Mobile Cloud Storage Over 5G: A Mechanism Design Approach

被引:6
作者
Siddavaatam, Richa [1 ]
Woungang, Isaac [1 ]
Carvalho, Glaucio H. S. [1 ]
Anpalagan, Alagan [2 ]
机构
[1] Ryerson Univ, Dept Comp Sci, Toronto, ON M5B 2K3, Canada
[2] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada
来源
IEEE SYSTEMS JOURNAL | 2019年 / 13卷 / 04期
基金
加拿大自然科学与工程研究理事会;
关键词
5G wireless network; mobile cloud storage; mobile edge computing (MEC); mobile cloud computing (MCC); radio resource management (RRM) design; OPTIMIZATION; ALLOCATION; RADIO;
D O I
10.1109/JSYST.2019.2908391
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to meet the increasing demand for the data storage, 5G wireless networks embodying mobile edge computing (MEC) features arise as a compelling solution. In this paper, the dense heterogeneous network (HetNet) and the MEC infrastructure are exploited to propose a mobile cloud storage framework that minimizes the data transmission delay. The proposed framework is composed of two parts: A data management with error correction (DMEC) scheme, and a radio resource management (RRM) scheme. The DMEC scheme, derived from the redundant array of inexpensive disks (RAID) technology, is implemented in the user equipment (UE) side, and it intelligently exploits the overlapping coverage of HetNet to minimize the transmission delay. On the other hand, the RRM scheme, based on mechanism design, presents the physical resource block allocation problem as a graph coloring problem and performs the radio resource allocation in multiuser scenario to maximize the network performance. The RRM scheme also comprises a pricing algorithm, which calculates the price a UE needs to pay for the resources. The proposed RRM scheme exhibits several desirable characteristics such as incentive compatibility, efficiency, and truthfulness, all derived from the Vickrey-Clarke-Groves mechanism. Simulation results are presented, showing that the proposed framework when compared to baseline techniques, minimizes the transmission delay by 10(2) % which places our proposal as effective and efficient solution for the mobile cloud storage problem.
引用
收藏
页码:4060 / 4071
页数:12
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