Performance Evaluation of a Cartography EnhancedOLSR for Mobile Multi-Hop Ad Hoc Networks

Mohamed BelhassenHANA Research Group

mohamed.belhassen@gmail.com

Abdelfettah BelghithHANA Research Group

abdelfattah.belghith@ensi.rnu.tn

Mohamed Amine AbidHANA Research Group

abidmedamine@gmail.com

Abstract—In this paper, we propose the integration of acartography gathering scheme to enhance the capacity of theOptimized Link State Routing Protocol (OLSR) to properly tracknode movements in dynamic networks. We propose an improvedversion of OLSR called the Cartography Enhanced OptimizedLink State Routing Protocol (CE-OLSR), a novel routing protocoldesigned for mobile multi-hop ad hoc networks. Our contributionis three fold. First, we propose an efficient network cartographycollection scheme solely based on OLSR signaling traffic. Weshow that this cartography is much richer than the mere topologygathered by the seminal OLSR. Second, we designed an enhancedversion of OLSR based on the collected cartography. We showthat CE-OLSR insures a much better responsiveness and copesappropriately with the mobility of nodes. Third, we conduct anextensive set of simulations to compare the performance of ourproposal against that of OLSR.

Simulations results show that the proposed CE-OLSR outper-forms greatly OLSR in terms of a much better route validity,a much higher throughput and a much lower average delay.For instance, at a speed of 20 𝑚/𝑠, CE-OLSR achieves a routevalidity beyond 93% while that provided by OLSR barely attains30%. At high speeds, CE-OLSR delivers more than 3 times thethroughput of OLSR with an average end to end delay 21 timessmaller. As such, CE-OLSR stands out not only as an appropriaterouting protocol for mobile multi-hop ad hoc networks, but alsoa viable protocol for the transport of time critical data.

Index Terms— OLSR Protocol, Network Cartography,MANETS, Routing Validity

I. INTRODUCTION

Mobility has been the main challenge in the design ofappropriate and efficient routing protocols in mobile multi-hopad hoc networks (MANETs). Even though the OLSR protocol[1] is conceived specially for these networks, it is still unableto completely fit their inherent characteristics. In fact, nodemobility significantly degrades its functioning. According tothe basic OLSR version, the only mean to better track thetimely changing network topology consists in properly tuningthe periodicity of the control messages. The scarcity of thewireless network resources, however, prevents the viability ofsuch a solution. To adapt OLSR to the characteristics of suchdynamic networks several extensions and improvements of thebasic OLSR were proposed, such as the F-OLSR [2], P-OLSR[3], [15], [10] among many others.

In this work, we propose to utilize the network cartographyas a ground basis on which we perform our routing decisionsto overcome the mobility effect. The remainder of the paper isorganized as follows. Section 2 presents some relevant related

work. In section 3, we identify and analyze the main issuesfacing OLSR in MANETs, mainly its slow responsiveness tomobility and its link discovery problems. In section 4, wedetail our proposed CE-OLSR. Section 5 is devoted to definethe performance metrics used to evaluate and position ourscheme against OLSR based on extensive simulation results.Finally we conclude the paper in section 6.

II. RELATED WORK AND MOTIVATION

Proactive routing protocols are generally divided into twomain classes: the link state protocols (LS) with OLSR [1]as the main representative, and the distance vector protocols(DV) with DSDV [4] as the main representative. In the LSprotocols case, each node constructs a global network viewbased on the disseminated topological information. This viewis used to calculate the routing table by applying a shortest pathalgorithm. In the DV protocols case, the routing table is rathercalculated in a distributed fashion. A node has no need to knowthe whole network topology to compute routes; it only uses theinformation contained in the distance vectors received from itsneighbors to select the best gateway (i.e.,n next hop) towardsa given destination. Thus, the link state protocols providericher information about the network connectivity compared todistance vector protocols. In proactive routing whether basedon DV or LS, a huge amount of topological information hasto be exchanged among nodes. This may lead to a scalabilityproblem, namely an enormous processing load at every nodeand the difficulty to build and retain an up to date view aboutthe network connectivity as the network node density growsbeyond a certain limit.

In the quest to solve this scalability issue, several solutionswere proposed in the literature. One first tendency consists inimproving the behavior of some existing seminal LS protocolsto fit the characteristics of MANETs as it is the case ofOLSR. In this protocol, the Multi-Point Relay (MPR) conceptis introduced specifically to reduce the number of exchangedcontrol messages as is also the adoption of a compositetopological signaling leading to a lower signaling overhead butat the expense some incompleteness of the perceived topologyview (a node gets only a sub-topology of the network). Thesecond tendency consists in the emergence of new routingprotocol classes such as the location based protocols [6][5] or the stability routing protocols. The former drive therouting function based on the nodes’ geographical location.

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For example, the Location Aided Routing protocol (LAR)[5]uses these locations to limit the searching space for a targetdestination. The source node relies on the last known positionof the target in order to estimate the expected zone in which itcan be presently located. According to this zone, a set of nodesthat should be involved in the route discovery is determined(request zone). In [7] authors proposed the DREAM protocolwhich proactively maintains the nodes’ locations in data struc-tures (routing tables). Every node has to partially flood its datapackets to nodes in the direction of the target. Other locationbased proposals could be found in other research works suchas the GPSR [8], GFG [9], GRA [12], ALSAR [18] amongothers.

On the other hand, stability routing protocols were proposedespecially to mitigate the effect of nodes mobility on the per-tinence or established routes. Recently, several stable routingprotocols and metrics were proposed to face this particularproblem [16], [17], [14], [13]. In these protocols, the goalis to find a route which lasts over time: we need to selectpaths that remain correct until the following routing update.The stability definition differs from one work to another. In[14], the stability is proportional to the residual connectivitytime between the links’ end points composing a route. In[13], it is rather perceived as a function of the receivedsignal strength. In [19], the stability criterion is defined asthe existence probability of complete routes. The crux of thestability routing relies in proactively switching data packets toa more reliable paths. In [11], the authors studied the problemof finding paths subject to two criteria: stability and numberof hops, as routes composed of a large number of hops inducetoo much traffic inside the network and consequently may leadto poor performance even though they are stable.

In this paper, our contribution is three fold. Firstly, wepropose a gathering scheme of the cartography of the network(i.e., the coordinates of the nodes) using exactly the very sameOLSR signaling mechanism. As such, no additional signalingmessages are required to build this cartography. Secondly andas this cartography provides a much richer view of the currentnetwork, we propose an enhanced version of OLSR that wecall the Cartography Enhanced Optimized Link State Routing(CE-OLSR). Thirdly, we conduct an extensive set of simula-tions using different scenarios to evaluate the performance ofour proposal and show the betterments achieved in terms ofmuch better route stability, much better throughput and muchless end to end delay allowing CE-OLSR to be a convenientrouting protocol for the transport of real time traffic.

III. THE BASIC OPTIMIZED LINK STATE ROUTING

PROTOCOL: LIMITATIONS AND CRITICAL ANALYSIS

Despite the ability of OLSR to reduce the routing traffic,a deep study of its functioning reveals several limitations. Inseminal OLSR, a node builds the network topology through theexchange of control messages. To reduce this signaling traffic,OLSR acts at two different levels. Firstly, a node discovers its2-hops neighborhood through the exchange of local HELLOmessages. Based on the collected information, it selects a

subset of nodes from its 1-hop neighbors that covers all its2-hops neighbors. The node is then advertised to the rest ofthe network only through this selected subset of nodes, calledMPRs. Nodes selected as MPRs have to generate and forwardTopology Control messages (TC messages) to enable the restof nodes constructing the entire network topology. Secondly,the MPRs announce a subset of their links to the wholenetwork. They declare the links with their MPR selectors toinsure that all the nodes can be reached with a minimum hopcount (covering topology). These two mechanisms adoptedby OLSR to reduce the control traffic overhead make it,however, more sensitive to the loss of control messages (due toseveral problems such as collisions) which is a rather commonphenomenon in ad hoc networks.

OLSR is conceived originally to be independent fromthe underlying layers. This makes it unable to assess theinstantaneous quality of the links. Further mechanisms arethen required which are usually accomplished by collectingstatistics from the neighborhood as is the case, for instance,of the Expected Transmission Count (ETX) [20] metric orthe Hysteresis Strategy proposed in the RFC3626 of OLSR[1]. In the context of mobile ad hoc networks, these strategiesseem to be inadequate due to the short life time of a link. Bydefault, OLSR uses the hop count metric in its routing processwhich makes the selected routes break down rapidly due to themobility of nodes.

Another issue arises from the slow responsiveness of OLSRregarding topology changes. Thereby, OLSR delays one neigh-bor’s detection until the corresponding link is deemed sym-metric. This entails a three way handshake accomplished usingHELLO messages. The induced latency gets larger when usingthe advanced link sensing mechanism (Hysteresis Strategy)described in the RFC3626 (Section14.3) [1] which requiresmore time to assess the quality of the link.

Furthermore, in OLSR each node keeps using indiscrimi-nately the gathered topological information as long as it isnot expired. As such, the OLSR protocol has no mean todistinguish between new and stale topological informationwhether they come from HELLO or TC messages. As aconsequence, a node may select an outdated (but not expired)route even though it holds newer topological information.

IV. THE CE-OLSR PROTOCOL

In this section, we detail the overall functioning of ourprotocol. The motivation behind our proposal consists amongothers, in the resolution of the previously discussed issues fac-ing the OLSR deployment in the context of mobile multi-hopad hoc networks. Our proposal is a cartography-based routingprotocol. Since the network cartography is a richer structurethan a simple knowledge of the network connectivity, wecan expect a significant improvement of the routing function.To this end, an adequate and efficient network cartographygathering scheme is important to enhance the efficiency of therouting decision. The network dynamics (the mobility of thenodes) invalidate rapidly the collected network cartography.

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Therefore, the routing function should consider this issuecarefully to enhance its functioning.

A. The Cartography Gathering Scheme

We assume that each node in the network is able to knowits position at any time. The existence on the market ofseveral low cost GPS receivers and various cheap localizationtechniques play in the favor of such an assumption. In addition,a couple of nodes are assumed to be neighbors if they arein transmission range of each other. As a result, a link is bydefault considered to be symmetric. Recall that OLSR uses twokinds of control messages to discover and build the networktopology. The neighborhood (1 and 2 hops) is discovered usingHELLO messages. The rest of the network (nodes fartherthan 2-hops away) is discovered through TC messages. Thisvery signaling traffic is then used to disseminate also the thecartography of the entire network without any need for newcontrol message types. We simply add a new field to carry outthe coordinates of a node in its generated control messages.More specifically, each node includes its current position aswell as those of its known neighbors in each generated HELLOmessage, and each MPR has to include the positions of itsMPR Selectors in its generated TC.

This very simple cartography gathering scheme leverages,indeed, the routing protocol robustness against packets lossesas illustrated by Fig. 1 representing a given part of a network.According to the legend of this figure, node A is a MPR ofnodes B and C, B is a MPR of nodes C and D, and E is aMPR of node D. If the TC generated by B (𝑇𝐶𝐵 advertisingnodes C and D) is lost then, in the OLSR case, the linksdeclared in this TC (B→C and B→D) can not be discoveredby the nodes farther than 2-hops until they receive the next𝑇𝐶𝐵 . Nevertheless, CE-OLSR deduces these links from thecollected cartographic information about nodes B, C and Dcontained in the successfully received 𝑇𝐶𝐴 (advertizing thelinks A→C and A→B as well as the position of nodes C andB) and 𝑇𝐶𝐸 (advertizing the link E→D as well as the positionof node D). This enhancement concerns TC messages as wellas HELLO messages. Indeed, suppose that node A missesthe HELLO message generated by B (𝐻𝐵) and successfullyreceives 𝐻𝐶 . Since 𝐻𝐶 contains the positions of nodes C andB, node A deduces that B is one of its neighbors (because thedistance between A and B is less or equal to the transmissionrange). That way, CE-OLSR makes control messages morerobust against packets losses.

Moreover and as we have discussed in the last section,the significant latency of the required OLSR three way hand-shake needed to check the symmetry of a link impacts itsability to adequately track topological changes in any node’sneighborhood. To overcome this limitation, we further requirethat each node includes in its generated HELLO messagesnot only the positions of its symmetric neighbors but alsothose of its asymmetric neighbors. Upon receiving a HELLOmessage, a node has to store the cartographic informationabout asymmetric neighbors in a new dedicated structure for

Fig. 1: A sample part of a mobile ad hoc network

a subsequent use. This enhances the timely perception and theaccurate tracking of the neighborhood.

The third problem evoked in the previous section, concernsthe inaptitude of OLSR to distinguish between fresh and staletopological information. CE-OLSR solves this issue in orderto enhance the accuracy of the used cartographic information.In Fig. 1, node A discovers the position of node D from theHELLO messages 𝐻𝐵 and 𝐻𝐶 and from 𝑇𝐶𝐸 . All thesethree messages advertise node D position. These advertisedpositions of node D can be different and node A has no wayto decide which one is the currently most accurate. The lastreceived position is not necessarily the currently most accurateas we ignore from which 𝐻𝐷 the advertised location wasretrieved. To be able to distinguish between stale and freshcartographic information, we propose to take advantage ofthe seminal sequence number already used in OLSR HELLOmessages. Positions in TC messages are then augmented bythe sequence numbers of their advertising Hello messages.

For now, all what we have done is to propose a cartographygathering scheme that overcomes three of the aforementioneddeficiencies of the OLSR protocol. First, the CE-OLSR pro-tocol is endowed with a robustness against packet lossescompared to OLSR thanks to its ability to infer more linksfrom the collected cartography. Second, the topology changesare better tracked for CE-OLSR protocol rapidly considers thetopological information collected about its 1-hop and 2-hopsneighbors. Third, CE-OLSR is able to discriminate betweenfresh and stale cartographic information. That way, it is ableto identify the most accurate topology from the collectedcartography.howeverH, we still need to mitigate the impactof mobility on the validity of established routes.

B. The Mobility Problem: the Stable Routing Scheme

Nodes mobility makes the collected network cartographystales rapidly over time. To overcome such a problem, therouting protocol needs to track the nodes mobility and ade-quately select routes that can last longer over time. At the firsttrial, we may think of increasing the frequency of emittingrouting control traffic. In practice, such a solution can not besuitable for ad hoc networks due to their limited resources.The mobility problem needs to be considered otherwise. Tosolve this issue, our proposal utilizes the richness of thegathered cartography and introduces the concept of stablerouting. Two moving neighbors remain neighbors as long as

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their movement keeps them in transmission range. Stabilitymay be then achieved by willingly underestimating the actualgathered network connectivity by considering that any twonodes are neighbors if the distance separating them is lessthan another smaller transmission range. This modified trans-mission range is equal to the real transmission range minus aconsidered Stability Distance. The more this Stability Distanceis increased the greater the routes’ stability will be. On theother side, such a solution makes the network become lessconnected, especially with a large Stability Distance choice,which leads to the increase of the number of hops requiredto reach destination nodes which in turn can be a problemespecially with sparse networks.

Therefore, using the collected cartography and the modifiedtransmission range, each node builds the network connectivity.Then, it simply runs a shortest path algorithm, Dijkstra forinstance, to identify the retained gateway (next hop) for eachdestination node in the network. A routing table is then createdkeeping an entry for each possible target node.

V. COMPARISON OF OLSR AND CE-OLSR

A. Evaluation Metric

As we are basing our routing proposal on the networkcollected cartography, the pertinence of this cartography is ofutmost importance in leveraging the validity of the establishedroutes. The validity of the routes measures the consistency ofthe routing table of a node by comparing it to the (unknown)real network topology (extracted from the simulator).

The performance of a routing protocol is highly linked to thevalidity of the network topology. Indeed, if nodes route datapackets through out of range gateways (due to the mobility),the network resources are uselessly wasted without deliveringthe data packets to their ultimate destinations. In addition, ifthe nodes perceive different topologies of the network, loopsmay appear in the established routes. These loops make trafficconsuming further network resources vainly. So, it is importantto conceive a metric (the validity of the routes) that adequatelyreflects the ability of the routing protocol to find availablecorrect routes. A route between a source-destination pair isbuilt starting from the source node and going through the nexthop nodes of the corresponding routing tables until reachingthe destination. This route is termed valid if it exists in thereal network. Routes to destinations marked unreachable inthe routing table of a given source node, are also termed validif they do not exist in the real network. Other than these twocases, the route is considered as invalid. The validity of theroutes at a given source node is defined as the percentage ofvalid routes in the network.

B. Simulation Set Up

In this section, we detail the common parameters used in ourconducted simulations. We consider a mobile ad hoc networkcontaining 100 mobile nodes (with initial random positions),and covering an area of 1000 m by 1000 m. The nodes mobilityis driven by the random way point model. The transmissionrange of all nodes is set to 250 m. The network capacity

is fixed to 11 Mbps. The MAC is enabled to retransmitdata packets 3 times before dropping them from transmissionqueues. For both OLSR and CE-OLSR, we use a priority IPlayer in which routing control messages (Hellos and TCs) areserved before awaiting data packets. The priority IP queuecan buffer up to 100 packets. In this queue 30% of its size areexclusively used by control messages and the remaining 70%are shared between data and control packets. The priority IPbenefit is two fold. Firstly, it speeds up the dissemination ofrouting traffic which makes routes more consistent and closerto the real network topology. Secondly, it insures that packetsare routed using the most fresh topological information whichsaves a great amount of valuable network resources. For bothOLSR and CE-OLSR, the TC REDUNDANCY parameter isset to 0. Hence, MPRs publish only the links with their MPRselectors in the generated TC messages. In addition, we setthe TC period to 8 seconds and the HELLO one to 2 sec-onds. The Stability Distance parameter of CE-OLSR is set totwice the Tolerance Distance (Stability Distance=2×ToleranceDistance=50 𝑚). In the simulations invoking data traffic, 10CBR (Constant Bit Rate) data streams are set up between10 randomly chosen nodes pairs. However, the source nodes(respectively the destination nodes) of these 10 streams arekept immobilized at the left edge (respectively at the rightedge) of the network area to ensure a path length rangingbetween 4 to 6 hops approximately. The data packets size is setto 1000 𝐵𝑦𝑡𝑒𝑠. The selected scenarios are run for a simulationtime equal to 300 𝑠, the first 100 𝑠 of which are prunedas transient. The remaining time duration is divided into 10equal observation windows. The following curves represent theaverages over these 10 periods. The simulation results for thevalidity of the established routes are calculated for a sourcekept immobilized at the top left cornet of the network area.

C. Simulation Results

In the first part of our simulations, we compare our cartog-raphy based routing protocol (CE-OLSR) with OLSR in termsof the validity of routes. Fig. 2 portrays the route validity ofCE-OLSR and OLSR as a function of the mobility of thenodes. We clearly observe that CE-OLSR outperforms largelyOLSR. For a stationary network, that is a speed of 0 𝑚/𝑠, bothprotocols provides a 100% validity as expected. Once nodesstart moving, the validity of the routes provided by OLSR startfalling sharply while that provided by CE-OLSR prevails andsustains superbly. For a speed of 2 𝑚/𝑠, CE-OLSR delivers avalidity approaching the 100%, while that delivered by OLSRdrops to approximately 83%. The OLSR performance is deeplyaffected by the increase of the nodes speed. Indeed, at a speedof 10 𝑚/𝑠, its routes validity drops to 43%, while that of CE-OLSR levels to around 95%. For a high speed of 20 𝑚/𝑠,OLSR fails down to track the mobility of the nodes and canhardly deliver 95% validity, while that provided by CE-OLSRstabilizes around the 93%. As such, we observe that CE-OLSRis very robust against the mobility of nodes and thrives wellto deliver a very high validity of the routes.

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The performance enhancement obtained when using CE-OLSR comes from both its dedicated efficient cartography-gathering and its stable routing schemes. The cartography-gathering makes the node aware of the freshest known car-tographic information about each node in the the network. Infact, with CE-OLSR, a node can distinguish between new andstale cartographic information whether it comes from HELLOor TC messages. This is accomplished by stamping the carto-graphic information by the sequence number of the HELLOmessage from which it has been extracted. Consequently, anode retains the best known cartographic information. Further-more, CE-OLSR and to the contrary of OLSR, is allowed touse prematurely the gathered topological information about its1-hop and 2-hops neighbors. This fast adaptation to the current1-hop and 2-hops neighborhood changes has a beneficialeffect on the routing protocol efficiency. The crux of ourproposed cartography gathering scheme lies in its ability tomaintain a perfectly correct view about its 1-hop and 2-hops neighborhood using the cartographic information. Thestable routing scheme, on the other hand, is applied mainlyto mitigate the mobility of nodes. This scheme makes theestablished routes more stable as its uses shorter links.

Having such a nice result in terms of routes validity, we canexpect that CE-OLSR delivers also a very satisfactory through-put. Fig. 3 represents the throughputs achieved by OLSR andCE-OLSR as a function of the traffic load and for differentspeeds ranging between 0 𝑚/𝑠 and 20 𝑚/𝑠. In a stationaryad hoc network, Fig. 3.(a), OLSR slightly outperforms CE-OLSR for a data traffic load below 𝜌 = 40 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐. Thisis due to the stability routing scheme adopted in CE-OLSRwhich increases slightly the length of the routes that, in turn,consumes some additional network resources. Beyond 𝜌 =40 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐, CE-OLSR outperforms OLSR. This superiorityof CE-OLSR at high workload in a stationary network is akinto its robustness against control packets losses by inferringunpublished links from cartographic information. Fig. 4.(a)confirms that CE-OLSR is more robust than OLSR againstcontrol packets losses since the routes validity in CE-OLSRis better than that in OLSR for a high traffic. For example,for a traffic of 75 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐 per flow, the routes validity inCE-OLSR is equal to 92% while that of OLSR is only equalto 82%.

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Fig. 3: The throughput of OLSR and CE-OLSR as a functionof the data traffic load(a): 𝑠𝑝𝑒𝑒𝑑 = 0 𝑚/𝑠 (b): 𝑠𝑝𝑒𝑒𝑑 = 5 𝑚/𝑠(c): 𝑠𝑝𝑒𝑒𝑑 = 10 𝑚/𝑠 (d): 𝑠𝑝𝑒𝑒𝑑 = 20 𝑚/𝑠

For scenarios invoking mobility, CE-OLSR substantiallyoutperforms OLSR in terms of a much larger greater through-put. In Fig. 3.(b) relative to the speed of 5 𝑚/𝑠 , CE-OLSRthroughput exceeds that of OLSR by more than 37% virtuallyover all traffic loads but null. This gain in throughput reachesaround 117% for a speed of 10 𝑚/𝑠 as portrayed in Fig. 3.(c).It rises to around 278% for a speed of 20 𝑚/𝑠 as shown onFig. 3.(d). However, we note that the throughput of both CE-OLSR and OLSR, is affected by mobility. Nevertheless, aswe previously mentioned, CE-OLSR is much less influencedby this problem thanks to its fast adaptation to topologicalchanges and the judicious stability routing scheme applied that

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avoids the use of unstable links. For instance, CE-OLSR fora high speed of 20 𝑚/𝑠 and a high traffic load, achieves 52%of the throughput its delivered in a stationary network. OLSRin such a case, can only deliver 15%.

Furthermore and in the quest to better ascertain the effi-ciency of our routing proposal in terms of throughput, Fig. 4assesses the forwarding capability of CE-OLSR versus thatof OLSR. This figure portrays the number of data packetssuccessfully received as a function of the number of traversedhops for a speed of 10 𝑚/𝑠 and 𝜌 = 20 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐. Weclearly observe that data packets make considerably morehops in CE-OLSR than in OLSR. Recall that routes lengthare comprised between 4 to 6 hops as we immobilized thesources and destinations of our streams on both ends of thenetworks area. For example, among the 2000 sent packets,1653 packets succeed in reaching the 4𝑡ℎ hop in CE-OLSR;while, in OLSR only 560 data packets make such a progresstoward their destinations.

Now, we turn to investigate the average end to end delayof received data packets, which is a central performancemetric especially for real time applications. Fig. 5 portraysthe average end to end delay as a function of the data trafficload and for different node speeds. For a stationary network,both OLSR and CE-OLSR provide adequate similar averageend to end delay of less than 0.021𝑠 for a data traffic load ofup to 𝜌 = 30 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐 as shown in Fig. 5.(a). As soon asnodes start moving, OLSR gets affected severely. As shownin Fig. 5.(b) which is relative to a node speed of 2 𝑚/𝑠,OLSR requires more delay to be able to deliver data packetswhen the data traffic load per source gets beyond 20 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐.At 𝜌 = 30 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐, OLSR takes 0.113 𝑠 while CE-OLSRrequires an average delay of just 0.035 𝑠. The average delaygets worst for OLSR for higher node speeds. At a speed of5 𝑚/𝑠 (Fig. 5.(c)), the CE-OLSR performance is more than 18times better than OLSR for 𝜌 = 30 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐. Indeed, at thisspeed, the delay of OLSR is increased to 0.733 𝑠 which makesOLSR tacitely unsuitable for any time critical applications. Fora speed of 10 𝑚/𝑠 (Fig. 5.(d)), CE-OLSR still maintains anacceptable end to end delay of only 0.082 𝑠 which is 21 timesbetter than that of OLSR at 𝜌 = 30 𝑃𝑘𝑡𝑠/𝑠𝑒𝑐.

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VI. CONCLUSION

In this work, we identified the main reasons impacting theOLSR protocol performance in the context of mobile multi-hop ad hoc networks. We proposed an efficient cartographygathering mechanism using the same exact signaling trafficof OLSR by augmenting the signaling messages with datafields to carry the cartography information. Based on sucha cartography, we proposed a novel routing protocol calledthe Cartography Enhanced Optimized Routing Protocol (CE-OLSR).

CE-OLSR is composed of two steps. In the first step, anovel cartography gathering scheme is run to identify the

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best known cartographic information about each node inthe network. In the second step, a stable routing scheme isapplied. Conducted simulations showed the effectiveness ofour proposed protocol in terms of much better route validity,much higher throughput and much lower end to end packetdelay. The validity of the established routes stayed way abovethe 90% for CE-OLSR while that of OLSR degraded down to30% for a high speed of 20 𝑚/𝑠. For this speed, CE-OLSRprovided a throughput 3 times higher than that of OLSR andan average end to end delay 21 times lower. Even for highworkload and very dynamic networks, CE-OLSR requiresa rather small average end to end delay, hence making it asuitable protocol for the transport of time critical data.

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