یک طرح برون‌سپاری وظایف آگاه از جابه‌جایی اشیاء مبتنی بر الگوریتم بهینه‌سازی کلونی مورچه در پردازش مه نرم‌افزار-محور

نوع مقاله : علمی-پژوهشی

نویسندگان

1 استادیار، دانشکده مهندسی کامپیوتر، دانشگاه یزد، یزد، ایران

2 دانشجوی دکترا، دانشکده مهندسی کامپیوتر، دانشگاه یزد، یزد، ایران

چکیده

محاسبات مه رویکرد نوینی است که با هدف کاهش زمان پاسخ کاربرد‌های حساس به تأخیر و بهبود ارائه خدمات به کاربران، امکان برون‌سپاری وظایف (داده‌ها) اینترنت اشیاء را به تجهیزات شبکه فراهم می‌کند. این مقاله یک طرح برون‌سپاری وظیفه به محیط مه با بهره‌مندی از مزایای شبکه‌های نرم‌افزار-‌محور ارائه می‌دهد. در این پژوهش یک مدل ریاضی بهینه‌سازی برنامه‌ریزی خطی عدد صحیح مختلط (MILP) با هدف کمینه‌سازی تأخیر و هزینه ناشی از جابه‌جایی اشیاء و با در نظر گرفتن پردازش محلی، مشارکت گره‌های مه، توزیع برنامه‌های کاربردی و محدودیت منابع گره‌های مه ارائه شده است. با توجه به اینکه مدل ریاضی ارائه شده در این مسئله ان‌پی‌-سخت است، یک الگوریتم فرا‌-ابتکاری مبتنی بر بهینه‌سازی کلونی مورچه و با در نظر گرفتن محدودیت‌های مدل ریاضی ارائه شده است. مقادیر حاصل از ارزیابی روش پیشنهادی با مقدار بهینه حاصل از مدل ریاضی، روش‌ تصادفی و یک الگوریتم ابتکاری ارائه شده در کارهای مرتبط مقایسه شده است. نتایج حاصل نشان می‌دهد تأخیر و هزینه کل برون‌سپاری در روش پیشنهادی به ترتیب 22% و 28.75% از مقادیر بهینه بیشتر است و روش پیشنهادی قادر به کاهش تأخیر به میزان 20% و کاهش هزینه مهاجرت نتایج به میزان 40% نسبت به روش ابتکاری مقایسه شده است.

کلیدواژه‌ها

عنوان مقاله [English]

A Mobility Aware Task Offloading Scheme Based On Ant Colony Optimization Algorithm In Software-Defined Fog Computing

نویسندگان [English]

  • S.A. Mostafavi 1
  • E. Barkhordari 2
1 Department of Computer Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
2 Department of Computer Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
چکیده [English]

Fog computing is a new paradigm which enables offloading IOT data (tasks) to the network devices. The aim of this approach is reducing the response time for delay-sensitive applications and improving the quality of service for users. This paper presents a task offloading scheme with taking advantages of the Software-Defind Networks. In this research a mixed integer linear programming (MILP) optimization model is presented with the aim of minimizing delay and mobility cost of things, which considers local computing, fog nodes participation, applications distribution and resource limitations. Whereas the presented mathematical model is Np-hard, a meta-heuristic algorithm based on the ant colony optimization is proposed by considering constraints of the mathematical model. The results obtained from evaluation of the proposed method is compared with the optimal value obtained from the mathematical model, random method and a heuristic algorithm presented in related works. The results of evaluation show that the delay and the total offloading cost in the proposed method are 22% and 28.75% higher than the optimal values, respectively. Also, the proposed method is capable to reduce the delay by 20% and reduce the migration cost of computing results by 40% compared to the heuristic method in state-of-the-art.

کلیدواژه‌ها [English]

  • Internet of Things
  • fog computing
  • task offloading
  • mobility of things
  • ant colony optimization
  • software-defined networking

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