The energy demands of Ethernet links have been an active focus of research in the recent years. This work has enabled a new generation of energy-efficient Ethernet (EEE) interfaces able to adapt their power consumption to the actual traffic demands, thus yielding significant energy savings. With the energy consumption of single network connections being a solved problem, in this paper, we focus on the energy demands of link aggregates that are commonly used to increase the capacity of a network connection. We build on known energy models of single EEE links to derive the energy demands of the whole aggregate as a function on how the traffic load is spread among its powered links. We then provide a practical method to share the load that minimizes overall energy consumption with controlled packet delay and prove that it is valid for a wide range of EEE links. Finally, we validate our method with both synthetic and real traffic traces captured in Internet backbones.
There are several areas where energy can be saved in the current Internet that were first identified in @cite_31 . The existence of spare installed capacity was one of the identified aspects. Several works proposed to power off unused links during low load periods concentrating traffic on just a few network paths @cite_19 @cite_29 @cite_23 @cite_6 @cite_15 . Of all these proposals, @cite_23 @cite_6 also take into consideration aggregated links between two network devices. However, all these works focus on long timescales, usually hours, while we are interested in much lower timescales, as such, both approaches can be seen as complementary. Links (and network paths) can be powered off when the long-term traffic load is low enough, while, for the short timescales, another approach should be used to reduce the energy usage of those links in the aggregate that remain active.
@cite_15 @cite_29 @cite_6 @cite_19 @cite_23 @cite_31
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Rapid growth of ICT (Information Communication Technologies) energy consumption involves the need for proposing new mechanisms to enhance their energy efficiency. Focusing on energy consumption of networking equipment, this paper presents a study to achieve a tradeoff between the amount of energy that could be saved in wired networks and the discrete number of energy levels to be implemented by line cards. We use bio-inspired computing based on GA (Genetic Algorithms) and PSO (Particle Swarm Optimization) in order to assess the most suitable network configurations in terms of energy savings for different-sized networks such as NSFNet, Geant and AT&T. Results show a comparison between both bio-inspired algorithms in which, although GA produces better results, PSO achieves a reduction in computation time with an optimality gap below 1.7 . From a practical point of view, a limited number, such as four energy levels, is enough to achieve significant reductions in energy consumption. Recent data confirm that the power consumption of the information and communications technologies (ICT) and of the Internet itself can no longer be ignored, considering the increasing pervasiveness and the importance of the sector on productivity and economic growth. Although the traffic load of communication networks varies greatly over time and rarely reaches capacity limits, its energy consumption is almost constant. Based on this observation, energy management strategies are being considered with the goal of minimizing the energy consumption, so that consumption becomes proportional to the traffic load either at the individual-device level or for the whole network. The focus of this paper is to minimize the energy consumption of the network through a management strategy that selectively switches off devices according to the traffic level. We consider a set of traffic scenarios and jointly optimize their energy consumption assuming a per-flow routing. We propose a traffic engineering mathematical programming formulation based on integer linear programming that includes constraints on the changes of the device states and routing paths to limit the impact on quality of service and the signaling overhead. We show a set of numerical results obtained using the energy consumption of real routers and study the impact of the different parameters and constraints on the optimal energy management strategy. We also present heuristic results to compare the optimal operational planning with online energy management operation . According to several studies, the power consumption of the Internet accounts for up to 10 of the worldwide energy consumption and is constantly increasing. The global consciousness on this problem has also grown, and several initiatives are being put into place to reduce the power consumption of the ICT sector in general. In this paper, we face the problem of minimizing power consumption for Internet service provider (ISP) networks. In particular, we propose and assess strategies to concentrate network traffic on a minimal subset of network resources. Given a telecommunication infrastructure, our aim is to turn off network nodes and links while still guaranteeing full connectivity and maximum link utilization constraints. We first derive a simple and complete formulation, which results into an NP-hard problem that can be solved only for trivial cases. We then derive more complex formulations that can scale up to middle-sized networks. Finally, we provide efficient heuristics that can be used for large networks. We test the effectiveness of our algorithms on both real and synthetic topologies, considering the daily fluctuations of Internet traffic and different classes of users. Results show that the power savings can be significant, e.g., larger than 35 . The paper copes with the reduction of network power consumption by the definition of new routing algorithms, able to take into account the energy consumed by the network devices. In particular, based on the power consumption characterization of the network devices obtained using the Energy Profile (EP) concept, the paper presents the analysis of the exact solution of the Energy Aware Routing (EAR) problem solved with a Mixed Integer Programming solver. The analysis is aimed at evaluating the impact on the performance of three relevant aspects of the problem: the approximation of the actual EP, the traffic load and the topology of the network. Furthermore, the paper proposes a heuristic solution of the EAR, denoted as Dijkstra-based Power Aware Routing Algorithm (DPRA), defined in order to cope with the complexity of the exact solution. In this paper we examine the somewhat controversial subject of energy consumption of networking devices in the Internet, motivated by data collected by the U.S. Department of Commerce. We discuss the impact on network protocols of saving energy by putting network interfaces and other router & switch components to sleep. Using sample packet traces, we first show that it is indeed reasonable to do this and then we discuss the changes that may need to be made to current Internet protocols to support a more aggressive strategy for sleeping. Since this is a position paper, we do not present results but rather suggest interesting directions for core networking research. The impact of saving energy is huge, particularly in the developing world where energy is a precious resource whose scarcity hinders widespread Internet deployment.