TY - GEN
T1 - Exploiting geometry in the SINRk model
AU - Aschner, Rom
AU - Citovsky, Gui
AU - Katz, Matthew J.
N1 - Funding Information: Work by R. Aschner was partially supported by the Lynn and William Frankel Center for Computer Sciences. Work by R. Aschner, G. Citovsky, and M. Katz was partially supported by grant 2010074 from the United States – Israel Binational Science Foundation. Work by M. Katz was partially supported by grant 1045/10 from the Israel Science Foundation. Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2015.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - We introduce the SINRk model, which is a practical version of the SINR model. In the SINRk model, in order to determine whether s’s signal is received at c, where s is a sender and c is a receiver, one only considers the k most significant senders w.r.t. to c (other than s). Assuming uniform power, these are the k closest senders to c (other than s). Under this model, we consider the well-studied scheduling problem: Given a set L of sender-receiver requests, find a partition of L into a minimum number of subsets (rounds), such that in each subset all requests can be satisfied simultaneously. We present an O(1)- approximation algorithm for the scheduling problem (under the SINRk model). For comparison, the best known approximation ratio under the SINR model is O(log n). We also present an O(1)-approximation algorithm for the maximum capacity problem (i.e., for the single round problem), obtaining a constant of approximation which is considerably better than those obtained under the SINR model. Finally, for the special case where k = 1, we present a PTAS for the maximum capacity problem. Our algorithms are based on geometric analysis of the SINRk model.
AB - We introduce the SINRk model, which is a practical version of the SINR model. In the SINRk model, in order to determine whether s’s signal is received at c, where s is a sender and c is a receiver, one only considers the k most significant senders w.r.t. to c (other than s). Assuming uniform power, these are the k closest senders to c (other than s). Under this model, we consider the well-studied scheduling problem: Given a set L of sender-receiver requests, find a partition of L into a minimum number of subsets (rounds), such that in each subset all requests can be satisfied simultaneously. We present an O(1)- approximation algorithm for the scheduling problem (under the SINRk model). For comparison, the best known approximation ratio under the SINR model is O(log n). We also present an O(1)-approximation algorithm for the maximum capacity problem (i.e., for the single round problem), obtaining a constant of approximation which is considerably better than those obtained under the SINR model. Finally, for the special case where k = 1, we present a PTAS for the maximum capacity problem. Our algorithms are based on geometric analysis of the SINRk model.
UR - http://www.scopus.com/inward/record.url?scp=84927782200&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-662-46018-4_8
DO - https://doi.org/10.1007/978-3-662-46018-4_8
M3 - Conference contribution
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 125
EP - 135
BT - Algorithms for Sensor Systems - 10th International Symposium on Algorithms and Experiments for Sensor Systems, Wireless Networks and Distributed Robotics, ALGOSENSORS 2014, Revised Selected Papers
A2 - Gao, Jie
A2 - Efrat, Alon
A2 - Fekete, Sándor P.
A2 - Zhang, Yanyong
PB - Springer Verlag
T2 - 10th International Symposium on Algorithms and Experiments for Sensor Systems, Wireless Networks and Distributed Robotics, ALGOSENSORS 2014
Y2 - 12 September 2014 through 12 September 2014
ER -