A lightweight and cost effective edge intelligence architecture based on containerization technology

Al-Rakhami, Mabrook; Gumaei, Abdu; Alsahli, Mohammed Abdullah; Hassan, Mohammad Mehedi; Alamri, Atif; Guerrieri, Antonio; Fortino, Giancarlo

doi:10.1007/s11280-019-00692-y

Cited by 31 publications

(21 citation statements)

References 22 publications

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“…This technology makes building and maintaining Virtual Machine (VM) containers more straightforward. That, in turn, conveniently facilitates running node clusters in the architecture [58]. The MQTT protocol provides a connection between the IoT devices and the IOTA network.…”

Section: B Setup For Our Experimentsmentioning

confidence: 99%

ProChain: Provenance-Aware Traceability Framework for IoT-Based Supply Chain Systems

Al-Rakhami

Al‐Mashari

2022

IEEE Access

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The current value of the world food system amounts to roughly $8 trillion, which represents approximately 10% of the global economies. Therefore, the quality of food and food products concerns not only all the end consumers but also millions of employees and entrepreneurs within the global food industry. Achieving the best possible quality of food throughout all the engaged processes requires constantly tracing and monitoring several crucial environmental conditions that may have a significant impact on the products' quality. The Industrial Internet of Things (IIoT) is a system of dedicated sensors paired with the Internet that can overcome and prevent issues within the food industry. The interconnected elements bear the responsibility for monitoring, evaluating, and tracking the conditions where the food products undergo processing, and it checks the products' quality throughout their life cycle. Nevertheless, even IIoT has its challenges. The first such challenge relates to the storage and accessibility of the obtained data. What can make the data readily available to all individuals and entities involved in the industry? The second significant challenge relates to tracing items that pass through numerous processes involving different parties. This work proposed ProChain, a Provenance-aware Traceability Framework for IoT-based Supply Chain Systems. A proposed comprehensive framework of all the information acquired by the sensors and the complete set of provenance data addressed these challenges. Additionally, a thorough simulation of the proposed framework on the Raspberry PI 3B IoT device reviewed the ProChain efficiency in the cloud and local simulation environments. ProChain demonstrated tractability, transparency, and complex security as examples of the principal attributes of the IOTA 2.0 protocol in the food industry.

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Section: B Setup For Our Experimentsmentioning

confidence: 99%

ProChain: Provenance-Aware Traceability Framework for IoT-Based Supply Chain Systems

Al-Rakhami

Al‐Mashari

2022

IEEE Access

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“…The scope of container applications cuts across every industry [50]. In the literature, the use of container-based edge computing was found in: a civil construction application [51], a crane maneuvering application to avoid accidents with construction workers [52], monitoring patient fall detection [29]; human activity recognition [53]; autonomous vehicles [33]; real-time video processing [3,41]; real-time process control [54,55]; intelligent farming [56]; factory system software management [57] and modular cyber-physical system [58]. In [59], authors present the implementation of a container-based MQTT broker.…”

Section: Container Applications In Edge Computingmentioning

confidence: 99%

Container Placement and Migration in Edge Computing: Concept and Scheduling Models

Oleghe

2021

IEEE Access

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Containers are a form of software virtualization, rapidly becoming the de facto way of providing edge computing services. Research on container-based edge computing is plentiful, and this has been buoyed by the increasing demand for single digit, milliseconds latency computations. A container scheduler is part of the architecture that is used to manage and orchestrate multiple container-based applications on heterogenous computing nodes. The scheduler decides how incoming computing requests are allocated to containers, which edge nodes the containers are placed on, and where already deployed containers are migrated to. This paper aims to clarify the concept of container placement and migration in edge servers and the scheduling models that have been developed for this purpose. The study illuminates the frameworks and algorithms upon which the scheduling models are built. To convert the problem to one that can be solved using an algorithm, the container placement problem in mostly abstracted using multi-objective optimization models or graph network models. The scheduling algorithms are predominantly heuristic-based algorithms, which are able to arrive at sub-optimal solutions very quickly. There is paucity of container scheduling models that consider distributed edge computing tasks. Research in decentralized scheduling systems is gaining momentum and the future outlook is in scheduling containers for mobile edge nodes.

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“…Because of the richness of resources typical of cloud platforms, cloudbased CPSs and cloud-assisted IoT extend and augment the computing capacity of CPSs to conduct resource-hungry applications. The Cloud computing model is keen to use centralized shared resources and addresses the raising popularity of smart apps by integrating exclusive resources and the data obtained from them [2].…”

Section: Summary Of This Issuementioning

confidence: 99%

“…The result is that issues such as cybersecurity, self-learning, real-time networks and tailored connectivity can all be adequately dealt with [2]. In their previous work [6], the authors of the paper "A Lightweight and Cost Effective Edge Intelligence Architecture based on Containerization Technology" [2] proposed the idea to build and integrate Docker containers within the edge and pinpoint the Edge Intelligence's potential in the vertical-specific scenarios of use. Their current study, included in this Special Issue, extends this idea further and focuses on the utilization of Docker technology into the recognition of human activity.…”

Section: Summary Of This Issuementioning

confidence: 99%

Smart computing and cyber technology for cyberization

et al. 2020

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Following the well-known concepts of computerization and informatization, an emerging era of cyberization, which is considered as a reformation of the present physical, social and mental worlds, has become a hotly discussed trend in the new cyber world. Cyberization refers to using communication and computer technologies to interconnect computers and various electronic terminal devices distributed in different locations. It allows users to share software, hardware and data resources according to certain network protocols. Cyberization has greatly improved the practical utility of computers and has been widely applied in transportation, finance, business management, education, telecommunications, commerce, and so on in our daily life [1]. During the cyberization process, a large number of real things will conjugatively map to various kinds and levels of cyber existence in cyber world. It is said that cyberization has already taken place in a variety of fields along with the development of several emerging computing paradigms and information communication technologies, such as ubiquitous/ pervasive computing, social computing and networking, and wearable technologies, etc. Specifically, with the rapid growth of Internet of Things and cognitive cyber-physical systems, more and more digital things or cyber entities, are engaged or generated in the integrated cyber world. Emerging technologies in smart environments, such as smart computing and smart objects, become very significant, promising, and enabling issues in cyberization, to enhance

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A lightweight and cost effective edge intelligence architecture based on containerization technology

Cited by 31 publications

References 22 publications

ProChain: Provenance-Aware Traceability Framework for IoT-Based Supply Chain Systems

ProChain: Provenance-Aware Traceability Framework for IoT-Based Supply Chain Systems

Container Placement and Migration in Edge Computing: Concept and Scheduling Models

Smart computing and cyber technology for cyberization

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