Edge to Cloud Tools: A Multivocal Literature Review

Edge-to-cloud computing is an emerging paradigm for distributing computational tasks between edge devices and cloud resources. Different approaches for orchestration, offloading, and many more purposes have been introduced in research. However, it is still not clear what has been implemented in the industry. This work aims to merge this gap by mapping the existing knowledge on edge-to-cloud tools by providing an overview of the current state of research in this area and identifying research gaps and challenges. For this purpose, we conducted a Multivocal Literature Review (MLR) by analyzing 40 tools from 1073 primary studies (220 PS from the white literature and 853 PS from the gray literature). We categorized the tools based on their characteristics and targeted environments. Overall, this systematic mapping study provides a comprehensive overview of edge-to-cloud tools and highlights several opportunities for researchers and practitioners for future research in this area

Orchestration in the Cloud-to-Things Compute Continuum: Taxonomy, Survey and Future Directions

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems has been increasing rapidly. These IoT use cases often require simultaneous access to geographically distributed arrays of sensors, and heterogeneous remote, local as well as multi-cloud computational resources. This gives birth to the extended Cloud-to-Things computing paradigm. The emergence of this new paradigm raised the quintessential need to extend the orchestration requirements i.e., the automated deployment and run-time management) of applications from the centralised cloud-only environment to the entire spectrum of resources in the Cloud-to-Things continuum. In order to cope with this requirement, in the last few years, there has been a lot of attention to the development of orchestration systems in both industry and academic environments. This paper is an attempt to gather the research conducted in the orchestration for the Cloud-to-Things continuum landscape and to propose a detailed taxonomy, which is then used to critically review the landscape of existing research work. We finally discuss the key challenges that require further attention and also present a conceptual framework based on the conducted analysis.Comment: Journal of Cloud Computing Pages: 2

Function-as-a-Service for the Cloud-to-Thing Continuum: A Systematic Mapping Study

Until recently, Internet of Things applications were mainly seen as a means to gather sensor data for further processing in the Cloud. Nowadays, with the advent of Edge and Fog Computing, digital services are dragged closer to the physical world, with data processing and storage tasks distributed across the whole Cloud-to-Thing continuum. Function-as-a-Service (FaaS) is gaining momentum as one of the promising programming models for such digital services. This work investigates the current research landscape of applying FaaS over the Cloud-to-Thing continuum. In particular, we investigate the support offered by existing FaaS platforms for the deployment, placement, orchestration, and execution of functions across the whole continuum using the Systematic Mapping Study methodology. We selected 33 primary studies and analyzed their data, bringing a broad view on the current research landscape in the area.acceptedVersio