Mobility and energy aware routing algorithm for mobile ad-hoc networks

Rashid, Umair; Waqar, Omer; Kiani, Aysha Karim

doi:10.1109/icee.2017.7893434

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…In this section, we present the simulation results and discussions of the proposed algorithm. The performance of proposed routing algorithm, MARA, is compared with AODV [5], MAD [21], and MAE [31]. We used the quantitative performance metrics used in [22,23].…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Mobility‐Aware Routing Algorithm for Mobile Ad Hoc Networks

Sirmollo

Bitew

2021

Wireless Communications and Mobile Computing

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Mobile ad hoc network (MANET) is a group of wireless mobile nodes that create a temporary network without the help of any central administration or standard support services. Mobility of nodes determines the overall performance of MANET networks. High mobility of nodes causes frequent changes in the network topology, and this leads to link breakage and increases reinitiating of the route discovery process. MANETs commonly use broadcasting techniques for route discovery process. However, it can cause redundant rebroadcasts, packet collisions, and channel contention. The main objective of this paper is to design and develop the mobility-aware routing algorithm (MARA) to enhance the performance of the routing protocol in MANETs. The proposed scheme allows mobile nodes to rebroadcast or discard received broadcasted messages. The decision is based on the combination of node speed, distance between nodes, and residual energy of nodes. These parameters are considered both in route request and route reply process to reduce the chance of link breakage and broadcast storm problems. The proposed algorithm has been evaluated based on the performance metrics: packet delivery ratio, average end-to-end delay, throughput, and routing overhead. We have used network simulator NS-2 V-2.35. The simulation results revealed that MARA outperforms ad hoc on-demand distance vector (AODV), mobility and direction aware (MAD), and mobility and energy-aware (MAE) routing protocols.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Mobility‐Aware Routing Algorithm for Mobile Ad Hoc Networks

Sirmollo

Bitew

2021

Wireless Communications and Mobile Computing

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“…To increase the lifetime of the network, authors Rashid et al 12 had developed the mobility and energy‐aware AODV (MEAODV) protocol. In the MANET, the major challenges of designing a routing protocol are energy management and mobility.…”

Section: Related Workmentioning

confidence: 99%

“…Also, the rate of energy consumption was considered for efficient routing node selection. These factors were facilitated the network to survive a longer period for successful routing 12 …”

Section: Related Workmentioning

confidence: 99%

Mobility speed prediction using ARIMA and RNN for random walk mobility model in mobile ad hoc networks

Theerthagiri

Thangavelu²

2021

Concurrency and Computation

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In this article, an auto‐regressive integrated moving average (ARIMA) modeling has been proposed to predict the mobility speed of the nodes in the mobile ad hoc networks (MANETs). The mobility speed prediction supports effective route discovery to enhance efficient and reliable routing. The random walk mobility model had been used to forecast the mobility of the nodes. Subsequently, various the recurrent neural network (RNN) model has been developed with different number hidden neurons, and the prediction results are compared with proposed ARIMA based results. The Akaike information criterion, auto‐correlation function metrics are evaluated to assess the dataset's quality. Several network scenarios are evaluated with various speeds and the number of nodes. The results of the proposed ARIMA model are compared with the RNN results. It demonstrates that the proposed model has higher prediction rates with reduced error rates of 0.1%–1.4% than RNN values. Such that the proposed methods facilitate the higher prediction rate of 10%–26% as compared with the RNN. Therefore, the proposed mobility speed prediction techniques support the effective routing in the MANETs.

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Stable Reduced Link Break Routing Technique in Mobile Ad Hoc Network

Hanji¹,

Shettar²

2018

Communications in Computer and Information Science

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Mobility and energy aware routing algorithm for mobile ad-hoc networks

Cited by 9 publications

References 12 publications

Mobility‐Aware Routing Algorithm for Mobile Ad Hoc Networks

Mobility‐Aware Routing Algorithm for Mobile Ad Hoc Networks

Mobility speed prediction using ARIMA and RNN for random walk mobility model in mobile ad hoc networks

Stable Reduced Link Break Routing Technique in Mobile Ad Hoc Network

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