Physical-layer network coding(PNC) promises substantial theoretical gain to achieve the maximum system throughput in cooperative relay transmission. However, with the increasing global warming, how to reduce power con...Physical-layer network coding(PNC) promises substantial theoretical gain to achieve the maximum system throughput in cooperative relay transmission. However, with the increasing global warming, how to reduce power consumption while satisfy system throughput requirement is becoming a vital issue. In this paper, we investigate energy-efficiency resource allocation(RA) based on PNC with amplify-and-forward(AF) protocol in orthogonal frequency division multiple(OFDM) bidirectional transmission. To minimize the overall transmit power consumption with required system throughput requirement, we consider joint subcarriers and power allocation and formulate the objective task into a constrained optimization problem where the best relay node is selected to minimize total transmit power. The closed form optimization power allocation solutions are acquired by analytical derivation. Based on derivation, we propose a novel optimal energy-efficient power allocation(OE-PA). Numerical results are given to evaluate the performance of the derived scheme as compared to other schemes and show that our scheme has signifi cant improvement to energy saving.展开更多
Recently, several novel computing paradigms are proposed, e.g., fog computing and edge computing. In such more decentralized computing paradigms, the location and resource for code execution and data storage of end ap...Recently, several novel computing paradigms are proposed, e.g., fog computing and edge computing. In such more decentralized computing paradigms, the location and resource for code execution and data storage of end applications could also be optionally distributed among different places or machines. In this paper, we position that this situation requires a new transparent and usercentric approach to unify the resource management and code scheduling from the perspective of end users. We elaborate our vision and propose a software-defined code scheduling framework. The proposed framework allows the code execution or data storage of end applications to be adaptively done at appropriate machines under the help of a performance and capacity monitoring facility, intelligently improving application performance for end users. A pilot system and preliminary results show the advantage of the framework and thus the advocated vision for end users.展开更多
基金supported by the Science Instrument Special Funds of the National Natural Science Foundation of China under Grant No.61027003the National High Technology Research and Development Program of China under Grant No.2012AA01A50604
文摘Physical-layer network coding(PNC) promises substantial theoretical gain to achieve the maximum system throughput in cooperative relay transmission. However, with the increasing global warming, how to reduce power consumption while satisfy system throughput requirement is becoming a vital issue. In this paper, we investigate energy-efficiency resource allocation(RA) based on PNC with amplify-and-forward(AF) protocol in orthogonal frequency division multiple(OFDM) bidirectional transmission. To minimize the overall transmit power consumption with required system throughput requirement, we consider joint subcarriers and power allocation and formulate the objective task into a constrained optimization problem where the best relay node is selected to minimize total transmit power. The closed form optimization power allocation solutions are acquired by analytical derivation. Based on derivation, we propose a novel optimal energy-efficient power allocation(OE-PA). Numerical results are given to evaluate the performance of the derived scheme as compared to other schemes and show that our scheme has signifi cant improvement to energy saving.
基金supported in part by Initiative Scientific Research Program in Tsinghua University under Grant No.20161080066in part by International Science&Technology Cooperation Program of China under Grant No.2013DFB10070
文摘Recently, several novel computing paradigms are proposed, e.g., fog computing and edge computing. In such more decentralized computing paradigms, the location and resource for code execution and data storage of end applications could also be optionally distributed among different places or machines. In this paper, we position that this situation requires a new transparent and usercentric approach to unify the resource management and code scheduling from the perspective of end users. We elaborate our vision and propose a software-defined code scheduling framework. The proposed framework allows the code execution or data storage of end applications to be adaptively done at appropriate machines under the help of a performance and capacity monitoring facility, intelligently improving application performance for end users. A pilot system and preliminary results show the advantage of the framework and thus the advocated vision for end users.
