یک استراتژی آگاهانه سبز برای قرار دادن ماشین مجازی در مراکز داده ابری
محورهای موضوعی : Computer Engineeringهدایت نصراللهی ماتک 1 , همایون موتمنی 2 , بهنام برزگر 3 , ابراهیم اکبری 4 , حسین شیرکاهی 5
1 - 1Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
2 - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
3 - Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
4 - Department of Computer engineering, Sari Branch, Islamic Azad University, Sari, IRAN.
5 - Department of computer engineering, Jouybar branch, Islamic Azad University, Jouybar, Iran
کلید واژه: رایانش ابری, قرار دادن ماشین مجازی, بهینه سازی چند هدفه, الگوریتم های فراابتکاری.,
چکیده مقاله :
این مقاله روشی را برای بهینه‌سازی مشکل تامین ماشین مجازی با هدف دوگانه، که یک چالش در مراکز داده ابری است، ارائه می‌کند. در محیط ابری، تعادل بین منافع ارائه دهندگان خدمات و مشتریان مهم است. از دیدگاه تولیدکنندگان، بهینه سازی مصرف انرژی و کاهش هزینه ها ضروری است. از دیدگاه کاربران، دستیابی به سطح مناسبی از کیفیت خدمات مطلوب است و تأخیر شبکه یکی از عواملی است که به کاهش آن کمک می کند. بنابراین، بهینه سازی استفاده از پهنای باند برای کاهش تاخیر شبکه، دومین هدف مهمی است که در این مطالعه در نظر گرفته شده است. برای حل این مشکل، یک روش دو هدفه مبتنی بر الگوریتم ژنتیک ارائه شده است که نتایج نزدیک به بهینه را در زمان قابل قبولی ارائه می دهد. ارزیابی‌ها برتری الگوریتم پیشنهادی را از نظر مصرف انرژی کل و ترافیک کل در شبکه در مقایسه با روش‌های مبتنی بر الگوریتم ژنتیک، کلونی مورچه‌ها، الگوریتم FFD حریص و روش استقرار تصادفی نشان می‌دهد.
Abstract – This paper presents a method for optimizing the dual-target virtual machine provisioning problem, which is a challenge in cloud data centers. In the cloud environment, it is important to balance the interests of service providers and customers. From the producers’ viewpoint, optimizing energy consumption and reducing costs are essential. From the users’ point of view, it is desirable to achieve an adequate level of quality of service, and network latency is one of the factors that contribute to its reduction. Therefore, optimizing bandwidth usage to reduce network delay is the second important objective considered in this study. To solve this problem, a two-objective method based on a genetic algorithm is presented, which provides near-optimal results in an acceptable time. The evaluations show the superiority of the proposed algorithm in terms of total energy consumption and total traffic in the network compared with methods based on a genetic algorithm, ant colony, greedy FFD algorithm, and randomized deployment method.
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