Beschreibung:
Today's highly parameterized large-scale distributed computing systems may be composed of a large number of various components (computers, databases, etc) and must provide a wide range of services. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system's services and resources, and different, often conflicting, expectations and requirements. Moreover, the information and data processed in such dynamic environments may be incomplete, imprecise, fragmentary, and overloading. All of the above mentioned issues require some intelligent scalable methodologies for the management of the whole complex structure, which unfortunately may increase the energy consumption of such systems.
Evolutionary Green Computing Solutions for Distributed Cyber Physical Systems.-Energy-Aware provisioning of HPC services with virtualised web services.-Macro Level Models of Power Consumption for Servers in Distributed System.-Energy and Security Awareness in Evolutionary-driven Grid Scheduling.-Power Consumption Constrained Task Scheduling Using Enhanced Genetic Algorithms.-Thermal Management in Many-Core Systems .-Sustainable and Reliable On-chip Wireless Communication Infrastructure for Massive Muliti-core Systems.-Exploiting Multi-Objective Evolutionary Algorithms for Designing Energy-efficient Solutions to Data Compression and Node .Localization in Wireless Sensor Networks.