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A Branch-and-Bound Algorithm for Building Optimal Data Gathering Tree in Wireless Sensor Networks

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  • Xiaojun Zhu

    (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China; and Key Laboratory of Safety-Critical Software (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology, China)

  • Shaojie Tang

    (Naveen Jindal School of Management, University of Texas at Dallas, Richardson, TX 75080)

Abstract

In this paper, we consider the maximum lifetime data gathering tree (MLDT) problem in sensor networks. A data gathering tree is a spanning tree rooted at a specified sink so that every node can send its messages to the sink along the tree. The lifetime of a tree is defined as the minimum lifetime among nodes where each node’s lifetime is determined by its initial energy and transmission load. The MLDT problem is NP-hard, and the state-of-the-art solution formulates a decision version of the problem as an integer linear program (ILP) and then solves it by conducting binary search over all possible lifetimes. In this paper, we first give an ILP for the optimization problem rather than its decision version, and then show that using ILP solvers to solve these programs could be highly inefficient. We then propose a branch-and-bound algorithm that incorporates two novel features. First, the bounding method takes into account integer flows, and contains a new set of constraints. Second, a special set of edges are deleted to reduce the number of subproblems generated by the branching process. Numerical simulations on randomly generated networks show that the proposed algorithm outperforms existing algorithms in terms of the number of solved problem instances in a fixed amount of time. Summary of Contribution : We study the maximum lifetime data gathering tree (MLDT) problem in the context of wireless sensor network. MLDT is a fundamental problem in both computer science and operations research. Since sensor nodes are often resource limited, the data gathering tree must be carefully constructed to prolong the network lifetime. In this paper, we first give an integer linear program for the optimization problem rather than its decision version, and then show that using ILP solvers to solve these programs could be highly inefficient. We then propose a branch and bound algorithm that incorporates two novel features.

Suggested Citation

  • Xiaojun Zhu & Shaojie Tang, 2021. "A Branch-and-Bound Algorithm for Building Optimal Data Gathering Tree in Wireless Sensor Networks," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1446-1460, October.
    • Handle: RePEc:inm:orijoc:v:33:y:2021:i:4:p:1446-1460
    DOI: 10.1287/ijoc.2020.1012
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    References listed on IDEAS

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    1. Luis Gouveia, 1995. "A 2n Constraint Formulation for the Capacitated Minimal Spanning Tree Problem," Operations Research, INFORMS, vol. 43(1), pages 130-141, February.
    2. M. Kritikos & G. Ioannou, 2017. "A greedy heuristic for the capacitated minimum spanning tree problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1223-1235, October.
    3. Gouveia, Luis & Joao Lopes, Maria, 2005. "The capacitated minimum spanning tree problem: On improved multistar constraints," European Journal of Operational Research, Elsevier, vol. 160(1), pages 47-62, January.
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    Cited by:

    1. Marco Casazza & Alberto Ceselli, 2022. "Exact Algorithms for Maximum Lifetime Data-Gathering Tree in Wireless Sensor Networks," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1987-2002, July.

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