Energy-Adaptive and Bottleneck-Aware Many-to-Many Communication Scheduling for Battery-Free WSNs

Battery-free wireless sensor networks (BF-WSNs) have captured the interest of research community in recent years. Compared with traditional battery-powered WSNs (BP-WSNs), BF-WSNs can prolong the lifetime of the network by exploiting ambient energy. Many-to-many communication is widely used in many applications of WSNs and the problem of minimum-latency many-to-many communication scheduling in BF-WSNs is of great significance. However, this problem has not been studied yet. The existing algorithms for BP-WSNs and BF-WSNs are not suitable for minimum-latency many-to-many scheduling problem in BF-WSNs. Also, different from BP-WSNs, energy-bottleneck nodes with low recharge rate and high workload in BF-WSNs make the problem more challenging. To address these issues, in this article, we first study the problem of many-to-many scheduling in BF-WSNs with the purpose of minimizing communication latency. The problem is formally defined and proved to be NP-hard. The energy-adaptive and bottleneck-aware scheduling algorithm for many to many in BF-WSNs is proposed. The correctness and average latency of the proposed algorithm are carefully analyzed. Extensive simulations show that our algorithm has high performance, in terms of communication latency and energy usage ratio. Furthermore, we also extend the proposed algorithm to other network models.

Automated summary

Battery-free wireless sensor networks have attracted research interest due to their ability to prolong network lifetime through ambient energy exploitation. However, the minimum-latency many-to-many communication scheduling problem in BF-WSNs has not been studied. This article proposes an energy-adaptive and bottleneck-aware scheduling algorithm for BF-WSNs, which is shown to have high performance through extensive simulations.