  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.
