TY - GEN
T1 - GMP
T2 - 26th IEEE Internationa26th IEEE International Conference on Distributed Computing Systems, ICDCS 2006
AU - Wu, Shibo
AU - Candan, Kasim
PY - 2006/12/1
Y1 - 2006/12/1
N2 - In this paper, we propose a novel Geographic Multicast routing Protocol (GMP) for wireless sensor networks1. The proposed protocol is fully distributed and stateless. Given a set of the destinations, the transmitting node first constructs a virtual Euclidean Steiner tree rooted at itself and including the destinations, using a novel and highly efficient reduction ratio heuristic (called rrSTR). Based on this locally computed tree and the information regarding the locations of its immediate neighbors, the transmitting node then splits the destinations into a set of groups and calculates a next hop for each of these groups. A copy of the packet and the locations of the corresponding group of destination nodes are directed towards the corresponding hop. The simulation results on NS2 show that the average per-destination hop count obtained using GMP is comparable to the existing PBM [21] algorithm and significantly less than obtained by using LGS [5]. Most significantly, GMP requires 25% less hops and energy than alternative algorithms.
AB - In this paper, we propose a novel Geographic Multicast routing Protocol (GMP) for wireless sensor networks1. The proposed protocol is fully distributed and stateless. Given a set of the destinations, the transmitting node first constructs a virtual Euclidean Steiner tree rooted at itself and including the destinations, using a novel and highly efficient reduction ratio heuristic (called rrSTR). Based on this locally computed tree and the information regarding the locations of its immediate neighbors, the transmitting node then splits the destinations into a set of groups and calculates a next hop for each of these groups. A copy of the packet and the locations of the corresponding group of destination nodes are directed towards the corresponding hop. The simulation results on NS2 show that the average per-destination hop count obtained using GMP is comparable to the existing PBM [21] algorithm and significantly less than obtained by using LGS [5]. Most significantly, GMP requires 25% less hops and energy than alternative algorithms.
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U2 - 10.1109/ICDCS.2006.44
DO - 10.1109/ICDCS.2006.44
M3 - Conference contribution
AN - SCOPUS:33947649004
SN - 0769525407
SN - 9780769525402
T3 - Proceedings - International Conference on Distributed Computing Systems
BT - 26th IEEE Internationa26th IEEE International Conference on Distributed Computing Systems, ICDCS 2006
Y2 - 4 July 2006 through 7 July 2006
ER -