4th International IEEE Conference on Broadband Communications, Networks, Systems

Research Article

Energy-aware Scheduling with Deadline and Reliability Constraints in Wireless Networks

  • @INPROCEEDINGS{10.1109/BROADNETS.2007.4550411,
        author={G. Sudha Anil Kumar and G. Manimaran and Z. Wang},
        title={Energy-aware Scheduling with Deadline and Reliability Constraints in Wireless Networks},
        proceedings={4th International IEEE Conference on Broadband Communications, Networks, Systems},
        proceedings_a={BROADNETS},
        year={2008},
        month={6},
        keywords={Access protocols  Computer network reliability  Energy consumption  Processor scheduling  Resource management  Scheduling algorithm  Streaming media  Throughput  Wireless application protocol  Wireless networks},
        doi={10.1109/BROADNETS.2007.4550411}
    }
    
  • G. Sudha Anil Kumar
    G. Manimaran
    Z. Wang
    Year: 2008
    Energy-aware Scheduling with Deadline and Reliability Constraints in Wireless Networks
    BROADNETS
    IEEE
    DOI: 10.1109/BROADNETS.2007.4550411
G. Sudha Anil Kumar1,*, G. Manimaran1,*, Z. Wang1,*
  • 1: Real-Time Computing and Networking Laboratory Dept. of Electrical and Computer Engineering Iowa State University, Ames, IA 50011
*Contact email: anil@iastate.edu, gmani@iastate.edu, zhengdao@iastate.edu

Abstract

In this paper, we address the problem of scheduling a set of periodic real-time messages in a wireless network with the objective of minimizing the total energy consumption while meeting deadline and reliability constraints. We formally prove that this problem is NP-hard and solve it in two stages. First, we consider a simple model that assumes that the wireless channel is completely reliable and the network is fully provisioned. Using the technique of employing multiple hop-by-hop transmissions instead of a single direct hop transmission as the basis, we prove that the strategy of choosing the hop distances such that they are equidistant is optimal in terms of energy consumption under the deadline constraint. Based on the intuition provided by the optimal strategy, we present heuristic scheduling algorithms for a more realistic wireless channel model and network condition. Our simulation results show that the proposed scheduling algorithms provide significant energy savings over the baseline algorithms.