951 research outputs found
Redundant VoD Streaming Service in a Private Cloud: Availability Modeling and Sensitivity Analysis
For several years cloud computing has been generating
considerable debate and interest within IT corporations.
Since cloud computing environments provide storage and processing
systems that are adaptable, efficient, and straightforward,
thereby enabling rapid infrastructure modifications to be made
according to constantly varying workloads, organizations of
every size and type are migrating to web-based cloud supported
solutions. Due to the advantages of the pay-per-use model and
scalability factors, current video on demand (VoD) streaming
services rely heavily on cloud infrastructures to offer a
large variety of multimedia content. Recent well documented
failure events in commercial VoD services have demonstrated
the fundamental importance of maintaining high availability in
cloud computing infrastructures, and hierarchical modeling has
proved to be a useful tool for evaluating the availability of
complex systems and services. This paper presents an availability
model for a video streaming service deployed in a private
cloud environment which includes redundancy mechanisms in
the infrastructure. Differential sensitivity analysis was applied
to identify and rank the critical components of the system
with respect to service availability. The results demonstrate that
such a modeling strategy combined with differential sensitivity
analysis can be an attractive methodology for identifying which
components should be supported with redundancy in order to
consciously increase system dependability
Stochastic models for quality of service of component connectors
The intensifying need for scalable software has motivated modular development and using systems distributed over networks to implement large-scale applications. In Service-oriented Computing, distributed services are composed to provide large-scale services with a specific functionality. In this way, reusability of existing services can be increased. However, due to the heterogeneity of distributed software systems, software composition is not easy and requires additional mechanisms to impose some form of a coordination on a distributed software system. Besides functional correctness, a composed service must satisfy various quantitative requirements for its clients, which are generically called its quality of service (QoS). Particularly, it is tricky to obtain the overall QoS of a composed service even if the QoS information of its constituent distributed services is given. In this thesis, we propose Stochastic Reo to specify software composition with QoS aspects and its compositional semantic models. They are also used as intermediate models to generate their corresponding stochastic models for practical analysis. Based on this, we have implemented the tool Reo2MC. Using Reo2MC, we have modeled and analyzed an industrial software, the ASK system. Its analysis results provided the best cost-effective resource utilization and some suggestions to improve the performance of the system.UBL - phd migration 201
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