Adding Spatial Information to Software Component Model - the Localization Effect Ali Hassan
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Engage: a Deployment Management System
Engage: A Deployment Management System Jeffrey Fischer Rupak Majumdar Shahram Esmaeilsabzali genForma Corp, USA MPI-SWS, Germany MPI-SWS, Germany jeffrey.fi[email protected] [email protected] [email protected] Abstract figurations between individual components and services can cause Many modern applications are built by combining independently the application to become unstable or corrupted. developed packages and services that are distributed over many While there are tools that automate portions of this process for machines with complex inter-dependencies. The assembly, instal- specific packages, e.g., package managers on Linux distributions, lation, and management of such applications is hard, and usually there are few tools that provide end-to-end functionality for the en- performed either manually or by writing customized scripts. We tire software stack, especially for distributed applications running present Engage, a system for configuring, installing, and managing on many nodes (e.g., in a private or public cloud infrastructure). complex application stacks. Engage consists of three components: a In practice, large-scale software stacks are often managed using domain-specific model to describe component metadata and inter- custom script-based tools and manual techniques. This process is component dependencies; a constraint-based algorithm that takes error-prone, as upgrades to individual packages can break existing a partial installation specification and computes a full installation and implicit dependencies in the system. It is also labor-intensive, plan; and a runtime system that co-ordinates the deployment of the since the process must be performed manually by system admin- ff application across multiple machines and manages the deployed istrators, developers, and end-users, and e ort may be duplicated system. -
Papers from the 12Th Advanced Summer School on Service-Oriented Computing (Summersoc’18)
RC25681 (WAT1810-052) October 23, 2018 Computer Science IBM Research Report Papers From the 12th Advanced Summer School on Service-Oriented Computing (SummerSOC’18) Johanna Barzen1, Rania Khalaf2, Frank Leymann1, Bernhard Mitschang1 Editors 1University of Stuttgart Universitätsstraße 38 70569 Stuttgart, Germany 2IBM Research Division, Cambridge 75 Binney Street Cambridge, MA 02142 USA Research Division Almaden – Austin – Beijing – Brazil – Cambridge – Dublin – Haifa – India – Kenya – Melbourne – T.J. Watson – Tokyo – Zurich LIMITED DISTRIBUTION NOTICE: This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). Many reports are available at http://domino.watson.ibm.com/library/CyberDig.nsf/home. The 12th Advanced Summer School on Service-Oriented Computing June 24 - June 29 2018 Hersonissos, Crete, Greece th The 12 Advanced Summer School on Service Oriented Computing (SummerSOC’18) continued a successful series of summer schools that started in 2007, regularly attracting world-class experts in Service Oriented Computing to present state-of-the-art research during a week-long program organized in several thematic tracks: patterns and IoT, Quantum Computing, formal methods for SOC, computing in the clouds, data science, e-Health and emerging topics. The advanced summer school is regularly attended by top researchers from academia and industry as well as by PhD and graduate students. -
Fuzzy-Based Microservice Resource Management Platform for Edge Computing in the Internet of Things
sensors Article Fuzzy-Based Microservice Resource Management Platform for Edge Computing in the Internet of Things David Chunhu Li 1 , Chiing-Ting Huang 2, Chia-Wei Tseng 2 and Li-Der Chou 2,* 1 Information Technology and Management Program, Ming Chuan University, Taoyuan City 333321, Taiwan; [email protected] 2 Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320317, Taiwan; [email protected] (C.-T.H.); [email protected] (C.-W.T.) * Correspondence: [email protected]; Tel.: +886-03-4227151 Abstract: Edge computing exhibits the advantages of real-time operation, low latency, and low network cost. It has become a key technology for realizing smart Internet of Things applications. Microservices are being used by an increasing number of edge computing networks because of their sufficiently small code, reduced program complexity, and flexible deployment. However, edge computing has more limited resources than cloud computing, and thus edge computing networks have higher requirements for the overall resource scheduling of running microservices. Accordingly, the resource management of microservice applications in edge computing networks is a crucial issue. In this study, we developed and implemented a microservice resource management platform for edge computing networks. We designed a fuzzy-based microservice computing resource scaling (FMCRS) algorithm that can dynamically control the resource expansion scale of microservices. We proposed and implemented two microservice resource expansion methods based on the resource usage of edge network computing nodes. We conducted the experimental analysis in six scenarios Citation: Li, D.C.; Huang, C.-T.; and the experimental results proved that the designed microservice resource management platform Tseng, C.-W.; Chou, L.-D. -
A Novel Genetic Service Function Deployment Management Platform for Edge Computing
Hindawi Mobile Information Systems Volume 2020, Article ID 8830294, 22 pages https://doi.org/10.1155/2020/8830294 Research Article A Novel Genetic Service Function Deployment Management Platform for Edge Computing David Chunhu Li ,1 Bo-Hun Chen,2 Chia-Wei Tseng,2 and Li-Der Chou 2 1Information Technology Management Program, Ming Chuan University, Taoyuan 333, Taiwan 2Department of Computer Science and Information Engineering, National Central University, Taoyuan 32001, Taiwan Correspondence should be addressed to Li-Der Chou; [email protected] Received 29 May 2020; Revised 27 August 2020; Accepted 21 September 2020; Published 9 October 2020 Academic Editor: Konglin Zhu Copyright © 2020 David Chunhu Li et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. *e various applications of the Internet of *ings and the Internet of Vehicles impose high requirements on the network environment, such as bandwidth and delay. To meet low-latency requirements, the concept of mobile edge computing has been introduced. *rough virtualisation technology, service providers can rent computation resources from the infrastructure of the network operator, whereas network operators can deploy all kinds of service functions (SFs) to the edge network to reduce network latency. However, how to appropriately deploy SFs to the edge of the network presents a problem. Apart from improving the network efficiency of edge computing service deployment, how to effectively reduce the cost of service deployment is also important to achieve a performance-cost balance. In this paper, we present a novel SF deployment management platform that allows users to dynamically deploy edge computing service applications with the lowest network latency and service deployment costs in edge computing network environments. -
Automatic Deployment of Component-Based Applications Tudor Alexandru Lascu, Jacopo Mauro, Gianluigi Zavattaro
Automatic deployment of component-based applications Tudor Alexandru Lascu, Jacopo Mauro, Gianluigi Zavattaro To cite this version: Tudor Alexandru Lascu, Jacopo Mauro, Gianluigi Zavattaro. Automatic deployment of component- based applications. Science of Computer Programming, Elsevier, 2015, 10.1016/j.scico.2015.07.006. hal-01233485 HAL Id: hal-01233485 https://hal.inria.fr/hal-01233485 Submitted on 25 Nov 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Automatic Deployment of Component-based Applications I Tudor A. Lascu1, Jacopo Mauro1, Gianluigi Zavattaro1 Department of Computer Science and Engineering - FoCUS INRIA Research Team University of Bologna, Italy Abstract In distributed systems like those based on cloud or service-oriented frameworks, applications are typically assembled by deploying and connecting a large num- ber of heterogeneous software components, spanning from fine-grained packages to coarse-grained complex services. Automation techniques and tools have been proposed to ease the deployment process of these complex system. By relying on a formal model of components, we describe a sound and complete algorithm for computing the sequence of actions that permits the deployment of a desired configuration even in the presence of circular dependencies among components. -
Cloudcamp: a Model-Driven Generative Approach for Automating Cloud Application Deployment and Management
TECHNICAL REPORT CloudCAMP: A Model-driven Generative Approach for Automating Cloud Application Deployment and Management Anirban Bhattacharjee, Yogesh Barve, Aniruddha Gokhale Department of Electrical Engineering and Computer Science Vanderbilt University, Nashville, Tennessee, USA Email: {anirban.bhattacharjee; yogesh.d.barve; a.gokhale}@vanderbilt.edu Takayuki Kuroda NEC Corporation Kawasaki, Kanagawa, Japan Email: [email protected] Abstract Businesses today are moving their infrastructure to the cloud environment to reduce their IT budgets and improve compliance to regulatory control. By using the cloud, industries also aim to deploy and deliver new applications and services rapidly with the ability to scale their applications horizontally and vertically to meet customer demands. Despite these trends, reliance on old school IT management and administration has left a legacy of poor manageability and inflexible infrastructure. In this realm, the DevOps community has made available various tools for deployment, management, and orchestration of complex, distributed cloud applications. Despite these modern trends, the continued reliance on old school IT management and administration methods have left a majority of developers lacking with the domain expertise to create, provision and manage complex IT environments using abstracted, script-centric approaches provided by DevOps tools. To address these challenges while emphasizing vendor-agnostic approaches for broader applicability, we present a model-driven generative approach that is compliant with the TOSCA specification where the users can model their business-relevant models, requiring only little domain expertise. In this context, the paper describes the metamodel of the domain-specific language that abstracts the business-relevant application requirements to generate the corresponding fully deployable infrastructure-as-code solutions, which can deploy, run, and manage the applications in the cloud environment.