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

机译:利用空闲时间进行无线传感器网络中的即时调度

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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.
机译:我们考虑了无线传感器网络中实时数据收集的问题,其中数据需要在端到端的期限内传递到一个或多个接收器。为了提高端到端截止期限丢失率的性能,现有方法通过基于每个分组截止期限和其他因素(例如到接收器的距离)对分组进行优先级调度来调度分组。但是,在现有的实时方案中,影响端到端性能的重要因素(例如排队延迟和缓冲区溢出)已被很大程度上忽略。数据包优先级本身不能解决这些问题,并且实际上可能加剧它们的实时数据收集,因为许多高优先级数据包可能同时争夺受限的网络资源。在传感器网络中,通道带宽和缓冲区空间通常非常有限,这些问题会极大地影响实时性能。基于此观察结果,我们提出了即时调度(JiTS)策略,在该策略中,应明智地将数据包在其空闲时间内延迟,以减少争用并平衡使用网络缓冲区的负载。考虑潜在的争用,我们探索了几种在不同的中间节点延迟数据包的策略。此外,我们还显示了路由协议对实时性能有重大影响。特别是,最短路径路由可比地理转发带来更好的性能,后者通常用于无线传感器网络中的实时数据传输。通过广泛的仿真研究,我们证明,与在各种情况下针对传感器网络(RAP和SPEED)进行实时数据包传递的两种最新方法相比,JiTS可以显着提高截止日期未命中率和数据包丢弃率。值得注意的是,JiTS既不需要较低层(例如,MAC层)的支持,也不需要传感器节点之间的同步。

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