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With the development of wireless networks, the scale of network optimization problems is growing correspondingly. While algorithms have been designed to reduce complexity in solving these problems under given size, the approach of directly reducing the size of problem has not received much attention. This motivates us to investigate an innovative approach to reduce problem scale while maintaining...
Cloud datacentres are acknowledged as being massive energy consumers, which may have significant environment impacts. Service providers have an ethical responsibility to reduce the environmental impact of server resources and a simultaneous and complementary commercial desire to reduce energy costs. Zombie servers in the datacenters are one of the primary sources of undesirable energy expenditures...
Energy consumption is one of the key challenges faced by cloud computing. In this paper, we investigate ways of improving the energy usage of cloud computing environments by better resource management and consolidation. Our methodology focuses on critically reviewing and comparing the existing methods that are available in relation to schedulers and allocation policies through a simulated environment...
Multi-radio multi-channel (MR-MC) networks contribute significant enhancement in the network throughput by exploiting multiple radio interfaces and non-overlapping channels. While throughput optimization is one of the main targets in allocating resource in MR-MC networks, recently, the network energy efficiency is becoming a more and more important concern. Although turning on more radios and exploiting...
Given the fact that the virtualization technology improves resource utilization and reduces the operational expenses, it also causes a considerable impact on the system performance in the form of virtualization overheads. With the emergence of virtualization technology, new virtualization platforms are also being developed in the commercial market. The aim of this research study is to investigate...
We study how to achieve optimal network capacity in the most energy-efficient manner over a general large-scale wireless network, say, a multi-hop multi-radio multi-channel (MR-MC) network. We develop a multi-objective optimization framework for computing the resource allocation that leads to optimal network capacity with minimal energy consumption. Our framework is based on a linear programming multi-commodity...
Multi-radio multi-channel (MR-MC) networks as a promising technique to enhance the capacity of wireless networks have received a lot of attentions recently. While most of the existing studies focus on capacity optimization, energy-efficient resource allocation for MR-MC networks is an emerging area yet to be exploited. In this paper, we develop an optimization framework for energy-aware optimal resource...
This article establishes models about the impact on FDI to energy consumption in China by combining input-output method and Logarithmic Mean Divisia Index (LMDI). The result are industrial effect from increasing number of FDI leads to lower China's energy consumption intensity, and output effect goes against energy consumption intensity. Thus China should strengthen the investment-oriented of FDI,...
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