Towards automatic tuning of adaptive computations in autonomic middleware
Proceedings of the 9th International Workshop on Adaptive and Reflective Middleware
An Analysis of Provisioning and Allocation Policies for Infrastructure-as-a-Service Clouds
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Future Generation Computer Systems
Self-adaptive and sensitivity-aware QoS modeling for the cloud
Proceedings of the 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Scheduling highly available applications on cloud environments
Future Generation Computer Systems
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Infrastructure resources on-demand requires resource provision (e.g., CPU and memory) to be both sufficient and necessary, which is the most important issue and a challenge in Cloud Computing. Platform as a service (PaaS) encapsulates a layer of software that includes middleware, and even development environment, and provides them as a service for building and deploying cloud applications. In PaaS, the issue of on-demand infrastructure resource management becomes more challenging due to the thousands of cloud applications that share and compete for resources simultaneously. The fundamental solution is to integrate and coordinate the resource consumption and allocation management of a cloud application. The difficulties of such a solution in PaaS are essentially how to maximize the resource utilization of an application, and how to allocate resources to guarantee adequate resource provision for the system. In this paper, we propose an approach to managing infrastructure resources in PaaS by leveraging two adaptive control loops: the resource consumption optimization loop and the resource allocation loop. The optimization loop improves the resource utilization of a cloud application via management functions provided by the corresponding middleware layers of PaaS. The allocation loop provides or reclaims appropriate amounts of resources to/from the application system while guaranteeing its performance. The two loops are integrated to run consecutively and repeatedly to provide infrastructure resources on-demand by first trying to improve resource utilization, and then allocating more resources when necessary. We implement a framework, SmartRod, to investigate our approach. The experiment on SmartRod proves its effectiveness on infrastructure resource management.