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Increasing the lifespan of wireless adhoc network using probabilistic approaches: a survey

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Abstract

This survey paper will help practitioner to identify various issues and challenges in increasing lifespan of wireless adhoc network and classify variety of solutions. In battlefield where tactical operations are involved, one has to set best wireless adhoc network for information exchange while retaining better energy level. Initiating with the description of wireless adhoc network, the survey describes the various issues, problems with traditional routing, and probabilistic approaches for distributing packets. While setting large network, energy and end to end delay is considered to be important factor. There are wide range of applications which are required for a wireless node even if they have various constraints in terms of range of communication, energy, topology, processing capability and storage. Channel state information has a vital for signal processing and network operation. There are many issues with Channel state information acquisition methods which are responsible for reducing the opportunities in energy saving are also described in this paper. Various methodologies have been proposed by many researchers to enhance the lifetime of the wireless adhoc network, where groups are of different sizes. This survey also provides the metric for testing the performance of a network. Neural Network seems to be the best method to provide efficient threshold values for selecting group head and cluster head using back propagation algorithm where weight adjustment is been done by Particle Swarm Optimization algorithm. It provides intelligent organization of network for better efficiency. Efficient technique have been proposed for increasing the networks lifetime. Simulation results show that increase in packet size increase throughput of wireless adhoc network in grid network. Usage of Pareto distribution improves the overall residual energy and average residual energy of the wireless Adhoc Network. Pareto distribution is been utilized while distribution of packets. We presume that this survey will help to generate learning resource to understand the ongoing contributions in the area of enhancing battery life of a wireless node in Adhoc network, the different procedures for the designers and their practices in developing more efficient and practical solutions, especially for future research in improving the network lifespan.

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Abbreviations

Er :

Residual energy—remaining energy of a node

PDR:

Packet delivery ratio—number of successful packet delivered

Throughput:

Average number of packets delivered per second

E2E delay:

End to end delay of packet from source to destination

Normalized routing overhead:

Total number of routing packets transmitted per data packet

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Authors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra, India

    Suresh Kurumbanshi

  2. Department of Electronics Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra, India

    Shubhangi Rathkanthiwar

Authors
  1. Suresh Kurumbanshi
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  2. Shubhangi Rathkanthiwar
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Correspondence to Suresh Kurumbanshi.

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Kurumbanshi, S., Rathkanthiwar, S. Increasing the lifespan of wireless adhoc network using probabilistic approaches: a survey. Int. j. inf. tecnol. 10, 537–542 (2018). https://doi.org/10.1007/s41870-018-0177-1

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  • DOI: https://doi.org/10.1007/s41870-018-0177-1

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