A Dynamic Reliability-Aware Service Placement for Network Function Virtualization (NFV)

Abstract

Network softwarization is one of the major paradigm shifts in the next generation of networks. It enables programmable and flexible management and deployment of the network. Network function virtualization (NFV) is referred to the deployment of software functions running on commodity servers instead of traditional hardware-based middle-boxes. It is an example of network softwarization. In NFV, a service is defined as a chain of software functions named service chain function (SFC). The process of allocating the resources of servers to the services, called service placement, is the most challenging mission in NFV. Dynamic nature of the service arrivals and departures as well as meeting the service level agreement make the service placement problem even more challenging. In this paper, we propose a model for dynamic reliability-aware service placement based on the simultaneous allocation of the main and backup servers. Then, we formulate the dynamic reliability-aware service placement as an infinite horizon Markov decision process (MDP), which aims to minimize the placement cost and maximize the number of admitted services. In the proposed MDP, the number of active services in the network is considered to be the state of the system, and the state of the idle resources is estimated based on it. Also, the number of possible admitted services is considered as the action of the presented MDP. To evaluate each possible action in the proposed MDP, we use a sub-optimal method based on the Viterbi algorithm named Viterbi-based Reliable Static Service Placement (VRSSP) algorithm. We determine the optimal policy based on value iteration method using an algorithm named VRSSP-based Value Iteration (VVI) algorithm. Eventually, through the extensive simulations, the superiority of the proposed model for dynamic reliability-aware service placement compared to the static solutions is inferred.