Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network

Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network

Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus...

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Main Author: Goudar, Swetha Indudhar
Format: Thesis
Language:eng
eng
Published: 2017
Subjects:
TK6570 Mobile Communication System.
Online Access:https://etd.uum.edu.my/6813/1/s95141_01.pdf
https://etd.uum.edu.my/6813/2/s95141_02.pdf
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id my-uum-etd.6813
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Hassan, Suhaidi
Habbal, Adib M. Monzer
topic TK6570 Mobile Communication System.
spellingShingle TK6570 Mobile Communication System.
Goudar, Swetha Indudhar
Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
description Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus degrading overall system performance. The current RAT selection approach is biased towards network-centric criteria pertaining to signal strength. However, the paradigm shift from network-centric to user-centric approach necessitates a multi-criteria selection process, with methodology relating to both network and user preferences in the context of future generation networks. Hence, an effective selection approach is required to avoid unnecessary handovers in RAT. The main aim of this study is to propose the Context-aware Multiattribute decision making for RAT (CMRAT) selection for investigating the need to choose a new RAT and further determine the best amongst the available methods. The CMRAT consists of two mechanisms, namely the Context-aware Analytical Hierarchy Process (CAHP) and Context-aware Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS). The CAHP mechanism measures the need to switch from the current RAT, while CTOPSIS aids in decision making to choose the best target RAT. A series of experimental studies were conducted to validate the effectiveness of CMRAT for achieving improved system performance. The investigation utilises shopping mall and urban dense network scenarios to evaluate the performance of RAT selection through simulation. The findings demonstrated that the CMRAT approach reduces delay and the number of handovers leading to an improvement of throughput and packet delivery ratio when compared to that of the commonly used A2A4-RSRQ approach. The CMRAT approach is effective in the RAT selection within UDN environment, thus supporting heterogeneous RAT deployment in future 5G networks. With context-aware selection, the user-centric feature is also emphasized.
format Thesis
qualification_name other
qualification_level Doctorate
author Goudar, Swetha Indudhar
author_facet Goudar, Swetha Indudhar
author_sort Goudar, Swetha Indudhar
title Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
title_short Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
title_full Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
title_fullStr Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
title_full_unstemmed Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
title_sort context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network
granting_institution Universiti Utara Malaysia
granting_department Awang Had Salleh Graduate School of Arts & Sciences
publishDate 2017
url https://etd.uum.edu.my/6813/1/s95141_01.pdf
https://etd.uum.edu.my/6813/2/s95141_02.pdf
_version_ 1747828119105961984
spelling my-uum-etd.68132021-05-09T02:50:26Z Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network 2017 Goudar, Swetha Indudhar Hassan, Suhaidi Habbal, Adib M. Monzer Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences TK6570 Mobile Communication System. Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus degrading overall system performance. The current RAT selection approach is biased towards network-centric criteria pertaining to signal strength. However, the paradigm shift from network-centric to user-centric approach necessitates a multi-criteria selection process, with methodology relating to both network and user preferences in the context of future generation networks. Hence, an effective selection approach is required to avoid unnecessary handovers in RAT. The main aim of this study is to propose the Context-aware Multiattribute decision making for RAT (CMRAT) selection for investigating the need to choose a new RAT and further determine the best amongst the available methods. The CMRAT consists of two mechanisms, namely the Context-aware Analytical Hierarchy Process (CAHP) and Context-aware Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS). The CAHP mechanism measures the need to switch from the current RAT, while CTOPSIS aids in decision making to choose the best target RAT. A series of experimental studies were conducted to validate the effectiveness of CMRAT for achieving improved system performance. The investigation utilises shopping mall and urban dense network scenarios to evaluate the performance of RAT selection through simulation. The findings demonstrated that the CMRAT approach reduces delay and the number of handovers leading to an improvement of throughput and packet delivery ratio when compared to that of the commonly used A2A4-RSRQ approach. The CMRAT approach is effective in the RAT selection within UDN environment, thus supporting heterogeneous RAT deployment in future 5G networks. With context-aware selection, the user-centric feature is also emphasized. 2017 Thesis https://etd.uum.edu.my/6813/ https://etd.uum.edu.my/6813/1/s95141_01.pdf text eng public https://etd.uum.edu.my/6813/2/s95141_02.pdf text eng public other doctoral Universiti Utara Malaysia [1] Cisco. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update. Available in this link. [Online]. Available: http://www.cisco.com/c/en/us/solutions/ collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html, February 2015. [2] O. Fagbohun, “Comparative Studies on 3G, 4G and 5G Wireless Technology,” IOSR Journal of Electronics and Communication Engineering, vol. 9, no. 3, pp. 88–94, 2014. [3] A. Gohil, H. Modi, and S. Patel, “5G Technology of Mobile Communication: A Survey,” in International Conference on Intelligent Systems and Signal Processing (ISSP), March 2013, pp. 288–292. [4] V. Pereira and T. Sousa, “Evolution of Mobile Communications: from 1G to 4G,” Department of Informatics Engineering of the University of Coimbra, Portugal, 2004. [5] P. Pirinen, “A Brief Overview of 5G Research Activities,” in 1st International Conference on 5G for Ubiquitous Connectivity (5GU), Nov 2014, pp. 17–22. [6] W. H. Chin, Z. Fan, and R. Haines, “Emerging Technologies and Research Challenges for 5G Wireless Networks,” IEEE Wireless Communications, vol. 21, no. 2, pp. 106–112, April 2014. [7] A. Osseiran, F. Boccardi, V. Braun, K. Kusume, P. Marsch, M. Maternia, O. Queseth, M. Schellmann, H. Schotten, H. Taoka, H. Tullberg, M. Uusitalo, B. Timus, and M. Fallgren, “Scenarios for 5G Mobile and Wireless Communications: The Vision of the METIS Project,” IEEE Communications Magazine, vol. 52, no. 5, pp. 26–35, May 2014. [8] N. Bhushan, J. Li, D. Malladi, R. Gilmore, D. Brenner, A. Damnjanovic, R. Sukhavasi, C. Patel, and S. Geirhofer, “Network Densification: The Dominant Theme forWireless Evolution into 5G,” IEEE Communications Magazine, vol. 52, no. 2, pp. 82–89, February 2014. [9] NOKIA. 5G Use Cases and Requirements. [Online]. Available: http://networks.nokia.com/sites/default/files/ document/5g_requirements_white_paper.pdf, 2014. [10] J. Xu, J. Wang, Y. Zhu, Y. Yang, X. Zheng, S. Wang, L. Liu, K. Horneman, and Y. Teng, “Cooperative Distributed Optimization for the Hyper-dense Small Cell Deployment,” IEEE Communications Magazine, vol. 52, no. 5, pp. 61–67, 2014. [11] N. Wang, E. Hossain, and V. K. Bhargava, “Backhauling 5G Small Cells: A Radio Resource Management Perspective,” IEEE Wireless Communications, vol. 22, no. 5, pp. 41–49, 2015. [12] A. Tudzarov and T. Janevski, “M-RATS: Mobile-Based Radio Access Technology Selector for Heterogeneous Wireless Environment,” in Proceedings of the 18th Telecommunications forum, TELFOR, 2010. [13] S. Barmpounakis, A. Kaloxylos, P. Spapis, and N. Alonistioti, “COmpAsS: A Context-Aware, User-oriented RAT Selection Mechanism in Heterogeneous Wireless Networks,” in Proc. Int. Conf. on Advanced Commun. and Computation (INFOCOMP), Paris, 2014. [14] G. Global, “Future internet ppp,” [Online]. Available: http://www.fi-ppp.eu/, 2013. [15] J. Pan, S. Paul, and R. Jain, “A Survey of the Research on Future Internet Architectures,” IEEE Communications Magazine, vol. 49, no. 7, pp. 26–36, 2011. [16] Ericsson. 5G Systems Enabling Industry and Socirty Transformation. [Online]. Available: http://www.ericsson.com/co/res/docs/whitepapers/ what-is-a-5g-system.pdf,January,2015. [17] B. Angoma, M. Erradi, Y. Benkaouz, A. Berqia, and M. C. Akalay, “HaVe- 2W3G: A Vertical Handoff Solution Between WLAN, WiMAX and 3G Networks,” in 7th International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2011, pp. 101–106. [18] O. Khattab and O. Alani, “Mobile IPv4 Based Procedure for Loose Coupling Architecture to Optimize Performance in Heterogeneous Wireless Networks,” International Journal of Computer Networks and Wireless Communications (IJCNWC), vol. 3, no. 1, pp. 56–61, 2013. [19] A. Kaloxylos, S. Barmpounakis, P. Spapis, and N. Alonistioti, “An Efficient RAT Selection Mechanism for 5G Cellular Networks,” in International Conference on Wireless Communications and Mobile Computing (IWCMC). IEEE, 2014, pp. 942–947. [20] B. Bangerter, S. Talwar, R. Arefi, and K. Stewart, “Networks and Devices for the 5G Era,” IEEE Communications Magazine, vol. 52, no. 2, pp. 90–96, February 2014. [21] METIS. The 5G Future Scenarios Identified by METIS The First Step Toward a 5G Mobile and Wireless Communications System. [Online]. Available: https://www.metis2020.com/press-events/press/the-5g-future-scenarios-identified- by-metis/?doing_wp_cron=1425104069. 4943730831146240234375, September5, 2013. [22] H. Tullberg, H. Droste, M. Fallgren, P. Fertl, D. Gozalvez-Serrano, E. Mohyeldin, O. Queseth, and Y. Seien, “METIS research and standardization: A path towards a 5G system,” in Globecom Workshops (GC Workshops). IEEE, 2014, pp. 577–582. [23] M. Emmelmann, T. Langgäertner, and M. Sonnemann, “System Design and Implementation of Seamless Handover Support Enabling Real-Time Telemetryhighly Mobile Users,” in Proceedings of the 6th ACM International Symposium on Mobility Management and Wireless Access. ACM, 2008, pp. 1–8. [24] J. Park and J. Chung, “Network Selection Based on Network Service Zone for Macro Mobility,” in Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human. ACM, 2009, pp. 295–299. [25] A. Bazzi, “A Softer Vertical Handover Algorithm for Heterogeneous Wireless Access Networks,” in IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC). IEEE, 2010, pp.2156–2161. [26] O. Khattab and O. Alani, “Algorithm for Seamless Vertical Handover in Heterogeneous Mobile Networks,” in Science and Information Conference (SAI). IEEE, 2014, pp. 652–659. [27] T. Ahmed, K. Kyamakya, M. Ludwig, K. Anne, J. Schroeder, S. Galler, K. Kyamakya, K. Jobmann, D. Jannach, K. Leopold et al., A Context-Aware Vertical Handover Decision Algorithm for Multimode Mobile Terminals and its Performance, 2006. [28] A. Sgora, D. D. Vergados, and P. Chatzimisios, “An Access Network Selection Algorithm for Heterogeneous Wireless Environments,” in IEEE Symposium on Computers and Communications (ISCC). IEEE, 2010, pp. 890–892. [29] A. Hasswa, N. Nasser, and H. Hassanein, “A seamless Context-Aware Architecture for Fourth Generation Wireless Networks,” Wireless Personal Communications, vol. 43, no. 3, pp. 1035–1049, 2007. [30] P. Bellavista, A. Corradi, and C. Giannelli, “A Unifying Perspective on Context- Aware Evaluation and Management of Heterogeneous Wireless Connectivity,” IEEE Communications Surveys & Tutorials, vol. 13, no. 3, pp. 337–357, 2011. [31] P. Makris, D. N. Skoutas, and C. Skianis, “A Survey on Context-Aware Mobile and Wireless Networking: On Networking and Computing Environments Integration,” IEEE Communications Surveys & Tutorials, vol. 15, no. 1, pp. 362–386, 2013. [32] G. Mahardhika, M. Ismail, and R. Nordin, “MULTI-CRITERIA VERTICAL HANDOVER DECISION ALGORITHM IN HETEROGENEOUS WIRELESS NETWORK,” Journal of Theoretical & Applied Information Technology, vol. 53, no. 2, 2013. [33] S. Boussen, N. Tabbane, S. Tabbane, and F. Krief, “A Context Aware Vertical Handover Decision Approach Based on Fuzzy Logic,” in International Conference on Communications and Networking (ComNet). IEEE, 2014, pp. 1–5. [34] G. D. Abowd, A. K. Dey, P. J. Brown, N. Davies, M. Smith, and P. Steggles, “Towards a Better Understanding of Context and Context-awareness,” in Handheld and Ubiquitous Computing. Springer, 1999, pp. 304–307. [35] K. Santhi and G. S. Kumaran, “Migration to 4 G: Mobile IP Based Solutions,” in Advanced Int’l Conference on Telecommunications and Int’l Conference on Internet and Web Applications and Services (AICT-ICIW’06). IEEE, 2006, pp.76–76. [36] M. Abdullah and A. Yonis, “Performance of LTE Release 8 and Release 10 in Wireless Communications,” in International Conference on Cyber Security, Cyber Warfare and Digital Forensic (CyberSec). IEEE, 2012, pp. 236–241. [37] L.-C. Wang and S. Rangapillai, “A Survey on Green 5G Cellular Networks,” in International Conference on Signal Processing and Communications (SPCOM), July 2012, pp. 1–5. [38] A. Osseiran. Mobile and Wireless Communications system for 2020 and beyond (5G). [Online]. Available: https://www.metis2020.com/ wp-content/uploads/presentations/ITU-R-2020-VisionWS.pdf,2014 [39] T. Nakamura, S. Nagata, A. Benjebbour, Y. Kishiyama, T. Hai, S. Xiaodong, Y. Ning, and L. Nan, “Trends in Small Cell Enhancements in LTE Advanced,” IEEE Communications Magazine, vol. 51, no. 2, pp. 98–105, 2013. [40] D. Soldani and A. Manzalini, “Horizon 2020 and Beyond: On The 5G Operating System for a True Digital Society,” IEEE Vehicular Technology Magazine, vol. 10, no. 1, pp. 32–42, 2015. [41] N. Brahmi, “METIS: Mobile Communications for 2020 and Beyond,” ITGFachbericht-Mobil kommunikation–Technologien und Anwendungen, 2013. [42] M. Jaber, M. A. Imran, R. Tafazolli, and A. Tukmanov, “5G Backhaul Challenges and Emerging Research Directions: A Survey,” IEEE Access, vol. 4, pp. 1743–1766, 2016. [43] C. V. N. Index, “Global mobile data traffic forecast update, 2012-2017,” Cisco white paper, 2013. [44] I. Al-Surmi, M. Othman, and B. M. Ali, “Mobility Management for IP-Based Next Generation Mobile Networks: Review, Challenge and Perspective,” Journal of Network and Computer Applications, vol. 35, no. 1, pp. 295–315, 2012. [45] M. Kassar, B. Kervella, and G. Pujolle, “Architecture of an Intelligent Inter-System Handover Management Scheme,” in Future Generation Communication and Networking, vol. 1. IEEE, 2007, pp. 332–337. [46] L.-J. Chen, T. Sun, G. Yang, and M. Gerla, “USHA: A Simple and Practical Seamless Vertical Handoff Solution,” in IEEE Consumer Communications and Networking Conference, vol. 2, 2006, pp. 3–1. [47] M. Adnan, H. Zen, and A.-K. Othman, “Vertical Handover Decision Processes for Fourth Generation Heterogeneous Wireless Networks,” Asian Journal of Applied Sciences, vol. 1, no. 5, 2013. [48] L.-J. Chen, T. Sun, B. Chen, V. Rajendran, and M. Gerla, “A Smart Decision Model for Vertical Handoff,” in Proceedings of the 4th International Workshop on Wireless Internet and Reconfigurability, Athens, Greece, 2004. [49] P. Goyal and S. Saxena, “A Dynamic Decision Model for Vertical Handoffs Across Heterogeneous Wireless Networks,” World Academy of Science, Engineering and Technology, vol. 31, no. 677-682, pp. 3–1, 2008. [50] M. Kassar, B. Kervella, and G. Pujolle, “An Overview of Vertical Handover Decision Strategies in Heterogeneous Wireless Networks,” Computer Communications, vol. 31, no. 10, pp. 2607–2620, 2008. [51] A. Dutta, S. Das, D. Famolari, Y. Ohba, K. Taniuchi, V. Fajardo, R. M. Lopez, T. Kodama, and H. Schulzrinne, “Seamless Proactive Handover Across Heterogeneous Access Networks,” Wireless Personal Communications, vol. 43, no. 3, pp. 837–855, 2007. [52] E. Stevens-Navarro, Y. Lin, and V.W.Wong, “An MDP-Based Vertical Handoff Decision Algorithm for HeterogeneousWireless Networks,” IEEE Transactions on Vehicular Technology,, vol. 57, no. 2, pp. 1243–1254, 2008. [53] A. Singhrova and N. Prakash, “A review of vertical handoff decision algorithm in heterogeneous networks,” in Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and The 1st International Symposium on Computer Human Interaction in Mobile Technology. ACM, 2007, pp. 68–71. [54] P. Dong, H. Zhang, H. Luo, T.-Y. Chi, and S.-Y. Kuo, “A Network-Based Mobility Management Scheme for Future Internet,” Computers & electrical engineering, vol. 36, no. 2, pp. 291–302, 2010. [55] M. Corici, J. Fiedler, T. Magedanz, and D. Vingarzan, “Access Network Discovery and Selection in the FutureWireless Communication,” Mobile Networks and Applications, vol. 16, no. 3, pp. 337–349, 2011. [56] A. Ahmed, L. Merghem-Boulahia, and D. Gaïti, “An Intelligent Agent-Based Scheme for Vertical Handover Management across Heterogeneous Networks,” annals of telecommunications-annales des télécommunications, vol. 66, no. 9- 10, pp. 583–602, 2011. [57] C.-L. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications a State-of-the-art Survey. Springer Science & Business Media, 2012, vol. 186. [58] D. E. Charilas and A. D. Panagopoulous, “Multiaccess radio network enviroments,” IEEE Vehicular Technology Magazine, vol. 5, no. 4, pp. 40–49, 2010. [59] K. De Vogeleer, S. Ickin, D. Erman, and M. Fiedler, “Perimeter: A User-Centric Mobility Framework,” in IEEE 35th Conference on Local Computer Networks (LCN). IEEE, 2010, pp. 625–626. [60] M. A. Khan, U. Toseef, S. Marx, and C. Goerg, “Game-theory based User Centric Network Selection with Media Independent Handover Services and Flow Management,” in Eighth Annual Communication Networks and Services Research Conference (CNSR). IEEE, 2010, pp. 248–255. [61] M. Tuysuz and H. A. Mantar, “Network-assisted QoS-based Fast Handover with Smart Scanning over IEEE 802.11 WLANs,” in IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2013, pp. 2946–2950. [62] V. Jesus, S. Sargento, D. Corujo, N. Senica, M. Almeida, and R. L. Aguiar, “Mobility with QoS support for Multi-interfaceTerminals: Combined User and Network Approach,” in 12th IEEE Symposium on Computers and Communications, ISCC. IEEE, 2007, pp. 325–332. [63] J. McNair and F. Zhu, “Vertical Handoffs in Fourth-Generation Multinetwork Environments,” IEEEWireless Communications,, vol. 11, no. 3, pp. 8–15, 2004. [64] B.-J. Chang and J.-F. Chen, “Cross-Layer-Based Adaptive Vertical Handoff with Predictive RSS in Heterogeneous Wireless Networks,” Vehicular Technology, IEEE Transactions on, vol. 57, no. 6, pp. 3679–3692, 2008. [65] S. Mohanty and I. F. Akyildiz, “A Cross-Layer (layer 2+ 3) Handoff Management Protocol for Next-Generation Wireless Systems,” IEEE Transactions on Mobile Computing, vol. 5, no. 10, pp. 1347–1360, 2006. [66] X. Yan, Y. A. ¸Sekercio˘glu, and S. Narayanan, “A Survey of Vertical Handover Decision Algorithms in Fourth Generation HeterogeneousWireless Networks,” Computer Networks, vol. 54, no. 11, pp. 1848–1863, 2010. [67] W. Mohr and W. Konhauser, “Access Network Evolution beyond Third Generation Mobile Communications,” IEEE Communications Magazine, vol. 38, no. 12, pp. 122–133, 2000. [68] X. Yan, N. Mani, and Y. A. Sekercioglu, “A Traveling Distance Prediction based Method to Minimize Unnecessary Handovers from Cellular Networks to WLANs,” IEEE Communications Letters, vol. 12, no. 1, pp. 14–16, 2008. [69] H.-H. Choi, “An Optimal Handover Decision for Throughput Enhancement,” IEEE Communications Letters, vol. 14, no. 9, pp. 851–853, 2010. [70] M. J. Kim, S. W. Son, and B. H. Rhee, “A New Approach Network Selection with MIH between WLAN and WMAN,” in Fourth International Conference on Computer Sciences and Convergence Information Technology, ICCIT ’09., Nov 2009, pp. 751–755. [71] A. Calvagna and G. Di Modica, “A User-Centric Analysis of Vertical Handovers,” in Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots. ACM, 2004, pp. 137– 146. [72] C. W. Lee, L. M. Chen, M. C. Chen, and Y. S. Sun, “A Framework of Handoffs in Wireless Overlay Networks Based on Mobile IPv6,” IEEE Journal on Selected Areas in Communications, vol. 23, no. 11, pp. 2118–2128, 2005. [73] K. Yang, I. Gondal, B. Qiu, and L. S. Dooley, “Combined SINR based Vertical Handoff Algorithm for next Generation Heterogeneous Wireless Networks,” in IEEE Global Telecommunications Conference GLOBECOM. IEEE, 2007, pp. 4483–4487. [74] K. Hong, S. Lee, L. Kim, and P. Song, “Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2009, p. 15, 2009. [75] N. Nasser, A. Hasswa, and H. Hassanein, “Handoffs in Fourth Generation Heterogeneous Networks,” IEEE Communications Magazine, vol. 44, no. 10, pp. 96–103, 2006. [76] R. Tawil, G. Pujolle, and O. Salazar, “A Vertical Handoff Decision Scheme in Heterogeneous Wireless Systems,” in IEEE Vehicular Technology Conference, VTC Spring. IEEE, 2008, pp. 2626–2630. [77] H. J.Wang, R. H. Katz, and J. Giese, “Policy-Enabled Handoffs Across Heterogeneous Wireless Networks,” in Second IEEE Workshop on Mobile Computing Systems and Applications, 1999. Proceedings. WMCSA’99. IEEE, 1999, pp. 51–60. [78] S. Lee, K. Sriram, K. Kim, Y. H. Kim, and N. Golmie, “Vertical Handoff Decision Algorithms for Providing Optimized Performance in HeterogeneousWireless Networks,” IEEE Transactions on Vehicular Technology, vol. 58, no. 2, pp. 865–881, 2009. [79] D. Guo and X. Li, “An Adaptive Vertical Handover Algorithm based on the Analytic Hierarchy Process for Heterogeneous Networks,” in 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015, pp. 2059–2064. [80] R. A. Taha and T. Daim, “Multi-criteria Applications in Renewable Energy Analysis, a Literature Review,” in Research and Technology Management in the Electricity Industry. Springer, 2013, pp. 17–30. [81] R. Chai, W.-G. Zhou, Q.-B. Chen, and L. Tang, “A Survey on Vertical Handoff Decision for Heterogeneous Wireless Networks,” in IEEE Youth Conference on Information, Computing and Telecommunication, 2009, pp. 279–282. [82] W. Song, J.-M. Chung, D. Lee, C. Lim, S. Choi, and T. Yeoum, “Improvements to Seamless Vertical Handover Between Mobile WiMAX and 3GPP UTRAN through The Evolved Packet Core,” IEEE Communications Magazine, vol. 47, no. 4, pp. 66–73, April 2009. [83] M. Zekri, J. Pokhrel, B. Jouaber, and D. Zeghlache, “Reputation for Vertical Handover Decision Making,” in 17th Asia-Pacific Conference on Communications (APCC). IEEE, 2011, pp. 318–323. [84] S. Horrich, S. Ben Jamaa, and P. Godlewski, “Adaptive Vertical Mobility Decision in Heterogeneous Networks,” in Third International Conference on Wireless and Mobile Communications, ICWMC’07. IEEE, 2007, pp. 44–44. [85] J. Geldermann and O. Rentz, “Bridging the Gap Between American and European MADM-Approaches,” in Proc. of the 51st Meeting of the European Working Group Multicriteria Aid for Decisions Madrid, 2000. [86] I. Lassoued, J. Bonnin, Z. Ben Hamouda, and A. Belghith, “A Methodology for Evaluating Vertical Handoff Decision Mechanisms,” in Seventh International Conference on Networking, ICN. IEEE, 2008, pp. 377–384. [87] L. Abdullah and C. Rabiatul Adawiyah, “Simple Additive Weighting Methods of Multi criteria Decision Making and Applications: A Decade Review,” International Journal of Information Processing & Management, vol. 5, no. 1, 2014. [88] S. Maaloul, M. Afif, and S. Tabbane, “Vertical Handover Decision Policy Based on the End User’s Perceived Quality of Service,” in 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA), March 2013, pp. 493–498. [89] N. Singh and B. Singh, “Vertical Handoff Decision in 4G Wireless Networks using Multi Attribute Decision Making Approach,” Wireless networks, vol. 20, no. 5, pp. 1203–1211, 2014. [90] A. Afshari, M. Mojahed, and R. M. Yusuff, “Simple Additive Weighting Approach to Personnel Selection Problem,” International Journal of Innovation, Management and Technology, vol. 1, no. 5, p. 511, 2010. [91] A. Ismail and B.-H. Roh, “Adaptive Handovers in Heterogeneous Networks using Fuzzy MADM,” in International Conference on Mobile IT Convergence, Sept 2011, pp. 99–104. [92] O. A. Taiwo and O. E. Falowo, “Comparative Analysis of Algorithms for Making Multiple-sessions Handover Decisions in next Generation Wireless Networks,” in AFRICON, 2013, Sept 2013, pp. 1–6. [93] M. Drissi and M. Oumsis, “Performance Evaluation of Multi-criteria Vertical Handover for Heterogeneous Wireless Networks,” in Intelligent Systems and Computer Vision (ISCV), March 2015, pp. 1–5. [94] M. Pink, M. Sprejz, and H. Koenig, “A Coordinated Group Decision for Vertical Handovers in Heterogeneous Wireless Networks,” in International Conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications (Mobilware), Nov 2013, pp. 130–137. [95] P. TalebiFard and V. C. Leung, “A Dynamic Context-aware Access Network Selection for Handover in Heterogeneous Network Environments,” in IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2011, pp. 385–390. [96] K. Savitha and C. Chandrasekar, “Vertical handover decision schemes using saw and wpm for network selection in heterogeneous wireless networks,” Global Journal of Computer Science and Technology, 2011. [97] J. D. Martinez-Morales, U. Pineda-Rico, and E. Stevens-Navarro, “Performance Comparison between MADM Algorithms for Vertical Handoff in 4G Networks,” in 7th International Conference on Electrical Engineering Computing Science and Automatic Control (CCE). IEEE, 2010, pp. 309–314. [98] P. TalebiFard and V. C. Leung, “Context-Aware Mobility Management in Heterogeneous Network Environments,” JoWUA, vol. 2, no. 2, pp. 19–32, 2011. [99] Y. K. Hwang, Ching-Lai, Multiple Attribute Decision Making Methods and Applications A State-of-the-Art Survey. Springer, 1981. [100] M. Alkhawlani, K. Alsalem, and A. Hussein, “Multi-Criteria Vertical Handover by TOPSIS and Fuzzy Logic,” in International Conference on Communications and Information Technology (ICCIT), March 2011, pp. 96–102. [101] S. J. Yang and W. C. Tseng, “Utilizing Weighted Rating of Multiple Attributes Scheme to Enhance Handoff Efficiency in Heterogeneous Wireless Networks,” in International Conference on Wireless Communications and Signal Processing (WCSP), Nov 2011, pp. 1–6. [102] F. Bari and V. Leung, “Multi-attribute Network selection by Iterative TOPSIS for Heterogeneous Wireless Access,” in 4th IEEE Conference on Consumer Communications and Networking, 2007, pp. 808–812. [103] I. Chamodrakas and D. Martakos, “A Utility-based Fuzzy TOPSIS Method for Energy Efficient Network Selection in Heterogeneous Wireless Networks,” Applied Soft Computing, vol. 12, no. 7, pp. 1929–1938, 2012. [104] M. Lahby, L. Cherkaoui, and A. Adib, “An Enhanced TOPSIS based Network Selection Technique for next Generation Wireless Networks,” in 20th International Conference on Telecommunications (ICT). IEEE, 2013, pp. 1–5. [105] W. Panjanda and O. Wongwirat, “A Scoring Method Improvement of Analytic Hierarchy Process Using Linear Programming Technique for Vertical Handover Decision,” in International Symposium on Wireless Personal Multimedia Communications (WPMC). IEEE, 2014, pp. 373–378. [106] A. Mehbodniya, F. Adachi, and G. Guan, “A New Multi-Attribute Base-Station Association Technique for Hybrid Wireless Networks,” Proc. of IEICE Tech. Rep, vol. 112, no. 443, pp. 145–149, 2013. [107] V. Gupta, “Network Discovery and User Preferences for Network Selection in 3G-WLAN Interworking Environment,” in Fifth International Conference on Communication Systems and Networks (COMSNETS). IEEE, 2013, pp. 1–2. [108] Y. Nkansah-Gyekye and J. I. Agbinya, “Vertical Handoff Between WWAN and WLAN,” in International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies, ICN/ICONS/MCL. IEEE, 2006, pp. 132–132. [109] R. K. Goyal and S. Kaushal, “Effect of Utility Based Functions on Fuzzy-AHP based Network Selection in Heterogenous Wireless Networks,” in 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS). IEEE, 2015, pp. 1–5. [110] J. Inwhee, K. Won-Tae, and H. Seokjoon, “A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks,” IEICE transactions on communications, vol. 91, no. 1, pp. 314–317, 2008. [111] Q. Song and A. Jamalipour, “A Network Selection Mechanism for Next Generation Networks,” in IEEE International Conference on Communications, ICC, vol. 2. IEEE, 2005, pp. 1418–1422. [112] O. Markaki, D. Charilas, and D. Nikitopoulos, “Enhancing Quality of Experience in next Generation Networks through Network Selection Mechanisms,” in IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2007, pp. 1–5. [113] D. Zhang, Y. Zhang, N. Lv, and Y. He, “An Access Selection Algorithm based on GRA Integrated with FAHP and Entropy Weight in Hybrid Wireless Environment,” in 7th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2013, pp. 1–5. [114] M. Khan, C. Jung, P. C. Uzoh, C. Zhenbo, J. Kim, Y. Yoon, A. Nadeem, and K. Han, “Enabling Vertical Handover Management based on Decision Making in Heterogeneous Wireless Networks,” in International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2015, pp. 952–957. [115] P. N. Tran and N. Boukhatem, “The Distance to the Ideal Alternative (DiA) Algorithm for Interface Selection in Heterogeneous Wireless Networks,” in Proceedings of the 6th ACM International Symposium on Mobility Management and Wireless Access. ACM, 2008, pp. 61–68. [116] M. Lahby, L. Cherkaoui, and A. Adib, “New Multi Access Selection method based on Mahalanobis Distance,” Applied Mathematical Sciences, vol. 6, no. 53-56, pp. 2745–2760, 2012. [117] I. Cinemre, T. Mahmoodi, and M. Tatipamula, “Learning-Based Multi Attribute Network Selection in Heterogeneous Wireless Access.” [118] Q. He, “A Fuzzy Logic Based Vertical Handoff Decision Algorithm Between WWAN and WLAN,” in 2nd International Conference on Networking and Digital Society (ICNDS), vol. 2. IEEE, 2010, pp. 561–564. [119] J. Dhar, K. S. Ravi, and R. K. Yashwanth, “Network Selection in Heterogeneous Wireless Environment: a Ranking Algorithm,” in Third International Conference on Wireless Communication and Sensor Networks, WCSN’07. IEEE, 2007, pp. 41–44. [120] F. Bari and V. Leung, “Application of ELECTRE to Network Selection in A Hetereogeneous Wireless Network Environment,” in IEEE Conference on Wireless Communications and Networking, March 2007, pp. 3810–3815. [121] F. Kaleem, A. Mehbodniya, A. Islam, K. K. Yen, and F. Adachi, “Dynamic Target Wireless Network Selection Technique using Fuzzy Linguistic Variables,” China communications, vol. 10, no. 1, pp. 1–16, 2013. [122] K. Anupama, S. S. Gowri, B. P. Rao, and T. S. Murali, “A Promethee Approach for Network Selection in Heterogeneous Wireless Eenvironment,” in International conference on Advances in computing, communications and informatics (ICACCI). IEEE, 2014, pp. 2560–2564. [123] E. Obayiuwana and O. E. Falowo, “Network Selection in Heterogeneous Wireless Networks using Multi-criteria Decision-making Algorithms: A Review,” Wireless Networks, pp. 1–33, 2016. [124] Q.-T. Nguyen-Vuong, N. Agoulmine, E. H. Cherkaoui, and L. Toni, “Multicriteria Optimization of Access Selection to Improve the Quality of Experience in HeterogeneousWireless Access Networks,” IEEE Transactions on Vehicular Technology, vol. 62, no. 4, pp. 1785–1800, 2013. [125] S. Balasubramaniam and J. Indulska, “Vertical Handover Supporting Pervasive Computing in Future Wireless Networks,” Computer Communications, vol. 27, no. 8, pp. 708–719, 2004. [126] B. Schilit, N. Adams, and R. Want, “Context-aware computing applications,” in First Workshop on Mobile Computing Systems and Applications, WMCSA. IEEE, 1994, pp. 85–90. [127] S. Balasubramaniam, T. Pfeifer, and J. Indulska, “Active Node Supporting Context-Aware Vertical Handover in Pervasive Computing Environment with Redundant Positioning,” in 1st International Symposium on Wireless Pervasive Computing. IEEE, 2006, pp. 1–6. [128] O. S. Vaidya and S. Kumar, “Analytic Hierarchy Process: An Overview of Applications,” European Journal of Operational Research, vol. 169, no. 1, pp. 1–29, 2006. [129] L. Blessing and A. Chakrabarti, DRM: A Design Research Methodology. Springer Verlag, 2009. [130] A. Habbal, “TCP SINTOK: Transmission Control Protocol with Delay-based Loss Detection and Contention Avoidance Mechanisms For Mobile Ad hoc Networks,” Ph.D. dissertation, School of Computing, Universiti Utara Malaysia, 2014. [131] O. Balci, “Verification Validation and Accreditation of Simulation Model,” in Proceedings of the 29th conference on Winter simulation. IEEE Computer Society, 1997, pp. 135–141. [132] S. Kurkowski, T. Camp, and M. Colagrosso, “MANET Simulation Studies: The Incredibles,” ACM SIGMOBILE Mobile Computing and Communications Review, vol. 9, no. 4, pp. 50–61, 2005. [133] A. Cook and M. Skinner, “How to Perform Credible verification, Validation, and Accreditation for Modeling and Simulation,” The Journal of Defense Software Engineering,, 2005. [134] R. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. John Wiley & Sons, 1990. [135] ——, The Art of Computer Systems Performance Analysis. John Wiley & Sons, 2008. [136] L. K. John, “8.2 Performance Evaluation: Techniques, Tools, and Benchmarks,” The Computer Engineering Handbook, vol. 8, p. 21, 2002. [137] H. Al-Bahadili, Simulation in Computer Network Design and Modeling: Use and Analysis: Use and Analysis. IGI Global, 2012. [138] J. Mo, “Performance Modeling of Communication Networks with Markov Chains,” Synthesis Lectures on Data Management, vol. 3, no. 1, pp. 1–90, 2010. [139] M. Hassan and R. Jain, High Performance TCP/IP Networking. Prentice Hall, 2003. [140] S.-m. Liu, S. Pan, Z.-k. Mi, Q.-m. Meng, and M.-h. Xu, “A simple Additive Weighting Vertical Handoff Algorithm based on SINR and AHP for Heterogeneous Wireless Networks,” in International Conference on Intelligent Computation Technology and Automation (ICICTA), vol. 1. IEEE, 2010, pp. 347–350. [141] V. Sasirekha and M. Ilanzkumaran, “Heterogeneous Wireless Network Selection using FAHP Integrated with TOPSIS and VIKOR,” in International Conference on Pattern Recognition, Informatics and Mobile Engineering (PRIME). IEEE, 2013, pp. 399–407. [142] Y. Li, X. Guo, Y. Li, and X. Zheng, “A Utility-based Network Selection Mechanism in Heterogeneous Wireless Networks,” in International Conference on Wireless Networks and Information Systems, 2009. WNIS’09. IEEE, 2009, pp. 201–204. [143] E. Stevens-Navarro and V. Wong, “Comparison Between Vertical Handoff Decision Algorithms for HeterogeneousWireless Networks,” in IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring., vol. 2, May 2006, pp. 947–951. [144] I. Chantaksinopas, P. Oothongsap, and A. Prayote, “Network selection delay comparison of network selection techniques for safety applications on vanet,” in 13th Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2011, pp. 1–7. [145] F. Bari and V. C. Leung, “Use of Non-monotonic Utility in Multi-attribute Network Selection,” in Wireless Technology. Springer, 2009, pp. 21–39. [146] Q. Song and A. Jamalipour, “Network selection in an integrated wireless lan and umts environment using mathematical modeling and computing techniques,” IEEE wireless communications, vol. 12, no. 3, pp. 42–48, 2005. [147] A. Mehbodniya, F. Kaleem, K. K. Yen, and F. Adachi, “A novel wireless network access selection scheme for heterogeneous multimedia traffic,” in IEEE 10th Consumer Communications and Networking Conference (CCNC). IEEE, 2013, pp. 485–489. [148] D. Charilas, O. Markaki, and E. Tragos, “A Theoretical Scheme for Applying Game Theory and Network Selection Mechanisms in Access Admission Control,” in 3rd International Symposium on Wireless Pervasive Computing, (SWPC). IEEE, 2008, pp. 303–307. [149] N. Singh and Manisha, “Optimal network selection using madm algorithms,” in 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS). IEEE, 2015, pp. 1–6. [150] T. L. Saaty, “How to make a Decision:The Analytic Hierarchy Process,” European Journal of Operational Research, vol. 48, no. 1, pp. 9–26, 1990. [151] L. Ekiz, C. Lottermann, D. Öhmann, T. Tran, O. Klemp, C. Wietfeld, and C. F. Mecklenbräuker, “Potential of Cooperative Information for Vertical Handover Decision Algorithms,” in 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013). IEEE, 2013, pp. 455–460. [152] S. F. Yunas, M. Valkama, and J. Niemelä, “Spectral and Energy Efficiency of Ultra-Dense Networks under Different Deployment Strategies,” IEEE Communications Magazine, vol. 53, no. 1, pp. 90–100, 2015. [153] S. I. Goudar, S. C. Chit, B. Mounira, M. Radia, and S. Hassan, “Implementation of an Offloading Strategy in Heterogeneous Environment,” The 4th International Conference on Internet Applications, Protocols and Services (NETAPPS), 2015. [154] 3GPP, “QoS Concepts and Architecture,” TS22.107, 2005. [155] J. Kurose and K. Ross, Computer Networks: A Top Down Approach Featuring the Internet. Pearson Addison Wesley, 2012. [156] J. F. Kurose, Computer Networking: A Top-Down Approach Featuring the Internet, 3rd Edition. Pearson Education India, 2005. [157] T. L. Saaty and L. G. Vargas, Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. Springer Science & Business Media, 2012, vol. 175. [158] Y. Wind and T. L. Saaty, “Marketing Applications of the Analytic Hierarchy Process,” Management science, vol. 26, no. 7, pp. 641–658, 1980. [159] T. L. Saaty and M. Takizawa, “Dependence and Independence: From Linear Hierarchies to Nonlinear Networks,” European Journal of Operational Research, vol. 26, no. 2, pp. 229–237, 1986. [160] R. W. Saaty, “The Analytic Hierarchy Process What it is and How it is Used,” Mathematical modelling, vol. 9, no. 3, pp. 161–176, 1987. [161] T. L. Saaty, “Fundamentals of decision making and priority theory with the ahp,” 1994. [162] P. N. Tran and N. Boukhatem, “Comparison of MADM Decision Algorithms for Interface Selection in Heterogeneous Wireless Networks,” in 16th International Conference on Software, Telecommunications and Computer Networks, SoftCOM. IEEE, 2008, pp. 119–124. [163] K. Savitha and C. Chandrasekar, “Vertical Handover decision schemes using SAW and WPM for Network selection in Heterogeneous Wireless Networks,” arXiv preprint arXiv:1109.4490, 2011. [164] 3GPP, “LTE Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2 (3GPP TS 36.300 version 11.5.0 Release 11) ,” Tech. Rep., 2013.

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