Security, Trust, and Privacy in Opportunistic Multihop Wireless Networks

Krishna, M. Bala

doi:10.1201/b16754-22

Cited by 1 publication

(1 citation statement)

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“…In ref. [33] security and privacy issue in opportunistic networks are highlighted. Based on the received attributes' messages, the MIWS estimates the weights of the attributes BW, buffer size and MobSp, which are denoted by BW, BS and MobSp, respectively, that is, the set of attributes is F = {BW, BS, MobSp}.…”

Section: Case Studymentioning

confidence: 99%

Innovative mutual information‐based weighting scheme in stateless opportunistic networks

et al. 2021

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Recently, opportunistic networks (OppNets) are considered as one of the most attractive developments of mobile ad hoc networks that have emerged, thanks to the development of intelligent devices. Owing to the harsh and dynamic topology of these networks, attaining high delivery ratio is a challenging issue. Hence, it is imperative to select which node's attribute must be adjusted to achieve a higher performance in such unpredictable networks. A mutual information-based weighting scheme (MIWS) that exploits the entropy concept to assess the impact of the nodes' attributes on the network performance was proposed. The weighting procedure aims to figure out the correlative relations between different attributes and delivery ratio performance of the network. The high weight of certain attributes implies a correspondingly high impact in achieving efficient data forwarding. The proposed scheme is proofed conceptually and simulated using the Opportunistic Network Environment simulator. In contrast to previous studies conducted in the context of weight resolution, the proposed approach allows us to address this issue in real-time stateless non-social OppNets. Regardless of the deployed routing protocol, experiments show that adjusting nodes' attributes based on the proposed MIWS can improve the performance up to encouraging delivery ratios. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Case Studymentioning

confidence: 99%