Optimal radio resource allocation for mobile task offloading in cellular networks

The increasing capabilities of mobile devices (MDs) enable users to run desktoplevel applications and tasks anywhere. However, the local execution of resource-demanding mobile tasks, such as real-time rendering in 3D gaming, may result in poor performance and short battery lifetime on MDs. One solution to the resource scarcity problem on MDs is to offload resource-demanding mobile tasks to surrogates, which are remote servers with stronger capabilities. When multiple MDs in the same cell attempt to offload mobile tasks to surrogates through a cellular network, the communication latencies for data transmissions may be high due to limited radio resources. To improve the offloading performance of mobile tasks, the limited radio resources should be carefully scheduled to reduce the communication latencies of data transmissions. As motivated, we pose the optimal radio resource allocation problem for the mobile task offloading in cellular networks, and solve the problem. Moreover, extensive numerical results show the performance comparison of the optimal radio resource allocation plan and two baseline plans.

[1]  Shoichi Noguchi,et al.  An Analysis of the M/G/1 Queue Under Round-Robin Scheduling , 1971, Oper. Res..

[2]  Rajeev Agrawal,et al.  Joint scheduling and resource allocation in uplink OFDM systems for broadband wireless access networks , 2009, IEEE Journal on Selected Areas in Communications.

[3]  Song Ci,et al.  Quality-driven cross-layer optimized video delivery over LTE , 2010, IEEE Communications Magazine.

[4]  Mads Darø Kristensen,et al.  Scavenger: Transparent development of efficient cyber foraging applications , 2010, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[5]  Geoffrey Ye Li,et al.  Joint User Pairing and Resource Allocation for LTE Uplink Transmission , 2012, IEEE Transactions on Wireless Communications.

[6]  Kun Yang,et al.  Performance Analysis of Fault-Tolerant Offloading Systems for Pervasive Services in Mobile Wireless Environments , 2008, 2008 IEEE International Conference on Communications.

[7]  Tao Jiang,et al.  Performance optimization for cyber foraging network via dynamic spectrum allocation , 2011, 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[8]  Sujit Dey,et al.  Adaptive Mobile Cloud Computing to Enable Rich Mobile Multimedia Applications , 2013, IEEE Transactions on Multimedia.

[9]  Yung-Hsiang Lu,et al.  Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? , 2010, Computer.

[10]  Alan Messer,et al.  Adaptive offloading for pervasive computing , 2004, IEEE Pervasive Computing.

[11]  Dusit Niyato,et al.  A Dynamic Offloading Algorithm for Mobile Computing , 2012, IEEE Transactions on Wireless Communications.

[12]  Mohsen Sharifi,et al.  A Survey and Taxonomy of Cyber Foraging of Mobile Devices , 2012, IEEE Communications Surveys & Tutorials.

[13]  Jiangzhou Wang,et al.  Chunk-Based Resource Allocation in OFDMA Systems—Part II: Joint Chunk, Power and Bit Allocation , 2012, IEEE Transactions on Communications.

[14]  Kun Yang,et al.  On effective offloading services for resource-constrained mobile devices running heavier mobile Internet applications , 2008, IEEE Communications Magazine.

[15]  Emmanouel A. Varvarigos,et al.  Fair Scheduling Algorithms in Grids , 2007, IEEE Transactions on Parallel and Distributed Systems.