تخلیه‌بار محاسباتی آگاه از تحرک و انرژی در رایانش لبه برای شبکه‌های مبتنی بر چند پهپاد

چکیده مقاله :

شبکه‌های ارتباطی و اینترنت اشیا با توسعه مداوم، به نیازمندی‌های مختلفی پاسخ می‌دهند. محدودیت‌های اندازه، توان محاسباتی و مصرف انرژی در دستگاه‌های اینترنت اشیا چالش‌های اساسی این فضا محسوب می‌شوند. این مقاله بر روی ترکیب پهپادها با رایانش لبه تاکید دارد به‌طوری‌که این یکپارچگی، پوشش پیشرفته و پشتیبانی محاسباتی کارآمد را فراهم می‌کند، به ویژه در شرایط نامعلوم مانند واکنش به حوادث. راه‌حل پیشنهادی، با لحاظ تحرک گره‌های اینترنت اشیا و با هدف بهبود کارایی انرژی کل سیستم، مسئله برنامه‌ریزی مسیر پهپاد و تخلیه‌بار محاسباتی به صورت توامان مدل‌سازی شده می‌کند. سپس، یک الگوریتم تخلیه‌بار محاسباتی و برنامه‌ریزی مسیر آگاه از تحرک و انرژی بر مبنای مجموعه پوششی کارآمد پهپادها ارائه شده است که با استفاده از ارتباطات و توافق‌های اجماعی بین گره‌های اینترنت اشیا به حداکثر رساندن کارایی انرژی سیستم کمک می‌کند. نتایج ارزیابی نشان می‌دهد که روش پیشنهادی کارایی انرژی را تا ۱۳۷ درصد و میزان مصرف انرژی را تا ۲۸ درصد نسبت به کارهای پیشین بهبود می بخشد.

چکیده انگلیسی :

Communication networks and the Internet of Things respond to various needs with continuous development. The limitations of size, computing power and energy consumption in Internet of Things devices are the main challenges of this space. This paper emphasizes combining UAVs with edge computing so that this integration provides advanced coverage and efficient computing support, especially in uncertain situations such as incident response. The proposed solution, in terms of the mobility of IoT nodes and with the aim of improving the energy efficiency of the whole system, the problem of UAV path planning and computation offloading is jointly modeled. Then, a mobility- and energy-aware computation offloading and path planning algorithm based on the efficient coverage set of UAVs is presented, which helps to maximize the energy efficiency of the system by using communication and consensus agreements between IoT nodes. The evaluation results show that the proposed method improves energy efficiency by 137% and energy consumption by 28% compared to previous works.

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