8,685 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
On the feasibility of collaborative green data center ecosystems
The increasing awareness of the impact of the IT sector on the environment, together with economic factors, have fueled many research efforts to reduce the energy expenditure of data centers. Recent work proposes to achieve additional energy savings by exploiting, in concert with customers, service workloads and to reduce data centers’ carbon footprints by adopting demand-response mechanisms between data centers and their energy providers. In this paper, we debate about the incentives that customers and data centers can have to adopt such measures and propose a new service type and pricing scheme that is economically attractive and technically realizable. Simulation results based on real measurements confirm that our scheme can achieve additional energy savings while preserving service performance and the interests of data centers and customers.Peer ReviewedPostprint (author's final draft
ClouNS - A Cloud-native Application Reference Model for Enterprise Architects
The capability to operate cloud-native applications can generate enormous
business growth and value. But enterprise architects should be aware that
cloud-native applications are vulnerable to vendor lock-in. We investigated
cloud-native application design principles, public cloud service providers, and
industrial cloud standards. All results indicate that most cloud service
categories seem to foster vendor lock-in situations which might be especially
problematic for enterprise architectures. This might sound disillusioning at
first. However, we present a reference model for cloud-native applications that
relies only on a small subset of well standardized IaaS services. The reference
model can be used for codifying cloud technologies. It can guide technology
identification, classification, adoption, research and development processes
for cloud-native application and for vendor lock-in aware enterprise
architecture engineering methodologies
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
Symbiotic and sensitivity-aware architecture for globally-optimal benefit in self-adaptive cloud
Due to the uncertain and dynamic demand for Quality of Service (QoS) in cloud-based systems, engineering self-adaptivity in cloud architectures require novel approaches to support on-demand elasticity. The architecture should dynamically select an elastic strategy, which optimizes the global benefit for QoS and cost objectives for all cloud-based services. The architecture shall also provide mechanisms for reaching the strategy with minimal overhead. However, the challenge in the cloud is that the nature of objectives (e.g., throughput and the required cost) and QoS interference could cause overlapping sensitivity amongst intra-and inter-services objectives, which leads to objective-dependency (i.e., conflicted or harmonic) during optimization. In this paper, we propose a symbiotic and sensitivity-aware architecture for optimizing global-benefit with reduced overhead in the cloud. The architecture dynamically partitions QoS and cost objectives into sensitivity independent regions, where the local optimums are achieved. In addition, the architecture realizes the concept of symbiotic feedback loop, which is a bio-directional self-adaptive action that not only allows to dynamically monitor and adapt the managed services by scaling to their demand, but also to adaptively consolidate the managing system by re-partitioning the regions based on symptoms. We implement the architecture as a prototype extending on decentralized MAPE loop by introducing an Adaptor component. We then experimentally analyze and evaluate our architecture using hypothetical scenarios. The results reveal that our symbiotic and sensitivity-aware architecture is able to produce even better global benefit and smaller overhead in contrast to other non sensitivity-aware architectures
Benefit-Cost Analysis for Transportation Planning and Public Policy: Towards Multimodal Demand Modeling
This report examines existing methods of benefit-cost analysis (BCA) in two areas, transportation policy and transportation planning, and suggests ways of modifying these methods to account for travel within a multimodal system. Although the planning and policy contexts differ substantially, this report shows how important multimodal impacts can be incorporated into both by using basic econometric techniques and even simpler rule-of-thumb methods. Case studies in transportation planning focus on the California Department of Transportation (Caltrans), but benchmark California’s competencies by exploring methods used by other states and local governments. The report concludes with a list and discussion of recommendations for improving transportation planning models and methods. These will have immediate use to decision makers at Caltrans and other state DOTs as they consider directions for developing new planning capabilities. This project also identifies areas, and lays groundwork, for future research. Finally, by fitting the planning models into the broader context of transportation policy, this report will serve as a resource for students and others who wish to better understand BCA and its use in practice
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