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Modern fog network architectures, empowered by IoT applications and 5G communications technologies, are characterized by the presence of a huge number of mobile nodes, which undergo frequent handovers, introducing a significant load on the involved network entities. Considering the distributed and flat nature of these architectures, DMM can be the only viable option for efficiently managing handovers in these scenarios. The existing DMM solutions are capable of providing smooth handovers, but lack robustness from the security point of view. Indeed, DMM depends on external mechanisms for handover security and uses a centralized device, which has obvious security and performance implications in flat architectures where hierarchical dependencies can introduce problems. We propose a new DMM schema based on the blockchain, capable of resolving hierarchical security issues without affecting the network layout, and also satisfying fully distributed security requirements with less consumption of energy. [ABSTRACT FROM PUBLISHER]

Currently, cloud computing is the target business environment for many enterprises and government organizations. However, despite the huge potential gains that can be achieved, security represents a fundamental issue, which prevents the massive cloud adoption in mission-critical Information Technology sectors. The most common security issues are amplified in the cloud environment since new complex features, with their inherent weaknesses, enter into the problem space, particularly those associated to multitenancy and elasticity. Thus, new threats, such as the energy-related denial-of-service attacks against large-scale cloud infrastructures, may involve not only the quality of the delivered services but also their operational costs in terms of energy bill. The longer is the time necessary to identify such attacks, the heavier is the impact on the overall energy consumption and, consequently, on the associated expenses. This work presents a detailed analysis of such new sophisticated menaces, by focusing on those that are specifically tailored to originate the worst-case energy demands by leveraging properly crafted low-rate traffic patterns in order to ensure stealth operations. We present some strategies exploiting the cloud flexibility in order to increase in a fraudulent way the overall energy consumption and analyze their impact within large-scale cloud infrastructures. This should help cloud providers in understanding such weaknesses and highlighting their root causes, as well as in providing some hints on how they can counter these subtle security issues. [ABSTRACT FROM PUBLISHER]

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]

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]

Despite the significant degree of technological maturity reached by large-scale optical transmission infrastructures, new critical issues are emerging as side effects associated to their energy consumption, environmental impact and related costs, now accounting for an important part of the networks' operational expenditures. To face this problem, we propose a single-stage routing and wavelength assignment scheme, based on several network engineering extensions to the Generalised Multi-Protocol Label Switching (GMPLS) control plane protocols, mainly Open Shortest Path First, with new composed metrics and information transport facilities. It is structured according to a simple multi-objective optimisation approach aiming at containing the network's energy consumption and ecological impact while balancing the overall load and maintaining an acceptable connection demand satisfaction rate. The proposed solution is able to operate effectively in wide area wavelength routing scenarios, where multiple heterogeneous equipment, ranging from pure photonic to opaque routing/switching, amplification and regeneration devices are deployed in a GMPLS-empowered network. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In the last years, an increasing interest in location services characterized the market of mobile ubiquitous devices (smartphones, handhelds, etc.). Several technologies and solutions have been developed to determine the position of mobile devices in their operating space, each with its specific degree of precision and accuracy. In this scenario, the ideal location service should be able of tracking the mobile terminal in any place it moves to, both indoors and outdoors. However, while outdoor location services have already achieved a satisfactory degree of technological maturity and effectiveness, a really ubiquitous location service that works satisfactorily in both indoor and outdoor scenarios is not yet available. In order to cope with the above challenge, this work proposes a hybrid location approach designed to choose and switch among multiple positioning technologies supported by the mobile device and available in the surrounding environment, in a dynamic and transparent way during the user movement. It combines signal strength-based fingerprinting techniques for indoor positioning together with traditional GPS-based positioning for the outdoor localization and performs opportunistic technology switching according to a count-and-threshold mechanism. The resulting solution is able to leverage the different features of the wireless networks and of the global positioning technologies, in order to provide ubiquitous location services across indoor and outdoor scenarios, as well as to minimize power consumption of the mobile device. [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]

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]

Internet of Things (IoT) is a promising technology for improving our lives and society by integrating smart devices in our environment and paving the way for novel ICT application, spanning from smart cities to energy efficiency and home automation. However, such a vision encompasses the availability of thousands of smart devices, or even more, that continuously exchange a huge volume of data among each other and with cloud-based services, raising a big data problem. Such a problem can be approached by properly applying data fusion practices within an IoT infrastructure. Due to the characteristics and peculiarities of the communications among smart devices within the IoT, an event-based data fusion is needed, where devices exchange notifications of events among each others. Such data fusion should be focused on special devices where notification heterogeneity, and data source trust issues have to be faced with. Accordingly, the contribution of this work is proposing (i) a novel broker-less event-based communication protocol specifically tailored to sensors with constrained resources, (ii) a solution for flexible event-based communications among heterogeneous data sources, and (iii) an approach based on the theory of evidence for data fusion processes that depend on the matching and trust degree of the data to be fused. [ABSTRACT FROM AUTHOR]