On the wireless virtualization with QoE constraints

Wireless virtualization is emerging as a new paradigm to improve wireless spectrum utilization by subleasing radio frequency (RF) channels through slicing. This paper investigates wireless virtualization where wireless resources for virtual wireless networks adapted based on availability of leasable RF slices as well as the demands from the users of virtual wireless networks. The user utilities are subject to quality‐of‐experience requirements such as coverage, rate, mobility, and delay requirements. With the help of software defined network controller, wireless infrastructure providers (WIPs) slice their RF bands to sublease those slices to mobile virtual network operators (MVNOs). In wireless virtualization, MVNOs work as independent service provides, and thus, the end users negotiate directly to MVNOs regardless of WIPs used behind the scene (this concept is analogous to the Uber being a taxi company without owning any vehicles). The performance of the proposed approach is evaluated with the help of numerical results obtained from simulations by using different metrics such as percentage of RF band of WIP, outage probability, and data rate.

[1]  Sanjay Kumar,et al.  Virtual WiFi: bring virtualization from wired to wireless , 2011, VEE '11.

[2]  Christine Morin,et al.  A Survey of Recoverable Distributed Shared Virtual Memory Systems , 1997, IEEE Trans. Parallel Distributed Syst..

[3]  C. Robusto The Cosine-Haversine Formula , 1957 .

[4]  Raouf Boutaba,et al.  A survey of network virtualization , 2010, Comput. Networks.

[5]  Danda B. Rawat,et al.  Cyber-Physical Systems: From Theory to Practice , 2015 .

[6]  Luiz A. DaSilva,et al.  Spectrum Without Bounds, Networks Without Borders , 2014, Proceedings of the IEEE.

[7]  Sachin Katti,et al.  SoftRAN: software defined radio access network , 2013, HotSDN '13.

[8]  Vikram Srinivasan,et al.  CloudIQ: a framework for processing base stations in a data center , 2012, Mobicom '12.

[9]  Andreas Timm-Giel,et al.  LTE mobile network virtualization , 2011, Mob. Networks Appl..

[10]  Sachin Shetty,et al.  Dynamic Spectrum Access for Wireless Networks , 2015, SpringerBriefs in Electrical and Computer Engineering.

[11]  Andreas Timm-Giel,et al.  LTE wireless virtualization and spectrum management , 2010, WMNC2010.

[12]  Tho Le-Ngoc,et al.  SpringerBriefs in Computer Science , 2013 .

[13]  Danda B. Rawat,et al.  Wireless network virtualization for enhancing security: Status, challenges and perspectives , 2016, SoutheastCon 2016.

[14]  Danda B. Rawat Game theoretic approach for wireless virtualization with coverage and QoS constraints , 2017, 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[15]  Dong Hee Shin,et al.  Overlay networks in the West and the East: a techno-economic analysis of mobile virtual network operators , 2008, Telecommun. Syst..

[16]  Sampath Rangarajan,et al.  NVS: A Substrate for Virtualizing Wireless Resources in Cellular Networks , 2012, IEEE/ACM Transactions on Networking.

[17]  Sampath Rangarajan,et al.  CellSlice: Cellular wireless resource slicing for active RAN sharing , 2013, 2013 Fifth International Conference on Communication Systems and Networks (COMSNETS).

[18]  Herbert W. Yankee,et al.  Engineering Graphics , 1970 .

[19]  Danda B. Rawat,et al.  Payoff Optimization Through Wireless Network Virtualization for IoT Applications: A Three Layer Game Approach , 2019, IEEE Internet of Things Journal.

[20]  Md. Motaharul Islam,et al.  A Survey on Virtualization of Wireless Sensor Networks , 2012, Sensors.

[21]  Luiz A. DaSilva,et al.  Customized services over virtual wireless networks: The path towards networks without borders , 2013, 2013 Future Network & Mobile Summit.

[22]  Raouf Boutaba,et al.  Network virtualization: state of the art and research challenges , 2009, IEEE Communications Magazine.

[23]  Yunnan Wu,et al.  A Survey on Network Codes for Distributed Storage , 2010, Proceedings of the IEEE.