Abstract
As two promising paradigms in next generation cellular systems, service function chaining (SFC) and mobile edge computing (MEC) have attracted great interests, and would bring more delay-sensitive services to users in proximity. Nevertheless, owing to time-varying channel conditions and finite server resources, the SFC deployment in edge networks is nontrivial. In this work, leveraging both the coordinated multiple points (CoMP)-based zero-forcing beamforming and ℓp (0 < p < 1) norm-based successive convex approximation (SCA) methods, we investigate the SFC deployment in the edge. First, under the constraints of processing and link capacity, transmission power and service function ordering, we build a mixed-integer nonlinear programming (MINLP)-based cost optimization problem, to minimize both the flow and power cost. Then, using the dirty paper-based CoMP zero-forcing beamforming method, the interference among SFSs is canceled, and the original problem is recast as a interference-free one. Next, the ℓp (0 < p < 1) norm-based SCA method works to produce a series of convex subproblem, the iterative solution of which is proved to converge to optimal solution of original one at a linear convergence rate. Finally, numerical results are used to validate proposed method, showing that the wireless resource management deserves special interests in the SFC deployment in edge networks.
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