ADEPT2 - Next Generation Process Management Technology

If current process management systems shall be applied to a broad spectrum of applications, they will have to be significantly improved with respect to their technological capabilities. In particular, in dynamic environments it must be possible to quickly implement and deploy new processes, to enable ad-hoc modifications of single process instances at runtime (e.g., to add, delete or shift process steps), and to support process schema evolution with instance migration, i.e., to propagate process schema changes to already running instances. These requirements must be met without affecting process consistency and by preserving the robustness of the process management system. In this paper we describe how these challenges have been addressed and solved in the ADEPT2 Process Management System. Our overall vision is to provide a next generation process management technology which can be used in a variety of application domains

Technical Report: A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

To improve customer experience, datacenter operators offer support for simplifying application and resource management. For example, running workloads of workflows on behalf of customers is desirable, but requires increasingly more sophisticated autoscaling policies, that is, policies that dynamically provision resources for the customer. Although selecting and tuning autoscaling policies is a challenging task for datacenter operators, so far relatively few studies investigate the performance of autoscaling for workloads of workflows. Complementing previous knowledge, in this work we propose the first comprehensive performance study in the field. Using trace-based simulation, we compare state-of-the-art autoscaling policies across multiple application domains, workload arrival patterns (e.g., burstiness), and system utilization levels. We further investigate the interplay between autoscaling and regular allocation policies, and the complexity cost of autoscaling. Our quantitative study focuses not only on traditional performance metrics and on state-of-the-art elasticity metrics, but also on time- and memory-related autoscaling-complexity metrics. Our main results give strong and quantitative evidence about previously unreported operational behavior, for example, that autoscaling policies perform differently across application domains and by how much they differ.Comment: Technical Report for the CCGrid 2018 submission "A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

Adaptive service discovery on service-oriented and spontaneous sensor systems

Service-oriented architecture, Spontaneous networks, Self-organisation, Self-configuration, Sensor systems, Social patternsNatural and man-made disasters can significantly impact both people and environments. Enhanced effect can be achieved through dynamic networking of people, systems and procedures and seamless integration of them to fulfil mission objectives with service-oriented sensor systems. However, the benefits of integration of services will not be realised unless we have a dependable method to discover all required services in dynamic environments. In this paper, we propose an Adaptive and Efficient Peer-to-peer Search (AEPS) approach for dependable service integration on service-oriented architecture based on a number of social behaviour patterns. In the AEPS network, the networked nodes can autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly discover and self-configure any services available on the disaster area and deliver a real-time capability by self-organising themselves in spontaneous groups to provide higher flexibility and adaptability for disaster monitoring and relief

A Framework for QoS-aware Execution of Workflows over the Cloud

The Cloud Computing paradigm is providing system architects with a new powerful tool for building scalable applications. Clouds allow allocation of resources on a "pay-as-you-go" model, so that additional resources can be requested during peak loads and released after that. However, this flexibility asks for appropriate dynamic reconfiguration strategies. In this paper we describe SAVER (qoS-Aware workflows oVER the Cloud), a QoS-aware algorithm for executing workflows involving Web Services hosted in a Cloud environment. SAVER allows execution of arbitrary workflows subject to response time constraints. SAVER uses a passive monitor to identify workload fluctuations based on the observed system response time. The information collected by the monitor is used by a planner component to identify the minimum number of instances of each Web Service which should be allocated in order to satisfy the response time constraint. SAVER uses a simple Queueing Network (QN) model to identify the optimal resource allocation. Specifically, the QN model is used to identify bottlenecks, and predict the system performance as Cloud resources are allocated or released. The parameters used to evaluate the model are those collected by the monitor, which means that SAVER does not require any particular knowledge of the Web Services and workflows being executed. Our approach has been validated through numerical simulations, whose results are reported in this paper

Open data and the academy: an evaluation of CKAN for research data management

This paper offers a full and critical evaluation of the open source CKAN software (http://ckan.org) for use as a Research Data Management (RDM) tool within a university environment. It presents a case study of CKAN's implementation and use at the University of Lincoln, UK, and highlights its strengths and current weaknesses as an institutional Research Data Management tool. The author draws on his prior experience of implementing a mixed media Digital Asset Management system (DAM), Institutional Repository (IR) and institutional Web Content Management System (CMS), to offer an outline proposal for how CKAN can be used effectively for data analysis, storage and publishing in academia. This will be of interest to researchers, data librarians, and developers, who are responsible for the implementation of institutional RDM infrastructure. This paper is presented as part of the dissemination activities of the Jisc-funded Orbital project (http://orbital.blogs.lincoln.ac.uk

Abmash: Mashing Up Legacy Web Applications by Automated Imitation of Human Actions

Many business web-based applications do not offer applications programming interfaces (APIs) to enable other applications to access their data and functions in a programmatic manner. This makes their composition difficult (for instance to synchronize data between two applications). To address this challenge, this paper presents Abmash, an approach to facilitate the integration of such legacy web applications by automatically imitating human interactions with them. By automatically interacting with the graphical user interface (GUI) of web applications, the system supports all forms of integrations including bi-directional interactions and is able to interact with AJAX-based applications. Furthermore, the integration programs are easy to write since they deal with end-user, visual user-interface elements. The integration code is simple enough to be called a "mashup".Comment: Software: Practice and Experience (2013)

MobiThin management framework: design and evaluation

In thin client computing, applications are executed on centralized servers. User input (e.g. keystrokes) is sent to a remote server which processes the event and sends the audiovisual output back to the client. This enables execution of complex applications from thin devices. Adopting virtualization technologies on the thin client server brings several advantages, e.g. dedicated environments for each user and interesting facilities such as migration tools. In this paper, a mobile thin client service offered to a large number of mobile users is designed. Pervasive mobile thin client computing requires an intelligent service management to guarantee a high user experience. Due to the dynamic environment, the service management framework has to monitor the environment and intervene when necessary (e.g. adapt thin client protocol settings, move a session from one server to another). A detailed performance analysis of the implemented prototype is presented. It is shown that the prototype can handle up to 700 requests/s to start the mobile thin client service. The prototype can make a decision for up to 700 monitor reports per second