مقاله انگلیسی رایگان در مورد پروتکل MAC مبتنی بر یادگیری تقویتی – IEEE 2019
مشخصات مقاله | |
ترجمه عنوان 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 |
انتشار | مقاله سال ۲۰۱۹ |
تعداد صفحات مقاله انگلیسی | ۱۲ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه IEEE |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۴٫۶۴۱ در سال ۲۰۱۸ |
شاخص H_index | ۵۶ در سال ۲۰۱۹ |
شاخص SJR | ۰٫۶۰۹ در سال ۲۰۱۸ |
شناسه ISSN | ۲۱۶۹-۳۵۳۶ |
شاخص Quartile (چارک) | Q2 در سال ۲۰۱۸ |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر، مهندسی فناوری اطلاعات |
گرایش های مرتبط | شبکه های کامپیوتری |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | دسترسی – IEEE Access |
دانشگاه | Department of Electronic Engineering, University of York, York YO10 5DD, U.K |
کلمات کلیدی | 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 |
شناسه دیجیتال – doi |
https://doi.org/10.1109/ACCESS.2019.2953801 |
کد محصول | E14027 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract I. Introduction II. Previous Work III. ALOHA-Q IV. UW-ALOHA-Q V. Simulations Authors Figures References |
بخشی از متن مقاله: |
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]. |