کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6885405 | 1444511 | 2018 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review
ترجمه فارسی عنوان
نظارت بر برنامه های کاربردی خود سازگار در چارچوب محاسبات لبه: بررسی پیشرفته ای از هنر
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کلمات کلیدی
محاسبات لبه، پردازش ابری، فن آوری های نظارت، تجزیه و تحلیل مورد نیاز، برنامه های سازگار، طبقه بندی مورد نیاز نظارت،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Recently, a promising trend has evolved from previous centralized computation to decentralized edge computing in the proximity of end-users to provide cloud applications. To ensure the Quality of Service (QoS) of such applications and Quality of Experience (QoE) for the end-users, it is necessary to employ a comprehensive monitoring approach. Requirement analysis is a key software engineering task in the whole lifecycle of applications; however, the requirements for monitoring systems within edge computing scenarios are not yet fully established. The goal of the present survey study is therefore threefold: to identify the main challenges in the field of monitoring edge computing applications that are as yet not fully solved; to present a new taxonomy of monitoring requirements for adaptive applications orchestrated upon edge computing frameworks; and to discuss and compare the use of widely-used cloud monitoring technologies to assure the performance of these applications. Our analysis shows that none of existing widely-used cloud monitoring tools yet provides an integrated monitoring solution within edge computing frameworks. Moreover, some monitoring requirements have not been thoroughly met by any of them.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems and Software - Volume 136, February 2018, Pages 19-38
Journal: Journal of Systems and Software - Volume 136, February 2018, Pages 19-38
نویسندگان
Salman Taherizadeh, Andrew C. Jones, Ian Taylor, Zhiming Zhao, Vlado Stankovski,