Cooperative Service Placement and Request Routing in Mobile Edge Networks for Latency-Sensitive Applications

被引:8
|
作者
Somesula, Manoj Kumar [1 ]
Mothku, Sai Krishna [2 ]
Annadanam, Sudarshan Chakravarthy [3 ]
机构
[1] Natl Inst Technol Jalandhar, Dept Comp Sci & Engn, Jalandhar 144027, Punjab, India
[2] Natl Inst Technol Tiruchirappalli, Tiruchirappalli 620015, Tamil Nadu, India
[3] Natl Inst Technol Calicut, Dept Comp Sci & Engn, Calicut 673601, Kerala, India
来源
IEEE SYSTEMS JOURNAL | 2023年 / 17卷 / 03期
关键词
Circular convex set (CCS); heuristic algorithm; mobile edge computing (MEC)s; request routing; service placement; APPROXIMATIONS; COMMUNICATION; OPTIMIZATION; COMPUTATION;
D O I
10.1109/JSYST.2023.3260028
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The emergence of mobile applications like self-driving cars, networked gaming, virtual reality, and augmented reality has created a demand for computation-intensive and latency critical applications. The dense deployment of base stations (BSs) makes the overlapping coverage of BS that induces the placement of services and routing the requests to the appropriate node is a challenging issue. Further, the limited resources at the edge node invite additional problems of allocating the existing limited edge resources cooperatively to fulfil the user demands. To address the problems mentioned above, we formulate the cooperative service placement and routing problem by placing the diversified latency critical services to maximize the time utility with the deadline and resource constraints. The problem is formulated as an integer linear programming problem for cooperative service placement in mobile edge networks. A greedy and randomized rounding technique is presented to solve the service caching and request routing problems decomposed from the proposed problem. Further, a heuristic algorithm based on the circular convex set is presented to solve the proposed NP-hard problem. Extensive simulation results demonstrate that the proposed cooperative service placement schemes significantly improve the delay, cache hit ratio, load on cloud, and time utility performance compared with existing mechanisms.
引用
收藏
页码:4050 / 4061
页数:12
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