NFV/SDN Enabled Architecture for Efficient Adaptive Management of Renewable and Non-Renewable Energy

Abstract

Ever-increasing energy consumption, the depletion of non-renewable resources, the climate impact associated with energy generation, and finite energy-production capacity are important concerns that drive the urgent creation of new solutions for energy management. In this regard, by leveraging the massive connectivity provided by emerging 5G communications, this paper proposes a long-term sustainable Demand-Response (DR) architecture for the efficient management of available energy consumption for Internet of Things (IoT) infrastructures. The proposal uses Network Functions Virtualization (NFV) and Software Defined Networking (SDN) technologies as enablers and promotes the primary use of energy from renewable sources. Associated with architecture, this paper presents a novel consumption model conditioned on availability and in which the consumers are part of the management process. To efficiently use the energy from renewable and non-renewable sources, several management strategies are herein proposed, such as prioritization of the energy supply and workload scheduling using time-shifting capabilities. The complexity of the proposal is analyzed in order to present an appropriate architectural framework. The energy management solution is modeled as an Integer Linear Programming (ILP) and, to verify the improvements in energy utilization, an algorithmic solution and its evaluation are presented. Finally, open research problems and application scenarios are discussed.

Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies

“…Use of a finite and discrete-time window for performing the time shifting (forward and backward) for the service execution. In this regard, in a preliminary study [19], we proved that the use small time shifting intervals (e.g., intervals up to two or three time slots) is enough to achieve considerable improvements in energy use (e.g., 100% energy utilization and improved service processing). In addition, a small time shifting interval is preferred because increasing this parameter produces a non-polynomial increase in the complexity of the optimal energy management problem, as demonstrated in [19].…”

“…In this work, we chose the last option, anticipating a future in which the penetration of green energy allows meeting all energy demand and requires adaptive mechanisms to leverages its generation. Moreover, we validated this approach in [19]. The considerations of the architectural framework and the enabling technologies needed for energy management, as well as the interaction between generation and consumption sides presented in [19], are taken as a baseline for the adaptive energy management solution presented in this paper.…”

“…Moreover, we validated this approach in [19]. The considerations of the architectural framework and the enabling technologies needed for energy management, as well as the interaction between generation and consumption sides presented in [19], are taken as a baseline for the adaptive energy management solution presented in this paper. In this regard, this paper represents an evolution of our previous work in [19] towards an efficient and environmentally friendly energy-management for mobile networks.…”

“…Cost AR comb : Cost function related to the processing of services and defined by Equation (18). • Cost pri comb : Cost function related to the priority level of services and defined by Equation (19). cost Equation (19).…”

An Improved Switch Migration Decision Algorithm for SDN Load Balancing

“…S Oftware Defined Networking (SDN) is known to be a promising architecture that separates control planes and the data plane. One of the applications of SDN is the adaptive energy consumption of IoT infrastructures in the deployment of Internet of Everything [1]. SDN come with a new network architecture that simplifies the network through rapid innovation, flexible management, and programmability such that the behaviors of the system are dynamically customized [2].…”