Optimized device centric aggregation mechanisms for mobile devices with multiple wireless interfaces

Abstract Wireless broadband technologies and services are witnessing exponential growth to meet the demands of mobile users. State-of-the-art wireless networks are evolving with enhancements spanning all protocol layers and all network components from radio access to core network nodes. This has been coupled with a tremendous transformation of end user mobile devices towards multi-purpose smartphones and tablets with multi-core processing power, extendable memory storage, large battery capacity, and support for a wide range of wireless connectivity options. A standard smartphone currently can support short range Bluetooth and WiFi-Direct connectivity, local area WiFi connectivity, and long range 2G/3G/4G mobile connectivity. This naturally provides opportunities for data aggregation utilizing multiple wireless interfaces simultaneously to enhance device and network performance. In this work, we present the design, implementation, and testing of optimized device-centric data aggregation mechanisms for both file downloading and video streaming applications. The main novelty of the proposed mechanisms is their device-centric design, which makes them practical and feasible without any changes to wireless standards; moreover, they are scalable to support any number of wireless interfaces whereas previous related work has dealt with devices having two interfaces only. To demonstrate the effectiveness of the proposed mechanisms in terms of performance gains and practical feasibility, we develop an experimental testbed using Android devices and perform extensive testing for several network scenarios.

[1]  Kinda Khawam,et al.  A Hybrid Approach for Radio Access Technology Selection in Heterogeneous Wireless Networks , 2013, Wireless Personal Communications.

[2]  Rocky K. C. Chang,et al.  Measuring the quality of experience of HTTP video streaming , 2011, 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops.

[3]  Mykhailo Klymash,et al.  A survey of converging solutions for heterogeneous mobile networks , 2014, IEEE Wireless Communications.

[4]  Halim Yanikomeroglu,et al.  Device-to-device communication in 5G cellular networks: challenges, solutions, and future directions , 2014, IEEE Communications Magazine.

[5]  Aleksandr Ometov,et al.  A unifying perspective on proximity-based cellular-assisted mobile social networking , 2016, IEEE Communications Magazine.

[6]  Klaus I. Pedersen,et al.  Dual connectivity for LTE small cell evolution: functionality and performance aspects , 2016, IEEE Communications Magazine.

[7]  Meryem Simsek,et al.  When cellular meets WiFi in wireless small cell networks , 2013, IEEE Communications Magazine.

[8]  Kameswari Chebrolu,et al.  Bandwidth aggregation for real-time applications in heterogeneous wireless networks , 2006 .

[9]  Songqing Chen,et al.  Help your mobile applications with fog computing , 2015, 2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking - Workshops (SECON Workshops).

[10]  Zaher Dawy,et al.  Energy-throughput tradeoffs in cellular/WiFi heterogeneous networks with traffic splitting , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[11]  Qixun Zhang,et al.  Design and Performance Analysis of a Fairness-Based License-Assisted Access and Resource Scheduling Scheme , 2016, IEEE Journal on Selected Areas in Communications.

[12]  Sanaa Sharafeddine,et al.  Practical device-centric WiFi/cellular link aggregation mechanism for mobile devices , 2015, 2015 11th International Conference on Innovations in Information Technology (IIT).

[13]  Bernard Cousin,et al.  A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks , 2015, IEEE Journal on Selected Areas in Communications.

[14]  Koichi Asatani,et al.  A new application-level link aggregation and its implementation on Android terminals , 2012, Wirel. Commun. Mob. Comput..

[15]  Joongheon Kim,et al.  The Useful Impact of Carrier Aggregation: A Measurement Study in South Korea for Commercial LTE-Advanced Networks , 2017, IEEE Vehicular Technology Magazine.

[16]  Marco Conti,et al.  Data Offloading Techniques in Cellular Networks: A Survey , 2015, IEEE Communications Surveys & Tutorials.

[17]  Fangli Xu,et al.  Overview of 3GPP LTE-advanced carrier aggregation for 4G wireless communications , 2012, IEEE Communications Magazine.

[18]  H. Anthony Chan,et al.  Bandwidth aggregation in heterogeneous wireless networks: A survey of current approaches and issues , 2012, J. Netw. Comput. Appl..

[19]  Drakoulis Martakos,et al.  A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks , 2012, Appl. Soft Comput..

[20]  Khaled A. Harras,et al.  OSCAR: a deployable adaptive mobile bandwidth sharing and aggregation system , 2014, MobiQuitous.

[21]  Bheemarjuna Reddy Tamma,et al.  A Dynamic Link aggregation Scheme for heterogeneous wireless networks , 2014, 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).

[22]  Zaher Dawy,et al.  An optimized approach to video traffic splitting in heterogeneous wireless networks with energy and QoE considerations , 2017, J. Netw. Comput. Appl..

[23]  Jong-Ok Kim.  Feedback-based traffic splitting for wireless terminals with multi-radio devices , 2010, IEEE Transactions on Consumer Electronics.

[24]  Khaled A. Harras,et al.  An optimal deployable bandwidth aggregation system , 2013, Comput. Networks.

[25]  Jonathan Ling,et al.  Enhanced capacity and coverage by Wi-Fi LTE integration , 2015, IEEE Communications Magazine.

[26]  Nazim Agoulmine,et al.  A user-centric and context-aware solution to interface management and access network selection in heterogeneous wireless environments , 2008, Comput. Networks.

[27]  Zhang Xiong,et al.  TCP-FIT: An improved TCP algorithm for heterogeneous networks , 2016, J. Netw. Comput. Appl..

[28]  Nada Chendeb Taher,et al.  Network-Centric Versus User-Centric Multihoming Strategies in LTE/WiFi Networks , 2017, IEEE Transactions on Vehicular Technology.

[29]  Juan Antonio Cordero,et al.  Multi-path TCP performance evaluation in dual-homed (wired/wireless) devices , 2016, J. Netw. Comput. Appl..

[30]  Ming Wang,et al.  Energy-Efficient Bandwidth Aggregation for Delay-Constrained Video Over Heterogeneous Wireless Networks , 2017, IEEE Journal on Selected Areas in Communications.