Literature DB >> 33494366

Quantitative Study on the Impact of Energy Consumption Based Dynamic Selfishness in MANETs.

Axida Shan1,2, Xiumei Fan1, Celimuge Wu3, Xinghui Zhang1,4, Shujia Fan5.   

Abstract

Cooperative communication and resource limitation are two main characteristics of mobile ad hoc networks (MANETs). On one hand, communication among the nodes in MANETs highly depends on the cooperation among nodes because of the limited transmission range of the nodes, and multi-hop communications are needed in most cases. On the other hand, every node in MANETs has stringent resource constraints on computations, communications, memory, and energy. These two characteristics lead to the existence of selfish nodes in MANETs, which affects the network performance in various aspects. In this paper, we quantitatively investigate the impacts of node selfishness caused by energy depletion in MANETs in terms of packet loss rate, round-trip delay, and throughput. We conducted extensive measurements on a proper simulation platform incorporating an OMNeT++ and INET Framework. Our experimental results quantitatively indicate the impact of node selfishness on the network performance in MANETs. The results also imply that it is important to evaluate the impact of node selfishness by jointly considering selfish nodes' mobility models, densities, proportions, and combinations.

Entities:  

Keywords:  MANET; OMNeT++; energy consumption; impact; selfishness

Year:  2021        PMID: 33494366     DOI: 10.3390/s21030716

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  A Hybrid Price Auction-Based Secure Routing Protocol Using Advanced Speed and Cosine Similarity-Based Clustering against Sinkhole Attack in VANETs.

Authors:  Yushintia Pramitarini; Ridho Hendra Yoga Perdana; Thong-Nhat Tran; Kyusung Shim; Beongku An
Journal:  Sensors (Basel)       Date:  2022-08-03       Impact factor: 3.847

2.  Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model.

Authors:  Lan Zheng
Journal:  Comput Intell Neurosci       Date:  2022-09-21
  2 in total

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