Performance evaluation of MADM-based methods for network selection in a multimedia wireless environment

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• 作者：Ramona Trestian ; Olga Ormond ; Gabriel-Miro Muntean
• 关键词：Network selection ; Heterogeneous wireless networks ; Energy conservation
• 刊名：Wireless Networks
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：21
• 期：5
• 页码：1745-1763
• 全文大小：5,070 KB
• 参考文献：1.Cisco Systems, Inc. (2011). Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2010-015. Resource Document. http://?www.?ieee802.?org/-/?ad_?hoc/?bwa/?public/?sep11/?nowell_-1_-911.?pdf . Accessed September 22, 2014.
  2.Cisco Systems, Inc. (2014). Cisco Visual Networking Index: The Zettabyte Era. Resource Document. http://?www.?cisco.?com/?c/?en/?us/?solutions/?collateral/?service-provider/?visual-networking-index-vni/?VNI_?Hyperconnectivit?y_?WP.?pdf . Accessed September 22, 2014.
  3.Cisco Systems, Inc. (2012). Cisco Visual Networking Index: Forecast and Methodology, 2011-2016. Resource Document. http://?www.?slideshare.?net/?zahidtg/?cisco-vni-2012 . Accessed September 22, 2014.
  4.Yeh, C.-H. (2002). A problem-based selection of multi-attribute decision-making methods. International Transactions in Operational Research, 9(2), 169-81. doi:10.-111/-475-3995.-0348 .MATH View Article
  5.Wang, H. J., Katz, R. H., & Giese, J. (1999). Policy-enabled handoffs across heterogeneous wireless networks. In Proceedings of Second IEEE Workshop on Mobile Computing Systems and Applications, 1999. WMCSA-9 (pp. 51-0). doi:10.-109/?MCSA.-999.-49277 .
  6.Adamopoulou, E., Demestichas, K., Koutsorodi, A., & Theologou, M. (2005). Intelligent access network selection in heterogeneous networks—Simulation results. In 2nd International Symposium on Wireless Communication Systems, 2005 (pp. 279-83). doi:10.-109/?ISWCS.-005.-547704 .
  7.Tawil, R., Pujolle, G., & Salazar, O. (2008). A vertical handoff decision scheme in heterogeneous wireless systems. In IEEE Vehicular Technology Conference, 2008. VTC Spring 2008 (pp. 2626-630). doi:10.-109/?VETECS.-008.-76 .
  8.Nguyen-Vuong, Q.-T., Ghamri-Doudane, Y., & Agoulmine, N. (2008). On utility models for access network selection in wireless heterogeneous networks. In IEEE Network Operations and Management Symposium, 2008. NOMS 2008 (pp. 144-51). doi:10.-109/?NOMS.-008.-575128 .
  9.Bakmaz, B., BojkoviC, Z., & Bakmaz, M. (2007). Network selection algorithm for heterogeneous wireless environment. In IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007 (pp. 1-). doi:10.-109/?PIMRC.-007.-394315 .
  10.Bari, F., & Leung, V. C. M. (2007). Automated network selection in a heterogeneous wireless network environment. IEEE Network, 21(1), 34-0. doi:10.-109/?MNET.-007.-14536 .View Article
  11.Bari, F., & Leung, V. (2007). Multi-attribute network selection by iterative TOPSIS for heterogeneous wireless access. In 4th IEEE Consumer Communications and Networking Conference, 2007. CCNC 2007 (pp. 808-12). doi:10.-109/?CCNC.-007.-64 .
  12.Trestian, R., Ormond, O., & Muntean, G. (2010). Power-friendly access network selection strategy for heterogeneous wireless multimedia networks. In 2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) (pp. 1-). doi:10.-109/?ISBMSB.-010.-463147 .
  13.Fül?p, J. (2005). Introduction to decision making methods. Laboratory of Operations Research and Decision Systems: Computer and Automation Institute, Hungarian Academy of Sciences. Resource Document. http://?academic.?evergreen.?edu/?projects/?bdei/?documents/?decisionmakingme?thods.?pdf . Accessed 22 Sept 2014.
  14.Bari, F., & Leung, V. (2007). Application of ELECTRE to network selection in a hetereogeneous wireless network environment. In IEEE Wireless Communications and Networking Conference, 2007. WCNC 2007 (pp. 3810-815). doi:10.-109/?WCNC.-007.-97 .
  15.Cui, H., Yan, Q., Cai, Y., Gao, Y., & Wu, L. (2008). Heterogeneous network selection using a novel multi- attribute decision method. In Third International Conference on Communications and Networking in China, 2008. ChinaCom 2008 (pp. 153-57). doi:10.-109/?CHINACOM.-008.-684991 .
  16.Pervaiz, H. (2010). A Multi-criteria decision making (MCDM) network selection model providing enhanced QoS differentiation to customers. In 2010 International Conference on Multimedia Computing and Information Technology (MCIT) (pp. 49-2). doi:10.-109/?MCIT.-010.-444854 .
  17.Song, Q., & Jamalipour, A. (2005). A network selection mechanism for next generation networks. In 2005 IEEE International Conference on Communications, 2005. ICC 2005 (Vol. 2, pp. 1418-422). doi:10.-109/?ICC.-005.-494578 .
  18.Yafang, W., Huimin, C., & Jinyan, Z. (2010). Network access selection algorithm based on the analytic hierarchy process and gray relation analysis. In 2010 4th International Conference on New Trends in Information Science and Service Science (NISS) (pp. 503-06).
  19.Fu, J., Wu, J., Zhang, J., Ping, L., & Li, Z. (2010). A novel AHP and GRA based handover decision mechanism in heterogeneous wireless networks. In R. Zhu, Y. Zhang, B. Liu, & C. Liu (Eds.), Information computing and applications (pp. 213-20). Berlin: Springer. Retrieved from http://?link.?springer.?com/?chapter/-0.-007/-78-3-642-16
• 作者单位：Ramona Trestian (1)
  Olga Ormond (2)
  Gabriel-Miro Muntean (3)
  
  1. Design Engineering and Mathematics Department, School of Science and Technology, Middlesex University, London, UK
  2. Research and Enterprise Hubs, Dublin City University, Dublin, Ireland
  3. Performance Engineering Laboratory, School of Electronic Engineering, Dublin City University, Dublin, Ireland
  
• 刊物类别：Computer Science
• 刊物主题：Computer Communication Networks
  Electronic and Computer Engineering
  Business Information Systems
  
• 出版者：Springer Netherlands
• ISSN：1572-8196

文摘

As mobile devices have become more affordable, easy to use and powerful, the number of mobile users and their bandwidth demands have experienced a significant growth. Considering the rising popularity of power hungry applications (e.g., multimedia), battery power capacity is an important concern—as upgrades are not keeping up with the advances in other technologies (e.g., central processing unit and memory). Mobile users now demand better power and battery management techniques to prolong their mobile battery performance. This, together with the need for green information communications technology, provides motivation for researchers to develop energy efficient techniques to reduce the power consumption in next-generation wireless networks while meeting user’s quality expectations. This paper conducts a realistic performance evaluation of a number of widely used multi attribute decision making (MADM)-based methods for network selection that aim at keeping the mobile users Always Best Connected anywhere and anytime. The main trade-off parameters considered include energy efficiency and user perceived quality levels for multimedia streaming. The energy consumption is modeled using real experimental results for an android mobile device. Similarly, the multimedia quality function was modeled using real user data, combined with a qualitative study to determine the resulting mean opinion scores. The performance analysis shows that the weighted multiplicative method (MEW) finds a better energy-quality trade-off for users in a heterogeneous wireless environment in comparison with three other MADM solutions.