Cost Efficient Edge Intelligence Framework Using Docker Containers

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

doi:10.1109/dasc/picom/datacom/cyberscitec.2018.00138

Cited by 28 publications

(16 citation statements)

References 16 publications

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“…Muhammad Alam et al [41] proposed a modular and scalable edge computing architecture based on lightweight virtualization using Docker and microservices. Mabrook Al-Rakhami et al [42] proposed an edge computing framework based on Docker to enable the performing of data processing close to the environment. Yuzhou Huang et al [43] proposed intelligent edge computing through training the model in the cloud and offloading it to the edge based on the Docker that enables the prediction model to be operated in the edge platform.…”

Section: Related Workmentioning

confidence: 99%

Enhanced Service Framework Based on Microservice Management and Client Support Provider for Efficient User Experiment in Edge Computing Environment

Jin

Kim

2021

IEEE Access

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Leveraging the edge computing paradigm, computing resources are deployed in the network edge to provide heterogeneous services. Edge computing delivers sensing and actuating services to the Internet from the constrained Internet of Things (IoT) devices. Meanwhile, management of various elements is provided by offloading sufficient computing and storage to the edge of the networks for the IoT environments such as home, factory, and private spaces without cloud servers. In this paper, we propose an enhanced service framework based on microservice management and client support provider for efficient user experiments in the edge computing environment. For providing the edge computing service and management in the network edge, this paper presents an edge-computing architecture that provides various functions through microservice modules on the edge platform engine. Through the microservices, the interfaces are provided to the client to access the device, data, and additional services. Using Docker, the microservice modules are deployed in the edge platform to provide the services. However, the services and management functions need to be presented to the clients based on the friendly user interfaces. For providing the user interfaces of the services and Docker engine to the clients, the client support service provider is developed and deployed in the network edge based on the edge platform. Therefore, the proposed edge platform provides the services and management to the users for accessing the resources and functions through visualized interfaces in the IoT environment based on edge computing. The performance of our proposed system can be checked through the test result screen and delay time. Compared to controlling edge computing by using a command-line tool for users, we made it easy for general users who are not computer savvy to access edge services through a graphic user interface. And by measuring the delay time and comparing the execution time, it can be seen that the proposed system operates faster.

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Section: Related Workmentioning

confidence: 99%

Enhanced Service Framework Based on Microservice Management and Client Support Provider for Efficient User Experiment in Edge Computing Environment

Jin

Kim

2021

IEEE Access

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“…Edge computing reduces application latency because its computing and storage capacity is situated at the edge of the network, closer to the end-user. In our previous papers [17,18], we introduced a new edge computing model that enabled us to reduce latency from processes occurring in the cloud, wherein the data were processed close to the edge. After data collection in the edge, we were able to add another layer, a more generalized structure of the edge, to the cloud.…”

Section: A Edge Computingmentioning

confidence: 99%

“…A Docker compared to a virtual machine (VM) shows its lightweight component abilities, which significantly assist algorithmic processing. Just like with a VM, the Dockers are isolated, but because the container works without any guest OS, we have a lightweight and easy-to-manage software that runs on the edge device [18]. Figure 2 shows the Docker daemon that manages the creation of containers and images created for the application [18].…”

Section: Docker Containersmentioning

confidence: 99%

FallDeF5: A Fall Detection Framework Using 5G-Based Deep Gated Recurrent Unit Networks

et al. 2021

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Fall prevalence is high among elderly people, which is challenging due to the severe consequences of falling. This is why rapid assistance is a critical task. Ambient assisted living (AAL) uses recent technologies such as 5G networks and the internet of medical things (IoMT) to address this research area. Edge computing can reduce the cost of cloud communication, including high latency and bandwidth use, by moving conventional healthcare services and applications closer to end-users. Artificial intelligence (AI) techniques such as deep learning (DL) have been used recently for automatic fall detection, as well as supporting healthcare services. However, DL requires a vast amount of data and substantial processing power to improve its performance for the IoMT linked to the traditional edge computing environment. This research proposes an effective fall detection framework based on DL algorithms and mobile edge computing (MEC) within 5G wireless networks, the aim being to empower IoMT-based healthcare applications. We also propose the use of a deep gated recurrent unit (DGRU) neural network to improve the accuracy of existing DL-based fall detection methods. DGRU has the advantage of dealing with time-series IoMT data, and it can reduce the number of parameters and avoid the vanishing gradient problem. The experimental results on two public datasets show that the DGRU model of the proposed framework achieves higher accuracy rates compared to the current related works on the same datasets.

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“…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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Cost Efficient Edge Intelligence Framework Using Docker Containers

Cited by 28 publications

References 16 publications

Enhanced Service Framework Based on Microservice Management and Client Support Provider for Efficient User Experiment in Edge Computing Environment

Enhanced Service Framework Based on Microservice Management and Client Support Provider for Efficient User Experiment in Edge Computing Environment

FallDeF5: A Fall Detection Framework Using 5G-Based Deep Gated Recurrent Unit Networks

Smart computing and cyber technology for cyberization

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