Large scale energy harvesting sensor networks with applications in smart cities

Abstract

Wireless sensor networks (WSNs), with a wide range of applications in smart cities (e.g. environmental monitoring, intelligent traffic management, healthcare), have energy self-sufficiency as one of the main bottlenecks in their implementation. Thanks to the recent advances in energy harvesting (EH), i.e., capturing energy from ambient renewable sources, it is now a promising solution for low-power and low-rate WNSs. In this paper, we consider two open problems of practical importance to the data quality optimization problem. In this paper, first the probabilistic energy causality constraint for the online consideration of the EH scenarios is proposed. Our realistic assumptions consider causal energy state information, instead of the non-causal cases and the ones based on offline prediction studied in literature. In addition, we propose a novel EH-aware routing protocol, based on opportunistic relaying. This routing protocol is shown to have significant benefits in finding the best path with no prior knowledge of the topology and with minimal overhead, making it an efficient protocol for EH-WSNs.