Service discovery and negotiation with COWS

To provide formal foundations to current (web) services technologies, we put forward using COWS, a process calculus for specifying, combining and analysing services, as a uniform formalism for modelling all the relevant phases of the life cycle of service-oriented applications, such as publication, discovery, negotiation, deployment and execution. In this paper, we show that constraints and operations on them can be smoothly incorporated in COWS, and propose a disciplined way to model multisets of constraints and to manipulate them through appropriate interaction protocols. Therefore, we demonstrate that also QoS requirement specifications and SLA achievements, and the phases of dynamic service discovery and negotiation can be comfortably modelled in COWS. We illustrate our approach through a scenario for a service-based web hosting provider

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels. Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load. To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions. The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments. The proposed InterCloud environment supports scaling of applications across multiple vendor clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape

Design and Evaluation of a Probabilistic Music Projection Interface

We describe the design and evaluation of a probabilistic interface for music exploration and casual playlist generation. Predicted subjective features, such as mood and genre, inferred from low-level audio features create a 34- dimensional feature space. We use a nonlinear dimensionality reduction algorithm to create 2D music maps of tracks, and augment these with visualisations of probabilistic mappings of selected features and their uncertainty. We evaluated the system in a longitudinal trial in users’ homes over several weeks. Users said they had fun with the interface and liked the casual nature of the playlist generation. Users preferred to generate playlists from a local neighbourhood of the map, rather than from a trajectory, using neighbourhood selection more than three times more often than path selection. Probabilistic highlighting of subjective features led to more focused exploration in mouse activity logs, and 6 of 8 users said they preferred the probabilistic highlighting mode

Non-functional Property based service selection: A survey and classification of approaches

In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed

Raising the Datagram API to Support Transport Protocol Evolution

Some application developers can wield huge resources to build new transport protocols, for these developers the present UDP Socket API is perfectly fine. They have access to large test beds and sophisticated tools. Many developers do not have these resources. This paper presents a new high-level Datagram API that is for everyone else, this has an advantage of offering a clear evolutionary path to support new requirements. This new API is needed to move forward the base of the system, allowing developers with limited resources to evolve their applications while accessing new network services

Incorporating prediction models in the SelfLet framework: a plugin approach

A complex pervasive system is typically composed of many cooperating \emph{nodes}, running on machines with different capabilities, and pervasively distributed across the environment. These systems pose several new challenges such as the need for the nodes to manage autonomously and dynamically in order to adapt to changes detected in the environment. To address the above issue, a number of autonomic frameworks has been proposed. These usually offer either predefined self-management policies or programmatic mechanisms for creating new policies at design time. From a more theoretical perspective, some works propose the adoption of prediction models as a way to anticipate the evolution of the system and to make timely decisions. In this context, our aim is to experiment with the integration of prediction models within a specific autonomic framework in order to assess the feasibility of such integration in a setting where the characteristics of dynamicity, decentralization, and cooperation among nodes are important. We extend an existing infrastructure called \emph{SelfLets} in order to make it ready to host various prediction models that can be dynamically plugged and unplugged in the various component nodes, thus enabling a wide range of predictions to be performed. Also, we show in a simple example how the system works when adopting a specific prediction model from the literature