PSPL: A Generalized Model to Convert Existing Neighbor Discovery Algorithms to Highly Efficient Asymmetric Ones for Heterogeneous IoT Devices

Abstract

Neighbor discovery is a prerequisite procedure in communication among energy-limited Internet-of-Things (IoT) devices. Discovering neighbors should be achieved in an energy-efficient way. Communication between heterogeneous IoT devices is a common phenomenon for achieving extensive connections among IoT devices. Generally, existing asymmetric neighbor discovery methods are evolved from the symmetric methods and lack specialized designs for heterogeneous IoT devices which led to relatively poor energy-efficient performance. In this article, we use a generalized slot model using pure sending (PS) slot and pure listening (PL) slot, called PSPL, to convert existing neighbor discovery algorithms (symmetric and asymmetric) to highly energy-efficient asymmetric ones. The core idea of PSPL is that to achieve highly energy-efficient one-way discovery, PS slot and PL slot are only used in devices with smaller and larger energy budgets, respectively, and the length of PL slot is much larger than that of PS slot. In this way, the energy efficiency of asymmetric neighbor discovery can be substantially improved. After implementing one-way discovery, two-way discovery can be easily achieved with mutual assistance. Two examples of how to convert existing algorithms into highly efficient asymmetric ones are presented, the one is to convert Disco to Disco+PSPL and the other one is to convert Griassdi to Griassdi+PSPL. The theoretical analysis results indicate that with the same energy budget, Disco+PSPL and Griassdi+PSPL reduce the worst case latency bounds by up to 82.28% and 87.69%, respectively, compared with the best known asymmetric solutions. The simulation evaluation verifies the effectiveness of our designs.