An Energy Driven Architecture for Wireless Sensor Networks

Most wireless sensor networks operate with very limited energy sources-their batteries, and hence their usefulness in real life applications is severely constrained. The challenging issues are how to optimize the use of their energy or to harvest their own energy in order to lengthen their lives for wider classes of application. Tackling these important issues requires a robust architecture that takes into account the energy consumption level of functional constituents and their interdependency. Without such architecture, it would be difficult to formulate and optimize the overall energy consumption of a wireless sensor network. Unlike most current researches that focus on a single energy constituent of WSNs independent from and regardless of other constituents, this paper presents an Energy Driven Architecture (EDA) as a new architecture and indicates a novel approach for minimising the total energy consumption of a WS

A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing

Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper proposes an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment. We have analyzed the performance of our approach using the CloudSim toolkit. The experimental results show that our approach has immense potential as it offers significant improvement in the aspects of response time and makespan, demonstrates high potential for the improvement in energy efficiency of the data center, and can effectively meet the service level agreement requested by the users.Comment: arXiv admin note: text overlap with arXiv:1006.0308 by other author

Linear combinations of DVFS-enabled processor frequencies to modify the energy-aware scheduling algorithms

The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms involve two passes: schedule generation and slack reclamation. The latter is typically achieved by lowering processor frequency for tasks with slacks. In this paper, we revisit this energy reduction technique from a different perspective and propose a new slack reclamation algorithm which uses a linear combination of the maximum and minimum processor frequencies to decrease energy consumption. This algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 1,500 randomly generated task graphs, and 300 task graphs of each of two real-world applications (Gauss-Jordan and LU decomposition). The results show that the amount of energy saved in the proposed algorithm is 13.5%, 25.5% and 0.11% for random, LU decomposition and Gauss-Jordan task graphs, respectively; these percentages for the reference DVFS-based algorithm are 12.4%, 24.6% and 0.1%, respectively.10 page(s