TY - GEN
T1 - Connectivity problem in wireless networks
AU - Kowalski, Dariusz R.
AU - Rokicki, Mariusz A.
PY - 2010/12/13
Y1 - 2010/12/13
N2 - We study the complexity of the following connectivity problem in wireless networks: for a given placement of n nodes in the plane, the goal is to compute a channel and power assignment that forms strongly connected communication structure spanning all nodes. The complexity measure is the total number of assigned channels, and the goal is to minimize this number. We work with two signal inference models: Geometric Radio Networks (GRN) and Signal to Interference Plus Noise Ratio (SINR). We show a generic polynomial-time transformation from the wide class of separable assignments in GRN to assignments in the SIRN model. This transformation preserves asymptotic complexity, i.e., the number of channels used in the assignments. In this way we show an assignment, constructed in polynomial-time, guarantying connectivity in the SINR model by using only O(log n) channels, which is an improvement over the best previous result O(log2 n) presented in [21].
AB - We study the complexity of the following connectivity problem in wireless networks: for a given placement of n nodes in the plane, the goal is to compute a channel and power assignment that forms strongly connected communication structure spanning all nodes. The complexity measure is the total number of assigned channels, and the goal is to minimize this number. We work with two signal inference models: Geometric Radio Networks (GRN) and Signal to Interference Plus Noise Ratio (SINR). We show a generic polynomial-time transformation from the wide class of separable assignments in GRN to assignments in the SIRN model. This transformation preserves asymptotic complexity, i.e., the number of channels used in the assignments. In this way we show an assignment, constructed in polynomial-time, guarantying connectivity in the SINR model by using only O(log n) channels, which is an improvement over the best previous result O(log2 n) presented in [21].
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U2 - 10.1007/978-3-642-15763-9_32
DO - 10.1007/978-3-642-15763-9_32
M3 - Conference contribution
AN - SCOPUS:78649863855
SN - 3642157629
SN - 9783642157622
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 344
EP - 358
BT - Distributed Computing - 24th International Symposium, DISC 2010, Proceedings
T2 - 24th International Symposium on Distributed Computing, DISC 2010
Y2 - 13 September 2010 through 15 September 2010
ER -