A novel context-aware RPL algorithm based on a triangle module operator

For the use in low-power and lossy networks(LLNs)under complex and harsh communication conditions,the routing protocol for LLNs(RPL)standardized by the Internet Engineering Task Force is specially designed.To improve the performance of LLNs,we propose a novel context-aware RPL algorithm based on a triangle module operator(CAR-TMO).A novel composite context-aware routing metric(CA-RM)is designed,which synchronously evaluates the residual energy index,buffer occupancy ratio of a node,expected transmission count(ETX),delay,and hop count from a candidate parent to the root.CA-RM considers the residual energy index and buffer occupancy ratio of the candidate parent and its preferred parent in a recursive manner to reduce the effect of upstream parents,since farther paths are considered.CA-RM comprehensively uses the sum,mean,and standard deviation values of ETX and delay of links in a path to ensure a better performance.Moreover,in CAR-TMO,the membership function of each routing metric is designed.Then,a comprehensive membership function is constructed based on a triangle module operator,the membership function of each routing metric,and a comprehensive context-aware objective function.A novel mechanism for calculating the node rank and the mechanisms for preferred parent selection are proposed.Finally,theoretical analysis and simulation results show that CAR-TMO outperforms several state-of-the-art RPL algorithms in terms of the packet delivery ratio and energy efficiency.