Resource management in cloud platform as a service systems: Analysis and opportunities

Costache, Stefania; Dib, Djawida; Parlavantzas, Nikos; Morin, Christine

doi:10.1016/j.jss.2017.05.035

Cited by 28 publications

(23 citation statements)

References 21 publications

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“…Jennings et al [39] and Costache et al [40] present classifications of resource management techniques in cloud platforms. More specifically, Jennings [41] and Borg [42], the predecessor of Kubernetes.…”

Section: Related Workmentioning

confidence: 99%

A Comprehensive Feature Comparison Study of Open-Source Container Orchestration Frameworks

et al. 2019

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(1) Background: Container orchestration frameworks provide support for management ofcomplex distributed applications. Different frameworks have emerged only recently, and they havebeen in constant evolution as new features are being introduced. This reality makes it difficult forpractitioners and researchers to maintain a clear view of the technology space. (2) Methods: wepresent a descriptive feature comparison study of the three most prominent orchestrationframeworks: Docker Swarm, Kubernetes, and Mesos, which can be combined with Marathon,Aurora or DC/OS. This study aims at (i) identifying the common and unique features of allframeworks, (ii) comparing these frameworks qualitatively ánd quantitatively with respect togenericity in terms of supported features, and (iii) investigating the maturity and stability of theframeworks as well as the pioneering nature of each framework by studying the historical evolutionof the frameworks on GitHub. (3) Results: (i) we have identified 124 common features and 54 uniquefeatures that we divided into a taxonomy of 9 functional aspects and 27 functional sub-aspects. (ii)Kubernetes supports the highest number of accumulated common and unique features for all 9functional aspects; however, no evidence has been found for significant differences in genericitywith Docker Swarm and DC/OS. (iii) Very little feature deprecations have been found and 15 out of27 sub-aspects have been identified as mature and stable. These are pioneered in descending orderby Kubernetes, Mesos, and Marathon. (4) Conclusion: there is a broad and mature foundation thatunderpins all container orchestration frameworks. Likely areas for further evolution and innovationinclude system support for improved cluster security and container security, performance isolationof GPU, disk and network resources, and network plugin architectures.

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Section: Related Workmentioning

confidence: 99%

A Comprehensive Feature Comparison Study of Open-Source Container Orchestration Frameworks

et al. 2019

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“…In such architecture a VM image is dedicated to PHP applications, while another VM image is only used to execute Java Servlet applications. A more detailed presentation of PaaS cloud providers can be found in [6].…”

Section: Context and Motivationmentioning

confidence: 99%

“…At each of these 3 phases, PaaS clouds deliver several parameters to control the execution of applications [6]. During the development phase, the application's programming language is specified as well as the version of the language interpreter when required.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Analysis of PaaS Users Parameters on Applications Energy Consumption

Guyon

Orgerie

Morin

2018

2018 IEEE International Conference on Cloud Engineering (IC2E)

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Abstract-Reducing the energy consumed by datacenters becomes of major importance due to the current climate changes and the increasing success of cloud computing. Studies to optimize the energy consumption of cloud systems exist but do not take into account the end-user. The goal of this paper is to understand and quantify the link between the PaaS parameters a user can configure and the application energy consumption. In this work we summarize the parameters available at the PaaS layer and measure their influence on the energy consumed by RUBiS, a web application benchmark. Different database technologies and programming languages are compared as well as their software versions. Experimentation results show that by themselves the existing PaaS parameters can variate the application energy consumption. Although it shows that different programming languages do not consume the same, we discovered that a wider energy difference exists between database technologies which means higher energy savings is possible when the less consuming technology is used. Thus, users could optimize the energy impact of their applications by carefully configuring on-hand PaaS parameters.

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“…19,20 Cloud has economic and technological benefits in the service provisioning domain. 21 Four aspects of services are offered to the customers, including Software as a Service, 22,23 Platform as a Service, 24,25 Infrastructure as a Service, 26,27 and Expert as a Service. [28][29][30][31][32] However, it has faced to different challenges like scheduling, 33,34 resource allocation, 35 service composition, 36 replication, 37,38 load balancing, 39 energy consumption, 40,41 big data, [42][43][44] and trust management.…”

mentioning

confidence: 99%

Nature inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments

Asghari

Navimipour

2018

Int J Communication

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Summary Many sorts of services in the cloud environments must be composited based on the user's requests to meet the requirements. Thus, the distributed services are joined to the cloud services through service composition. Also, it is known as NP‐hard problems and many researchers significantly are focused on this problem in recent years. Therefore, many different nature‐inspired meta‐heuristic techniques are proposed for solving this problem. The nature‐inspired meta‐heuristic techniques have an important role in solving the service composition problem in the cloud environments, but there is not a wide‐ranging and detailed paper about reviewing and studying the important mechanisms in this field. Therefore, this study presents a comprehensive analysis of the nature‐inspired meta‐heuristic techniques for the service composition issue in the cloud computing. The review also contains a classification of the important techniques. These classifications include Ant Colony Optimization, Bee Colony Optimization, Genetic Algorithm, Particle Swarm Optimization, Cuckoo Optimization Algorithm, Bat Algorithm, greedy algorithm, and hybrid algorithm. An important aim of this paper is to highlight the emphasis on the optimization algorithms, and the benefits to tackle the challenges are encountered in the cloud service composition. Also, this paper presents the advantages and disadvantages of the nature‐inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments. Moreover, this paper aims to provide more efficient service composition algorithms in the future. Finally, the obtained results have shown that the discussed algorithms have an important effect in solving the cloud service composition problem, and this effect has been increased in recent years.

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Resource management in cloud platform as a service systems: Analysis and opportunities

Cited by 28 publications

References 21 publications

A Comprehensive Feature Comparison Study of Open-Source Container Orchestration Frameworks

A Comprehensive Feature Comparison Study of Open-Source Container Orchestration Frameworks

An Experimental Analysis of PaaS Users Parameters on Applications Energy Consumption

Nature inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments

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