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An Adaptive Neighbour Knowledge-Based Hybrid Broadcasting for Emergency Communications

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 44))

Abstract

In recent years, mobile ad-hoc networks have rooted their pillars for emergency communication owing to reasonable cost, diversity, and easiness of mobile devices. The mobile ad-hoc networks is a self-coordinated, distributed and infrastructure-less network of mobiles nodes. These characteristics of MANET enhanced the applicability of MANET in the field of emergency communication such as military and police operations, flood control and fire disaster management, etc. In MANET, a broadcast storm causes network problems as there are redundant broadcasts and packet collisions. Classical broadcast methods have motivated on evading broadcast storms by preventing some rebroadcasts. The further problem is the link breakages induced by node instability and their power exhaustion. In this research, we propose an adaptive neighbor knowledge-based hybrid broadcasting method to address these network problems. This method refines the counter threshold based on neighbourhood, mobility and energy of the node and makes use of the refined thresholds to make the broadcasting decision. The proposed method perform best as compared to AMECBB and TCBB by decreasing delay, packet dropping, and routing overhead and energy consumption.

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Correspondence to Manjusha Deshmukh , S. N. Kakarwal or Ratnadeep Deshmukh .

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Deshmukh, M., Kakarwal, S.N., Deshmukh, R. (2020). An Adaptive Neighbour Knowledge-Based Hybrid Broadcasting for Emergency Communications. In: Smys, S., Senjyu, T., Lafata, P. (eds) Second International Conference on Computer Networks and Communication Technologies. ICCNCT 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-030-37051-0_10

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  • DOI: https://doi.org/10.1007/978-3-030-37051-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37050-3

  • Online ISBN: 978-3-030-37051-0

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