Energy Cost Minimization by Joint Radio and NFV Resource Allocation: E2E QoS Framework
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In this paper, we propose an end to end joint radio and network function virtualization (NFV) resource allocation for next generation networks providing different types of services with different requirements in terms of latency and data rate. We consider both the access and core parts of the network, and formulate a novel optimization problem whose aim is to perform the radio resource allocation jointly with virtual network function (VNF) embedding, scheduling, and resource allocation such that the network cost, defined as the consumed energy and the number of utilized network servers, is minimized. The proposed optimization problem is non-convex, NP-hard, and mathematically intractable, and hence, we adopt the alternative search method (ASM) to decouple the main problem into some sub-problems of lower complexity. Moreover, w propose a novel heuristic algorithm for embedding and scheduling of VNFs by proposing a novel admission control (AC) algorithm. Then, we compare the performance of the proposed algorithm with a greedy-based solution in terms of the acceptance ratio and the number of active servers. Our simulation results show that the proposed heuristic algorithm outperforms the conventional ones by approximately 8
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