Performance evaluation of a cartography enhanced OLSR for mobile multi-hop ad hoc networks

Belhassen, Mohamed; Belghith, Abdelfettah; Abid, Mohamed Amine

doi:10.1109/wiad.2011.5983303

Cited by 25 publications

(23 citation statements)

References 11 publications

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“…The maximum bandwidth and minimum delay have been choose as QoS parameters in order to improve quality requirements in the MPRs selection and routing information. The proposed algorithm found the optimal MPRs with guarantee maximum bandwidth and minimum delay has better result than others in static and mobile networks simulation [12].…”

Section: Introductionmentioning

confidence: 94%

The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

et al. 2012

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Section: Introductionmentioning

confidence: 94%

The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

et al. 2012

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“…As proactive routing protocols we can cite OLSR [13] and its extensions (like DOLSR [14], M-OLSR [15] or CE-OLSR [16]), DSDV [17] and B.A.T.M.A.N [18].…”

Section: Routing Protocols For Uaanetsmentioning

confidence: 99%

Emulation-Based Performance Evaluation of Routing Protocols for Uaanets

Maxa¹,

Roudière²,

Larrieu³

2015

Lecture Notes in Computer Science

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Abstract. UAV Ad hoc NETwork (UAANET) is a subset of the wellknown Mobile Ad-hoc NETworks (MANETs). It consists of forming an ad hoc network with multiple small Unmanned Aerial Vehicles (UAVs) and the Ground Control Station (GCS). Similar to MANETs, the UAANET communication architecture is infrastructure-less and self-configuring network of several nodes forwarding data packets. However, it also has some specific features that brings challenges on network connectivity. Consequently, an adapted routing protocol is needed to exchange data packets within UAANETs. In this paper, we introduce a new hybrid experimental system that can evaluate different types of adhoc routing protocols under a realistic UAANET scenario. It is based on virtual machines and the Virtualmesh [1] framework to emulate physical aspects. We evaluated AODV, DSR and OLSR efficiency in a realistic scenario with three UAVs scanning an area. Our results show that AODV outperformed OLSR and DSR.

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“…This is indeed a challenging task as the requirement for additional signaling to detect and share obstacle locations and contours should be limited to its minimum so that resources are left for the effective transmission of data. In this paper, we propose an autonomous obstacle detection scheme that relies on the cartography enhanced OLSR [6,8]. Our proposed scheme does not require any additional signaling overhead as it relies completely on the use of CE-OLSR signaling but induces some additional 2 Mobile Information Systems computation time at each node that will be identified and investigated in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…or an additional signaling overhead. In fact, we propose a novel lightweight obstacle detection scheme entirely based on the original signalling of the cartography enhanced OLSR (CE-OLSR) protocol [8]. More precisely, we use the joint awareness of CE-OLSR about the link states and the network cartography to discover the pairs of nodes (position pairs) in the network that are unable to communicate due to obstructing obstacles.…”

Section: Introductionmentioning

confidence: 99%

Autonomic Obstacle Detection and Avoidance in MANETs Driven by Cartography Enhanced OLSR

Belghith

Belhassen

Dhraief

et al. 2015

Mobile Information Systems

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The presence of obstructing obstacles severely degrades the efficiency of routing protocols in MANETs. To mitigate the effect of these obstructing obstacles, routing in MANETs is usually based on the a priori knowledge of the obstacle map. In this paper, we investigate rather the dynamic and autonomic detection of obstacles that might stand within the network. This is accomplished using the enhanced cartography optimized link state routing CE-OLSR with no extra signaling overhead. The evaluation of the performance of our proposed detection scheme is accomplished through extensive simulations using OMNET++. Results clearly show the ability of our proposed scheme to accurately delimit the obstacle area with high coverage and efficient precision ratios. Furthermore, we integrated the proposed scheme into CE-OLSR to make it capable of autonomously detecting and avoiding obstacles. Simulation results show the effectiveness of such an integrated protocol that provides the same route validity as that of CE-OLSR-OA which is based on the a priori knowledge of the obstructing obstacle map.

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Performance evaluation of a cartography enhanced OLSR for mobile multi-hop ad hoc networks

Cited by 25 publications

References 11 publications

The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

Emulation-Based Performance Evaluation of Routing Protocols for Uaanets

Autonomic Obstacle Detection and Avoidance in MANETs Driven by Cartography Enhanced OLSR

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