Search

This work analyzes a new and very subtle kind of security threat that can affect large-scale cloud-based IT service infrastructures, by exploiting the computational resources of their component data center to waste as much energy as possible. The consequence of these threats ranges from increased costs in the energy bill, to penalization for exceeding the agreed quantity of greenhouse gases (GHG) emissions, up to complete denial of service caused by electrical outages due to power budget exhaustion. We analyzed different types of such attacks with their potential impacts on the energy consumption, modeled their behavior and quantified how current energy-proportional technologies may provide attackers with great opportunities for raising the target facility emissions and costs. These efforts resulted in a simple model with some parametric reference values that can be used to estimate the impact of such attacks also in presence of very large infrastructures containing thousands or millions of servers. [ABSTRACT FROM AUTHOR]

The containment of power consumption and the use of alternative green sources of energy are the new main goals of telecommunication operators, to cope with the rising energy costs, the increasingly rigid environmental standards, and the growing power requirements of modern high-performance networking devices. To address these challenges, we envision the necessity of introducing energy-efficiency and energy-awareness in the design, configuration and management of networks, and specifically in the design and implementation of enhanced control-plane protocols to be used in next generation networks. Accordingly, we focus on research and industrial challenges that foster new developments to decrease the carbon footprint while leveraging the capacities of highly dynamic, ultra-high-speed, networking. We critically discuss current approaches, research trends and technological innovations for the coming green era and we outline future perspectives towards new energy-oriented network planning, protocols and algorithms. We also combine all the above elements into a comprehensive energy-oriented network model within the context of a general constrained routing and wavelength assignment problem framework, and analyze and quantify through ILP formulations the savings that can be attained on the next generation networks. [ABSTRACT FROM AUTHOR]

• Methods for forecasting energy demand and production are proposed. • Predictions contribute to balance and smoothen the electricity intake from the power grid. • Experimental evaluation is performed on data recorded on a real energy-management system. • The ARIMA and TBATS models are configured and then compared with other forecasting methods. Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical prediction methods and compared them with other models on datasets from a household equipped with photovoltaics and an energy management system. The evaluation results have shown a mean absolute error of 73.62 Watts for the TBATS model, which is far better than the one obtained with neural forecasting methods. [ABSTRACT FROM AUTHOR]

Despite the wide deployment of advanced wireless coverage infrastructures, finding the best way for achieving secure mobile communication in every-day's life activities is still an open question. Indeed, a large number of mobile terminals, supporting multiple networking technologies, may be used to manage data from everywhere and at anytime. However, the effort required for achieving security, given the complexity of cryptographic algorithms, heavily affects the power consumption of terminals. Such energy demand, together with the one required to manage communication activities, makes energy-efficient secure communication among hardware-constrained handheld devices a challenging topic. In this work, we introduce an analytic energy model for secure communication among multi-mode terminals. This model describes the energy consumption of mobile terminals operating within a dynamic network scenario, considering both their interconnection and secure data exchange issues, in order to develop adaptive strategies for energy-efficient secure communications. Finally, the model has been validated through simulation. [ABSTRACT FROM AUTHOR]

Abstract: Energy consumption is now one of the most important issues for network carriers, since the majority of the energy needed for their operation is consumed in the wireless access and optical transport networks. The continuous growth in the wireless customers and traffic volumes and the consequent energy demand on modern carriers’ broadband infrastructures require reconsidering their energy efficiency, by starting from the formulation of new, more complete and representative network models that should become the foundations for modern energy-aware control plane architectures. Accordingly, this work presents a novel comprehensive energy model for next-generation wireless access-over-optical-transport networks characterized by hybrid power systems (i.e., multiple dynamically available power sources). The objective is to identify the energy-related information that need to be handled at the control plane layer to support energy-aware networking practices. Such information can be made available to suitable energy-aware routing and wavelength assignment algorithms that may exploit them to optimize the overall network energy-consumption and reducing the associated carbon footprint. The proposed model may be taken as a reference for the implementation of new energy-aware control plane protocols (routing and signaling) that make use of power-related considerations to achieve energy-efficiency and energy-awareness in wavelength-routed network infrastructures. [Copyright &y& Elsevier]