Energy and Cost Efficient Resource Allocation for Blockchain-Enabled NFV

Network function virtualization (NFV) is a promising technology to make 5G networks flexible and agile. NFV decreases operators’ OPEX and CAPEX by decoupling the physical hardware from the functions they perform. In NFV, users’ service request can be viewed as a service function chain (SFC) consisting of several virtual network functions (VNFs) which are connected through virtual links. Resource allocation in NFV is done through a centralized authority called NFV Orchestrator (NFVO). This centralized authority suffers from some drawbacks such as single point of failure and security. Blockchain (BC) technology is able to address these problems by decentralizing resource allocation. The drawbacks of NFVO in NFV architecture and the exceptional BC characteristics to address these problems motivate us to focus on NFV resource allocation to users’ SFCs without the need for an NFVO. To this end, we assume there are two types of users: users who send SFC requests (SFC requesting users) and users who perform mining process (miner users). For SFC requesting users, we formulate NFV resource allocation (NFV-RA) problem as a multi-objective problem to minimize the energy consumption and utilized resource cost, simultaneously. To address this problem, we propose an Approximation-based Resource Allocation algorithm (ARA) using Majorization-Minimization approximation method to convexify NFV-RA problem. Furthermore, due to the high complexity of ARA algorithm, we propose a low complexity Hungarian-based Resource Allocation (HuRA) algorithm using Hungarian algorithm for server allocation. Through the simulation results, we show that our proposed ARA and HuRA algorithms achieve near-optimal performance with lower computational complexity. Also, ARA algorithm outperforms the existing algorithms in terms of number of active servers, energy consumption, and average latency. Moreover, the mining process is the foundation of BC technology. In wireless networks, mining is performed by resource-limited mobile users. Since the mining process requires high computational complexity, miner users cannot perform it alone. So, in this article, we assume that miner users can perform mining process with participating of other users. For mining process, the problem of minimizing the energy consumption and cost of users’ processing resources is formulated as a linear programming problem that can be optimally solved in polynomial time.