TY - GEN
T1 - Context-awareness handoff planning in heterogeneous wireless networks
AU - Huang, Hsiao Yun
AU - Wang, Chiung Ying
AU - Hwang, Ren Hung
N1 - Funding Information:
The research is supported by the NSC97-2221-E-194-011-MY3,NSC97-2221-E-194-012-MY3,NSC97-2221-E-194-027-MY2, National Science Council, ROC.
PY - 2010
Y1 - 2010
N2 - This paper addresses a context-awareness handoff planning mechanism in heterogeneous wireless networks for seamless ubiquitous access. The proliferation of digital devices with communication capability heralds the era of ubiquitous computing, as predicted by Mark Weiser. Mobile devices with multi-mode interfaces can access heterogeneous wireless networks, such as wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX) network and third generation (3G) network. In heterogeneous wireless networks, different network provides different network capability, transmission range, data rate, access cost, security policy and quality of service. Therefore, a ubiquitous access aims to provide users intelligent human-centric context-aware handoff mechanism in heterogeneous wireless networks at anytime anywhere is gradually become an important issue. Optimal handoff planning in heterogeneous wireless networks considers the needs of users, accessing service and the surrounding context. However, most of existing handoff mechanisms only considered few contexts that lead to not able to select the most suitable network for individual user. In this paper, we propose a human-centric context-aware solution to access most appropriate network that satisfies individual user's requirement, fulfills seamless data transmission and reduces handoff delay. We develop two integrated approaches for context-awareness handoff planning mechanisms, namely MADM approach and GA approach. The MADM approach contains initial process and decision process. Initial process weights context by Analytic Hierarchy Process (AHP) method while decision process selects the most appropriate network by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The GA approach uses Genetic Algorithm to minimize handoff under given QoS constraints. Performance of proposed mechanisms is evaluated under different services with different QoS considerations. Our simulation results show that both mechanisms are able to derive a proper network handoff plan which guarantees QoS requirements and reduces delay, jitter, and number of handoffs.
AB - This paper addresses a context-awareness handoff planning mechanism in heterogeneous wireless networks for seamless ubiquitous access. The proliferation of digital devices with communication capability heralds the era of ubiquitous computing, as predicted by Mark Weiser. Mobile devices with multi-mode interfaces can access heterogeneous wireless networks, such as wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX) network and third generation (3G) network. In heterogeneous wireless networks, different network provides different network capability, transmission range, data rate, access cost, security policy and quality of service. Therefore, a ubiquitous access aims to provide users intelligent human-centric context-aware handoff mechanism in heterogeneous wireless networks at anytime anywhere is gradually become an important issue. Optimal handoff planning in heterogeneous wireless networks considers the needs of users, accessing service and the surrounding context. However, most of existing handoff mechanisms only considered few contexts that lead to not able to select the most suitable network for individual user. In this paper, we propose a human-centric context-aware solution to access most appropriate network that satisfies individual user's requirement, fulfills seamless data transmission and reduces handoff delay. We develop two integrated approaches for context-awareness handoff planning mechanisms, namely MADM approach and GA approach. The MADM approach contains initial process and decision process. Initial process weights context by Analytic Hierarchy Process (AHP) method while decision process selects the most appropriate network by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The GA approach uses Genetic Algorithm to minimize handoff under given QoS constraints. Performance of proposed mechanisms is evaluated under different services with different QoS considerations. Our simulation results show that both mechanisms are able to derive a proper network handoff plan which guarantees QoS requirements and reduces delay, jitter, and number of handoffs.
KW - context-awareness
KW - genetic algorithm
KW - handoff
KW - heterogeneous wireless networks
KW - human-centered computing
KW - MADM
KW - Ubiquitous computing
UR - http://www.scopus.com/inward/record.url?scp=85037728260&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-16355-5_34
DO - 10.1007/978-3-642-16355-5_34
M3 - Conference contribution
AN - SCOPUS:85037728260
SN - 3642163548
SN - 9783642163548
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 430
EP - 444
BT - Ubiquitous Intelligence and Computing - 7th International Conference, UIC 2010, Proceedings
PB - Springer Verlag
ER -