Mobile Lightweight Wireless Systems. First International ICST Conference, MOBILIGHT 2009, Athens, Greece, May 18-20, 2009, Revised Selected Papers

Research Article

Multicost Energy-Aware Broadcasting in Wireless Networks with Distributed Considerations

Download101 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-03819-8_32,
        author={Christos Papageorgiou and Panagiotis Kokkinos and Emmanouel Varvarigos},
        title={Multicost Energy-Aware Broadcasting in Wireless Networks with Distributed Considerations},
        proceedings={Mobile Lightweight Wireless Systems. First International ICST Conference, MOBILIGHT 2009, Athens, Greece, May 18-20, 2009, Revised Selected Papers},
        proceedings_a={MOBILIGHT},
        year={2012},
        month={6},
        keywords={},
        doi={10.1007/978-3-642-03819-8_32}
    }
    
  • Christos Papageorgiou
    Panagiotis Kokkinos
    Emmanouel Varvarigos
    Year: 2012
    Multicost Energy-Aware Broadcasting in Wireless Networks with Distributed Considerations
    MOBILIGHT
    Springer
    DOI: 10.1007/978-3-642-03819-8_32
Christos Papageorgiou, Panagiotis Kokkinos, Emmanouel Varvarigos

    Abstract

    In this paper we propose an energy-aware broadcast algorithm for wireless networks. Our algorithm is based on the multicost approach and selects the set of nodes that by transmitting implement broadcasting in an optimally energy-efficient way. The energy-related parameters taken into account are the node transmission power and the node residual energy. The algorithm’s complexity however is non-polynomial, and therefore, we propose a relaxation producing a near-optimal solution in polynomial time. We also consider a distributed information exchange scheme that can be coupled with the proposed algorithms and examine the overhead introduced by this integration. Using simulations we show that the proposed algorithms outperform other solutions in the literature in terms of energy efficiency. Moreover, it is shown that the near-optimal algorithm obtains most of the performance benefits of the optimal algorithm at a smaller computational overhead.