Systematic scalability assessment for feature oriented multi-tenant services

Preuveneers, Davy; Heyman, Thomas; Berbers, Yolande; Joosen, Wouter

doi:10.1016/j.jss.2015.12.024

Cited by 12 publications

(9 citation statements)

References 38 publications

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“…Reviewing and refining themes: the quality attributes, metrics (including their measurement methods or measurement functions, measurement result, unity of measurement), and measured cloud artifacts identified from the fourth step were checked against each other in order to understand what themes had to be merged with others or dropped. For example, availability and serviceability were merged because they had the same purpose, while throughput was dropped because it was a repeated metric (it was the same as the number of service requests served over total service time with the same measurement function [43], [44], [45]). We initially categorized and organized the metrics by considering the QoS characteristics, the quality attributes, and the name of the metrics.…”

Section: ) Synthesis Methodsmentioning

confidence: 99%

A Taxonomy of Quality Metrics for Cloud Services

et al. 2020

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A large number of metrics with which to assess the quality of cloud services have been proposed over the last years. However, this knowledge is still dispersed, and stakeholders have little or no guidance when choosing metrics that will be suitable to evaluate their cloud services. The objective of this paper is, therefore, to systematically identify, taxonomically classify, and compare existing quality of service (QoS) metrics in the cloud computing domain. We conducted a systematic literature review of 84 studies selected from a set of 4333 studies that were published from 2006 to November 2018. We specifically identified 470 metric operationalizations that were then classified using a taxonomy, which is also introduced in this paper. The data extracted from the metrics were subsequently analyzed using thematic analysis. The findings indicated that most metrics evaluate quality attributes related to performance efficiency (64%) and that there is a need for metrics that evaluate other characteristics, such as security and compatibility. The majority of the metrics are used during the Operation phase of the cloud services and are applied to the running service. Our results also revealed that metrics for cloud services are still in the early stages of maturity-only 10% of the metrics had been empirically validated. The proposed taxonomy can be used by practitioners as a guideline when specifying service level objectives or deciding which metric is best suited to the evaluation of their cloud services, and by researchers as a comprehensive quality framework in which to evaluate their approaches.

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Section: ) Synthesis Methodsmentioning

confidence: 99%

A Taxonomy of Quality Metrics for Cloud Services

et al. 2020

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“…Data extensibility is a great challenge with Shared model compared to isolated schema. [14] provides data extensibility using multi-tenant metadata and multitenant indexes. This type of design requires complex schema and creation of pre-allocated fields (dummy columns) violating relational database normalization rules [1].…”

Section: Shared Schema Modelmentioning

confidence: 99%

“…According to Antonio [14], a tenant in a multitenant environment subscribes or pays to use the SaaS application however a tenant comprises many end-users. In other words, a tenant represents a group of users of an organization that employs a set of SaaS customized functionalities in multi-tenant environment to achieve organizational goals.…”

Section: Introductionmentioning

confidence: 99%

Multi-tenancy Design Patterns in SaaS Applications: A Performance Evaluation Case Study

Abdul¹,

Bass²,

Ghavimi³

et al. 2018

IJDS

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Utility-like computing has emerged as the future of computing for many organizations seeking to remain competitive in today's business environment. Promising features such as rapid elasticity, low cost provisioning, pay-as-use model, layered security, measured service, resource pooling, are the reasons companies are opting for this technology. Cloud technologies are provided as services ranging from Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Data as a Service (DaaS). SaaS has become one of de facto approach for deploying cloud base services or applications for many businesses. At the core of SaaS is Multi-tenancy; multi-tenancy gives customers (i.e. tenants) and providers vast opportunities to leverage the power of cloud infrastructure by consolidating operational entities. The drive toward multi-tenancy in SaaS application is a result of the economic benefit derived by shared development and maintenance cost. This paper presents different multi-tenancy models at the data layer as dedicated, isolated and shared. The paper further empirically evaluates the performance of these models in a containerized environment. Our results show that under a containerized environment dedicated and isolated schema performed reasonably well in terms of latency when compared to shared model. Although the shared model proved to more resource efficient, it performance is greatly affected by finite resources shared by many concurrent tenants.

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“…We also have Preuveneers et al (2016) who present a tool support and a methodology to analyse the scalability of distributed, feature oriented multi-tenant software systems in a continuous integration process.…”

Section: Scalabilitymentioning

confidence: 99%

Towards a scalability approach for risk mitigation in electrical systems

Larbi

Belalem

Beldjilali

2018

IJKEDM

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Electrical energy has been used for decades to power domestic equipment, small and large industries and transportation with the electrification of everything, the availability of electricity becomes crucial. In order to guarantee the continuity of the electrical energy supply, companies must have effective means to prevent risks that may arise on the electricity networks. This paper is focused on the risk of insufficient power supply for end customers. The solutions consist of upsizing the existing equipment configuration and/or add other equipments in order to guarantee an increase in power supply. The proposed approach is based on distributed artificial entities corresponding to the distributed enterprise actors. We propose a control system, based on a decision making system to help decision-makers to take the best scalability solution. The results show that the degree of effectiveness of each type of scalability depends on one electrical system configuration to another.

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Systematic scalability assessment for feature oriented multi-tenant services

Cited by 12 publications

References 38 publications

A Taxonomy of Quality Metrics for Cloud Services

A Taxonomy of Quality Metrics for Cloud Services

Multi-tenancy Design Patterns in SaaS Applications: A Performance Evaluation Case Study

Towards a scalability approach for risk mitigation in electrical systems

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