The Experts below are selected from a list of 45090 Experts worldwide ranked by ideXlab platform
Jiao Bingli - One of the best experts on this subject based on the ideXlab platform.
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
ieee journal on selected areas in communications, 2013Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Engineering, Electrical & ElectronicTelecommunicationsSCI(E)28ARTICLE9348-3583
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Resource Allocation Using A Reverse Iterative Combinatorial Auction for Device-to-Device Underlay Cellular Networks
2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Li Dou, Jiao BingliAbstract:An innovative auction-based allocation scheme is proposed to improve the performance of device-to-device (D2D) communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which compete to obtain business as bidders while packages of D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit for packages of D2D links. And then a detailed non-monotonic descending price auction algorithm is explained. Further, we prove that the proposed scheme is cheat-proof, converges in a finite Number of Iteration rounds, and has lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000322375104152&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical & ElectronicTelecommunicationsEICPCI-S(ISTP)1
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
'Institute of Electrical and Electronics Engineers (IEEE)', 2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in Communications, 201
Bingli Jiao - One of the best experts on this subject based on the ideXlab platform.
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Efficiency resource allocation for device-to-device underlay communication systems: A reverse iterative combinatorial auction based approach
IEEE Journal on Selected Areas in Communications, 2013Co-Authors: Chen Xu, Qun Zhao, Lingyang Song, Zhu Han, Xiaoli Wang, Xiang Cheng, Bingli JiaoAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.
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resource allocation using a reverse iterative combinatorial auction for device to device underlay cellular networks
Global Communications Conference, 2012Co-Authors: Lingyang Song, Zhu Han, Bingli JiaoAbstract:An innovative auction-based allocation scheme is proposed to improve the performance of device-to-device (D2D) communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which compete to obtain business as bidders while packages of D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit for packages of D2D links. And then a detailed non-monotonic descending price auction algorithm is explained. Further, we prove that the proposed scheme is cheat-proof, converges in a finite Number of Iteration rounds, and has lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.
Xu Chen - One of the best experts on this subject based on the ideXlab platform.
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
ieee journal on selected areas in communications, 2013Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Engineering, Electrical & ElectronicTelecommunicationsSCI(E)28ARTICLE9348-3583
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Resource Allocation Using A Reverse Iterative Combinatorial Auction for Device-to-Device Underlay Cellular Networks
2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Li Dou, Jiao BingliAbstract:An innovative auction-based allocation scheme is proposed to improve the performance of device-to-device (D2D) communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which compete to obtain business as bidders while packages of D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit for packages of D2D links. And then a detailed non-monotonic descending price auction algorithm is explained. Further, we prove that the proposed scheme is cheat-proof, converges in a finite Number of Iteration rounds, and has lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000322375104152&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical & ElectronicTelecommunicationsEICPCI-S(ISTP)1
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
'Institute of Electrical and Electronics Engineers (IEEE)', 2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in Communications, 201
Safian Sharif - One of the best experts on this subject based on the ideXlab platform.
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optimization of process parameters in the abrasive waterjet machining using integrated sa ga
Applied Soft Computing, 2011Co-Authors: Azlan Mohd Zain, Habibollah Haron, Safian SharifAbstract:In this study, Simulated Annealing (SA) and Genetic Algorithm (GA) soft computing techniques are integrated to estimate optimal process parameters that lead to a minimum value of machining performance. Two integration systems are proposed, labeled as integrated SA-GA-type1 and integrated SA-GA-type2. The approaches proposed in this study involve six modules, which are experimental data, regression modeling, SA optimization, GA optimization, integrated SA-GA-type1 optimization, and integrated SA-GA-type2 optimization. The objectives of the proposed integrated SA-GA-type1 and integrated SA-GA-type2 are to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, to estimate the optimal process parameters values that has to be within the range of the minimum and maximum process parameter values of experimental design, and to estimate the optimal solution of process parameters with a small Number of Iteration compared to the optimal solution of process parameters with SA and GA optimization. The process parameters and machining performance considered in this work deal with the real experimental data in the abrasive waterjet machining (AWJ) process. The results of this study showed that both of the proposed integration systems managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.
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genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining
Engineering With Computers, 2011Co-Authors: Azlan Mohd Zain, Habibollah Haron, Safian SharifAbstract:In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the Number of Iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.
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integration of simulated annealing and genetic algorithm to estimate optimal solutions for minimising surface roughness in end milling ti 6al 4v
International Journal of Computer Integrated Manufacturing, 2011Co-Authors: Azlan Mohd Zain, Habibollah Haron, Safian SharifAbstract:In this study, simulated annealing (SA) and genetic algorithm (GA) soft computing techniques are integrated to search for a set of optimal cutting conditions value that leads to the minimum value of machining performance. Twointegration systems are proposed; integrated SA-GA-type1 and integrated SA-GA-type2. The considered machining performance is surface roughness (Ra) in end milling. The results of this study showed that both of the proposed integration systems managed to estimate the optimal cutting conditions, leading to the minimum value ofmachining performance when compared to the result of real experimental data. The proposed integration systems have also reduced the Number of Iteration in searching for the optimal solution compared to the conventional GA and conventional SA, respectively. In other words, the time for searching the optimal solution can be made faster by using the integrated SA-GA.
Han Zhu - One of the best experts on this subject based on the ideXlab platform.
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
ieee journal on selected areas in communications, 2013Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Engineering, Electrical & ElectronicTelecommunicationsSCI(E)28ARTICLE9348-3583
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Resource Allocation Using A Reverse Iterative Combinatorial Auction for Device-to-Device Underlay Cellular Networks
2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Li Dou, Jiao BingliAbstract:An innovative auction-based allocation scheme is proposed to improve the performance of device-to-device (D2D) communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which compete to obtain business as bidders while packages of D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit for packages of D2D links. And then a detailed non-monotonic descending price auction algorithm is explained. Further, we prove that the proposed scheme is cheat-proof, converges in a finite Number of Iteration rounds, and has lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000322375104152&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical & ElectronicTelecommunicationsEICPCI-S(ISTP)1
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Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
'Institute of Electrical and Electronics Engineers (IEEE)', 2012Co-Authors: Xu Chen, Song Lingyang, Han Zhu, Zhao Qun, Wang Xiaoli, Cheng Xiang, Jiao BingliAbstract:Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite Number of Iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in Communications, 201
