TY - GEN
T1 - Energy and traffic aware dynamic topology management for wireless cellular networks
AU - Jung, Hyun Sik
AU - Roh, Hee Tae
AU - Lee, Jang Won
PY - 2012
Y1 - 2012
N2 - In this paper, we study a dynamic topology management problem in the wireless cellular network, in which base stations can be switched on or off to save energy consumption of the network. To model non-uniform traffic demand over the network, we divide the entire network area into subareas, assuming that each of subareas has its own traffic demand, which can be satisfied by allocating enough bandwidth and power from a base station. With this network model, we propose a two-step algorithm for dynamic topology management. In the first step, we obtain the maximum radius of the service area for each base station by solving an optimization problem. In the second step, we first construct a graph based on the maximum radii obtained in the first step. We then identify the minimal set of base stations that should be switched on to satisfy the demand of each subarea in the network based on the shortest path algorithm on the constructed graph. From numerical results, we show that our algorithm provides a significant amount of energy saving, while adaptively considering the traffic demand of each subarea in the network.
AB - In this paper, we study a dynamic topology management problem in the wireless cellular network, in which base stations can be switched on or off to save energy consumption of the network. To model non-uniform traffic demand over the network, we divide the entire network area into subareas, assuming that each of subareas has its own traffic demand, which can be satisfied by allocating enough bandwidth and power from a base station. With this network model, we propose a two-step algorithm for dynamic topology management. In the first step, we obtain the maximum radius of the service area for each base station by solving an optimization problem. In the second step, we first construct a graph based on the maximum radii obtained in the first step. We then identify the minimal set of base stations that should be switched on to satisfy the demand of each subarea in the network based on the shortest path algorithm on the constructed graph. From numerical results, we show that our algorithm provides a significant amount of energy saving, while adaptively considering the traffic demand of each subarea in the network.
UR - http://www.scopus.com/inward/record.url?scp=84873539954&partnerID=8YFLogxK
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U2 - 10.1109/ICCS.2012.6406139
DO - 10.1109/ICCS.2012.6406139
M3 - Conference contribution
AN - SCOPUS:84873539954
SN - 9781467320542
T3 - 2012 IEEE International Conference on Communication Systems, ICCS 2012
SP - 205
EP - 209
BT - 2012 IEEE International Conference on Communication Systems, ICCS 2012
T2 - 2012 IEEE International Conference on Communication Systems, ICCS 2012
Y2 - 21 November 2012 through 23 November 2012
ER -