TY - JOUR
T1 - Location-aided routing with uncertainty in mobile ad hoc networks
T2 - A stochastic semidefinite programming approach
AU - Zhu, Yuntao
AU - Zhang, Junshan
AU - Partel, Kautilya
N1 - Funding Information:
The work of the first author was partially supported by ASU West MGIA and SRCA grants. The authors would also like to thank reviewers for their insightful comments.
PY - 2011/6
Y1 - 2011/6
N2 - We study location-aided routing under mobility in wireless ad hoc networks. Due to node mobility, the network topology changes continuously, and clearly there exists an intricate tradeoff between the message passing overhead and the latency in the route discovery process. Aiming to obtain a clear understanding of this tradeoff, we use stochastic semidefinite programming (SSDP), a newly developed optimization model, to deal with the location uncertainty associated with node mobility. In particular, we model both the speed and the direction of node movement by random variables and construct random ellipses accordingly to better capture the location uncertainty and the heterogeneity across different nodes. Based on SSDP, we propose a stochastic location-aided routing (SLAR) strategy to optimize the tradeoff between the message passing overhead and the latency. Our results reveal that in general SLAR can significantly reduce the overall overhead than existing deterministic algorithms, simply because the location uncertainty in the routing problem is better captured by the SSDP model.
AB - We study location-aided routing under mobility in wireless ad hoc networks. Due to node mobility, the network topology changes continuously, and clearly there exists an intricate tradeoff between the message passing overhead and the latency in the route discovery process. Aiming to obtain a clear understanding of this tradeoff, we use stochastic semidefinite programming (SSDP), a newly developed optimization model, to deal with the location uncertainty associated with node mobility. In particular, we model both the speed and the direction of node movement by random variables and construct random ellipses accordingly to better capture the location uncertainty and the heterogeneity across different nodes. Based on SSDP, we propose a stochastic location-aided routing (SLAR) strategy to optimize the tradeoff between the message passing overhead and the latency. Our results reveal that in general SLAR can significantly reduce the overall overhead than existing deterministic algorithms, simply because the location uncertainty in the routing problem is better captured by the SSDP model.
KW - Mobile ad hoc networks
KW - Routing
KW - Stochastic programming
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U2 - 10.1016/j.mcm.2010.08.025
DO - 10.1016/j.mcm.2010.08.025
M3 - Article
AN - SCOPUS:79953108361
SN - 0895-7177
VL - 53
SP - 2192
EP - 2203
JO - Mathematical and Computer Modelling
JF - Mathematical and Computer Modelling
IS - 11-12
ER -