| مشخصات مقاله | |
| ترجمه عنوان مقاله | بهینه سازی QoS مبتنی بر هوش مصنوعی برای ارتباط چند رسانه ای در سیستم های IoV |
| عنوان انگلیسی مقاله | Artificial Intelligence based QoS optimization for multimedia communication in IoV systems |
| انتشار | مقاله سال 2019 |
| تعداد صفحات مقاله انگلیسی | 26 صفحه |
| هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
| پایگاه داده | نشریه الزویر |
| نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
| مقاله بیس | این مقاله بیس نمیباشد |
| نمایه (index) | scopus – master journals – JCR |
| نوع مقاله | ISI |
| فرمت مقاله انگلیسی | |
| ایمپکت فاکتور(IF) |
5.341 در سال 2017 |
| شاخص H_index | 85 در سال 2019 |
| شاخص SJR | 0.844 در سال 2017 |
| شناسه ISSN | 0167-739X |
| شاخص Quartile (چارک) | Q1 در سال 2017 |
| رشته های مرتبط | مهندسی کامپیوتر |
| گرایش های مرتبط | هوش مصنوعی – الگوریتم و محاسبات |
| نوع ارائه مقاله |
ژورنال |
| مجله / کنفرانس | سیستم های کامپیوتری نسل آینده – Future Generation Computer Systems |
| دانشگاه | Sukkur IBA University, Sukkur, Sindh, 65200, Pakistan |
| کلمات کلیدی | AI ،QoE، ارتباط چند رسانه ای، IoV ،QoS، بهینه سازی، BQOA ،PQOA، خط کرسی |
| کلمات کلیدی انگلیسی | AI, QoE, Multimedia communication, IoV, QoS, Optimization, PQOA, BQOA, Baseline |
| شناسه دیجیتال – doi |
https://doi.org/10.1016/j.future.2018.12.008 |
| کد محصول | E12018 |
| 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: |
| Outline Highlights Abstract Keywords 1. Introduction 2. Related work 3. Proposed QoE optimization algorithms in IoV System 4. Experimental set-up 5. Future directions and tentative solutions 6. Conclusions Acknowledgments References |
| بخشی از متن مقاله: |
| Abstract Due to the advancements in multimedia communication in internet of vehicles (IoV) through emerging technologies i.e., WiFi, Bluetooth, and fifth generation (5G) etc. The critical challenge for IoV during multimedia communication in healthcare is the quality of experience (QoE) optimization by managing the mobility of wireless channel between vehicles. Besides, Artificial Intelligence (AI) based approaches have entirely changed the landscape of IoVs, also the portable devices for transmitting multimedia content in IoV system has become very necessary for the end-users in their respective fields. Most of the end users are facing is their annoyed and less satisfactory perspective about the quality they are experiencing i.e., QoE. If the service provisioning is not pleasant then most of the end-users/consumers give-up to continue, and finally market devaluates the overall performance of the devices, company or entire system. So remedy that problem this paper first proposes two novel algorithms named, Power-aware QoE Optimization (PQO) and Buffer-aware QoE Optimization (BQO) and compares their performance with the Baseline. Second proposes multimedia communication mechanism. Third, proposes the QoE optimization framework during multimedia communication in IoV system through portable devices. Besides, experimental results reveal that proposed PQO and BQO algorithms optimizes the QoE at (31%, 33.5%) with improved lifetime of portable devices at (25%, 27%) higher level than the Baseline (25%, 17) accordingly by satisfying the end-users. Hence, it is concluded that our proposed algorithms outperforms the Baseline, so can be considered as potential candidates for the IoV applications during multimedia communication. |