Transient behaviour of three-heterogeneous servers queue with system disaster and server repair

2017 ◽  
Vol 51 (4) ◽  
pp. 965-983 ◽  
Author(s):  
Ramupillai Sudhesh ◽  
P. Savitha
2020 ◽  
Vol 11 (1) ◽  
pp. 149
Author(s):  
Wu-Chun Chung ◽  
Tsung-Lin Wu ◽  
Yi-Hsuan Lee ◽  
Kuo-Chan Huang ◽  
Hung-Chang Hsiao ◽  
...  

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.


Author(s):  
Joydip Mondal ◽  
Arpit Mishra ◽  
Rajaram Lakkaraju ◽  
Parthasarathi Ghosh

Jets produced by the interaction of collapsing cavitating bubbles containing high-pressure gases can be utilized for wide variety of applications e.g. particle erosion, medical purposes (lithotripsy, sonoporation), tannery effluent treatment, etc. Among the many parameters, this jetting is largely influenced by spatial orientation of bubbles, their times of inception, relative bubble size ratio. In this context, multiple cavitating bubbles are able to generate numerous simultaneous jets, under suitable conditions, hence operating over a wider coverage area. Such multi-bubble arrangements can go a long way in enhancing the erosive impact on a target location even at cryogenic temperature (< 123 K) and hence necessitate investigation. In this paper, different configurations of multiple-bubble interactions are numerically simulated to examine jets directed towards a target location (fictitious particle, cell etc.) using computational fluid dynamics. No phase change is considered and the effect of gravity is neglected. The transient behaviour of the interface between the two interacting fluids (bubble and ambient liquid) is modelled using VOF (volume of fluid) method. In this paper, results obtained for different bubble configurations through numerical simulation are validated against suitable literature and further explored to assess the resulting jet effects. The time histories of interacting bubbles are presented and the consequent flow-fields are evaluated by the pressure and velocity distributions obtained. The same calculation is repeated in cryogenic environment and the results are compared. An attempt is made to approach towards an optimum arrangement and conditions for particle erosion.


2017 ◽  
Vol 49 (2) ◽  
pp. 603-628 ◽  
Author(s):  
Ramtin Pedarsani ◽  
Jean Walrand ◽  
Yuan Zhong

Abstract Modern processing networks often consist of heterogeneous servers with widely varying capabilities, and process job flows with complex structure and requirements. A major challenge in designing efficient scheduling policies in these networks is the lack of reliable estimates of system parameters, and an attractive approach for addressing this challenge is to design robust policies, i.e. policies that do not use system parameters such as arrival and/or service rates for making scheduling decisions. In this paper we propose a general framework for the design of robust policies. The main technical novelty is the use of a stochastic gradient projection method that reacts to queue-length changes in order to find a balanced allocation of service resources to incoming tasks. We illustrate our approach on two broad classes of processing systems, namely the flexible fork-join networks and the flexible queueing networks, and prove the rate stability of our proposed policies for these networks under nonrestrictive assumptions.


1989 ◽  
Vol 208 (3) ◽  
pp. A11
Author(s):  
F.C.M.J.M. van Delft ◽  
J. Siera ◽  
B.E. Nieuwenhuys
Keyword(s):  

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