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High availability is one of the key characteristics of Infrastructure-as-a-Service (IaaS) cloud. In this paper, we show a scalable method for availability analysis of large scale IaaS cloud using analytic models. To reduce the complexity of analysis and the solution time, we use an interacting Markov chain based approach. The construction and the solution(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Keywords: Analytic model Cloud CTMC Fixed-point iteration IaaS Interacting sub-models(More)
Cloud service providers are constantly looking for ways to increase revenue and reduce costs either by reducing capacity requirements or by supporting more users without adding capacity. Over-commit of physical resources, without adding more capacity, is one such approach. Workloads that tend to be 'peaky' are especially attractive targets for over-commit(More)
Handling diverse client demands and managing unexpected failures without degrading performance are two key promises of a cloud delivered service. However, evaluation of a cloud service quality becomes difficult as the scale and complexity of a cloud system increases. In a cloud environment, service request from a user goes through a variety of provider(More)
Wireless link layer multicast is an important service primitive for emerging applications, such as live video, streaming audio, and other content telecasts. The broadcast nature of the wireless channel is amenable to multicast because a single packet transmission may be received by all clients in the multicast group. However, in view of diverse channel(More)
In a large Infrastructure-as-a-Service (IaaS) cloud, component failures are quite common. Such failures may lead to occasional system downtime and eventual violation of Service Level Agreements (SLAs) on the cloud service availability. The availability analysis of the underlying infrastructure is useful to the service provider to design a system capable of(More)
Evolution of plethora of e-commerce sites resulted in fierce competition among their providers. In order to acquire new and retain existing customers, various producers and market managers effectively employ online feedback analytics tools. Most of the online feedback analysis tools are built using sentiment analysis models. Sentiment analysis evolved in(More)
The term resilience is used differently by different communities. In general engineering systems, fast recovery from a degraded system state is often termed as resilience. Computer networking community defines it as the combination of trustworthiness (dependability, security, performability) and tolerance (survivability, disruption tolerance, and traffic(More)
Cloud based services may experience changes – internal, external, large, small – at any time. Predicting and quantifying the effects on the quality-of-service during and after a change are important in the resiliency assessment of a cloud based service. In this paper, we quantify the resiliency of infrastructure-as-a-service (IaaS) cloud(More)
Optimizing for performance is often associated with higher costs in terms of capacity, faster infrastructure, and power costs. In this paper, we quantify the power-performance trade-offs by developing a scalable analytic model for joint analysis of performance and power consumption for a class of Infrastructure-as-a-Service (IaaS) clouds with tiered service(More)