Multicloud service composition: A survey of current approaches and issues

Lahmar, Fatma; Mezni, Haithem

doi:10.1002/smr.1947

Cited by 9 publications

(14 citation statements)

References 86 publications

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“…Existing research studies' major focus was on reducing the number of hosting clouds and, consequently, the intercloud communication cost, in addition to the composition sequences' total execution time. To meet these goals, several studies have considered MCSC as a combinatorial optimization problem, like in References and . For this purpose, they have used different algorithms such as genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), greedy algorithm, and so forth.…”

Section: Related Workmentioning

confidence: 99%

“…As for the adopted composition methods, we distinguish SFLA, skyline, gravitational attraction search, imperialist competitive algorithm, Petri net, FCA, game theory, and so forth. Combinatorial techniques, like in References , and , have also been applied, as the MCSC can be seen as an optimization problem. The greedy approach can offer an optimal solution, but it requires a high computation time .…”

Section: Related Workmentioning

confidence: 99%

“…For this reason, most of them proceed to reduce the search space by selecting the optimal combination of clouds, before making the service selection and composition. Other approaches have focused on optimizing the QoS levels of MCSCs, by considering attributes like execution time, network latency, and service location. However, these approaches totally ignore the environmental constraints that may affect the services involved in a composition.…”

Section: Related Workmentioning

confidence: 99%

“…From Table 1, we notice that most works have treated the SaaS service composition, [2][3][4][5][8][9][10][11][12] with a total absence of the PaaS model. However, few attempts 13,14 have treated IaaS service composition.…”

Section: Comparative Studymentioning

confidence: 99%

“…Taking as an example the combination of several SaaS applications (horizontal composition), which will be aggregated later with some IaaS services (eg, VMs and storage servers) that are requested by the user (vertical composition). In the literature, most works have treated the horizontal service composition, whereas few attempts have addressed the vertical service composition . However, there are some few works that have treated both vertical and horizontal service compositions …”

Section: Introductionmentioning

confidence: 99%

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Bringing semantics to multicloud service compositions

2020

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Summary Over the last decade, cloud computing has emerged as a new paradigm for delivering various on‐demand virtualized resources as services. Cloud services have inherited not only the major characteristics of web services but also their classical issues, in particular, the interoperability issues and the heterogeneous nature of their hosting environments. This latter problem must be taken into account when composing various cloud services, in order to answer users' complex requirements. Moreover, leading cloud providers started to offer their services across multiple clouds. This adds a new factor of heterogeneity, as composition engines must take into consideration the heterogeneity not only at the service level (eg, service descriptions) but also at the cloud level (eg, pricing models, security policies). In this context, the semantics of multicloud actors must be incorporated into the multicloud service composition (MCSC) process. However, most existing approaches have treated the semantic service composition in traditional single‐cloud environments. The few works in multicloud settings have ignored the semantics of cloud zones and resources. Moreover, they often focus on the general aspect of MCSC (eg, horizontal or vertical compositions). Even the few researchers who have addressed both vertical and horizontal service compositions, conducted their research studies in the context of single‐ cloud environments, which were proven to be unrealistic and offer limited quality of service (QoS) and security support. To ensure a high interoperability when composing services from multiple heterogeneous clouds and to enable a horizontal/vertical semantic service compositions, we take advantage of a standardized and semantically enriched generic service description, including all aspects (technical, operational, business, semantic, contextual) and supporting different cloud service models (SaaS, PaaS, IaaS, etc). We also incorporate Semantic Web Rule Language into the MCSC process to enable not only rule‐based reasoning about various composition constraints (eg, QoS constraints, cloud zones constraints) but also to provide accurate semantic matching of cloud services' capabilities. Conducted experiments have proven the ability of our approach to combine high‐quality services from the optimal number of clouds.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Comparative Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bringing semantics to multicloud service compositions

2020

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Harnessing idle edge resources for execution of cloud services: A comprehensive review

Trajano,

de Souza

2024

Trans Emerging Tel Tech

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This article presents a comprehensive investigation into voluntary resource sharing at the edge of the internet for cloud service execution. Through a systematic review, 460 scientific articles published between 2019 and 2023 were analyzed, compiling the primary recent contributions in the field. The study presents a taxonomy of the results and highlights the state of the art. Despite the growing interest in the topic in recent years due to the expansion of Edge and Fog Computing, numerous challenges and open research gaps were identified for the effective utilization of idle resources for cloud service execution at the edge. This paper delves into these challenges, emphasizing the need for extensive research in areas such as resource management, interoperability, incentive model establishment, and security and privacy concerns.

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Characterizing commodity serverless computing platforms

Wen

Liu

Chen

et al. 2021

J Software Evolu Process

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Serverless computing has become a new trending paradigm in cloud computing, allowing developers to focus on the development of core application logic and rapidly construct the prototype via the composition of independent functions. With the development and prosperity of serverless computing, major cloud vendors have successively rolled out their commodity serverless computing platforms. However, the characteristics of these platforms have not been systematically studied. Measuring these characteristics can help developers to select the most adequate serverless computing platform and develop their serverlessbased applications in the right way. To fill this knowledge gap, we present a comprehensive study on characterizing mainstream commodity serverless computing platforms, including AWS Lambda, Google Cloud Functions, Azure Functions, and Alibaba Cloud Function Compute. Specifically, we conduct both qualitative analysis and quantitative analysis. In qualitative analysis, we compare these platforms from three aspects (i.e., development, deployment, and runtime) based on their official documentation to construct a taxonomy of characteristics. In quantitative analysis, we analyze the runtime performance of these platforms from multiple dimensions with well-designed benchmarks. First, we analyze three key factors that can influence the startup latency of serverless-based applications. Second, we compare the resource efficiency of different platforms with 16 representative benchmarks.Finally, we measure their performance difference when dealing with different concurrent requests, and explore the potential causes in a black-box fashion. Based on the results of both qualitative and quantitative analysis, we derive a series of findings and provide insightful implications for both developers and cloud vendors.

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Multicloud service composition: A survey of current approaches and issues

Cited by 9 publications

References 86 publications

Bringing semantics to multicloud service compositions

Bringing semantics to multicloud service compositions

Harnessing idle edge resources for execution of cloud services: A comprehensive review

Characterizing commodity serverless computing platforms

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