A Hybrid Opportunistic Scalable and Energy Efficient Routing Design for Low Power Lossy Wireless Sensor Network

Abstract

The past decade has witnessed numerous routing design proposals for wireless newlinemulti-hop networks specifically forWireless Sensor Networks (WSN), and recently it s newlineallied Low Power, Lossy Networks (LLN) in the era of Internet of Things (IoT). The newlineprimary design issue in routing protocols that hinders the energy-efficient operation and scalability in resource-constrained lossy WSN is the communication overhead for route discovery and maintenance. The pre-computation of the route before data transmission does not adapt well to the network dynamics. Opportunistic Routing (OR) schemes increase the transmission reliability, despite lossy wireless radio links, by exploiting the broadcast nature of the wireless medium. However, OR schemes in low power, lossy WSN leads to energy drain in these constrained nodes due to constant overhearing, periodic beaconing for neighbourhood management, newlineand increase in packet header length. The increase in packet header length is newlinedue to the need to append the list of forwarding candidates in sorted priority order before data transmission, for coordination among forwarding candidates. A hybrid opportunistic energy-efficient cross-layered routing design is proposed for newlinelarge scale, low power and lossy WSN to address these issues. The key features of the proposed hybrid routing design includes the following A Corona driven Hybrid Opportunistic routing design that combines the reliability of OR during time-varying error-prone wireless links and energy efficiency of traditional unicast routing during stable wireless links. A fully distributed online forwarding candidate set selection, prioritization, and coordination with no significant increase in packet header length except for the corona level information, A cross-layered differentiated back-off exponent parameters assignment for contention based forwarding and dynamic forwarding delay computation in an online manner for candidate prioritization newline