An Energy Packet Network model for mobile networks with energy harvesting

Abstract

Mobile communications are a powerful contributor to social and economic development worldwide, including in less developed or remote parts of the world. However they are large users of electricity through their base stations, backhaul networks and Cloud servers, so that they have a large environmental impact when they use the electric grid. On the other hand, they could operate with renewable energy sources and thus reduce their CO2 impact and be accessible even in areas where the electric grid is unavailable or unreliable. The counterpart is that intermittent sources of energy, such as photovoltaic and wind, can affect the quality of service (QoS) that is experienced by mobile users. Thus in this paper we model the performance of mobile telecommunications that use intermittent and renewable energy sources. In such cases to analyse the performance of such systems, both the energy supply and the network traffic, can be modeled as random processes, and we develop mathematical models using the Energy Packet Network paradigm, where both data and energy flows are discretised. QoS metrics for the users are computed based on the traffic intensity and the availability of energy.

G-Networks and the Performance of ICT with Renewable Energy

“…In addition, the EPN paradigms use each EP to represent the fixed amount of energy in Joules, which can also be viewed as a pulse of power that lasts a certain time [36]. The amount of energy in such an EP can be small enough to be close to the smallest energy needs of consumers [36,39,41,84], or large enough to be a significant quantity to power large energy consumers [115]. In the latest research [63,117,118], the number of jobs or data packets that can be executed by one single EP is a random variable.…”

“…The EPN approach has been used for system analysis of a backhaul multi-hop connection of a wireless mobile network with energy harvesting [39]. The data or other traffic are carried out as data packets (DPs) rather than jobs.…”

“…The energy packet networks (EPN) [35,39,41,63,81,84,118] is a discrete state-space modeling framework that can analyze the interaction between discrete energy flows and job flows (or packets) in a single system. Energy packets (EPs), jobs and data packets are the customer classes in the EPN.…”

Performance Optimization With Energy Packets

“…Motivated by these considerations, recent work has developed the energy packet network (EPN) paradigm [30]- [32], which is a discrete state-space modeling framework based on G-networks [33], which have a broad range of applications [34], [35] and can be used for evaluating both performance and energy consumption in a system where computer jobs, data in the form of packets, and energy represented by energy packets (EPs), interact in a complex, interconnected computer-communication system. This approach uses queuing theory, so that the joint behavior of discretized energy flows and the flows of computer jobs and data are analyzed within a single model.…”

“…This approach uses queuing theory, so that the joint behavior of discretized energy flows and the flows of computer jobs and data are analyzed within a single model. It was recently used for the analysis of the backhaul of mobile networks operating with intermittent renewable energy [36]. In previous work [37]- [39] optimization algorithms were developed on the basis of queuing networks, to dispatch network packets and minimize composite cost functions combining overall network energy consumption and QoS.…”