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Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users' requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.

Abstract-In this paper, we propose a dynamic audit service for verifying the integrity of an untrusted and outsourced storage. Our audit service is constructed based on the techniques, fragment structure, random sampling, and index-hash table, supporting provable updates to outsourced data and timely anomaly detection. In addition, we propose a method based on probabilistic query and periodic verification for improving the performance of audit services. Our experimental results not only validate the effectiveness of our approaches, but also show our audit system verifies the integrity with lower computation overhead and requiring less extra storage for audit metadata.

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The message-based communication among services in Service-based Systems (SBS) is vulnerable to various security attacks and must be well protected by security mechanisms, which may affect performance due to available system resources. In this paper, an adaptive approach is presented to optimize the tradeoff between service performance and security according to SBS users’ requirements and preferences on performance and security. This adaptive approach is based on a tradeoff algorithm with quantitative performance and security metrics and the tradeoff objective function. An SBS example with a security service and a traffic service is used to illustrate the approach.