11,803 research outputs found
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
Smart, Autonomous and Reliable Internet of Things
AbstractThe dynamic rapidly changing and technology-rich digital environment enables the provision of added-value applications that exploit a multitude of devices contributing services and information. As the Internet of Things (IoT) techniques mature and become ubiquitous, emphasis is put upon approaches that allow things to become smarter, more reliable and more autonomous. In this paper we present challenges and enablers as technologies that will allow things to evolve and act in a more autonomous way, becoming more reliable and smarter. We describe decentralized management mechanisms targeting IoT-based systems in order to enable the exploitation of millions of devices, while we also present an architecture that allows things to learn based on others experiences. The proposed architectural approach also introduces situational knowledge acquisition and analysis techniques in order to make things aware of conditions and events affecting IoT-based systems behavior
A Reputation-Based Approach to Self-Adaptive Service Selection
Service-orientation provides concepts and tools for flexible composition and management of largescale distributed software applications. The automated run-time management of such loosely coupled software systems, however, poses still major challenges and is therefore an active research area, including the use of novel computing paradigms. In this context, the dynamic and adaptive selection of best possible service providers is an important task, which can be addressed by an appropriate middleware layer that allows considering different service quality aspects when managing the adaptive execution of distributed service workflows dynamically. In such an approach, service consumers are enabled to delegate the adaptive selection of service providers at run-time to the execution infrastructure. The selection criteria used are based on the cost of a service provision and the continuous, dynamic evaluation of reputations of providers, i.e. maintained track records of meeting the respective service commitments. This paper discusses the design and operating principle of such an automatic service selection middleware extension. Its ability to balance different quality criteria for service selection, such as service cost vs. the reliability of provision, is empirically evaluated based on a multi-agent platform approach
Microservice Transition and its Granularity Problem: A Systematic Mapping Study
Microservices have gained wide recognition and acceptance in software
industries as an emerging architectural style for autonomic, scalable, and more
reliable computing. The transition to microservices has been highly motivated
by the need for better alignment of technical design decisions with improving
value potentials of architectures. Despite microservices' popularity, research
still lacks disciplined understanding of transition and consensus on the
principles and activities underlying "micro-ing" architectures. In this paper,
we report on a systematic mapping study that consolidates various views,
approaches and activities that commonly assist in the transition to
microservices. The study aims to provide a better understanding of the
transition; it also contributes a working definition of the transition and
technical activities underlying it. We term the transition and technical
activities leading to microservice architectures as microservitization. We then
shed light on a fundamental problem of microservitization: microservice
granularity and reasoning about its adaptation as first-class entities. This
study reviews state-of-the-art and -practice related to reasoning about
microservice granularity; it reviews modelling approaches, aspects considered,
guidelines and processes used to reason about microservice granularity. This
study identifies opportunities for future research and development related to
reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table
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