Critical-Path Aware Scheduling for Latency Efficient Broadcast in Duty-Cycled Wireless Sensor Networks

Minimum latency scheduling has arisen as one of the most crucial problems for broadcasting in duty-cycled Wireless Sensor Networks (WSNs). Typical solutions for the broadcast scheduling iteratively search for nodes able to transmit a message simultaneously. Other nodes are prevented from transmissions to ensure that there is no collision in a network. Such collision-preventions result in extra delays for a broadcast and may increase overall latency if the delays occur along critical paths of the network. To facilitate the broadcast latency minimization, we propose a novel approach, critical-path aware scheduling (CAS), which schedules transmissions with a preference of nodes in critical paths of a duty-cycled WSN. This paper presents two schemes employing CAS which produce collision-free and collision-tolerant broadcast schedules, respectively. The collision-free CAS scheme guarantees an approximation ratio of in terms of latency, where denotes the maximum node degree in a network. By allowing collision at noncritical nodes, the collision-tolerant CAS scheme reduces up to 10.2 percent broadcast latency compared with the collision-free ones while requiring additional transmissions for the noncritical nodes experiencing collisions. Simulation results show that broadcast latencies of the two proposed schemes are significantly shorter than those of the existing methods

A distributed delay-efficient data aggregation scheduling for duty-cycled WSNs

With the growing interest in wireless sensor networks (WSNs), minimizing network delay and maximizing sensor (node) lifetime are important challenges. Since the sensor battery is one of the most precious resources in a WSN, efficient utilization of the energy to prolong the network lifetime has been the focus of much of the research on WSNs. For that reason, many previous research efforts have tried to achieve tradeoffs in terms of network delay and energy cost for such data aggregation tasks. Recently, duty-cycling technique, i.e., periodically switching ON and OFF communication and sensing capabilities, has been considered to significantly reduce the active time of sensor nodes and thus extend network lifetime. However, this technique causes challenges for data aggregation. In this paper, we present a distributed approach, named distributed delay efficient data aggregation scheduling (DEDAS-D) to solve the aggregation-scheduling problem in duty-cycled WSNs. The analysis indicates that our solution is a better approach to solve this problem. We conduct extensive simulations to corroborate our analysis and show that DEDAS-D outperforms other distributed schemes and achieves an asymptotic performance compared with centralized scheme in terms of data aggregation delay.N/

Minimum Energy Broadcast in Duty Cycled Wireless Sensor Networks

We study the problem of finding a minimum energy broadcast tree in duty cycled wireless sensor networks. In such networks, every node has a wakeup schedule and is awake and ready to receive packets or transmit in certain time slots during the schedule and asleep during the rest of the schedule. We assume that a forwarding node needs to stay awake to forward a packet to the next hop neighbor until the neighbor is awake. The minimum energy broadcast tree minimizes the number of additional time units that nodes have to stay awake in order to accomplish broadcast. We show that finding the minimum energy broadcast tree is NP-hard. We give two algorithms for finding energy-efficient broadcast trees in such networks. We performed extensive simulations to study the performance of these algorithms and compare them with previously proposed algorithms. Our results show that our algorithms exhibit the best performance in terms of average number of additional time units a node needs to be awake, as well as in terms of the smallest number of highly loaded nodes, while being competitive with previous algorithms in terms of the total number of transmissions and delay