期刊
IEEE TRANSACTIONS ON MOBILE COMPUTING
卷 21, 期 1, 页码 196-210出版社
IEEE COMPUTER SOC
DOI: 10.1109/TMC.2020.3006507
关键词
Cloud computing; Approximation algorithms; Delays; Mobile computing; Mobile handsets; Prediction algorithms; Servers; Mobile Edge computing; network function virtualization; VNF instance deployment; virtualized service provisioning; approximation and online algorithms; delay-sensitive request admission; utility gain maximization; user mobility; cloudlets or edge-clouds; resource allocations and provisioning in MEC; optimization problems
资金
- Australian Research Council [DP200101985]
- Research Grants Council of Hong Kong [CityU 11214316]
- Australian Research Council [DP200101985] Funding Source: Australian Research Council
Mobile edge computing (MEC) is a promising technology that brings cloud services to the network edge, providing network services for mobile users. Virtualized network services improve user experience and simplify network service deployment and resource management. However, providing reliable and seamless virtualized network services for mobile users in an MEC network is a challenging task.
Mobile edge computing (MEC) has emerged as a promising technology to push the cloud frontier to the network edge, provisioning network services in proximity of mobile users. Serving users at edge clouds can reduce service latency, lower operational cost, and improve network resource availability. Along with the MEC technology, network function virtualization (NFV) is another promising technique that implements various network service functions as pieces of software in cloudlets (servers or clusters of servers). Providing virtualized network service for mobile users can improve user service experience, simplify network service deployment, and ease network resource management. However, mobile users move in networks arbitrarily, and different users usually request different services with different resource demands and delay requirements. It thus poses a great challenge to providing reliable and seamless virtualized network services for mobile users in an MEC network while meeting their individual delay requirements, subject to resource capacities on the network. In this paper, we focus on the provisioning of virtualized network function services for mobile users in MEC that takes into account user mobility and service delay requirements. We first formulate two novel optimization problems of user service request admissions with the aims to maximize the accumulative network utility and accumulative network throughput for a given time horizon, respectively. We then devise a constant approximation algorithm for the utility maximization problem. We also develop an online algorithm for the accumulative throughput maximization problem. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising.
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