The main idea of the recent proposed clustering by fast search and find of density peaks (CFSFDP) clustering algorithm depicts the cluster center with the local density and distance and it achieves significant effects...
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ISBN:
(纸本)9781538672556
The main idea of the recent proposed clustering by fast search and find of density peaks (CFSFDP) clustering algorithm depicts the cluster center with the local density and distance and it achieves significant effects in typical applications. But it can't select the cluster centers adaptively. Therefore, an improved CFSFDP algorithm is proposed in this paper, which determines the cluster centers by the max-min algorithm. First, the max-min algorithm is introduced to obtain the number of categories. Then the local density and distance information is used to determine the cluster centers as do in CFSFDP algorithm. It can not only adaptively obtain categories number of the data, but also obtain the corresponding clustering centers. The simulation results show that the proposed algorithm can find the number of categories and find the cluster centers. Meanwhile, it can find the cluster centers which are hard to be obtained through decision diagram.
OFDMA (Orthogonal Frequency Division Multiple Access) is the key technology of the fourth-generation mobile communication and has been applied to many communication standards. In this paper, genetic algorithm (GA) is ...
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ISBN:
(纸本)9781509030712
OFDMA (Orthogonal Frequency Division Multiple Access) is the key technology of the fourth-generation mobile communication and has been applied to many communication standards. In this paper, genetic algorithm (GA) is applied to channel allocation of OFDMA system and is improved from three aspects: initial population, fitness function and user fairness. At the same time, combining improved genetic algorithm with greedy algorithm, max-min algorithm to do further improvement. Throughsimulation and comparison, author has found improved genetic algorithm can be used to compensate for defects of other algorithms in channel allocation, such as improve system throughput, ensure user fairness and reduce system time, which makes channel allocation scheme better and has certain practical application value in wireless communication system.
Efficient execution of scientific workflows in cloud environments, specifically using virtual machines (VMs) necessitates the optimal allocation of resources. However, striking the delicate balance between over-rentin...
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ISBN:
(纸本)9798350319439
Efficient execution of scientific workflows in cloud environments, specifically using virtual machines (VMs) necessitates the optimal allocation of resources. However, striking the delicate balance between over-renting and under-renting resources poses a significant challenge, impacting cost and execution time. To address this issue, this paper introduces two fair-share-based scheduling methods that bridge the gap between scheduling scientific workflows in the cloud and traditional fair-share scheduling problems. These methods encompass three crucial steps: partitioning, resource allocation, and scheduling. The workflow is divided into distinct partitions during the partitioning step, with computational requirements calculated for each partition. The resource allocation step distinguishes the two methods, wherein a fair distribution of VMs among partitions is pursued. The proposed methods employ the strategies of max-min and proportional fair share to ensure fair resource allocation. Subsequently, the scheduling step determines the execution schedule based on the allocated resources. Experimental results demonstrate the significant improvements achieved by the proposed methods, enhancing resource utilization and minimizing the elusive concept of makespan. This research paper describes the complexities associated with resource management in cloud-based scientific workflows and provides practical solutions to optimize execution efficiency in these environments.
OFDMA (Orthogonal Frequency Division Multiple Access) is the key technology of the fourth-generation mobile communication and has been applied to many communication standards. In this paper, genetic algorithm (GA) is ...
详细信息
ISBN:
(纸本)9781509030729
OFDMA (Orthogonal Frequency Division Multiple Access) is the key technology of the fourth-generation mobile communication and has been applied to many communication standards. In this paper, genetic algorithm (GA) is applied to channel allocation of OFDMA system and is improved from three aspects: initial population, fitness function and user fairness. At the same time, combining improved genetic algorithm with greedy algorithm, max-min algorithm to do further improvement. Throughsimulation and comparison, author has found improved genetic algorithm can be used to compensate for defects of other algorithms in channel allocation, such as improve system throughput, ensure user fairness and reduce system time, which makes channel allocation scheme better and has certain practical application value in wireless communication system.
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