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A Message-Passing Algorithm for Wireless Network Scheduling.

Ioannis Ch Paschalidis1, Fuzhuo Huang2, Wei Lai3

  • 1Department of Electrical and Computer Engineering, and Division of Systems Engineering, Boston University, 8 St. Mary's St., Boston, MA 02215, yannisp@bu.edu .

IEEE/ACM Transactions on Networking : a Joint Publication of the IEEE Communications Society, the IEEE Computer Society, and the ACM with Its Special Interest Group on Data Communication
|January 12, 2016
PubMed
Summary
This summary is machine-generated.

We developed a new distributed algorithm for wireless network scheduling, solving the Maximum Weighted Independent Set (MWIS) problem efficiently. This method provides optimal solutions for perfect graphs and demonstrates superior performance compared to existing approaches.

Keywords:
Wireless networksdistributed algorithmsgraph theorymaximum weighted independent set problemmessage-passingscheduling

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Area of Science:

  • Wireless communication networks
  • Distributed algorithms
  • Graph theory

Background:

  • Wireless network scheduling is crucial for managing interference and optimizing throughput.
  • Existing methods like Carrier Sense Multiple Access (CSMA) have limitations in complex interference scenarios.

Purpose of the Study:

  • To develop a novel, low-complexity, fully distributed algorithm for wireless network scheduling.
  • To address the Maximum Weighted Independent Set (MWIS) problem in wireless networks.
  • To achieve high-quality feasible solutions with local information.

Main Methods:

  • Formulating wireless scheduling as the Maximum Weighted Independent Set (MWIS) problem on a conflict graph.
  • Proposing a two-phase distributed algorithm based on message-passing.
  • Utilizing a gradient projection method to solve a novel, tight relaxation of the MWIS problem.
  • Constructing a feasible MWIS solution from the relaxed solution.

Main Results:

  • The algorithm guarantees optimal solutions for perfect graphs.
  • Demonstrates excellent performance in simulations compared to CSMA and other policies.
  • The proposed relaxation is tighter than standard linear programming relaxations.

Conclusions:

  • The novel distributed algorithm offers an efficient and effective solution for wireless network scheduling.
  • The method's reliance on local information makes it suitable for fully distributed implementations.
  • The algorithm's optimality for perfect graphs and strong simulation results highlight its practical applicability.