Real-time Data Collection Scheduling in Multi-hop Wireless Sensor Networks

TL;DR

This paper addresses real-time data collection in multihop wireless sensor networks by proposing schedulability conditions and algorithms that optimize routing, link, and packet scheduling to meet end-to-end delays.

Contribution

It introduces nearly optimal schedulability conditions and a family of algorithms for real-time data collection, including overload management, in WSNs.

Findings

Algorithms achieve a constant fraction of maximum schedulable load.

Proposed conditions are nearly tight and necessary for schedulability.

Simulation results validate theoretical analysis.

Abstract

We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be collected to the control center within a certain end-to-end delay. We first propose almost-tight necessary conditions for a set of different queries to be schedulable by a WSN. We then develop a family of efficient and effective data collection algorithms that can meet the real-time requirement under resource constraints by addressing three tightly coupled tasks: (1) routing tree construction for data collection, (2) link activity scheduling, and (3) packet-level scheduling. Our theoretical analysis for the schedulability of these algorithms show that they can achieve a constant fraction of the maximum schedulable load. For the case of overloaded networks where not all queries can be possibly satisfied, we propose an efficient approximation algorithm to select queries to maximize the total weight of selected schedulable queries. The simulations corroborate our theoretical analysis.