C3P-RPL: A collaborative and proactive approach for optimal peer to peer path selection and sustenance

Abstract

Internet of Things is evolving from information gathering platforms into collaborative systems where smart devices actively interact with each other in a seamless manner. For instance, Internet of Robotic Things is envisioned to provide augmented solutions through collaboration of varied smart devices and robots. These visions revolve around the ability of smart devices to directly communicate and cooperate with each other in real time. In this context, this paper is an attempt to study RPL's point to point routing that creates multi-hop paths between peer nodes. This standard routing protocol is known for robust and failsafe upward paths but its peer to peer (P2P) routes are reported to be sub optimal. This work assesses P2P performance of RPL's storing mode in a network of new generation devices having higher memory. Further, a Collaborative and Proactive Peer to Peer (C3P) path selection and sustenance approach is proposed where root node collates incremental topology from collaborative nodes and disseminates optimal single source shortest path trees SPT(n). A progressive node betweenness centrality score ensures spread out paths. Minor topology changes are accommodated through incremental node and edge updates to targeted SPT(n) locally. Storing SPTs in intermediate nodes reduces storage and packet size. Through simulations and testbed experiments, it is proven that C3P-RPL improves simultaneous peer to peer communication between all the nodes. Specifically, the path length is reduced by 30% and subsequently the network latency drops by 65% in an experimental testbed of 47 nodes, making it suitable for collaborations.