Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

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 Autonomic HPC Clouds

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.The long tail of science using HPC facilities is looking nowadays to instant available HPC Clouds as a viable alternative to the long waiting queues of supercomputing centers. While the name of HPC Cloud is suggesting a Cloud service, the current HPC-as-a-Service is mainly an offer of bar metal, better named cluster-on-demand. The elasticity and virtualization benefits of the Clouds are not exploited by HPC-as-a-Service. In this paper we discuss how the HPC Cloud offer can be improved from a particular point of view, of automation. After a reminder of the characteristics of the Autonomic Cloud, we project the requirements and expectations to what we name Autonomic HPC Clouds. Finally, we point towards the expected results of the latest research and development activities related to the topics that were identified.The work related to Autonomic HPC Clouds is supported by the European Commission under grant agreement H2020-6643946 (CloudLightning). The CLoudLightning project proposal was prepared by eight partner institutions, three of them as earlier partners in the COST Action IC1305 NESUS, benefiting from its inputs for the proposal. The section related to Autonomic Clouds is supported by the Romanian UEFISCDI under grant agreement PN-II-ID-PCE-2011- 3-0260 (AMICAS)

Investigating Decision Support Techniques for Automating Cloud Service Selection

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud based infrastructure services (e.g. storage, network, CPU).Comment: Accepted by IEEE Cloudcom 2012 - PhD consortium trac

Using Process Technology to Control and Coordinate Software Adaptation

We have developed an infrastructure for end-to-end run-time monitoring, behavior/performance analysis, and dynamic adaptation of distributed software. This infrastructure is primarily targeted to pre-existing systems and thus operates outside the target application, without making assumptions about the target's implementation, internal communication/computation mechanisms, source code availability, etc. This paper assumes the existence of the monitoring and analysis components, presented elsewhere, and focuses on the mechanisms used to control and coordinate possibly complex repairs/reconfigurations to the target system. These mechanisms require lower level effectors somehow attached to the target system, so we briefly sketch one such facility (elaborated elsewhere). Our main contribution is the model, architecture, and implementation of Workflakes, the decentralized process engine we use to tailor, control, coordinate, etc. a cohort of such effectors. We have validated the Workflakes approach with case studies in several application domains. Due to space restrictions we concentrate primarily on one case study, briefly discuss a second, and only sketch others