A new Mobility, Energy and Congestion Aware Routing scheme for MANETs

Minh, Hoa Le; Sexton, Graham; Aslam, Nauman; Boubezari, Rayana

doi:10.1109/csndsp.2014.6923931

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…However, at stage 2 opportunities for the better use of the second player's drone for the first player are formed (see Table II [4,4]. For the rest of the strategies, both players can not improve achievements of the first stage.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…The first 5 strategies do not allow any improvements (as well as strategies 7, 10 and 11) for both players, then make no changes to the drones' positions. However the 6−th strategy (drone 1 at (4, 6), drone 2 at (4, 4)) gives an opportunity for the first player to use the second drone as a 2-bridge ((5, 4), (4,4)) which brings the diameter to 12 for both of the players. Now the second player finds a better position for the second drone, namely (4, 6), which bring the diameter down to 11, however that action increases the diameter of the first player to 15.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…When the number of nodes wanting to transmit data increases some of the routing paths become congested and performance drops [4], [5]. In some cases the obstacles on the ground (lakes, buildings, etc.)…”

Section: Introductionmentioning

confidence: 99%

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A Dynamic Game of Mobile Agent Placement in a MANET

Gromova

Gromov

Timonin

et al. 2016

2016 International Conference on Systems Informatics, Modelling and Simulation (SIMS)

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Abstract-In this paper, we describe a novel game-theoretic formulation of the optimal mobile agents placement problem which arises in the context of Mobile Ad-hoc Networks (MANETs). In particular, we consider two classes of multistage games: sequential and simultaneous. For such games, the definitions of the Nash equilibria and the cooperative solution are given. The described games exhibit a number of interesting features. For instance, the Nash equilibrium may turn out to be unattainable in both a simultaneous and a sequential game. In this case, the game dynamics may exhibit the behaviour similar to that of a limit cycle albeit in a discrete space. A modelling environment for the analysis of different strategies of the players was developed in MATLAB. The programme generates various game situations and determines each players move by solving respective optimisation problems. Using the developed environment, two specific game scenarios were considered in detail.

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Section: Numerical Examplesmentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

See 1 more Smart Citation

A Dynamic Game of Mobile Agent Placement in a MANET

Gromova

Gromov

Timonin

et al. 2016

2016 International Conference on Systems Informatics, Modelling and Simulation (SIMS)

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“…As remote innovation in MANET, there is a nonattendance of the base structure. 8,9 A cluster head (CH)-based clustering algorithm at first chooses a node as a CH, and after that, the area of the chose node and itself frames a single cluster. 4 In any case, the mobility of sensor nodes influences the routing to process testing and complex, which hampers the energy efficiency of the routing protocols.…”

Section: Introductionmentioning

confidence: 99%

“…7 Considering the mobility and asset compelled condition, wireless sensor networks require energy efficient routing protocols, equipped for diminishing the bundle misfortune and improving heartiness against mobility of nodes. 8,9 A cluster head (CH)-based clustering algorithm at first chooses a node as a CH, and after that, the area of the chose node and itself frames a single cluster. 10 Mobility factor of nodes is computed utilizing dependability function.…”

Section: Introductionmentioning

confidence: 99%

Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET

Gupta

Khanna

Lakshmanaprabu

et al. 2018

Trans Emerging Tel Tech

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Mobile ad hoc network (MANET) is a gathering of self‐ruling mobile nodes in which ad hoc network framed without settled foundation. Dynamic topology property of MANET may debase the execution of the network, mobility attentiveness, and energy effectiveness because of an ideal cluster head (CH). The low energy adaptive clustering hierarchy protocol is used in the MANETs for enhancement of network life time by proficiently utilizing of the accessible constrained energy. Artificial fish swarm optimization is used to select the CH in MANET communication process. The election of CH takes care of mobility and remaining energy as well as the degree of connectivity for selecting nodes to serve as cluster for longer duration of time. From the implementation results, it is observed that the proposed method provides the maximum network life time as 80 to 140 hours and minimum energy consumption as 9 to 130 J, compared with existing protocol and optimization technique.

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