Home > Research > Publications & Outputs > Evaluation of Congestion Aware Social Metrics f...


Text available via DOI:

View graph of relations

Evaluation of Congestion Aware Social Metrics for Centrality-Based Routing

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Muhammad Arshad Islam
  • Muhammad Azhar Iqbal
  • Muhammad Aleem
  • Zahid Halim
  • Gautam Srivastava
  • Jerry Chun-Wei Lin
Article number5581259
<mark>Journal publication date</mark>21/06/2021
<mark>Journal</mark>Wireless Communications and Mobile Computing
Number of pages14
Publication StatusPublished
<mark>Original language</mark>English


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.