Performance Comparison of Image and Workload Management of Edge Computing Using Different Virtualization Technologies

Khalid, Mohammad Fairus; Ismail, Bukhary Ikhwan; Mydin, Mohd Nizam Mohd

doi:10.1166/asl.2017.7310

Cited by 9 publications

(4 citation statements)

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“…When judging the resource utilization, if the server resource usage reaches the upper or lower threshold and it is identified as a hot spot node or cold spot node that needs to be processed [2], the dynamic nature of the task is ignored, which will result in a large number of servers. ey are all judged as hot spot nodes, which will also bring a lot of meaningless task migration, cause a large degree of waste of resources, and seriously affect the service performance of the entire edge computing platform [26,27]. Based on the above reasons, the algorithm studied in this paper introduces a resource prediction algorithm to work with the migration decision algorithm when performing dynamic task migration to improve the quality of service of the entire system [28].…”

Section: Forecast Of Resources In the Short Termmentioning

confidence: 99%

International Import and Export Trade Forecasting Algorithm Based on Heterogeneous Dynamic Edge Computing System

Yingfei

2021

Mathematical Problems in Engineering

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As a new computing model, how to use edge computing to forecast import and export trade has become an issue of concern. This research mainly discusses the prediction algorithm of international import and export trade based on heterogeneous dynamic edge computing system. The dynamic task migration system studied in this paper mainly includes four parts: edge computing environment simulator, task generator, resource predictor, and migration decision maker. These four parts are not independent modules in the working process; they will interact with each other in the edge computing environment. In the data processing offloading strategy, the customs business personnel transfer the trade data that need to be predicted to the edge device cluster through the mobile terminal. After receiving the data transmitted by the business personnel, the edge device cluster uses data processing technology to process the data. After the data processing operation is completed, the processed data is directly used for prediction work. After the prediction work is completed, the data and results are uploaded to the central server. Finally, after the prediction work is completed, the edge device will feed back the prediction result to the mobile terminal and display the result on the user interface through the mobile terminal so that business personnel can understand the trade risk status. From August 2018 data application period, the monthly data of the import and export trade volume for the subsequent time span of ten years were regularly forecasted, and the correlation coefficient was still over 83%, and the RMSE also dropped significantly. The system designed in this study can effectively predict the annual estimated value of various economic indicators of international import and export trade.

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Section: Forecast Of Resources In the Short Termmentioning

confidence: 99%

International Import and Export Trade Forecasting Algorithm Based on Heterogeneous Dynamic Edge Computing System

Yingfei

2021

Mathematical Problems in Engineering

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“…Installation of the NuoDB software was performed per the manufacturer's instructions [37]. Also installed on each of the database nodes was the performance metric gathering tool, "nmon" [38], a software tool written in the C programming language, demonstrated to be effective in capturing metrics in performance testing research [39,40]. The nmon application captured data on database nodes for CPU utilization measured as a percent of total available, total system memory utilization measured in MB allocated, disk I/O measured in KB/s, and network I/O measured in KB/s, each of which represents a dependent variable in the experiment.…”

Section: Methodsmentioning

confidence: 99%

Performance Impact of Type-I Virtualization on a NewSQL Relational Database Management System

Osborne¹

2022

IJACSA

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For more than 40 years, the relational database management system (RDBMS) and the atomicity, consistency, isolation, durability (ACID) transaction guarantees provided through its use have been the standard for data storage. The advent of Big Data created a need for new storage approaches that led to NoSQL technologies, which rely on basic availability, soft-state, eventual consistency (BASE) transactions. Over the last decade, NewSQL RDBMS technology has emerged, providing the benefits of RDBMS ACID transaction guarantees and the performance and scalability of NoSQL databases. The reliance on virtualization in IT has continued to grow, but an investigation of current academic literature identified a void regarding the performance impact of virtualization of NewSQL databases. To help address the lack of research in this area, a quantitative experimental study was designed and carried out to answer the central research question, "What is the performance impact of Type-I virtualization on a NewSQL RDBMS?" VMware ESXi virtualization software, NuoDB RDBMS, and OLTP-Bench software were used to execute a mixed-load benchmark. Performance metrics were collected comparing bare metal and virtualized environments, and the data analyzed statistically to evaluate five hypotheses related to CPU utilization, memory utilization, disk and network input-output (I/O) rates, and database transactions per second. Findings indicated a negative performance impact on CPU and memory utilization, as well as network I/O rates. Performance improvements were noted in disk I/O rates and database transactions-per-second.

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“…According to the usage and performance of the edge clouds, the computing power and storage space can be adjusted on-demand to minimize the usage of resources, and improve the utilization of resources (Varghese et al , 2016). It can reduce the pressure on network traffic and decrease the response time to improve user experience (Khalid et al , 2016; Salman et al , 2015). Due to its advantages, edge computing has been applied in different applications, such as smart homes, smart factories, medical care, government, logistics, insurance, traffic monitoring, etc (Dastjerdi et al , 2016; Shi et al , 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Toward open manufacturing

Wang

Guo

et al. 2018

IMDS

223

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Purpose The purpose of this paper is to propose a cross-enterprises framework to achieve a higher level of sharing of knowledge and services in manufacturing ecosystems. Design/methodology/approach The authors describe the development of the emerging open manufacturing and discuss the model of knowledge creation processes of manufacturers. The authors present a decentralized framework based on blockchain and edge computing technologies, which consists of a customer layer, an enterprise layer, an application layer, an intelligence layer, a data layer, and an infrastructure layer. And a case study is provided to illustrate the effectiveness of the framework. Findings The authors discuss that the manufacturing ecosystem is changing from integrated and centralized systems to shared and distributed systems. The proposed framework incorporates the recent development in blockchain and edge computing that can meet the secure and distributed requirements for the sharing of knowledge and services in manufacturing ecosystems. Practical implications The proposed framework provides a more secure and controlled way to share knowledge and services, thereby supports the company to develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency, and effectiveness of manufacturing services. Originality/value The proposed framework incorporates the recent development in edge computing technologies to achieve a flexible and distributed network. With the blockchain technology, it provides standards and protocols for implementing the framework and ensures the security issues. Not only information can be shared, but the framework also supports in the exchange of knowledge and services so that the parties can contribute their parts.

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Performance Comparison of Image and Workload Management of Edge Computing Using Different Virtualization Technologies

Cited by 9 publications

References 0 publications

International Import and Export Trade Forecasting Algorithm Based on Heterogeneous Dynamic Edge Computing System

International Import and Export Trade Forecasting Algorithm Based on Heterogeneous Dynamic Edge Computing System

Performance Impact of Type-I Virtualization on a NewSQL Relational Database Management System

Toward open manufacturing

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