Exploiting slack time for just-in-time scheduling in wireless sensor networks

Abstract

We consider the problem of real-time data collection in wireless sensor networks, in which data need to be delivered to one or more sinks within end-to-end deadlines. To enhance performance with respect to end-to-end deadline miss ratio, existing approaches schedule packets by prioritizing them based on per-packet deadlines and other factors such as the distance to the sink. However, important factors affecting the end-to-end performance such as queuing delays and buffer overruns have largely been ignored in the existing real-time schemes. Packet prioritization by itself cannot assist with these issues, and may in fact, exacerbate them for real-time data collection, since many high priority packets may simultaneously contend for the constrained network resources. In sensor networks, where the channel bandwidth and buffer space are often quite limited, these issues can dramatically impact real-time performance. Based on this observation, we propose Just-in-Time Scheduling (JiTS) strategies where packets are judiciously delayed within their slack time to reduce contention and load balance the use of the network buffers. We explore several policies for delaying data packets at different intermediate nodes considering potential contention. In addition, we also show that the routing protocol has a significant impact on real-time performance. In particular, shortest path routing leads to considerably better performance than geographic forwarding, which is often used for real-time data transmission in wireless sensor networks. Using an extensive simulation study, we demonstrate that JiTS can significantly improve the deadline miss ratio and packet drop ratio compared to two state-of-the-art approaches for real-time packet delivery for sensor networks (RAP and SPEED) under various scenarios. Notably, JiTS requires neither lower layer (e.g., MAC layer) support nor synchronization among the sensor nodes.