مطالعه تطبیقی نرم افزارهای منبع باز استقرار و مدیریت رایانش ابری با استفاده از مدل کیفیت از دیدگاه پردازش کلان داده
محورهای موضوعی : پردازش چند رسانه ای، سیستمهای ارتباطی، سیستمهای هوشمند
1 - دانشگاه صنعتی امیرکبیر، دانشکده مهندسی کامپیوتر، گروه نرم‌افزار، تهران، ایران
2 - استادیار دانشگاه صنعتی امیرکبیر، دانشکده مهندسی کامپیوتر، گروه نرم‌افزار، تهران، ایران
کلید واژه: رایانش ابری, مدیریت ابر, ذخیره‌سازی کلان داده, مدل کیفیت, پردازش کلان داده,
چکیده مقاله :
روز به روز حجم داده‌های تولید شده توسط انسان‌ها در حال افزایش است. ذخیره‌سازی و پردازش داده‌ها، یکی از مباحث بسیار مهم در مواجهه با کلان داده‌ها است که نیازمند منابع ذخیره‌سازی و پردازشی گسترده می‌باشد. رایانش ابری به دلیل ویژگی‌ها و معماری خود، به عنوان یک زیرساخت امیدبخش برای این مساله مطرح است. برای ذخیره‌سازی و پردازش داده‌ها در بستر ابری، افراد و سازمان‌ها ممکن است برای کنترل و دسترسی بیشتر روی منابع و داده‌ها تمایل بیشتری به استقرار و مدیریت ابرهای خصوصی داشته باشند. برای استقرار و مدیریت ابرهای خصوصی نرم‌افزارهای متعدد منبع‌باز ارائه شده است که گزینش بین آنها به عنوان یک چالش به خصوص برای کسانی که تازه در این راه قدم بر می‌دارند مطرح است. هدف ما در این مقاله ارائه یک مدل کیفیت برای مدیریت زیرساخت ابری و مقایسه نرم‌افزارهای محبوب Eucalyptus، OpenStack و CloudStack بر اساس مدل کیفیت ارائه شده با تمرکز بر کلان داده به منظور نمایش قابلیت‌ها، ضعف‌ها و برتری‌های هر کدام در جهت کمک به گزینش بین آنها می باشد.
Introduction: The volume of data produced by human society is growing rapidly. Data is being produced in many different industries such as manufacturing, transportation, healthcare, and social networks. Due to the volume of data being produced, data storage and processing are among the most important issues when dealing with big data. The main challenges when dealing with big data are data storage and management, data processing and analytics, and resource management to provide the infrastructure needed to support the first two mentioned challenges. Cloud computing, due to its features and architecture, is a promising infrastructure to store and process big data. Different cloud computing deployment models exist, namely, public cloud, private cloud, community cloud, and hybrid cloud. To store and process big data in a cloud environment, individuals and organizations may be more inclined to deploy and manage private clouds to gain greater control and access to resources and their data. Numerous open-source software has been developed for the deployment and management of private clouds. Evaluating and choosing among them is a challenging task, especially for those who are new to these large-scale software systems. Furthermore, due to the continuous delivery of new releases with major changes or new features and modules for each of the cloud infrastructure management software, choosing among them could be a challenge even for an experienced user.Method: In this paper, first of all, we provide the Quality Model for Cloud Infrastructure (QMCI) for evaluation of cloud infrastructure management software. QMCI focuses on quality factors that are important when processing big data. The top-level factors of this model are 1- Functionality 2- Usability 3- Reliability 4- Supportability 5- Performance. The top-level factors are then divided into sub-factors to further refine the quality model. Metrics can be considered for the sub-factors to evaluate a cloud infrastructure management software.Discussion: Based on QMCI, multiple-criteria decision-making can be utilized to choose between cloud infrastructure management software that best suits a given set of criteria. In the remaining of this paper, three of the most popular open-source cloud infrastructure management software, namely, Eucalyptus, OpenStack, and Apache Cloud Stack are evaluated based on QMCI to compare their capabilities, weaknesses, and strengths from big data processing perspective. Previous literatures that considered the selected three cloud infrastructure management software were studies and utilized to perform the comparative study.
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