基于資源碎片的協(xié)同預(yù)留算法研究
發(fā)布時(shí)間：2018-10-25 07:59
【摘要】：在分布式系統(tǒng)中,資源協(xié)同預(yù)留是保證系統(tǒng)服務(wù)質(zhì)量的一項(xiàng)核心技術(shù)。然而在為用戶預(yù)留資源的過程中,預(yù)留作業(yè)會(huì)將完整的資源切割為不連續(xù)的小塊資源,形成資源碎片。這些資源碎片的形成和存在,降低了資源的利用率和作業(yè)的接納率。在有截止時(shí)間約束的作業(yè)調(diào)度過程中,為作業(yè)安排不同的可用資源,即不同的調(diào)度方案,產(chǎn)生的資源碎片不盡相同,對(duì)后續(xù)任務(wù)的接納也有不同的影響。通過對(duì)調(diào)度方案的優(yōu)化,可以有效地提高作業(yè)接納率和資源利用率。 本文分析了協(xié)同預(yù)留的研究歷史及現(xiàn)狀,研究了在多機(jī)單處理器的網(wǎng)格環(huán)境下資源碎片形成的原因,以及不同調(diào)度方案對(duì)作業(yè)接納率和資源利用率的影響。以上述分析為基礎(chǔ),本文考慮當(dāng)前作業(yè)調(diào)用的資源對(duì)整體資源的分割情況,將當(dāng)前作業(yè)的分配與后續(xù)作業(yè)的接納聯(lián)系起來,提出了對(duì)不同規(guī)模的資源碎片賦予不同權(quán)重的資源碎片接納能力量化方法。以此量化方法為標(biāo)準(zhǔn),提出了基于碎片的Best Fit算法(FSB)和基于碎片的Worst Fit算法(FSW)兩種提前預(yù)留算法,并對(duì)其性能進(jìn)行了仿真實(shí)驗(yàn)研究。 在仿真實(shí)驗(yàn)中,研究了在不同的作業(yè)靈活性、平均持續(xù)時(shí)間、系統(tǒng)負(fù)載和資源數(shù)量條件下,這兩種算法在作業(yè)接納率、資源利用率和作業(yè)平均減緩三個(gè)方面的性能。與Best Fit、First Fit、Min_LIP和Min_TIP四個(gè)算法進(jìn)行比較,證明了FSW和FSB算法在重負(fù)載下,可以取得較高的作業(yè)接納率。FSW算法與FSB相比較,由于算法設(shè)計(jì)思路相同,作業(yè)接納率與平均減緩和資源利用率的性能為嚴(yán)格的矛盾關(guān)系,FSW可以取得更高的作業(yè)接納率,而平均減緩更高,資源利用率更低。
[Abstract]:In distributed systems, collaborative reservation of resources is a core technology to ensure the quality of service. However, in the process of reserving resources for users, the whole resources will be cut into discrete pieces of resources, forming resource fragments. The formation and existence of these resource fragments reduce the utilization rate of resources and the acceptance rate of jobs. In the process of job scheduling with deadline constraints, different available resources, that is, different scheduling schemes, have different effects on the admission of subsequent tasks. By optimizing the scheduling scheme, the job acceptance rate and resource utilization can be improved effectively. In this paper, the history and present situation of collaborative reservation are analyzed. The causes of resource fragmentation in multi-processor grid environment and the influence of different scheduling schemes on job acceptance rate and resource utilization are studied. Based on the above analysis, this paper considers the partition of the whole resource by the resources called by the current job, and links the allocation of the current job with the acceptance of the subsequent job. A quantization method of resource debris acceptance capacity with different weights for different scales of resource debris is proposed. Based on this quantization method, two early reservation algorithms, (FSB) based on fragment Best Fit and (FSW) based on Worst Fit, are proposed, and their performance is studied by simulation experiments. In the simulation experiment, the performance of the two algorithms in the three aspects of job acceptance rate, resource utilization and job average reduction is studied under different conditions of job flexibility, average duration, system load and resource quantity. Compared with the four algorithms of Best Fit,First Fit,Min_LIP and Min_TIP, it is proved that FSW and FSB can achieve high job acceptance rate under heavy load. Compared with FSB, the FSW algorithm has the same design idea. There is a strict contradiction between job acceptance rate and the performance of average slowing and resource utilization. FSW can obtain higher job acceptance rate, higher average slow down and lower resource utilization.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP338.8
本文編號(hào)：2293103
[Abstract]:In distributed systems, collaborative reservation of resources is a core technology to ensure the quality of service. However, in the process of reserving resources for users, the whole resources will be cut into discrete pieces of resources, forming resource fragments. The formation and existence of these resource fragments reduce the utilization rate of resources and the acceptance rate of jobs. In the process of job scheduling with deadline constraints, different available resources, that is, different scheduling schemes, have different effects on the admission of subsequent tasks. By optimizing the scheduling scheme, the job acceptance rate and resource utilization can be improved effectively. In this paper, the history and present situation of collaborative reservation are analyzed. The causes of resource fragmentation in multi-processor grid environment and the influence of different scheduling schemes on job acceptance rate and resource utilization are studied. Based on the above analysis, this paper considers the partition of the whole resource by the resources called by the current job, and links the allocation of the current job with the acceptance of the subsequent job. A quantization method of resource debris acceptance capacity with different weights for different scales of resource debris is proposed. Based on this quantization method, two early reservation algorithms, (FSB) based on fragment Best Fit and (FSW) based on Worst Fit, are proposed, and their performance is studied by simulation experiments. In the simulation experiment, the performance of the two algorithms in the three aspects of job acceptance rate, resource utilization and job average reduction is studied under different conditions of job flexibility, average duration, system load and resource quantity. Compared with the four algorithms of Best Fit,First Fit,Min_LIP and Min_TIP, it is proved that FSW and FSB can achieve high job acceptance rate under heavy load. Compared with FSB, the FSW algorithm has the same design idea. There is a strict contradiction between job acceptance rate and the performance of average slowing and resource utilization. FSW can obtain higher job acceptance rate, higher average slow down and lower resource utilization.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP338.8
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
1 張偉哲;田志宏;張宏莉;何慧;劉文懋;;虛擬計(jì)算環(huán)境中的多機(jī)群協(xié)同調(diào)度算法[J];軟件學(xué)報(bào);2007年08期
2 李波;趙東風(fēng);沈斌;;支持資源預(yù)留的網(wǎng)格計(jì)算仿真平臺(tái)[J];系統(tǒng)仿真學(xué)報(bào);2006年S2期
，本文編號(hào)：2293103
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