A Local Betweenness Centrality Based Forwarding Technique for Social Opportunistic IoT Networks

Social Opportunistic IoT (Social OppIoT) networks is a subclass of Social Internet of Things (SIoT) networks. In social OppIoT, users perform communication in a distributed manner using smart devices by regularly moving around without any communication infrastructures, making routing a strenuous process due to its highly fragile connection intermittency and device mobility. Moreover, due to the growing heterogeneous devices, problems can exist in searching for the right relay node from a massive number of devices. In this paper, a novel forwarding scheme named “A Local Betweenness Centrality Based Forwarding Technique for Social Opportunistic IoT Networks” (LBCFT) has been proposed, which uses a reduction strategy to discard the inefficient devices. LBCFT introduces a new centrality measurement called local betweenness centrality to form the significant overlapping communities of network devices to boost forwarding. Message dissemination is controlled by handling inefficient devices using a reduction strategy, which includes the node’s trajectory and intra-community and inter-community centrality. The performance of LBCFT is evaluated through ONE Simulator against the existing analogous ideologies like Supernode, Geo-Routing with Angle-based Decision (GRAD), and the benchmark protocols BubbleRap, as well as PROPHET. The simulation results show that the proposed LBCFT protocol, on average, outperforms Supernode, GRAD, BubbleRap, and PROPHET by 5.22%, 36.51%, 64.12%, and 57.96% respectively, in terms of the delivery probability.