Security supportive energy-aware scheduling and energy policies for cloud environments

Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of performance and energy-aware strategies for resource allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to combine energy and performance-aware scheduling policies in order to hibernate those virtual machines that operate in idle state. The efficiency achieved by applying the proposed models has been tested using a realistic large-scale CC system simulator. Obtained results show that a balance between low energy consumption and short makespan can be achieved. Several security constraints may be considered in this model. Each security constraint is characterized by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL are computed during the scheduling process in order to provide proper security services. Experimental results show that the proposed solution reduces up to 45% of the energy consumption of the CC system. Such significant improvement was achieved by the combination of an energy-aware scheduler with energy-efficiency policies focused on the hibernation of VMs.COST Action IC140

Blockchain Technology in the Field of Energetics: Organization of Effective Energy Market

The article is devoted to the topic of blockchain applications in the field of energetics. A role of the technology in the digital economy development has been discussed; corresponding examples from Russian, Chinese, Estonian experience have been presented. A synergy between usage of blockchain and other information technology such as big data, intelligent avatars and the Internet of things has been demonstrated. Implementation of the blockchain technology into the functional scheme of the energy market has been proposed as a ways to ensure its decentralization and openness. Energy supply contracts can be negotiated directly between producers and consumers without intermediaries, so all the market actors have a high level of autonomy in purchasing and selling. The technology provides services for preparation and issuance of necessary invoices, as well as for making settlements for the entire transaction. Blockchain technology ensures economic and information security of transaction participants and includes convenient tools for realization of their market activities. Difficulties and risks, connected with the technology implementation, have been discussed, as well as main ways of its further development

Energy and performance-aware scheduling and shut-down models for efficient cloud-computing data centers.

This Doctoral Dissertation, presented as a set of research contributions, focuses on resource efficiency in data centers. This topic has been faced mainly by the development of several energy-efficiency, resource managing and scheduling policies, as well as the simulation tools required to test them in realistic cloud computing environments. Several models have been implemented in order to minimize energy consumption in Cloud Computing environments. Among them: a) Fifteen probabilistic and deterministic energy-policies which shut-down idle machines; b) Five energy-aware scheduling algorithms, including several genetic algorithm models; c) A Stackelberg game-based strategy which models the concurrency between opposite requirements of Cloud-Computing systems in order to dynamically apply the most optimal scheduling algorithms and energy-efficiency policies depending on the environment; and d) A productive analysis on the resource efficiency of several realistic cloud–computing environments. A novel simulation tool called SCORE, able to simulate several data-center sizes, machine heterogeneity, security levels, workload composition and patterns, scheduling strategies and energy-efficiency strategies, was developed in order to test these strategies in large-scale cloud-computing clusters. As results, more than fifty Key Performance Indicators (KPI) show that more than 20% of energy consumption can be reduced in realistic high-utilization environments when proper policies are employed.Esta Tesis Doctoral, que se presenta como compendio de artículos de investigación, se centra en la eficiencia en la utilización de los recursos en centros de datos de internet. Este problema ha sido abordado esencialmente desarrollando diferentes estrategias de eficiencia energética, gestión y distribución de recursos, así como todas las herramientas de simulación y análisis necesarias para su validación en entornos realistas de Cloud Computing. Numerosas estrategias han sido desarrolladas para minimizar el consumo energético en entornos de Cloud Computing. Entre ellos: 1. Quince políticas de eficiencia energética, tanto probabilísticas como deterministas, que apagan máquinas en estado de espera siempre que sea posible; 2. Cinco algoritmos de distribución de tareas que tienen en cuenta el consumo energético, incluyendo varios modelos de algoritmos genéticos; 3. Una estrategia basada en la teoría de juegos de Stackelberg que modela la competición entre diferentes partes de los centros de datos que tienen objetivos encontrados. Este modelo aplica dinámicamente las estrategias de distribución de tareas y las políticas de eficiencia energética dependiendo de las características del entorno; y 4. Un análisis productivo sobre la eficiencia en la utilización de recursos en numerosos escenarios de Cloud Computing. Una nueva herramienta de simulación llamada SCORE se ha desarrollado para analizar las estrategias antes mencionadas en clústers de Cloud Computing de grandes dimensiones. Los resultados obtenidos muestran que se puede conseguir un ahorro de energía superior al 20% en entornos realistas de alta utilización si se emplean las estrategias de eficiencia energética adecuadas. SCORE es open source y puede simular diferentes centros de datos con, entre otros muchos, los siguientes parámetros: Tamaño del centro de datos; heterogeneidad de los servidores; tipo, composición y patrones de carga de trabajo, estrategias de distribución de tareas y políticas de eficiencia energética, así como tres gestores de recursos centralizados: Monolítico, Two-level y Shared-state. Como resultados, esta herramienta de simulación arroja más de 50 Key Performance Indicators (KPI) de rendimiento general, de distribucin de tareas y de energía.Premio Extraordinario de Doctorado U

Utilising in-vehicle information to detect traffic conditions in vehicular ad-hoc networks

In the last decade, cooperative vehicular network has been one of the most studied areas for developing the intelligent transportation systems (ITS). It is considered as an important approach to share the periodic traffic situations over vehicular ad hoc networks (VANETs) to improve efficiency and safety over the road. In addition to the uses of ITS, VANETs will contribute in service access, cooperative driving, entertainment and navigation for cars of the future. Vehicle to vehicle and vehicle to infrastructure communication are two distinct avenues that make possible efficient delivery of messages through direct wireless transmissions in traffic regions. Furthermore, promising quality of communication performance is desirable for a communication system composed mostly if roaming participants; such a system needs to be dynamic, flexible and infrastructure-less. Thus VANET architecture is a natural fit for ITS. However, there are a number of issues in exchanging traffic data over high mobility of VANET, such as broadcast storms, hidden nodes and network instability. Therefore, vehicular traffic efficiency applications have been investigated recently using VANET. This aspect of research is primarily concerned with increasing the traffic awareness over roads. In this thesis, a novel model, Efficient Traffic Conditions Detection (ETraCD) is proposed to detect the traffic conditions utilising vehicles’ characteristics and in-vehicles sensors information to evaluate traffic situations that are gathered from the nodes (vehicles) in VANET. The model revolves around the core idea to what extent we will be considering the traffic characteristics between groups of cars rather than individual cars. This does not concern the physical transmission of data but the data processing in the network. More precisely, vehicles are clustered into traffic groups based on the similarity of sensors’s data. ETraCD (a) divides the situations of vehicles into clusters, (b) designs a set of metrics to get the correlations among vehicles and (c) detects the traffic condition in certain areas. These approaches have been simulated in NS3 network simulator to investigate the performance of stability of the network, latency, and the accuracy of traffic situations detection. The proposed model applies V2V clustering paradigm for detecting traffic conditions, it has been implemented and its features investigated through simulation runs. It shows the benefit of using the vehicular sensors informations such as ABS, windscreen lights and so on based on V2V communication to provide an efficient traffic conclusion in urban environment. Experiments also show improved overall performance when compared to previous protocols

JTIT

kwartalni

Virtual Prototyping Methodology for Power Automation Cyber-Physical-Systems

In this thesis, the author proposes a circular system development model which considers all the stages in a typical development process for industrial systems. In particular, the present work shows that the use of virtual prototyping at early stages of the system development may reduce the overall design and verification effort by allowing the exploration of the complete system architecture, and uncovering integration issues early on. The modeling techniques of this research are based on VHDL-AMS, yet supporting other modeling languages such as C/C++, SPICE, and Verilog-AMS, together with integrated simulation tools. Contrasting with conventional approaches, it is shown that the proposed methodology is adapted for small-scale Cyber-Physical Systems (CPS) design and verification thanks to the modularity and scalability of the modeling approach. The proposed modeling techniques enable seamlessly the CPS design together with the implementation of their subsystems. In particular, the contribution of this work improves the virtual prototyping approach that has been successfully used during the development of smart electrical sensors and monitoring equipment for high and medium voltage applications. The design of the measurement and self-calibration circuits of a medium voltage current sensor based on the Rogowski coil transducer is presented as an example. The proposed small-scale CPS design methodology based on virtual prototyping, namely VP-based design methodology, uses important theoretical concepts from layered design, component-based design, and platform-based design. These foundations are the basis to build a modeling methodology that provides a vehicle that can be used to improve system verification towards correct-by-design systems. The main contributions of this research are: the re-definition of the system development lifecycle by using a virtual prototyping methodology; the design and implementation of a model library that maximizes the reuse of computational models and their related IP; and a set of VHDL-AMS modeling guidelines established with the purpose of improving the modularity and scalability of virtual prototypes. These elements are key for supporting the introduction of virtual prototyping into industrial companies that can thoroughly profit from this approach, but cannot commit a specific team to the creation, support, and maintenance of computational models and its dedicated infrastructure. Thanks to the progressive nature of the proposed methodology, virtual prototypes can indeed be introduced with relatively low initial effort and enhanced over time. The presented methodology and its infrastructure may grow into a bidirectional communication medium between non-expert system designers (i.e. system architects and virtual integrators) and domain specialists such as mechanical designers, power electrical designers, embedded-electronics designers, and software designers. The proposed design methodology advocates the reduction of the CPS design complexity by the implementation of a meet-in-the-middle approach for system-level modeling. In this direction, the modeling techniques introduced in this work facilitate the architectural design space exploration, critical cross-domain variable analysis (especially important in the component interfaces), and system-level optimization and verification