Design and Performance Evaluation of Containerized Microservices on Edge Gateway in Mobile IoT

Gaur, Amit Singh; Budakoti, Jyoti; Lung, Chung-Horng

doi:10.1109/cybermatics_2018.2018.00055

Cited by 10 publications

(12 citation statements)

References 10 publications

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“…For calculating positive ideal solution, the benefit criteria should be chosen using maximum values and the cost criteria should be selected with the minimum value from matrix (5). The calculated value is represented by matrix (6).…”

Section: Proposed Mcvhd Methods Based On Enhanced Topsis Techniquementioning

confidence: 99%

“…Edge computing brings the datacenters (or mini-data centers) closer to the users or MTs to shorten the delay compared to Cloud computing. The concept of containerized microservices on mobile IoT Edge Gateway is presented in [5] [6], as a lightweight and efficient solution, which can be easily deployed and integrated with different development environments. In [7] [8] [9], the authors have discussed the benefits, challenges and performance evaluation of deployment of IoT gateways as a middleware solution at the Edge Gateway.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Vertical Handover Decision for Mobile IoT Edge Gateway Using Multi-Criteria and Fuzzy Logic Techniques

Gaur¹,

Budakoti²,

Lung³

2020

AIT

Self Cite

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Internet of Things (IoT) is ubiquitous, including objects or devices communicating through heterogenous wireless networks. One of the major challenges in mobile IoT is an efficient vertical handover decision (VHD) technique between heterogenous networks for seamless connectivity with constrained resources. The conventional VHD approach is mainly based on received signal strength (RSS). The approach is inefficient for vertical handover, since it always selects the target network with the strongest signal without taking into consideration of factors such as quality of service (QoS), cost, delay, etc. In this paper, we present a hybrid approach by integrating the multi-criteria based VHD (MCVHD) technique and an algorithm based on fuzzy logic for efficient VHD among Wi-Fi, Radio and Satellite networks. The MCVHD provides a lightweight solution that aims to achieving seamless connectivity for mobile IoT Edge Gateway over a set of heterogeneous networks. The proposed solution is evaluated in real time using a testbed containing real IoT devices. Further, the testbed is integrated with lightweight and efficient software techniques, e.g., microservices, containers, broker, and Edge/Cloud techniques. The experimental results show that the proposed approach is suitable for an IoT environment and it outperforms the conventional RSS Quality based VHD by minimizing handover failures, unnecessary handovers, handover time and cost of service.

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Section: Proposed Mcvhd Methods Based On Enhanced Topsis Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vertical Handover Decision for Mobile IoT Edge Gateway Using Multi-Criteria and Fuzzy Logic Techniques

Gaur¹,

Budakoti²,

Lung³

2020

AIT

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hardware [5] Raspberry Pi3 -ARM Cortex-A53 4-Core 1.2 GHz 1GB RAM [8] Intel Xeon E5-1620 v3 4-Core 3.5GHz 32GB RAM [6] Raspberry Pi3 [7] AMD Athlon (tm) 64 X2 2-Core 2.21GHz 1GB RAM [9] Raspberry Pi3…”

Section: Refmentioning

confidence: 99%

“…These approaches limit or preclude their use by restrained hardware. Furthermore, the lack of middleware for edge computing creates a scenario where developers need to develop their own solutions for a specific application [5], [6], [7], [9], [10].…”

Section: Introductionmentioning

confidence: 99%

An IoT Middleware Template Proposal

Cardoso¹,

Ferreira²,

Bauer³

et al. 2022

Anais Do XL Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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There are several different IoT middleware platforms available for IoT systems. However, most of these platforms require high computational hardware to be implemented, making their use in low-cost and computationally restricted devices difficult. This motivated us to develop an IoT architecture and template suitable for computationally restrained hardware to be a tool that can facilitate the development of new IoT middlewares. We tested the proposed architecture in two application scenarios, using hardware with low computational power. The results, in terms of RAM and CPU usage rates and response time, show the proposed architecture makes good use of the available resources.

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“…In [38] the author performed a comprehensive study on the performance of containers running on five single board computers that were popularly used as edge gateway platforms, with consideration of metrics such as CPU execution time and load, memory speed, disk I/O and network throughput, as well as power consumption. Similarly, in [39] the authors utilized containers to run microservices on an IoT edge gateway with WiFi, radio and satellite interfaces, and evaluated the container performance with aforementioned metrics as well as system bootup time. The authors in [40] focused on evaluating container hardware utilization and processing capabilities based on different runtime technologies.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective

Liu

Lan

Pang

et al. 2021

IEEE Open J. Ind. Electron. Soc.

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Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance.

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Design and Performance Evaluation of Containerized Microservices on Edge Gateway in Mobile IoT

Cited by 10 publications

References 10 publications

Vertical Handover Decision for Mobile IoT Edge Gateway Using Multi-Criteria and Fuzzy Logic Techniques

Vertical Handover Decision for Mobile IoT Edge Gateway Using Multi-Criteria and Fuzzy Logic Techniques

An IoT Middleware Template Proposal

Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective

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