Detecting Cloud (Anti)Patterns: OCCI Perspective

Brabra, Hayet; Mtibaa, Achraf; Sliman, Layth; Gaaloul, Walid; Benatallah, Boualem; Gargouri, Faïez

doi:10.1007/978-3-319-46295-0_13

Cited by 11 publications

(11 citation statements)

References 11 publications

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“…In the section, our objective is to experimentally prove the efficiency (in terms of easiness, coverage) of our simulation tool. In fact, the proposed extension can be easily integrated into any existing cloud computing API based on OCCI model such as OpenStack, Rackspace and Amazon S3 [14]. A user-friendly simulation GUI based on the proposed extension is provided to design easily the simulation configuration.…”

Section: Methodsmentioning

confidence: 99%

OCCI-Compliant Cloud Configuration Simulation

Ahmed-Nacer¹,

Gaaloul²,

Tata³

2017

2017 IEEE International Conference on Edge Computing (EDGE)

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In recent years many organizations such as, Amazon, Google, Microsoft, have accelerated the development of their cloud computing ecosystem. This rapid development has created a plethora of cloud resource management interfaces for provisioning, supervising, and managing cloud resources. Thus, there is an obvious need for the standardization of cloud resource management interfaces to cope with the prevalent issues of heterogeneity, integration, and portability issues. To this end, Open Cloud Computing Interface (OCCI) proposed one of the first widely accepted, community-based, open standard for managing any kinds of cloud resources. However, there is a strong need for having a simulation environment to study and analyze the performance of OCCI-compliant applications for two main reasons: (i) in absence of a simulation environment, these applications have to be tested on real cloud infrastructure, which induces a cost issue and (ii) various conditions prevailing in cloud environments are beyond the control of the developers involved in analyzing cloud resource allocation. Therefore, in this paper we propose, (i) an extension to the OCCI metamodel dedicated to the simulation of cloud resources using an opensource cloud simulation framework called CloudSim, (ii) a userfriendly graphical interface to generate the OCCI configuration for simulation.

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Section: Methodsmentioning

confidence: 99%

OCCI-Compliant Cloud Configuration Simulation

Ahmed-Nacer¹,

Gaaloul²,

Tata³

2017

2017 IEEE International Conference on Edge Computing (EDGE)

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“…Fig. 5 shows a partial instantiation of the (Anti) Pattern Ontology with information that we have extracted from a REST operation in the OOi RESTful API 9 in order to add a storage link between a volume and an instance of a VM. Once the detection rule for Compliant Link pattern was executed, the relationship "Rest:hasPattern" illustrated with red color, was instantiated between the Ptt:Compliant Link (Ptt:Pattern instance) and the Rest:Link Volume to Instance (REST:Operation instance).…”

Section: Analysis and Definition Of Detection Rulesmentioning

confidence: 99%

“…Evaluation of H3 (Extensibility). In our previous work [9], our approach allows defining 24 OCCI patterns and antipatterns. Currently, we added to this approach 21 new REST patterns and anti-patterns.…”

Section: Evaluation Of H2 (Usefulness)mentioning

confidence: 99%

“…To address this need, in our previous work [9], we leveraged patterns and anti-patterns to drive respectively the good and poor practices of OCCI best principles. In particular, we defined compliance to OCCI best principles as OCCI patterns and non-compliance to OCCI best principles as OCCI anti-patterns.…”

Section: Introductionmentioning

confidence: 99%

“…In the extension to our previous work [9], our ultimate objective is threefold: (i) Specifying along with OCCI (anti)patterns the REST (anti)patterns and providing their formal definitions; (ii) Assisting Cloud providers or API developers in revising their APIs by providing a set of correction recommendations to comply with both REST and OCCI best principles; And finally (iii) exploring the current application of OCCI and REST best principles on real Cloud APIs. To this end, we extend our previous work [9] (which only supports the definition of OCCI (anti)patterns and provides a set of SWRL 2 rules to automate their detection), with the following additional contributions:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On semantic detection of cloud API (anti)patterns

Brabra¹,

Mtibaa²,

Petrillo³

et al. 2019

Information and Software Technology

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Open standards are urgently needed for enabling software interoperability in Cloud Computing. Open Cloud Computing Interface (OCCI) provides a set of best design principles to create interoperable REST management APIs. Although OCCI is the only standard addressing the management of any kind of cloud resources, it does not support a range of best principles related to REST design. This often worsens REST API quality by decreasing their understandability and reusability. Objective: We aim at assisting cloud developers to enhance their REST management APIs by providing a compliance evaluation of OCCI and REST best principles and a recommendation support to comply with these principles. Method: First, we leverage patterns and anti-patterns to drive respectively the good and poor practices of OCCI and REST best principles. Then, we propose a semantic-based approach for defining and detecting REST and OCCI (anti)patterns and providing a set of correction recommendations to comply with both REST and OCCI best principles. We validated this approach by applying it on cloud REST APIs and evaluating its accuracy, usefulness and extensibility. Results: We found that our approach accurately detects OCCI and REST(anti)patterns and provides useful recommendations. According to the compliance results, we reveal that there is no widespread adoption of OCCI principles in existing APIs. In contrast, these APIs have reached an acceptable level of maturity regarding REST principles. Conclusion: Our approach provides an effective and extensible technique for defining and detecting OCCI and REST (anti)patterns in Cloud REST APIs. Cloud software developers can benefit from our approach and defined principles to accurately evaluate their APIs from OCCI and REST perspectives. This contributes in designing interoperable, understandable, and reusable Cloud management APIs. Thank to the compliance analysis and the recommendation support, we also contribute to improving these APIs, which make them more straightforward.

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Empirical Study on REST APIs Usage in Android Mobile Applications

Oumaziz

Belkhir

Vacher

et al. 2017

Service-Oriented Computing

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A large set of mobile applications (apps) heavily rely on services accessible through the Web via REST APIs. The mobile apps market is therefore becoming a key market for service providers. However, the way in which mobile apps use services in practice has never been studied. In this paper, we perform an empirical study in the Android ecosystem in which we analyze 500 popular applications and 15 popular services. We also conducted an online survey to identify which are the best practices for Android developers. Our results show that Android developers generally favor invoking services by using an official service library instead of directly invoking services with a generic HTTP client.Our study shows that Android developers prefer to use a dedicated library developed by the service provider if it exists. The main advantages of such a library are that it simplifies the calls of the REST services but also provides added-value such as Android Views for example.

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Detecting Cloud (Anti)Patterns: OCCI Perspective

Cited by 11 publications

References 11 publications

OCCI-Compliant Cloud Configuration Simulation

OCCI-Compliant Cloud Configuration Simulation

On semantic detection of cloud API (anti)patterns

Empirical Study on REST APIs Usage in Android Mobile Applications

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