Configurable composition and adaptive provisioning of web services

Web services composition has been an active research area over the last few years. However, the technology is still not mature yet and several research issues need to be addressed. In this paper, we describe the design of CCAP, a system that provides tools for adaptive service composition and provisioning. We introduce a composition model where service context and exceptions are configurable to accommodate needs of different users. This allows for reusability of a service in different contexts and achieves a level of adaptiveness and contextualization without recoding and recompiling of the overall composed services. The execution semantics of the adaptive composite service is provided by an event-driven model. This execution model is based on Linda Tuple Spaces and supports real-time and asynchronous communication between services. Three core services, coordination service, context service, and event service, are implemented to automatically schedule and execute the component services, and adapt to user configured exceptions and contexts at run time. The proposed system provides an efficient and flexible support for specifying, deploying, and accessing adaptive composite services. We demonstrate the benefits of our system by conducting usability and performance studies. © 2009 IEEE

Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

A Self-adaptive Agent-based System for Cloud Platforms

Cloud computing is a model for enabling on-demand network access to a shared pool of computing resources, that can be dynamically allocated and released with minimal effort. However, this task can be complex in highly dynamic environments with various resources to allocate for an increasing number of different users requirements. In this work, we propose a Cloud architecture based on a multi-agent system exhibiting a self-adaptive behavior to address the dynamic resource allocation. This self-adaptive system follows a MAPE-K approach to reason and act, according to QoS, Cloud service information, and propagated run-time information, to detect QoS degradation and make better resource allocation decisions. We validate our proposed Cloud architecture by simulation. Results show that it can properly allocate resources to reduce energy consumption, while satisfying the users demanded QoS

Adaptive e-learning grid platform

Many analysts believe that more and more organizations are looking to introduce e-learning as a way to solve critical business problems and as a vital component of an integrated approach to their training solutions. So we are introducing our next generation, e-learning grid platform to meet the evolving needs of the market, which include technology, content and services. This platform will define a new mode of service interaction and application creation. It proposes a user-friendly method for deploying interactive (mobile) devices and for accessing new and innovative added value services. The specific infrastructure will provide the technology necessary to access, arrange, manage and make available e-learning services and applications, for both individual end users and business

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

Performance Modeling to Support Multi-Tier Application Deployment to Infrastructure-As-A-Service Clouds

Infrastructure-as-a-service (IaaS) clouds support migration of multi-tier applications through virtualization of diverse application stack(s) of components which may require various operating systems and environments. To maximize performance of applications deployed to IaaS clouds while minimizing deployment costs, it is necessary to create virtual machine images to host application components with consideration for component dependencies that may affect load balancing of physical resources of VM hosts including CPU time, disk and network bandwidth. This paper presents results of an investigation utilizing physical machine (PM) and virtual machine (VM) resource utilization statistics to build performance models to predict application performance and rank performance of application component deployment configurations deployed across VMs. Our objective was to predict which component compositions provide best performance while requiring the fewest number of VMs. Eighteen individual resource utilization statistics were investigated for use as independent variables to predict service execution time using four different modeling approaches. Overall CPU time was the strongest predictor of execution time. The strength of individual predictors varied with respect to the resource utilization profiles of the applications. CPU statistics including idle time and number of context switches were good predictors when the test application was more disk I/O bound, while disk I/O statistics were better predictors when the application was more CPU bound. All performance models built were effective at determining the best performing service composition deployments validating the utility of our approach