Wsn Network
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Multi-Channel Scheduling and Spanning Trees: Throughput-Delay Trade-off for Fast Data Collection in Sensor Networks
¨ Amitabha Ghosh, Ozlem Durmaz Incel, V. S. Anil Kumar, and Bhaskar Krishnamachari
Two primary factors that affect the data collection rate (throughput) and timeliness (delay) are: (i) efficiency of the link scheduling protocol, and (ii) structure of the routing tree in terms of its node degrees and radius. In this paper, we utilize multiple frequency channels and design an efficient link scheduling protocol that gives a constant factor approximation on the optimal throughput in delivering aggregated data from all the nodes to the sink. To minimize the maximum delay subject to a given throughput bound, we also design an (α, β)bicriteria approximation algorithm to construct a BoundedDegree Minimum-Radius Spanning Tree, with the radius of the tree at most β times the minimum possible radius for a given degree bound ∆∗ , and the degree of any node at most ∆∗ + α, where α and β are positive constants. Lastly, we evaluate the efficiency of our algorithms on different types of spanning trees, and show that multi-channel scheduling, combined with optimal routing topologies, can achieve the best of both worlds in terms of maximizing the aggregated data collection rate and minimizing the maximum packet delay. Index Terms—Convergecast, TDMA scheduling, multiple channels, routing trees, approximation algorithms.
I. I NTRODUCTION ONVERGECAST, namely the many-to-one flow of data from a set of sources to a common sink over a tree-based routing topology, is a fundamental communication primitive in sensor networks. Such data flows can be triggered either by external events, such as user queries to periodically get a snapshot view of the network, or can be automated over long durations. For real-time, mission-critical, and high datarate applications [1]–[3], it is often critical to simultaneously maximize the data collection rate and minimize packet delays. In
Multi-Channel Scheduling and Spanning Trees: Throughput-Delay Trade-off for Fast Data Collection in Sensor Networks
¨ Amitabha Ghosh, Ozlem Durmaz Incel, V. S. Anil Kumar, and Bhaskar Krishnamachari
Two primary factors that affect the data collection rate (throughput) and timeliness (delay) are: (i) efficiency of the link scheduling protocol, and (ii) structure of the routing tree in terms of its node degrees and radius. In this paper, we utilize multiple frequency channels and design an efficient link scheduling protocol that gives a constant factor approximation on the optimal throughput in delivering aggregated data from all the nodes to the sink. To minimize the maximum delay subject to a given throughput bound, we also design an (α, β)bicriteria approximation algorithm to construct a BoundedDegree Minimum-Radius Spanning Tree, with the radius of the tree at most β times the minimum possible radius for a given degree bound ∆∗ , and the degree of any node at most ∆∗ + α, where α and β are positive constants. Lastly, we evaluate the efficiency of our algorithms on different types of spanning trees, and show that multi-channel scheduling, combined with optimal routing topologies, can achieve the best of both worlds in terms of maximizing the aggregated data collection rate and minimizing the maximum packet delay. Index Terms—Convergecast, TDMA scheduling, multiple channels, routing trees, approximation algorithms.
I. I NTRODUCTION ONVERGECAST, namely the many-to-one flow of data from a set of sources to a common sink over a tree-based routing topology, is a fundamental communication primitive in sensor networks. Such data flows can be triggered either by external events, such as user queries to periodically get a snapshot view of the network, or can be automated over long durations. For real-time, mission-critical, and high datarate applications [1]–[3], it is often critical to simultaneously maximize the data collection rate and minimize packet delays. In