TY - GEN
T1 - Leveraging load migration and basestaion consolidation for green communications in virtualized Cognitive Radio Networks
AU - Sheng, Xiang
AU - Tang, Jian
AU - Gao, Chenfei
AU - Zhang, Weiyi
AU - Wang, Chonggang
PY - 2013
Y1 - 2013
N2 - With wireless resource virtualization, multiple Mobile Virtual Network Operators (MVNOs) can be supported over a shared physical wireless network and traffic loads in a Base Station (BS) can be easily migrated to more power-efficient BSs in its neighborhood such that idle BSs can be turned off or put into sleep to save power. In this paper, we propose to leverage load migration and BS consolidation for green communications and consider a power-efficient network planning problem in virtualized Cognitive Radio Networks (CRNs) with the objective of minimizing total power consumption while meeting traffic load demand of each MVNO. First, we present a Mixed Integer Linear Programming (MILP) to provide optimal solutions. Then we present a general optimization framework to guide algorithm design, which solves two subproblems, channel assignment and load allocation, in sequence. For channel assignment, we present a (1/Δ)-approximation algorithm (where Δ is the maximum number of BSs a BS can potentially interfere with). For load allocation, we present a polynomial-time optimal algorithm for a special case where BSs are power-proportional as well as two effective heuristic algorithms for the general case. In addition, we present an effective heuristic algorithm that jointly solves the two subproblems. It has been shown by extensive simulation results that the proposed algorithms produce close-to-optimal solutions, and moreover, achieve over 45% power savings compared to a baseline algorithm that does not migrate loads or consolidate BSs.
AB - With wireless resource virtualization, multiple Mobile Virtual Network Operators (MVNOs) can be supported over a shared physical wireless network and traffic loads in a Base Station (BS) can be easily migrated to more power-efficient BSs in its neighborhood such that idle BSs can be turned off or put into sleep to save power. In this paper, we propose to leverage load migration and BS consolidation for green communications and consider a power-efficient network planning problem in virtualized Cognitive Radio Networks (CRNs) with the objective of minimizing total power consumption while meeting traffic load demand of each MVNO. First, we present a Mixed Integer Linear Programming (MILP) to provide optimal solutions. Then we present a general optimization framework to guide algorithm design, which solves two subproblems, channel assignment and load allocation, in sequence. For channel assignment, we present a (1/Δ)-approximation algorithm (where Δ is the maximum number of BSs a BS can potentially interfere with). For load allocation, we present a polynomial-time optimal algorithm for a special case where BSs are power-proportional as well as two effective heuristic algorithms for the general case. In addition, we present an effective heuristic algorithm that jointly solves the two subproblems. It has been shown by extensive simulation results that the proposed algorithms produce close-to-optimal solutions, and moreover, achieve over 45% power savings compared to a baseline algorithm that does not migrate loads or consolidate BSs.
KW - Green wireless communications
KW - basestation consolidation
KW - cognitive radio
KW - load migration
KW - virtualization
UR - http://www.scopus.com/inward/record.url?scp=84883105580&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883105580&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2013.6566919
DO - 10.1109/INFCOM.2013.6566919
M3 - Conference contribution
AN - SCOPUS:84883105580
SN - 9781467359467
T3 - Proceedings - IEEE INFOCOM
SP - 1267
EP - 1275
BT - 2013 Proceedings IEEE INFOCOM 2013
T2 - 32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013
Y2 - 14 April 2013 through 19 April 2013
ER -