Optimized traffic flow assignment in multi-homed, multi-radio mobile hosts

Multi-radio mobile communication devices are increasingly gaining market share due to the diversity of currently deployed and continuously emerging radio access technologies. Multi-homing support in multi-radio terminals, i.e., simultaneous use of two or more radio interfaces, provides improved user experience through increase in available bandwidth capacity and reliability of wireless access. Furthermore, optimized assignment of application traffic flows to available interfaces and radio access bearer services contributes to economic and power consumption efficiency. We study the problem of traffic flow assignment in a mobile node, multi-homed through a set of different technology radio interfaces. We provide an analytical formulation for the problem and prove its hardness through transformation from the Multiple Knapsack Problem with Assignment Restrictions. Problem solutions are approximated with a heuristic algorithm that is based on local search and is characterized by efficient execution times for a wide set of realistic problem sizes. The quality of approximation is rather satisfactory and is evaluated through comparison of heuristic and exact solutions for a large set of randomly generated problem instances. Moreover, an evaluation of the approach through simulation supports these findings and provides an estimation of the associated mobility management overhead that is limited and allows real deployment of the decision mechanism.

[1]  Lazaros F. Merakos,et al.  Toward a generic "always best connected" capability in integrated WLAN/UMTS cellular mobile networks (and beyond) , 2005, IEEE Wireless Communications.

[2]  Carlos A. Coello Coello,et al.  An updated survey of GA-based multiobjective optimization techniques , 2000, CSUR.

[3]  Thierry Ernst,et al.  Motivations and Scenarios for Using Multiple Interfaces and Global Addresses , 2008 .

[4]  Raghupathy Sivakumar,et al.  A Receiver-Centric Transport Protocol for Mobile Hosts with Heterogeneous Wireless Interfaces , 2003, MobiCom '03.

[5]  Randall R. Stewart,et al.  Stream Control Transmission Protocol , 2000, RFC.

[6]  E. Gustafsson,et al.  Always best connected , 2003, IEEE Wirel. Commun..

[7]  Nihat Kasap,et al.  Provider selection and task allocation issues in networks with different QoS levels and all you can send pricing , 2007, Decis. Support Syst..

[8]  Claudio Casetti,et al.  WiSE: Best-Path Selection in Wireless Multihoming Environments , 2007, IEEE Transactions on Mobile Computing.

[9]  Jean-Marie Bonnin,et al.  Automatic Multi-Interface Management Through Profile Handling , 2009, Mob. Networks Appl..

[10]  Vincent W. S. Wong,et al.  Comparison between Vertical Handoff Decision Algorithms for Heterogeneous Wireless Networks , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[11]  T. Noel,et al.  Power performance comparison of heterogeneous wireless network interfaces , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[12]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[13]  Xiaomin Zhu,et al.  A multi-path mechanism for reliable VoIP transmission over wireless networks , 2008, Comput. Networks.

[14]  Raghupathy Sivakumar,et al.  On effectively exploiting multiple wireless interfaces in mobile hosts , 2009, CoNEXT '09.

[15]  Paolo Bellavista,et al.  Mobility-aware Management of Internet Connectivity in Always Best Served Wireless Scenarios , 2009, Mob. Networks Appl..

[16]  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.

[17]  Janardhan R. Iyengar,et al.  Concurrent Multipath Transfer Using SCTP Multihoming Over Independent End-to-End Paths , 2006, IEEE/ACM Transactions on Networking.

[18]  Kameswari Chebrolu,et al.  Bandwidth aggregation for real-time applications in heterogeneous wireless networks , 2006, IEEE Transactions on Mobile Computing.

[19]  Nicolas Montavont,et al.  Flow Bindings in Mobile IPv6 and Nemo Basic Support , 2007 .

[20]  Paolo Toth,et al.  Knapsack Problems: Algorithms and Computer Implementations , 1990 .

[21]  Haiyun Luo,et al.  Flow Scheduling for End-Host Multihoming , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[22]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[23]  Yin Zhang,et al.  Optimizing cost and performance for multihoming , 2004, SIGCOMM '04.

[24]  Milind Dawande,et al.  Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions , 2000, J. Comb. Optim..

[25]  Emmanouel A. Giakoumakis,et al.  Towards flow scheduling optimization in multihomed mobile hosts , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[26]  Li Xiao,et al.  A Survey of Multihoming Technology in Stub Networks: Current Research and Open Issues , 2007, IEEE Network.

[27]  Nalini Venkatasubramanian,et al.  Multi-constraint dynamic access selection in always best connected networks , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[28]  Kang G. Shin,et al.  PRISM: Improving the Performance of Inverse-Multiplexed TCP in Wireless Networks , 2007, IEEE Transactions on Mobile Computing.