Analysing connectivity patterns and centrality metrics for opportunistic networks

Islam, Muhammad Arshad; Iqbal, Muhammad Azhar; Aleem, Muhammad; Halim, Zahid

doi:10.1109/c-code.2017.7918903

Cited by 1 publication

(1 citation statement)

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“…The routing simulations in this paper are performed by adapting the real-life social networks that are extracted using the traces of wireless devices. The results presented in this paper are extended from [31] which indicates that the message delivery ratio of the congestion aware metrics is observed compatible with the message delivery ratio for epidemic routing. The highlights of the article are as follows: evaluation of routing performance of three opportunistic network metrics, i.e., contact count, intercontact time, and average contact duration, to harness link congestion information; a comprehensive congestion analysis concerning both complete network and individual nodes of the network metrics by simulation using three real-life social networks.…”

Section: Data Availabilitysupporting

confidence: 66%

Evaluation of Congestion Aware Social Metrics for Centrality‐Based Routing

Islam

Iqbal

Aleem

et al. 2021

Wireless Communications and Mobile Computing

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Opportunistic networks utilize pocket switching for routing where each node forwards its messages to a suitable next node. The selection of the forwarder node is crucial for the efficient performance of a routing protocol. In any opportunistic network, some nodes have a paramount role in the routing process and these nodes could be identified with the assistance of the existing centrality measures available in network theory. However, the central nodes tend to suffer from congestion because a large number of nodes that are relatively less central attempt to forward their payload to the central nodes to increase the probability of the message delivery. This paper evaluates mechanisms to transform the social encounters into congestion aware metrics so that high-ranking central nodes are downgraded when they encounter congestion. The network transformations are aimed at aggregating the connectivity patterns of the nodes to implicitly accumulate the network information to be utilized by centrality measures for routing purposes. We have analyzed the performance of the metrics’ computed centrality measures using routing simulation on three real-world network traces. The results revealed that betweenness centrality along with the congestion aware network metrics holds the potential to deliver a competitive number of messages. Additionally, the proposed congestion aware metrics significantly balance the routing load among the central nodes.

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Section: Data Availabilitysupporting

confidence: 66%