Abstract
With the increasing popularity of the Internet, user requests for cloud applications have dramatically increased. The traditional model of relying on dedicated hardware to implement cloud applications has not kept pace with the rapid growth in demand. Network function virtualization (NFV) architecture emerged at a historic moment. By moving the implementation of functions to software, a separation of functions and hardware was achieved. Therefore, when user demand increases, cloud application providers only need to update the software; the underlying hardware does not change, which can improve network scalability. Although NFV solves the problem of network expansion, deploying service function chains into the underlying network to optimize indicators remains an important research problem that requires consideration of delay, reliability, and power consumption. In this paper, we consider the optimization of power consumption with the premise of guaranteeing a certain virtual function link yield. We propose an efficient algorithm that is based on first-fit and greedy algorithms to solve the problem. The simulation results show that the proposed algorithm substantially improves the path-finding efficiency, achieves a higher request acceptance ratio and reduces power consumption while provisioning the cloud applications. Compared with the baseline algorithm, the service function chain (SFC) acceptance ratio of our proposed algorithms improves by a maximum of approximately 15%, our proposed algorithm reduces the power consumption by a maximum of approximately 15%, the average link load ratio of our proposed algorithm reduces by a maximum of approximately 20%, and the average mapped path length of our proposed algorithm reduces by a maximum of approximately 1.5 hops.
Highlights
Traditional cloud application providers (CAPs) deploy network function via dedicated hardware [1], meaning network function is, closely linked to a device
Network function virtualization (NFV) [2] implements the separation of software and hardware; it overcomes the drawbacks that specific functions cannot be quickly upgraded, due to the attachment of the dedicated hardware in the traditional mode and substantially improves the flexibility and scalability of a network
We introduce the concept of “load balancing” and propose the direction-guided greedy (DGG) algorithm, which is based on the direction-guided FirstFit (DGFF) algorithm
Summary
Traditional cloud application providers (CAPs) deploy network function via dedicated hardware [1], meaning network function is, closely linked to a device. Reducing the power consumption that is used to map the virtual network function can generate lower costs, increase revenue for cloud application providers, and improve commercial competitiveness in industry. We propose the new algorithm direction-guided FirstFit (DGFF), which introduces “direction guidance” This algorithm employs efficient and accurate path-finding strategies that significantly improve its performance in cloud application provisioning. We simulate the proposed algorithm in terms of the SFC total acceptance ratio, SFC average power consumption, average mapped cost, the average running time of the algorithm, average node load ratio and average link load ratio of the network. The remainder of this paper is structured as follows: Section 2 introduces related studies; Section 3 introduces and describes the SFC deployment model; Section 4 proposes a heuristic algorithm to implement energy-saving SFC deployment; Section 5 presents and analyzes the simulation results; and Section 6 concludes the paper
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