Task admission control for cloud server pools

Abstract

This paper provides a model for task admission control and resource allocation in the cloud infrastructure. We have examined the performance of resource allocation in this solution through different test scenarios. Also, we have presented two algorithms to control the admission of incoming tasks. These algorithms are based upon establishing thresholds for task arrival rate and task blocking probability. Our experiments indicate that these simple admission control algorithms can vastly improve system performance.

Mining association rules for admission control and service differentiation in e‐commerce applications

“…Both internet server resource management and web data mining have attracted extensive research in the literature. Internet resource management can be achieved through resource provisioning (Urgaonkar et al, ; Urgaonkar, Kozat, Igarashi, & Neely, ; Villela et al, ; Xue et al, ), AC (Ashraf et al, ; Elnikety et al, ; Khojasteh et al, ; Konstanteli et al, ; Tomas & Tordsson, ; Wu et al, ), service differentiation (Chandra et al, ; Dutta et al, ; Hjort et al, ; Lakew et al, ), and request scheduling (Zhu, Yang, Chen, Wang, & Yin, ). It is common practice to combine more than one of the techniques to achieve better results.…”

“…It is common practice to combine more than one of the techniques to achieve better results. Khojasteh et al (), Urgaonkar et al () and Villela et al () uses queuing network model for resource allocation for internet applications in the clouds. It is common practice to employ both proactive and reactive approaches for long and short term resource provisioning (Urgaonkar et al, ).…”

“…Apart from "accept" or "reject" decisions, it also considers "deferment" mechanism to reduce total sessions to be rejected. The work in (Khojasteh et al, 2015) uses a probabilistic optimization model for AC in elastic clouds hosting horizontally scaling services; it takes into account eco-efficiency and cost, as well as affinity and anti-affinity rules possibly in place for the components that comprise the services. In (Wu et al, 2012), the authors considered users, Software-as-a-Service (SaaS) providers, Infrastructure-as-a-Service (IaaS) providers and various SLAs between them, and made AC and scheduling decisions from economic perspective.…”

“…ISPs always aim at maximizing their profits by making the best use of their resources, that is, while maintaining the SLAs, they will try to allocate resources to as many e‐commerce companies as possible. In system overloading situations, unless e‐commerce companies are willing to pay for extra resources, ISPs usually apply admission control (AC) Schemes (Ashraf, Byholm, & Porres, ; Elnikety, Nahum, Tracey, & Zwaenepoel, ; Khojasteh, Misic, & Misic, ; Konstanteli, Cucinotta, Psychas, & Varvarigou, ; Tomas & Tordsson, ; Wu, Garg, & Buyya, ) to their services. By rejecting less important requests when the system is overloaded, AC schemes can guarantee the performance of internet services.…”