Abstract—Reliable flooding in wireless sensor networks (WSNs) is desirable for a broad range of applications and net-work operations, and has been extensively investigated. However, relatively little work has been done for reliable flooding in low-duty-cycle WSNs with unreliable wireless links. It is a challenging problem to efficiently ensure 100 % flooding coverage considering the combined effects of low-duty-cycle operation and unreliable wireless transmission. In this work, we propose a novel dynamic switching-based reliable flooding (DSRF) framework, which is designed as an enhancement layer to provide efficient and reliable delivery for a variety of existing flooding tree structures in low-duty-cycle WSNs. The key novelty of DSRF lies in the dynamic switching decision making when encountering a transmission failure, where a flooding tree structure is dynamically adjusted based on the packet reception results for energy saving and delay reduction. DSRF is distinctive from existing works in that it explores both poor links and good links on demand. Through comprehensive performance comparisons, we demonstrate that, compared with the flooding protocol without DSRF enhancement, DSRF effectively reduces the flooding delay and the total number of packet transmission by 12 % 25 % and 10 % 15%, respectively. Remarkably, the achieved performance is close to the theoretical lower bound. I.

Abstract—For low-duty-cycle wireless sensor networks, mul-tihop broadcasting is a challenging problem, since every node has its own working schedules. In this paper, we design a novel broadcasting algorithm, of which key idea is to let some early wake-up nodes postpone their wake-up slots to overhear broadcasting message from its neighbors. This design utilizes the spatiotemporal locality of broadcasting to reduce the number of transmissions. We show that to find the broadcasting schedule with minimal latency and optimized total energy consumption is NP-hard, and then design an approximation algorithm that can guarantee the optimality of broadcasting latency and achieve a polylogarithmic approximation ratio for total energy consumption. Compared with the traditional solution, extensive experimental results show that our algorith-m achieves the minimal broadcasting latency while reducing energy consumption significantly. Keywords-low-duty-cycle WSNs; broadcast scheduling; ener-gy efficient; minimal latency I.