Noncontiguous processor allocation algorithms for mesh-connected multicomputers

1997 ◽  
Vol 8 (7) ◽  
pp. 712-726 ◽  
Author(s):  
V. Lo ◽  
K.J. Windisch ◽  
Wanqian Liu ◽  
B. Nitzberg
Keyword(s):  
Processor Allocation ◽  
Allocation Algorithms

A simple numerical method to simulate the flow through filter media: investigation of different fibre allocation algorithms

2021 ◽  
Author(s):  
Liliana Luca Xavier Augusto ◽  
Paolo Tronville ◽  
José Antônio Silveira Gonçalves ◽  
Gabriela Cantarelli Lopes
Keyword(s):  
Numerical Method ◽  
Filter Media ◽  
Flow Through ◽  
Allocation Algorithms

scholarly journals Minimizing Resource Waste in Heterogeneous Resource Allocation for Data Stream Processing on Clouds

2020 ◽  
Vol 11 (1) ◽  
pp. 149
Author(s):  
Wu-Chun Chung ◽  
Tsung-Lin Wu ◽  
Yi-Hsuan Lee ◽  
Kuo-Chan Huang ◽  
Hung-Chang Hsiao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Data Stream ◽  
Limited Attention ◽  
Heterogeneous Servers ◽  
Resource Allocation Algorithm ◽  
System Utilization ◽  
Allocation Algorithms ◽  
Considerable Resource ◽  
Heterogeneous Resources

Resource allocation is vital for improving system performance in big data processing. The resource demand for various applications can be heterogeneous in cloud computing. Therefore, a resource gap occurs while some resource capacities are exhausted and other resource capacities on the same server are still available. This phenomenon is more apparent when the computing resources are more heterogeneous. Previous resource-allocation algorithms paid limited attention to this situation. When such an algorithm is applied to a server with heterogeneous resources, resource allocation may result in considerable resource wastage for the available but unused resources. To reduce resource wastage, a resource-allocation algorithm, called the minimizing resource gap (MRG) algorithm, for heterogeneous resources is proposed in this study. In MRG, the gap between resource usages for each server in cloud computing and the resource demands among various applications are considered. When an application is launched, MRG calculates resource usage and allocates resources to the server with the minimized usage gap to reduce the amount of available but unused resources. To demonstrate MRG performance, the MRG algorithm was implemented in Apache Spark. CPU- and memory-intensive applications were applied as benchmarks with different resource demands. Experimental results proved the superiority of the proposed MRG approach for improving the system utilization to reduce the overall completion time by up to 24.7% for heterogeneous servers in cloud computing.

scholarly journals Allocation algorithms for personal TV advertisements

2012 ◽  
Vol 19 (2) ◽  
pp. 79-93 ◽  
Author(s):  
Ron Adany ◽  
Sarit Kraus ◽  
Fernando Ordonez
Keyword(s):  
Allocation Algorithms

Performance-driven processor allocation

2005 ◽  
Vol 16 (7) ◽  
pp. 599-611 ◽  
Author(s):  
J. Corbalan ◽  
X. Martorell ◽  
J. Labarta
Keyword(s):  
Processor Allocation
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