We present a decentralized approach towards scalable and energy-efficient management of virtual machine (VM) instances that are provisioned by large, enterprise clouds. In our approach, the computation resources of the data center are effectively organized into a hypercube structure. The hypercube seamlessly scales up and down as resources are either added or removed in response to changes in the number of provisioned VM instances. Without supervision from any central components, each compute node operates autonomously and manages its own workload by applying a set of distributed load balancing rules and algorithms. On one hand, underutilized nodes attempt to shift their workload to their hypercube neighbors and switch off. On the other, overutilized nodes attempt to migrate a subset of their VM instances so as to reduce their power consumption and prevent degradation of their own resources, which in turn may lead to SLA violations. In both cases, the compute nodes in our approach do not overload their counterparts in order to improve their own energy footprint. An evaluation and comparative study of the proposed approach provides evidence of its merits in terms of elasticity, energy efficiency, and scalability, as well as of its feasibility in the presence of high workload rates.

This article presents BPELcube, a framework comprising a scalable architecture and a set of distributed algorithms, which support the decentralized enactment of BPEL processes. In many application domains, BPEL processes are long-running, involve the exchange of voluminous data with external Web services, and are concurrently accessed by large numbers of users. In such context, centralized BPEL process execution engines pose considerable limitations in terms of scalability and performance. To overcome such problems, a scalable hypercube peer-to-peer topology is employed by BPELcube in order to organize an arbitrary number of nodes, which can then collaborate in the decentralized execution and monitoring of BPEL processes. Contrary to traditional clustering approaches, each node does not fully take charge of executing the whole process; rather, it contributes to the overall process execution by running a subset of the process activities and maintaining a subset of the process variables. Hence, the hypercube-based infrastructure acts as a single execution engine, where workload is evenly distributed among the participating nodes in a fine-grained manner. An experimental evaluation of BPELcube and a comparison with centralized and clustered BPEL engine architectures demonstrate that the decentralized approach yields improved process execution times and throughput.

In this paper, we propose Proteus, a generic query model for the discovery of operations offered by heterogeneous services. We demonstrate the need for such a model, and show how it unifies the task of service discovery through abstractions, which allow for the technology-independent formulation of service advertisements, queries, and query responses. On top of these generic elements, we build an intuitive, fuzzy-based query evaluation mechanism that supports the service matchmaking process by employing and appropriately combining existing similarity metrics. Thanks to the generality of Proteus, it is possible to seamlessly accommodate the discovery of operations provided by various types of services without the need of changing the existing service infrastructure. Thus, our approach is applicable to a variety of settings ranging from traditional web services to service-oriented grids, peer-to-peer networks, geospatial information systems, and so on. Overall, compared to the existing query models supported by standard service discovery technologies, our approach is marked by openness, flexibility, and improved performance in terms of precision and recall. The feasibility and efficiency of Proteus are verified by a series of experiments.

As the Web service technology matures, other computing paradigms such as peer-to-peer gradually adopt the service-oriented approach and are beginning to expose functionality as services. Hence there is a need for integration of these heterogeneous services, for the development of service-oriented applications. The first step to accomplish this is to establish a unified approach for service discovery. In this paper, we briefly present a query language along with its enacting service search engine which is used for effectively discovering Web and P2P services in a unified manner