Research on network coding aware energy efficient routing for wireless sensor networks

Abstract

Wireless sensor nodes in wireless sensor networks are generally battery powered and it is usually hard to change their batteries. Therefore, energy saving has always been the basic critical problem of wireless sensor networks. In recent years, network coding has become a promising technology to improve network throughput, reduce transmission number, and save energy, which has great potential to solve the energy efficiency problem of wireless sensor networks. In addition, some network coding aware routings have been proposed. However, the network coding condition of existing network coding aware routings may experience the problem of false-coding effect in some scenarios, and usually neglect node energy, which greatly influences the energy efficiency performance. Therefore, existing network coding aware routings are not suitable for wireless sensor networks. This paper proposes network coding aware energy efficient routing (NAER) for wireless sensor networks. In NAER, universal network coding condition is presented and proved to avoid false-coding problem. Besides, combined with the coverage control and topology control mechanism at lower layer, cross layer coding opportunity discover mechanism is presented to increase coding opportunities. In addition, a network coding aware energy efficient routing metric (NERM) is presented, which takes coding opportunity, node energy, and link quality into account jointly. Simulation results demonstrate that NAER improves the accuracy of coding discovery mechanism, increases the number of coding opportunities, saves node's energy consumption, and prolongs network lifetime.

Timely Data Delivery for Energy‐Harvesting IoT Devices

“…Such kinds of protocols can be found in Refs. [7–9]. Data delivery protocols for the battery‐free IoT or energy‐harvesting devices, however, are required to consider energy shortage problem because the devices usually harvest energy from unsteady or random sources such as radio frequency signals, wind, and more.…”

“…We have witnessed various energy-harvesting IoT devices. For example, the IoT devices harvest energy from sunlight [1] , radio frequency [2−5] , vibration [6] , and more. In fact, most energy-harvesting IoT devices face the problem of frequent energy shortage due to fluctuation in the harvested energy, especially in the case when the energy sources are random (e.g.…”