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2019 | Book

CELA: Cost-Efficient, Location-Aware VM and Data Placement in Geo-Distributed DCs Read chapter Read first chapter

Cloud Computing and Services Science

8th International Conference, CLOSER 2018, Funchal, Madeira, Portugal, March 19-21, 2018, Revised Selected Papers

Editors: Víctor Méndez Muñoz, Donald Ferguson, Dr. Markus Helfert, Claus Pahl

Publisher: Springer International Publishing

Book Series : Communications in Computer and Information Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes extended, revised and selected papers from the 8th International Conference on Cloud Computing and Services Science, CLOSER 2018, held in Funchal, Portugal in March 2018. The 11 papers presented in this volume were carefully reviewed and selected from a total of 94 submissions. CLOSER 2018 focused on the emerging area of Cloud Computing, inspired by some latest advances that concern the infrastructure, operations and available services throughout the global network.

Table of Contents

Frontmatter
CELA: Cost-Efficient, Location-Aware VM and Data Placement in Geo-Distributed DCs
Abstract
Geo-distributed data centres (DCs) that recently established due to the increasing use of on-demand cloud services have increasingly attracted cloud providers as well as researchers attention. Energy and data transmission cost are two significant problems that degrades the cloud provider net profit. However, increasing awareness about CO2 emissions leads to a greater demand for cleaner products and services. Most of the proposed approaches tackle these problems separately. This paper proposes green approach for joint management of virtual machine (VM) and data placement that results in less energy consumption, less CO2 emission, and less access latency towards large-scale cloud providers operational cost minimization. To advance the performance of the proposed model, a novel machine-learning model was constructed. Extensive simulation using synthetic and real data are conducted using the CloudSim simulator to validate the effectiveness of the proposed model. The promising results approve the efficacy of the CELA model compared to other competing models in reducing network latency, energy consumption, CO2 emission and total cloud provider operational cost.
Soha Rawas, Ahmed Zekri, Ali El Zaart
Will Cloud Gain an Edge, or, CLOSER, to the Edge
Abstract
This paper accompanies a keynote speech given at the 8th International Conference on Cloud Computing and Services Science, CLOSER 2018. The keynote offered an overview of ‘traditional’ and ‘new’ Cloud Computing, and what we might appreciate of each. In respect to ‘traditional’, issues of performance and energy efficiency, and the potential conflict between these, were discussed, as well as how these were still relevant to ‘new’ Cloud. Key to the ‘new’ Cloud is the advent of so-called function-as-a-service and edge, to which these issues of performance and lessons learned from energy efficiency can be applied. Important to this is to establish what we mean by edge as distinct from other things as may be similarly referred to. The relevance of new Cloud, then, to Connected and Autonomous Vehicles offers for an industry vertical that could exploit such formulations, and attempts to do this will lead to a variety of technical and research questions. Also, with a person in America having been killed by a vehicle acting autonomously near to the timing of this talk, safety concerns should never be far from thinking in addressing such questions.
Lee Gillam
Model-Based Generation of Self-adaptive Cloud Services
Abstract
An important shift in software delivery is the definition of a cloud service as an independently deployable unit by following the microservices architectural style. Container virtualization facilitates development and deployment by ensuring independence from the runtime environment. Thus, cloud services are built as container-based systems - a set of containers that control the lifecycle of software and middleware components. However, using containers leads to a new paradigm for service development and operation: Self-service environments enable software developers to deploy and operate container-based systems on their own - you build it, you run it. Following this approach, more and more operational aspects are transferred towards the responsibility of software developers. In this work, we propose a concept for self-adaptive cloud services based on container virtualization in line with the microservices architectural style and present a model-based approach that assists software developers in building these services. Based on operational models specified by developers, the mechanisms required for self-adaptation are automatically generated. As a result, each container automatically adapts itself in a reactive, decentralized manner. We evaluate a prototype, which leverages the emerging TOSCA standard to specify operational behavior in a portable manner.
Stefan Kehrer, Wolfgang Blochinger
A Record/Replay Debugger for Service Development on the Cloud
Abstract
Cloud based software development platforms are continuously becoming more powerful and penetrate towards the daily routines of modern developers. This paper presents a debugging approach that can be used in cloud based service development platforms where developer is working on relatively small sized scripts to be hosted on multi-tenant cloud platforms. Presented remote debugging approach utilizes record/replay technique to re-execute and record the variable evaluations whenever an exception is thrown during the developed service’s run-time. Additionally, an alternative recording scheme is also proposed that involves only recording external data accesses. Memory and run-time overhead of proposed approaches show that remote debugging approach can be useful especially when the minimal recording scheme is applied.
M. Subhi Sheikh Quroush, Tolga Ovatman
Smart Connected Digital Factories: Unleashing the Power of Industry 4.0
Abstract
Recent initiatives such as the Industrial IoT, or Industry 4.0, as it has been dubbed, are fundamentally reshaping the industrial landscape by promoting connected manufacturing solutions that realize a “digital thread” which connects all aspects of manufacturing including all data and operations involved in the production of goods and services. This paper focuses on Industry 4.0 technologies and how they support the emergence of highly-connected, knowledge-enabled factories, referred to as Smart Manufacturing Networks. Smart Manufacturing Networks comprise an ecosystem of connected factory sites, plants, and self-regulating machines able to customize output, and allocate resources over manufacturing clouds optimally to offer a seamless transition between the physical and digital worlds of product design and production.
Michael P. Papazoglou, Andreas S. Andreou
Interoperability Between SaaS and Data Layers: Enhancing the MIDAS Middleware
Abstract
Nowadays, the volume of digital data grows exponentially. As a result, many organizations store and provide their data in cloud computing services. While Software as a Service (SaaS) is a typical model for application delivery, Data as a Service (DaaS) and Database as a Service (DBaaS) are models to provide data and database management systems on demand, respectively. Heterogeneity of these services makes it difficult to automate communication among them. In these cases, SaaS applications require additional efforts to access those data. Besides that, the lack of standardization from DaaS and DBaaS generates a problem of communication among cloud layers. In this paper, we propose an enhancing version of MIDAS (Middleware for DaaS and SaaS) that provides interoperability between Services (SaaS) and Data layers (DaaS and DBaaS). Our current version of MIDAS is concerned with (i) presenting a Description Logic representation of the middleware and (ii) detailing the Web Crawler. Experiments were carried out to evaluate execution time, overhead, interoperability, and correctness. Results demonstrated our effectiveness on addressing interoperability concerns in cloud computing environments.
Elivaldo Lozer Fracalossi Ribeiro, Marcelo Aires Vieira, Daniela Barreiro Claro, Nathale Silva
Continuous Architecting with Microservices and DevOps: A Systematic Mapping Study
Abstract
Context: Several companies are migrating their information systems into the Cloud. Microservices and DevOps are two of the most common adopted technologies. However, there is still a lack of understanding how to adopt a microservice-based architectural style and which tools and technique to use in a continuous architecting pipeline.
Objective: We aim at characterizing the different microservice architectural style principles and patterns in order to map existing tools and techniques adopted in the context of DevOps.
Methodology: We conducted a Systematic Mapping Study identifying the goal and the research questions, the bibliographic sources, the search strings, and the selection criteria to retrieve the most relevant papers.
Results: We identified several agreed microservice architectural principles and patterns widely adopted and reported in 23 case studies, together with a summary of the advantages, disadvantages, and lessons learned for each pattern from the case studies. Finally, we mapped the existing microservices-specific techniques in order to understand how to continuously deliver value in a DevOps pipeline. We depicted the current research, reporting gaps and trends.
Conclusion: Different patterns emerge for different migration, orchestration, storage and deployment settings. The results also show the lack of empirical work on microservices-specific techniques, especially for the release phase in DevOps.
Davide Taibi, Valentina Lenarduzzi, Claus Pahl
Towards Pricing-Aware Consolidation Methods for Cloud Datacenters
Abstract
Cloud Computing has become the major candidate for commercial and academic compute infrastructures. Its virtualized solutions enable efficient, high-rate exploitation of computational and storage resources due to recent advances in data centre consolidation. Resources leased from these providers are offered under many pricing schemes which are often times influenced by the utilised consolidation techniques. In this paper, we provide a foundation to understand the inter-relationship of pricing and consolidation. This has a potential to reach additional gains for the providers from a new angle. To this end we discuss the introduction of a pricing oriented extension of the DISSECT-CF cloud simulator, and introduce a simple consolidation framework that allows easy experimentation with combined pricing and consolidation approaches. Using our generic extensions, we show several simple but easy to combine pricing strategies. Finally, we analyse the impact of consolidators on the profitability of providers applying our simple schemes with the help of real world workload traces.
Gabor Kecskemeti, Andras Markus, Attila Kertesz
Optimising QoS-Assurance, Resource Usage and Cost of Fog Application Deployments
Abstract
Identifying the best application deployment to distribute application components in Fog infrastructures – spanning the IoT-to-Cloud continuum – is a challenging task for application deployers. Indeed, it requires fulfilling all application requirements, whilst determining a trade-off among different objectives (i.e., QoS assurance, Fog resource consumption and cost), resulting in a complex and time-consuming decision-making process to be tuned manually. In this paper, we present a simple multi-objective optimisation scheme that permits selecting the best placement of application components, balancing the trade-off among QoS-assurance, Fog resource consumption and monthly deployment costs. We exploit our prototype, extended with parallel Monte Carlo simulations, and a motivating example to show how IT experts can benefit from our approach.
Antonio Brogi, Stefano Forti, Ahmad Ibrahim
Right Scaling for Right Pricing: A Case Study on Total Cost of Ownership Measurement for Cloud Migration
Abstract
Cloud computing promises traditional enterprises and independent software vendors a myriad of advantages over on-premise installations including cost, operational and organizational efficiencies. The decision to migrate software configured for on-premise delivery to the cloud requires careful technical consideration and planning. In this chapter, we discuss the impact of right-scaling on the cost modelling for migration decision making and price setting of software for commercial resale. An integrated process is presented for measuring total cost of ownership, taking in to account IaaS/PaaS resource consumption based on forecast SaaS usage levels. The process is illustrated with a real world case study.
Pierangelo Rosati, Frank Fowley, Claus Pahl, Davide Taibi, Theo Lynn
Malicious Behavior Classification in PaaS
Abstract
PaaS delivery model let cloud customers share cloud provider resources through their cloud applications. This structure requires a strong security mechanism that isolates customer applications to prevent interference. For concurrent configurations of common providers, cloud applications are mostly deployed as server side web applications that share a common thread pool. In this paper, a malicious thread behavior detection framework that utilizes machine learning algorithms is proposed to classify whether the cloud platform executes a malicious flow in the currently active thread. The framework uses CPU metrics of worker threads and N-Gram frequencies of basic, privacy-friendly user operations as its features during machine learning phase. The proof of concept results are evaluated on a real-life cloud application scenario using Random Forest, Adaboost and Bagging ensemble learning algorithms. The scenario results indicate that the malicious request detection accuracy of the proposed framework is up to 87.6%. It is foreseen that better feature selection and targeted classifiers may end up with better ratios.
Cemile Diler Özdemir, Mehmet Tahir Sandıkkaya, Yusuf Yaslan
Backmatter
Metadata
Title
Cloud Computing and Services Science
Editors
Víctor Méndez Muñoz
Donald Ferguson
Dr. Markus Helfert
Claus Pahl
Copyright Year
2019
Electronic ISBN
978-3-030-29193-8
Print ISBN
978-3-030-29192-1
DOI
https://doi.org/10.1007/978-3-030-29193-8

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