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A network of drone cameras can be deployed to cover live events, such as high-action sports game played on a large field, but managing networked drone cameras in real-time is challenging. Distributed approaches yield suboptimal solutions from lack of coordination but coordination with a centralized controller incurs round-trip latencies of several hundreds of milliseconds over a wireless channel....
How to reduce energy consumption under the restraints of satisfying customer service level by effective resource allocation and scheduling has become a key issue in cloud computing. In this paper, we propose a new resources-allocation and scheduling architecture for energy consumption optimization. Based on this architecture, a new energy consumption optimization model is designed to meet the real-time...
Recently, technologies on reducing energy consumption of data centers have drawn considerable attentions. One constructive way is to improve energy efficiency of servers. Aiming at this goal, we propose a new energy-aware optimization model based on the combination of data placement and task scheduling in this paper. The main contributions are: (1)The impact of servers' performance on energy consumption...
With the cloud paradigm being applied broadly, how to make an efficient scheme of resource placement regarding to the energy cost has become a prerequisite problem to be solved. But nearly all of existing resource placement approaches always ignore the energy use caused by virtual machine (VM) dynamical migration. In this paper, we established the energy consumption model in cloud computing environment,...
For the problem that the energy efficiency of the cloud computing data center is low, from the point of view of the energy efficiency of the servers, we propose a new energy-efficient multi-task scheduling model based on Google's massive data processing framework. To solve this model, we design a practical encoding and decoding method for the individuals, and construct an overall energy efficiency...
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