5th International Workshop on Resource Allocation, Cooperation and Competition in Wireless Networks

Research Article

Network Coding For Data Dissemination: It Is Not What You Know, But What Your Neighbors Don’t Know

  • @INPROCEEDINGS{10.1109/WIOPT.2009.5291585,
        author={Daniel E. Lucani and Frank H.P. Fitzek and Muriel M´edard and Milica Stojanovic},
        title={Network Coding For Data Dissemination: It Is Not What You Know, But What Your Neighbors Don’t Know},
        proceedings={5th International Workshop on Resource Allocation, Cooperation and Competition in Wireless Networks},
        publisher={IEEE},
        proceedings_a={RAWNET / WNC3},
        year={2009},
        month={10},
        keywords={},
        doi={10.1109/WIOPT.2009.5291585}
    }
    
  • Daniel E. Lucani
    Frank H.P. Fitzek
    Muriel M´edard
    Milica Stojanovic
    Year: 2009
    Network Coding For Data Dissemination: It Is Not What You Know, But What Your Neighbors Don’t Know
    RAWNET / WNC3
    IEEE
    DOI: 10.1109/WIOPT.2009.5291585
Daniel E. Lucani1,*, Frank H.P. Fitzek2,*, Muriel M´edard1,*, Milica Stojanovic3,*
  • 1: RLE, MIT Cambridge, Massachusetts, USA
  • 2: Aalborg University Aalborg, Denmark
  • 3: Northeastern University Boston, Massachusetts, USA
*Contact email: dlucani@mit.edu, ff@es.aau.dk, medard@mit.edu, millitsa@mit.edu

Abstract

We propose a linear network coding scheme to disseminate a finite number of data packets in arbitrary networks. The setup assumes a packet erasure channel, slotted time, and that nodes cannot transmit and receive information simultaneously. The dissemination process is completed when all terminals can decode the original data packets. We also assume a perfect knowledge of the information at each of the nodes, but not necessarily a perfect knowledge of the channel. A centralized controller decides which nodes should transmit, to what set of receiver nodes, and what information should be broadcasted. We show that the problem can be thought of as a scheduling problem, which is hard to solve. Thus, we consider the use of a greedy algorithm that only takes into account the current state of the system to make a decision. The proposed algorithm tries to maximize the impact on the network at each slot, i.e. maximize the number of nodes that will benefit from the coded packet sent by each active transmitter. We show that our scheme is considerably better, in terms of the number of slots to complete transmission, than schemes that choose the node with more information as the transmitter at every time slot.