Research On Dynamic Software Deployment In Cloud Environment

In cloud computing environment, it is common for a multi-component application to be deployed into the IT infrastructure on demand. The problem of finding a desired resolution of the deployment is referred to as the Application Component Placement Problem or ACP. Although the ACP has been studied both in the academy and industry for some years, so far these approaches all rely on a centralized node to collect the information about the network topology and hosts of the targeting environment so that it can make the optimized decision.In cloud environment, computing resources are shared by many applications and the IT infrastructure is dynamically changing, which makes collecting the dynamic information of the environment a more difficult task and waste much computing resources. In addition, when two or more clouds are involved in the deployment, there may exist privacy concern between different clouds so that a centralized approach cannot be applied. In our work, we focus on our research on the ACP problem in the cloud, and we proposed a distributed approach to solve the ACP. In our approach, we transform the ACP into a Distributed Constraint Optimization Problem or DCOP and solving the ACP becomes solving the DCOP. The detail of the algorithm and experiments are given. Besides this distributed approach, we also give a traditional centralized version that is designed for the cloud environment. We compared the two algorithms in different aspects and make a conclusion of their best usage scenario.In our work, we designed a system for application component placement in the cloud. The core of the system requires three basic components: the software description document, the agents that reside on the computing node and the web portal. We adopt the ACME language for the software description and extend it for our specific needs. The agents that reside on the computing node are the core component for executing a specific task for deploying an application. We designed the agents according to FIPA intelligent agent's standards and simplify it to keep its clearance. Finally, we give some practical scenes of using the software deployment system.