Resource allocation and request handling for user-aware content retrieval in the cloud

The user-aware content retrieval services are always data-intensive and require much resource to satisfy the user demand, which incurs the high cost of implementation. Considering that they could largely exploit the pay-as-you-go paradigm and the almost unlimited resource pool of the cloud, we investigate the design issues of deploying the services to the cloud in a cost-effective way. We formulate the resource allocation and request handling problem which aims at lowering the deployment cost and guaranteeing the service quality simultaneously. Due to the hardness of obtaining an optimal solution, we design two approximate algorithms with different points of emphasis and analyze their approximation ratios as well. In addition, we discuss the implementation issues in applying the proposed algorithms to the practical systems. Finally, the algorithms are evaluated and validated through both trace-based and synthesized simulations where they show a large improvement in terms of the total system cost.