پروتکل MAC مبتنی بر یادگیری تقویتی
ترجمه نشده

پروتکل MAC مبتنی بر یادگیری تقویتی

عنوان فارسی مقاله: پروتکل کنترل دسترسی متوسط (MAC) مبتنی بر یادگیری تقویتی (UW-ALOHA-Q) برای شبکه های حسگر صوتی زیر آب
عنوان انگلیسی مقاله: Reinforcement Learning Based MAC Protocol (UW-ALOHA-Q) for Underwater Acoustic Sensor Networks
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: شبکه های کامپیوتری - امنیت اطلاعات
کلمات کلیدی فارسی: پروتکل کنترل دسترسی متوسط (MAC)، پروتکل کنترل دسترسی متوسط، یادگیری تقویتی، شبکه های صوتی زیر آب
کلمات کلیدی انگلیسی: MAC protocol, medium Access control, reinforcement learning, underwater acoustic networks
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2953801
دانشگاه: Department of Electronic Engineering, University of York, York YO10 5DD, U.K
صفحات مقاله انگلیسی: 12
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14027
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

I. Introduction

II. Previous Work

III. ALOHA-Q

IV. UW-ALOHA-Q

V. Simulations

Authors

Figures

References

بخشی از مقاله (انگلیسی)

Abstract

The demand for regular monitoring of the marine environment and ocean exploration is rapidly increasing, yet the limited bandwidth and slow propagation speed of acoustic signals leads to low data throughput for underwater networks used for such purposes. This study describes a novel approach to medium access control that engenders efficient use of an acoustic channel. ALOHA-Q is a medium access protocol designed for terrestrial radio sensor networks and reinforcement learning is incorporated into the protocol to provide efficient channel access. In principle, it potentially offers opportunities for underwater network design, due to its adaptive capability and its responsiveness to environmental changes. However, preliminary work has shown that the achievable channel utilisation is much lower in underwater environments compared with the terrestrial environment. Three improvements are proposed in this paper to address key limitations and establish a new protocol (UW-ALOHA-Q). The new protocol includes asynchronous operation to eliminate the challenges associated with time synchronisation under water, offer an increase in channel utilisation through a reduction in the number of slots per frame, and achieve collision free scheduling by incorporating a new random back-off scheme. Simulations demonstrate that UW-ALOHA-Q provides considerable benefits in terms of achievable channel utilisation, particularly when used in large scale distributed networks.

Introduction

The Earth’s surface comprises 71% water [1] and the market value of coastal resources is estimated to be 3 trillion USD per year [2], with our oceans contributing 1.5 trillion USD annually in value-added to the global economy [3]. It is therefore unsurprising that the marine environment is central to a vast diversity of industries and areas of scientific importance. Examples of underwater applications include disaster detection far off coast, underwater security surveillance, as well as environmental and ecosystem data gathering. However, most of the ocean has not been explored since ocean exploration is significantly hampered by the inherently hostile and harsh environment for both people and equipment. To deal with the challenges of the underwater environment, wire free communication is necessary in order to monitor the oceans more effectively, remotely, and potentially in real time. Wireless Sensor Networks (WSNs) using radio technology are used for monitoring purposes in many applications in the terrestrial environment. However, this technology cannot be directly applied to the underwater environment since radio signals are heavily absorbed by water. Acoustic signals are the most viable means of communicating underwater, but technologies for underwater acoustic communications are complex and demand sophisticated signal processing, hence underwater devices tend to be bulky and expensive [4].