مروری بر تخصیص منابع و چارچوب‌های بهینه‌سازی در شبکه‌های رادیویی اقتضایی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 پژوهشکده فناوری اطلاعات و ارتباطات جهاددانشگاهی، تهران،ایران

2 دانشگاه هوایی شهید ستاری-دانشکده مهندسی برق

چکیده

امروزه با رشد و گسترش تقاضا برای خدمات مبتنی شبکه، استفاده از شبکه‌های رادیویی، به‌ویژه آن‌هایی که به زیرساخت‌های از پیش تعیین‌شده‌ای نیاز ندارند، مانند شبکه‌های رادیویی اقتضایی، متقاضیان زیادی پیداکرده است. چنین شبکه‌هایی با حداقل پیکربندی و استقرار سریع، برای موارد اضطراری مانند بلایا، بحران‌ها و کاربردهای نظامی مناسب می‌باشد. شبکه‌های رادیویی اقتضایی به‌عنوان یکی از پرکاربردترین شبکه‌ها به‌ویژه در موارد اضطراری شناخته‌ می‌شوند. در این مقاله تخصیص بهینه منابع رادیویی در شبکه‌های رادیویی اقتضایی که دارای هم‌بندی پویا هستند از دیدگاه‌های چارچوب‌های بهینه‌سازی، طراحی بین لایه‌ای و مسیریابی موردبررسی قرارگرفته می‌شود. چندین پژوهش‌ که در زمینه طراحی بین لایه‌ای، باهدف بهینه‌سازی در مصرف انرژی و عملکرد شبکه انجام پذیرفته‌شده نیز موردبررسی قرار می‌گیرد. ‌گام‌های کلیدی بهینه‌سازی یک مدل سیستم موردمطالعه قرار می‌گیرد. قالب مسئله‌های بهینه‌سازی یک هدفه و چندهدفه در شبکه‌های رادیویی اقتضایی با بررسی دستاوردهای کارهای جدید در هرکدام از این روش‌ها صورت گرفته موردمطالعه قرار می‌گیرد. الگوریتم‌ها و متریک‌های رایج در بهینه‌سازی با کارهای انجام‌شده در شبکه‌های رادیویی اقتضایی موردبررسی قرار می‌گیرد. بامطالعه کارهای انجام‌شده که از روش یادگیری تقویتی عمیق استفاده کرده‌اند نشان می‌دهیم که با اخذ بازخورد تصمیم از سیستم، در کنترل و مدیریت هزینه‌ها می‌توانیم تأثیر به سزایی داشته باشیم. تکنیک یادگیری تقویتی عمیق به‌عنوان راهکار کارآمد، برای تخصیص منابع در محیط پیچیده شبکه‌های نسل بعد کاندید می‌باشد و با یک حلقه بازخورد بین تصمیم و عملکرد سیستم موجب اصلاح و بهینه شدن تصمیم‌ها می‌گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A survey on Wireless Ad-hoc Network: Resource Allocation and Optimization Frameworks

نویسندگان [English]

  • Hamid Kordbacheh 1
  • hamid reza dalili oskouei 2
1 Research Institute for Information and Communication Technology, Academic Center for Education, Culture and Research, Tehran, Iran
2 Electrical Engineering Department,Shahid Sattari Aeronautical University of Science and Technology,Tehran, Iran
چکیده [English]

Nowadays, with the growing demand for network-based services, the use of wireless networks, especially those that do not require predetermined infrastructures, such wireless Ad-hoc networks (WANETs), has attracted many applicants. Such networks with minimal configuration and rapid deployment are suitable for emergencies such as disasters, crises, and military applications. WANETs are recognized as one of the most used networks, especially in emergencies. In this paper, optimal radio resource allocation of WANETs with dynamic topology is investigated from the perspective of optimization frameworks, cross-layer design, and routing. Research is being done in the field of cross-layer with the aim of optimizing energy consumption and network performance. The key steps that optimize the system model are discussed. The formulas of single-objective or multi-objective optimization problems in WANETs are studied by examining the achievements of new research done with each of these methods. Common algorithms and metrics used in optimization and tasks performed on WANETs are examined. By studying the work done using the deep reinforcement learning method, we show that by taking decision feedback from the system, we can have a significant impact on cost control and management. A deep reinforcement learning technique is a viable solution for resource allocation in the complex environment of next-generation networks, with a feedback loop between decision and system performance that refines and optimizes decisions.

کلیدواژه‌ها [English]

  • Radio ad-hoc networks
  • Optimization
  • Radio resource allocation
  • Cross-layer design
  • Routing
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