition=0.5 In this section we have compared the performance of the original OLSR protocol based on the MPR selection standard The edge weight E ij for the link L(i,j) (see figure 5) can be algorithm, and the two modified OLSR protocols related to estimated from the following relationship: different proposed model: : bandwidth model (QOLSR) , Eij = Min ( E i , E j ) . mobility model (MobOLSR), sum_bandwidth-mobility Model (Sum-OLSR), prd_bandwidth-mobility model (prd-OLSR) Where Ei : the remaining energy for the node i and Ei =0 and bandwidth-energy-mobility model(EN-OLSR). means that the node i have drained out its energy. Thus, routing protocol should omit such node in the process of learning routes. A. Performance metrics For comparison process, we have used the most important metrics for evaluating performance of MANET routing protocols during simulation. These considered metrics are: Figure 5. Link energy estimation example: E L (i ; j ) = 200 Normalized Routing Overhead (NRL): It represents the ratio of the control packets number propagated by every node in the To validate the robustness and efficiency of the proposed network to the data packets number received by the Metrics , we use four models: bandwidth model , mobility destination nodes. This metric reflect the efficiency of the model, sum_bandwidth-mobility Model, prd_bandwidth- implemented routing protocols in the network. mobility model and bandwidth-energy-mobility model. Packet Delivery Fraction (PDF): This is a total number of delivered data packets divided by total number of data packets transmitted by all nodes. This performance metric will give us an idea of how well the protocol is performing in terms of packet delivery by using different traffic models. Average End-to-End delay (Avg-End-to-End): This is the average time delay for data packets from the source node to the destination node. This metric is calculated by subtracting (9) ”time at which first packet was transmitted by source” from ”time at which first data packet arrived to destination”. This (10) includes all possible delays caused by buffering during route discovery latency, queuing at the interface queue, retransmission delays at the MAC layer, propagation and transfer times. (11) Collision: It represents the number of interfered packets during simulation time. It occurs when two or more stations Figure 6: the proposed metrics for QoS attempt to transmit a packet across the network at the same time. This is a common phenomenon in a shared medium . Metrics serves as Cost-to-Forward function. In OLSR, Packet collisions can result in the loss of packet integrity or metrics will be used as criterion in MPR selection algorithm. can impede the performance of a network 143 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 Avg_throughput: is the average rate of successful message ensure a good enhancement in terms of delay when compared delivery over a communication channel. Throughput and to the original OLSR protocol for all maximum speeds. quality-of-service (QoS) over multi-cell environments are two Precisely, the QOLSR and MobOLSR protocols delay is of the most challenging issues that must be addressed when around 1.25 seconds (enhancement by 0.4s comparing to he developing next generation wireless network standards original OLSR) with higher mobility rate (maximum speed equal to 140km/h) and decreases to almost 1.25 seconds (enhancement by 0.1sec comparing to he original OLSR) with B. Simulation environment static topology conditions. For simulating the original OLSR protocol and the modified For the original OLSR protocol the delay gets more than OLSR protocols related to our proposed criterions, we have twice as large being almost 2.1 sec for high mobility and used the OLSR protocol implementation which runs in version surprisingly increasing to over 1.4 seconds when the mobility 2.33 of Network Simulator NS2 [19-22]. is decreased. We use a network consisting of 50 mobile nodes to simulate For the intermediate speed (from 40m/s to 100m/s) a a high-density network. These nodes are randomly moved in lightweight difference between MobLSR and QOLSR is an area of 800m by 600m according to the Random Waypoint noticed (enhancement by 0.1sec for MobOLSR when (RWP) mobility model [21]. Moreover, to simulate a high compared to QOLSR for maximum speeds (0m/s and 30m/s)) dynamic environment (the worst case), we have consider the . This allows us to conclude that MobOLSR performs well RWP mobility model with a pause time equal to 0. nodes can than QOLSR for intermediate speed. According to the move arbitrarily with a maximum velocity of 140km/h. All Figure7-b, the original OLSR and MobOLSR protocols ensure simulations run for 100s. in the whole the same packet delivery fraction for all A random distributed CBR (Constant Bit Rate) traffic maximum speeds with a slight improvement for the original model is used which allows every node in the network to be a OLSR for all maximum speed. potential traffic source and destination. The CBR packet size is fixed at 512 bytes. The application agent is sending at a rate OLSR QOLSR De lay of 10 packets per second whenever a connection is made. All MOBOLSR peer to peer connections are started at times uniformly 2.5 distributed between 5s and 90s seconds. The total number of connections and simulation time are 8 and 100s, respectively. For each presented sample point, 40 random mobility 2 delay (s) scenarios are generated. The simulation results are thereafter statistically presented by the mean of the performance metrics. This reduces the chances that the observations are dominated 1.5 by a certain scenario which favors one protocol over another. As we are interested in the case of high mobility (i.e. high link status and topology changes) we have reduced the HELLO 1 0 20 40 60 80 100 interval and TC interval at 0.5s and 3s, respectively, for quick pause time(s) updates of the neighbors and topology data bases. Figure 7-a. Comparison of the three versions of the OLSR protocol in term of delay. C. Results and discussion Indeed, it can be seen that the number of packets dropped To show how the modified versions of the OLSR protocol along the path is quite similar for all maximum speed being are more adapted to the link status and topology changes approximately 45% at worst for the original OLSR and comparing to the original OLSR protocol, we have made MobOLSR and 35% for QOLSR. several performance comparison based on the five Moreover, the ratio is worse for a continuously changing performance metrics cited in Section 5-A. Moreover, with the network (i.e. high maximum speed) than for the static path supposed configuration cited above, we have run simulations conditions, because the number of link failures grows along in different mobility levels by varying maximum speed of with the mobility. However, it is interesting to notice that even nodes between 0km/h (no mobility) to 140km/h (very high with static topology conditions, sending nodes do not achieve mobility) in steps of 10km/h. To maximize performances we 100% packet delivery but only 85%-89%. This clearly shows have chosen the mobility coefficient equal to λ =0.75. the impact of the network congestion and packet interference as the load on the network increases. Moreover, when a) Comparing MobOLSR to OLSR and QOLSR comparing MobOLSR and original OLSR to QOLSR, QOLSR Figure 7-a shows that Mob-OLSR and QOLSR protocols protocol presents a remarkable degradation in PDF for all 144 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 maximum speeds. This is because QOLSR does not take into maximum speed. account the state of links in MPR selection process. In Figure7-d illustrates the normalized routing load (NRL) summary, we can say that the MobOLSR protocol is more introduced into the network for the three versions of OLSR adapted to all levels of mobility from 0m/s (no mobility) to protocol, where the number of routing packets is normalized 40m/s (very high mobility). against sent data packets. A fairly stable normalized control OLSR QOLSR Pdf message overhead would be a desirable property when MOBOLSR considering the performance as it would indicate that the actual control overhead increases linearly with maximum 90 speed of nodes due to the number of messages needed to establish and maintain connection. The original OLSR 75 protocol and MobOLSR protocol produces the lowest amount of NRL when compared to QOLSR protocol during all rate (%) 60 maximum speed values. Moreover, original OLSR and MobOLSR protocol produce the sme routing load for all the 45 maximum speed. 30 In the worst case (at the maximum speed value equal to 0 20 40 60 80 100 40m/s), the NRL increases to 2.1% for QOLSR protocol and pause time 1.3% for the original OLSR. Precisely, comparing to QOLSR Figure 7-b. Comparison of the three versions of the OLSR protocol, the MobOLSR and original OLSR protocols produce protocol in terms of packet delivery fraction. twice less routing packets. This explains that our proposed Figure7-c, shows the average throughput for the three criterion based on mobility parameter request less routing version of protocols. The original OLSR and MobOLSR packets to establish and maintain routes in the network. protocols ensure in the whole the same average throughput OLSR for all maximum speeds being approximately 125 kbps at QOLSR NRL MOBOLSR worst. 2.5 The ratio is worse for a continuously changing network 2 than for the static conditions. Moreover, it is interesting to notice that even with static topology conditions, the network 1.5 average throughput does not reach the channel capacity rate (%) (5Mbps) but only 230 kbps. This clearly shows the impact of 1 the network congestion and packet interference as the load on the network increases. 0.5 OLSR QOLSR Avg Throughput 0 MOBOLSR 0 20 40 60 80 100 pause time (s) Figure 7-d. Comparison of the three versions of the OLSR protocol in term of 230 NRL Collision is a common phenomenon in a shared medium. 200 Packet collisions can result in the loss of packet integrity or can impede the performance of a network especially qualtity of 170 service sensed by the end user. Interference and quality-of- service (QoS) over multi-cell environments are two challenging issues that must be addressed when developing 140 next generation wireless network standards. 110 Figure 7-e, shows that the original OLSR produces the 0 20 40 60 80 100 pause time (s) lowest amount of collision packet comparing to MobOLSR Figure 7-c. Comparison of the three versions of the OLSR and QOLSR. However, we can see that our proposed protocol protocol in term of throughput. MobOLSR ensures an enhancement by 56% comparing to QOLSR, The well known OLSR QoS extension for Manets. Thus, QOLSR ensures an enhancement by 10kbps The average number of collision packet for QOLSR (respct comparing to MobOLSR and the original OLSR for all 145 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 MobOLSR and the Original OLSR) is 30000 (respect 17000, OLSR Pdf QOLSR and 11000) for all maximum speed. Sum-OLSR Prd-MET OLSR 90 QOLSR Collision MOBOLSR 75 35000 30000 60 25000 45 Nbre (#) 20000 15000 30 10000 0 20 40 60 80 100 paus e tim e 5000 Figure 8-b. Comparison of the proposed versions of the OLSR protocol in terms 0 of delay 0 20 40 60 80 100 pause time Figure 7-e. Comparison of the three versions of the OLSR However , we notice that Prd-OLSR performs well comparing protocol in term of collision. to MomOLSR and Sum-OLSR. This is because Prd-OLSR select stable routes offering an optimal bandwidth. This is b) Comparing Sum-OLSR and Prd-OLSR to QOLSR confirmed by the improvement seen in the PDF parameter. MobOLSR protocol produces the lowest amount of NRL Figure8-a illustrates the average end to end delay for the when compared to Sum-OLSR and Prd-OLSR protocols proposed protocols (Sum-OLSR and OLSR Met2 MOBOLSR during all maximum speed values (figure8-d). Moreover, we and QOLSR). Comparing to QOLSR, it is interesting to notice notice that Sum-OLSR and Prd-OLSR protocols produce less that our proposed protocols MOBOLSR and Prd-OLSR amount of NRL compared to QOLSR for all the maximum perform well in a dynamic topology (enhancement by 0.5 sec speed. for maximum speed 40m/s to 80m/s). OLSR QOLSR Avg Throughput Furthermore, we can see that (figure8-b) Prd-OLSR Sum -OLSR performs well in term of PDF, when compared to the other Prd-OLSR proposed protocol (Sum-OLSR MOBOLSR and QOLSR) for all maximum speed. Precisely, Prd-OLSR gets more than 230 twice as large comparing to QOLSR. 200 OLSR Delay QOLSR Sum -OLSR 170 Prd-OLSR 2,5 140 2 110 0 20 40 60 80 100 delay pause tim e 1,5 Figure 8-c. Comparison of the proposed versions of the OLSR protocol in terms of throughput 1 0 20 40 60 80 100 This explains that our proposed criterion based on mobility pause tim e parameter request less routing packets to establish and maintain routes in the network. Figure 8-a. Comparison of the proposed versions of the OLSR protocol in terms of delay. A lightweight degradation in average throughput for Prd- OLSR protocol is shown in figure8-c comparing to QOLSR. 146 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 OLSR OLSR NRL Collision QOLSR QOLSR Sum -OLSR Sum-OLSR Prd-OLSR Prd-OLSR 2,5 35000 2 30000 25000 1,5 20000 1 15000 0,5 10000 5000 0 0 20 40 60 80 100 0 pause tim e 0 20 40 60 80 100 pause tim e Figure 8-d. Comparison of the proposed versions of the OLSR protocol in terms of NRL Figure 8-e. Comparison of the proposed versions: Collision Figure8-e, shows that the original QOLSR produces the OLSR provides the worst delay when compared to the highest amount of collision packet comparing to the others proposed protocols. Precisely, the QOLSR and ENOLSR proposed protocols. protocols delay is around 1.65 seconds (enhancement by The average number of collision packet for QOLSR (respct 0.3sec comparing to the original OLSR) with higher mobility Sum-OLSR and Prd-OLSR) is 33000 (respect 25000) for all rate (maximum speed equal to 140km/h) and decreases to maximum speed. almost 1.25 seconds (enhancement by 0.1sec comparing to he original OLSR) with static topology conditions. This allows us QOLSR produces an interfered environment in comparison to conclude that ENOLSR and QOLSR protocols ensure in with our proposed protocols. the whole the same delay. However, it is interesting to notice that all of the proposed protocols perform well than the ENOLSR uses the composite metric with energy original OLSR protocol in term of delay. constraints, from figures 9-a we notice that the proposed ENOLSR find a compromise between bandwidth, energy and A tolerable degradation in throughput is shown for our mobility. Our proposed protocol selects stable routes providing QOLSR protocol provides the worst amount of RNL when an optimum bandwidth while prolonging the lifetime of the compared to the others protocols. ENOLSR ensures an network. optimal NRL. It exceeds the NRL induced by OLSR and MobOLSR and performs QQLSR . In the worst case (at the maximum speed value equal to 40m/s), the NRL increases to 2.1% for QOLSR protocol, 1.3% for the original OLSR and 1.6% for ENOLSR,MOBOLSR and Sum-OLSR&2. In addition, QOLSR ensures the worst PDF when compared to the proposed protocols. An enhancement of 10% (resp 65%) when comparing to the Original OLSR protocol (resp MobOLSR) is noticed. 147 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 Figure 9-a. Performance comparison of the proposed versions of the OLSR protocol private information revealed by the nodes. Selfish nodes can misbehave and reveal false information if this behavior can OLSR QOLSR Collision MOBOLSR save their energy and mobility degree. Moreover, one of the Prd-MET EN_OLSR main drawback of the classical OLSR is the malicious use of 35000 the broadcast TC messages A malicious compromised node 30000 can flood the network with fake TC messages. In order to increase the network lifetime, ENOLSR 25000 protocol use the node residual energy for the routing process 20000 (equation 1). 15000 In particular, for the following sub-sections, simulation run 10000 for 70 sec. Nodes are nodes moves randomly according to the 5000 Random Waypoint (RWP) mobility model [22]. Nodes velocity can reach 40m/s and the pause time is equal to 10sec. 0 0 20 40 60 80 100 We choose the energy model defined in NS to model nodes paus e tim e energy consumption with (Pt_consume= 3 ; Pr_consume= 2; Figure 9-b. Comparison of the ENOLSR protocol : collision P_idle=0.07, P_sleep =06; P_transition=0.5). Nodes c) Prolonging network life time initial energy is fixed to 160. For comparison, we measure the average energy for nodes in MPRSet for both OLSR and Selfish nodes can have a major impact on the performance ENOLSR protocols. of the solutions presented in Section VI. In some extreme cases, these malicious nodes can cause serious denials of Figure10 shows that energy consumption for original service. The main problem comes from the fact that the MPRs OLSR is linear. For the ENOLSR protocol network life time and the optimal network paths are selected based some 148 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 is prolonged. Indeed, for the original OLSR (resp ENOLSR) [2] P. Jacquet, P. Muhlethaler, A. Qayyum, A. Laouiti, L. Viennot, T. Clauseen, "Optimized Link State Routing Protocol draft-ietf-manet-olsr-05.txt", INTERNET- the first node dies after 17sec (resp 43s). This is because DRAFT, IETF MANET Working Group during the normal process of selecting the MPR used by [3] T. Clausen (ed) and P. Jacquet (ed). “Optimized Link State Routing standard OLSR protocol, the MPRs are selected based on the protocol (OLSR)”. RFC 3626 Experimental, October 2003. parameters of reachebality (number of node they can reach in [4] K.oudidi, N.enneya, A. Loutfi, and M.Elkoutbi ’Mobilité et Routage OLSR’, In Proceedings of African Conference on Research in Computer Science level 2 : 2 hop neighbors). This induces a loss of energy for and Applied Mathematics CARI’08, pp. 646-657, October 2008, Rabat, the nodes that have been elected several times as MPRs. Morocco. OLSR [5] A. Laouiti, P. Muhlethaler, A. Najid, E. Plakoo, ”Simulation Results of the MPR_Set Avg_Residual_energy EN_OLSR OLSR Routing Protocol for Wireless Network”, 1st Mediterranean Ad-Hoc Networks workshop (Med-Hoc-Net), Sardegna, Italy, 2002. 180 [6] Nourddine Enneya, Kamal Oudidi, and Mohammed El Koutbi, "Enhancing Delay in MANET Using OLSR Protocol", International Journal of Computer 150 Science and Network Security IJCSNS", vol. 9, No. 1, 2009. 120 [7] S-B. Lee, G-S. Ahn, X. Zhang, A.T. Campbell: INSIGNIA: An IP-Based Quality of Service Framework for Mobile ad Hoc Networks, in Journal of ene rg y 90 Parallel and Distributed Computing, n.60, pp. 374-406, 2000. [8] Ying Ge Kunz, T. Lamont, L. ‘’Quality of service routing in ad-hoc 60 networks using OLSR ‘’ Commun. Res. Centre, Ottawa, Ont., Canada; Proceedings of the 36th Annual Hawaii International Conference on System 30 Sciences, (HICSS’03). [9] H. Badis, A. Munareto, K. A1 Agba, “QoS for Ad Hoc Networking Based 0 on Multiple Metrics: Bandwidth and Delay” The Fifth IEEE International 0 27 5 .7 2 1 9.9 1 2.7 1 7.2 2 4.5 2 3.9 2 8.4 3 2.1 3 9.7 3 8.5 4 2.6 4 7.7 4 9.5 5 1.1 5 6.3 60 6 4.3 Conference on Mobile and Wireless Communications Networks (MWCN 2003) Singapore - October, 2003 time [10] A. Munareto H. Badis, , K. AI Agba, “A Linl-state QoS Routing Protocol Figure 10 : MPRSet average residual energy for OLSR & ENOLSR for Ad Hoc Networks” IEEE Conference on Mobile and Wireless Communications Networks - MWCN 2002 Stockholm, Suede - September, 2002 [11] H. Badis and K. A. Agha. Internet draft draft-badis-manetqolsr- 01.txt: Contribution appears clearly in an environment where the Quality of service for ad hoc Optimized Link State Routing Protocol (QOLSR). nodes are intelligent and therefore does not revel true IETF MANET working group, September 2005. information during the process of MPR selection for fear they [12] Nauman Aslam', William Phillips', William Robertson' composite metric for quality of service routing in OLSR IEEE Conference 2004 - CCECE 2004- lose their energy. So, the generalized criterion is designed to CCGEI 2004, Niagara Falls, May/mai 2004 – cope with selfish nodes. [13] G.-S. Ahn, A. Campbell, A. Veres, L.-H. Sun, SWAN: Service Differentiation in stateless Wireless Ad hoc Networks, INFOCOM’2002, New VI. CONCLUSION AND FUTURE WORK York, New York, June 2002. Satisfying QoS requirements of the traffic in MANETs are the key functions for transmission required for multimedia applications. In this paper we have discussed the different approaches used to provide QoS functionality in OLSR. Our proposed metric is an attempt to make use of the available resources and find the most optimal path based on multiple metrics taking into account mobility and energy parameters. The proposed metric selects the most stable path based on mobility and energy information and QoS requirements on bandwidth. Our proposed approaches are , totally or partially, based on a mobility degree, residual energy and available bandwidth that is quantified and evaluated in time by each mobile node in the network. The proposed metric is expected to efficiently support real- time multimedia traffic with different QoS requirements. Simulation results show that the proposed protocols perform well when compared to the QOLSR protocol which is a well known OLSR QoS extension. The next step is to extend the proposed approaches to Wireless Sensor Network routing protocols. REFERENCES [1] IETF Mobile Ad-hoc Networking (manet) Working Group. http://www.ietf.org/html.charters/manet-charter.html, 2004. 149 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 1, April 2010 F.A. Kuipers, T. Korkmaz, M. Krunz, P. Van Mieghem, “Performance evaluation of constraint-based path selection algorithms”, IEEE Network 18 (5) (2004) 16–23 [14] S. Yilmaz, I. Matta, “Unicast Rotuing: Cost- Performance Tradeoffs” Technical Report BUCSTR- 2002 [15] G. Mohammad, S. Marco, “Maximizable Routing Metrics” IEEE/ACM Transactions, Volume 11, Issue 4 (August 2003), Pages: 663 - 675. [16] Cheikh SARR « De l’apport d’une évaluation précise des ressources de la qualité de service des réseaux ad hoc basés sur IEEE802.11 » thèse de doctorat, Institut Nationale des Sciences Appliquées de Lion, année 2007. [17] A. Qayyum, L. Viennot and A. Laouiti. “Multipoint relaying for flooding broadcast messages in mobile wireless networks”. In Proceedings of the Hawaii International Conference on System Sciences (HICSS’02), Big Island, Hawaii, January 2002. [18] P. Anelli & E. Horlait «NS-2: Principes de conception et d'utilisation» [19] Luzi Anderegg, Stephan Eidenbenz, “Ad hoc-VCG: a truthful and cost- efficient routing protocol for mobile ad hoc networks with selfish agents”, Proceedings of the 9th annual international conference on Mobile computing and networking, San Diego, CA, USA, 2003 [20] C. Bettstetter, G. Resta, and P. Santi. The Node Distribution of the Random Waypoint Mobility Model for Wireless AdHoc Networks. IEEE Transactions on Mobile Computing, 2(3):257–269, 2003. [21] http://isi.edu/nsnam/ns AUTHORS PROFILE K.Oudidi Born in 1976 at Marrakech Morocco. Completed his B. Tech and M. Tech. from Faculty of Sciences, My Ismail University - Errachidia in 1995 and 1999, respectively. He is a Ph.D. Student at the University of Mohammed –V- National School of Computer Science and Systems Analysis, His present field of interest is the mobility and Qos routing in mobile ad hoc networks. 150 http://sites.google.com/site/ijcsis/ ISSN 1947-5500