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ABSTRACT: We investigate the tradeoff between two mutually conflicting performance objectives-throughput and delay-for fast, periodic data collection in tree-based sensor networks arbitrarily deployed in 2-D. Two primary factors that affect the data collection rate (throughput) and timeliness (delay) are: 1) efficiency of the link scheduling protocol, and 2) 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 Bounded-Degree Minimum-Radius Spanning Tree, with the radius of the tree at most β times the minimum possible radius for a given degree bound Δ<sup>*</sup>, and the degree of any node at most Δ<sup>*</sup> + 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 multichannel 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.
IEEE/ACM Transactions on Networking 01/2012; · 2.03 Impact Factor
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ABSTRACT: We study the effect of routing topologies on maximizing the aggregated data collection rate and minimizing the maximum packet delay in TDMA-based sensor networks. We propose a bi-criteria formulation to the optimal routing tree construction problem, and show that a tree with bounded node degree and minimum radius can achieve the best trade-off between the data collection rate and packet delays.
INFOCOM IEEE Conference on Computer Communications Workshops , 2010; 04/2010
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ABSTRACT: Fast and periodic collection of aggregated data is of considerable interest for mission-critical and continuous monitoring applications in sensor networks. In the many-to-one communication paradigm known as convergecast, we consider scenarios where data packets are aggregated at each hop en route to a sink node along a tree-based routing topology and focus on maximizing the data collection rate at the sink by employing TDMA scheduling and multiple frequency channels. Our key result in the paper lies in proving that minimizing the schedule length for an arbitrary network in the presence of multiple frequencies is NP-hard, and in designing approximation algorithms with worst-case provable performance guarantees for geometric networks. In particular, we design a constant factor approximation for networks modeled as unit disk graphs (UDG) where every node has a uniform transmission range, and a O(Delta(T)log n) approximation for general disk graphs where nodes have different transmission ranges; n is the number of nodes in the network and Delta(T) is the maximum node degree on a given routing tree T. We also prove that a constant factor approximation is achievable on UDG even for unknown routing topologies so long as the maximum node degree in the tree is bounded by a constant. We also show that finding the minimum number of frequencies required to remove all the interfering links in an arbitrary network in NP-hard. We give an upper bound on the maximum number of such frequencies required and propose a polynomial time algorithm that minimizes the schedule length under this scenario. Finally, we evaluate our algorithms through simulations and show various trends in performance for different network parameters.
Mobile Adhoc and Sensor Systems, 2009. MASS '09. IEEE 6th International Conference on; 11/2009
