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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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 . 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 . We focus on energy saving in 802.11-based WLANs. Previous work has shown that, on the one hand, 802.11 wireless interfaces consume a significant amount of energy, on the other hand the use of current power management schemes can severely degrade the QoS performance of several Internet-based applications. Furthermore, the energy spent by wireless devices may even increase when the standard 802.11 power-saving mode (PSM) is implemented. These facts suggest that other solutions to energy saving are highly needed.In this paper, we consider the 802.11 distributed access scheme and we propose a novel approach that enables a station to enter a low-power operational state during channel contention. More specifically, our technique exploits the virtual carrier sense mechanism and the backoff function specified in the IEEE 802.11 DCF, so that a station can dramatically reduce its energy consumption without significant degradation of the QoS performance. To efficiently implement our mechanism, a low-power state with negligible transition time into the active state must be identified. This can be any of the non-standard, low-power states defined by proprietary solutions in the current or next-generation products [7,15,22]. By using the network simulator ns2, we evaluate the performance improvement that is obtained when the proposed mechanism is implemented, against the results attained through the standard DCF. The results show that we can achieve a reduction in energy consumption as large as 80 and 28 under, respectively, UDP and TCP traffic. According to recent research, the current Internet wastes energy due to an un-optimized network design, which does not consider the energy consumption of network elements such as routers and switches. Looking toward energy saving networks, a generalized problem called the energy consumption minimized network (EMN) had been proposed. However, due to the NP-completeness of this problem, it requires a considerable amount of time to obtain the solution, making it practically intractable for large-scale networks.In this paper, we re-formulate the NP-complete EMN problem into a simpler one using a newly defined concept called 'traffic centrality'. We then propose a new ant colony-based self-adaptive energy saving routing scheme, referred to as A-ESR, which exploits the ant colony optimization (ACO) method to make the Internet more energy efficient. The proposed A-ESR algorithm heuristically solves the re-formulated problem without any supervised control by allowing the incoming flows to be autonomously aggregated on specific heavily-loaded links and switching off the other lightly-loaded links. Additionally, the A-ESR algorithm adjusts the energy consumption by tuning the aggregation parameter s, which can dramatically reduce the energy consumption during nighttime hours (at the expense of tolerable network delay performance). Another promising capability of this algorithm is that it provides a high degree of self-organizing capabilities due to the amazing advantages of the swarm intelligence of artificial ants. The simulation results in real IP networks show that the proposed A-ESR algorithm performs better than previous algorithms in terms of its energy efficiency. The results also show that this efficiency can be adjusted by tuning s.