M‐DART: multi‐path dynamic address routing

Caleffi, Marcello; Paura, Luigi

doi:10.1002/wcm.986

Cited by 55 publications

(47 citation statements)

References 41 publications

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“…Address RouTing (DART) [33] and Multi-path DART (M-DART) [34] In DART / M-DART the main objective is geographical routing where the dynamic address assignment is based on the hierarchical tree as in LADC. M-DART provides multi-path routing compared to DART.…”

Section: Ladc Versus Dynamicmentioning

confidence: 99%

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Thomas

Mathew

2017

Ad Hoc Networks

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Section: Ladc Versus Dynamicmentioning

confidence: 99%

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Thomas

Mathew

2017

Ad Hoc Networks

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“…[12][13][14][15][16][17][18][19][20][21] Because of it, the problem of conflicting and incommensurate always exists and may not be removed.…”

Section: Motivationmentioning

confidence: 99%

“…Let the residual energy of a group of node n g is defined by Equation 15. Let the residual energy of a group of node n g is defined by Equation 15.…”

Section: Route Discoverymentioning

confidence: 99%

Energy efficient routing formation technique for hybrid ad hoc network using fusion of artificial intelligence techniques

Das

Tripathi

2017

Int J Communication

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Hybrid Ad-hoc NETwork (HANET) is a fusion of both the static and dynamic topologies. Each node of this network consists of low capacity battery. Because of heterogeneous characteristic of the topology, network parameters are imprecise in nature. This, in effect, the performance and lifetime of the network degrade. To overcome these issues, this paper proposes an optimized energy efficient routing (OE2R) method. This method is inspired by artificial intelligence techniques such as multiobjective optimization, geometric programming, aspiration level, and tolerance limit. The fusion of such stated artificial intelligence techniques provide an effective tool to optimize multiple conflict objectives and estimate imprecise parameters of the network, simultaneously. The proposed technique OE2R is simulated using LINGO optimization software. To justify the effectiveness of the proposed technique, its performance is compared with some existing methods such as approximate linear programming technique for average cost bounds and linear programming-based efficient message delivery approach in hybrid network in several passes of performance metrics. The simulation results show that the proposed OE2R method performs much better with the comparative methods and may be implemented as energy-efficient routing for HANET. KEYWORDSapproximation method, aspiration level, geometric programming, hybrid ad hoc network, multiobjective optimization, optimset Int J Commun Syst. 2017;30:e3340.wileyonlinelibrary.com/journal/dac

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“…In the link-disjoint paths, the destination node adopts a looser reply policy. It replies up to k copies of RREQ arriving via singular neighbours, discounting the first hops of these RREQs [23]. Singular neighbor who presents in the network guarantees link disjointness in the first hop of the RREP.…”

Section: Aomdvmentioning

confidence: 99%

ACO Agent Based Routing in AOMDV Environment

Kaur

Dhaka

Singh

2016

MATEC Web of Conferences

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Abstract. Mobile Ad-hoc Network (MANET) is a group of moving nodes which can communicate with each other without the help of any central stationary node. All the nodes in the MANET act as router for forwarding data packets. The nodes in the network also move randomly and there exists no fixed infrastructure. So, path breaks are the frequent problem in MANET. The routing protocol faces a lot of problem due these path breaks. Therefore, the routing protocol which is multipath in nature is more reliable than a unipath routing protocol. Ant colony optimization is a relatively new technique which is suitable for the optimization problems. AOMDV is a multipath routing protocol. Thus, if there happens to be path break, the packets can start following the new path which has already been selected. In this paper, we are trying to add ant's agents into AOMDV behavior. In this way, the new protocol will be benefited by the dual properties i.e. of ant's nature and multipath nature of AOMDV. The modified concept is simulated and the outcomes are compared with AOMDV, AODV and DSR routing protocols for few performance parameters. Results obtained are encouraging; the new algorithm performs better than traditional unipath and multipath routing protocols.

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M‐DART: multi‐path dynamic address routing

Cited by 55 publications

References 41 publications

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Energy efficient routing formation technique for hybrid ad hoc network using fusion of artificial intelligence techniques

ACO Agent Based Routing in AOMDV Environment

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