Composition of heterogeneous web services: A systematic review

Huf, Alexis; Siqueira, Frank

doi:10.1016/j.jnca.2019.06.008

Cited by 20 publications

(12 citation statements)

References 47 publications

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“…This is because semantics constitutes general theory that defines how to compose services conceptually rather than a concrete implementation (that can only be evaluated in specific scenarios). Significantly, fundamental semantics underlies so-called composition algorithms [8,89,90,91,92,93,94,95,96,97,98,99,100,101,102], programming frameworks [84,103,104,105,106,107,108], languages [109,110] and platforms [111,112,113,114,115,116,117], which have been somehow confusingly included in existing "IoT service composition" surveys [3,5,24,118,119].…”

Section: Related Workmentioning

confidence: 99%

Evaluating IoT service composition mechanisms for the scalability of IoT systems

Arellanes

Lau

2020

Future Generation Computer Systems

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The Internet of Things (IoT) is an emerging paradigm where practically every (physical and virtual) thing will be interconnected through innovative distributed services. Since the number of connected things is rapidly growing, IoT systems will require the composition of plenty of services into complex workflows. Thus, scalability in terms of the size of IoT systems becomes a significant concern. In this paper, we review and evaluate the fundamental semantics of existing IoT service composition mechanisms to determine how well they fulfil the scalability requirements of IoT systems. We identify scalability desiderata and, accordingly, our findings show that dataflows, orchestration and choreography do not fully satisfy such desiderata, unlike a novel composition mechanism called DX-MAN.

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Section: Related Workmentioning

confidence: 99%

Evaluating IoT service composition mechanisms for the scalability of IoT systems

Arellanes

Lau

2020

Future Generation Computer Systems

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“…There are quite a few survey papers on service composition in general (without explicit focus on the languages) over the years; we mention mostly the recent ones here. Huf et al [14] present a wide survey on service composition approaches with a focus on service type heterogeneity and the applied methods. Hamzei et al in [13] look at service composition techniques in IoT which they categorize into four classes, namely framework, SOA and RESTful, heuristic, and model-based.…”

Section: Related Workmentioning

confidence: 99%

A survey on service composition languages

Nikoo

Babur

Brand

2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

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In recent years, service-oriented architecture (SOA) has been adopted by industry in developing enterprise systems. Web service composition has been one of the challenging topics in SOA. Numerous approaches have been proposed to tackle this problem. In industry big companies such as Amazon, Netflix, and Uber have developed their own web service composition languages and tools. In academia, on the other hand, there have also been attempts to resolve some of the complexities in web service composition. In this survey we identify and evaluate current prominent service composition languages, and discuss our key findings. After a scan of dozens of service composition systems, 14 systems that used a language-based approach were included in this study. We believe that our findings will help people from industry and academia to learn about some of the major active composition languages and get an overall idea about their commonalities and differences. CCS CONCEPTS • Software and its engineering → Domain specific languages; Orchestration languages.

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“…In addition to the cloud, on the edge there are typically varying hardware and software platforms used to deploy and execute functionality [16]. New service composition algorithms for handling heterogeneity, handling long-running processes, and tools for managing heterogeneity from popular programming languages and frameworks need further research as explained by [21]. Furthermore, [46] point out that software frameworks need to implement resilience and methods for failover situations.…”

Section: Introductionmentioning

confidence: 99%

Service Orchestration for Object Detection on Edge and Cloud in Dependable Industrial Vehicles

Pettinen¹,

Hästbacka

2021

JMM

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Industrial applications, including autonomous systems and vehicles, rely on processing data on multiple physical devices. The composition of functionality across heterogeneous computing infrastructure is challenging, and will likely get even more challenging in the future as software in vehicles is updated to introduce new features and ensure the safety. New soft real-time use cases emerge and in such cases the model of offloading processing from a limited or malfunctioning device is a viable solution. This study examines orchestration of services across edge and cloud for an industrial vehicle application use case involving image based object detection using machine learning (ML) based models. First, service orchestration requirements are defined taking into account the dependable nature of industrial vehicle applications. Second, an implementation based on Arrowhead framework is presented and evaluated. The open Arrowhead framework offers means for dynamic service discovery, authorization and late binding of computational units. The feasibility of object detection as a service and the suitability of Arrowhead framework to support such orchestrations across edge and cloud is assessed.

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Composition of heterogeneous web services: A systematic review

Cited by 20 publications

References 47 publications

Evaluating IoT service composition mechanisms for the scalability of IoT systems

Evaluating IoT service composition mechanisms for the scalability of IoT systems

A survey on service composition languages

Service Orchestration for Object Detection on Edge and Cloud in Dependable Industrial Vehicles

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