ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술지 A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks
Cited 25 time in scopus Download 0 time Share share facebook twitter linkedin kakaostory
조인휘, 김원태, 홍석준
IEICE Transactions on Communications, v.E91-B no.1, pp.314-317
일본, 전자정보통신학회 (IEICE)
07MW1400, 모바일 컨버전스 컴퓨팅을 위한 단말적응형 임베디드 운영체제 기술개발, 김흥남
In this paper, we propose a novel network selection algorithm considering power consumption in hybrid wireless networks for vertical handover. CDMA, WiBro, WLAN networks are candidate networks for this selection algorithm. This algorithm is composed of the power consumption prediction algorithm and the final network selection algorithm. The power consumption prediction algorithm estimates the expected lifetime of the mobile station based on the current battery level, traffic class and power consumption for each network interface card of the mobile station. If the expected lifetime of the mobile station in a certain network is not long enough compared the handover delay, this particular network will be removed from the candidate network list, thereby preventing unnecessary handovers in the preprocessing procedure. On the other hand, the final network selection algorithm consists of AHP (Analytic Hierarchical Process) and GRA (Grey Relational Analysis). The global factors of the network selection structure are QoS, cost and lifetime. If user preference is lifetime, our selection algorithm selects the network that offers longest service duration due to low power consumption. Also, we conduct some simulations using the OPNET simulation tool. The simulation results show that the proposed algorithm provides longer lifetime in the hybrid wireless network environment. Copyright © 2008 The Institute of Electronics, Information and Communication Engineers.
KSP 제안 키워드
Battery level, Expected lifetime, Grey relational Analysis, Handover delay, Information and communication, Mobile station(MS), Network Interface Card, Network selection algorithm, OPNet simulation, Power Consumption Prediction, Preprocessing procedure