الگوریتم WCDG: یک روش جدید برای کاهش مصرف انرژی، افزایش تعادل بار بین گره‌ها و طول عمر در شبکه‌های حسگر بی‌سیم
محورهای موضوعی : مهندسی برق و کامپیوترسمانه عباسی دره‌ساری 1 , جمشید ابویی 2
1 - دانشگاه یزد
2 - دانشگاه یزد
کلید واژه: شبکه‌های حسگر بی‌سیم نمونه‌برداری فشرده اندازه‌گیری تصادفی تنک تجمیع داده درخت‌های مسیریابی وزن‌دار,
چکیده مقاله :
امروزه شبکه‌های حسگر بی‌سیم به طور گسترده در سیستم‌های نظارتی مورد استفاده قرار می‌گیرند. عمده‌ترین چالش در طراحی این شبکه‌ها، به حداقل رساندن هزینه انتقال داده است. تجمیع داده با استفاده از نظریه نمونه‌برداری فشرده، روشی مؤثر برای کاهش هزینه ارتباطات در گره چاهک می‌باشد. روش‌های تجمیع داده موجود که بر مبنای نمونه‌برداری فشرده عمل می‌کنند، برای هر نمونه اندازه‌گیری نیاز به شرکت تعداد زیادی از گره‌های حسگر دارند که منجر به ناکارآمدی در مصرف انرژی می‌شود. به منظور رفع این مشکل، در این مقاله از اندازه‌گیری‌های تصادفی تنک استفاده می‌‌گردد. از طرفی، تشکیل درخت‌های مسیریابی با هزینه کمتر و توزیع عادلانه بار در سطح شبکه، میزان مصرف انرژی را به طور قابل ملاحظه‌ای کاهش می‌دهند. در این راستا الگوریتم جدیدی با عنوان WCDG ارائه می‌شود که با ایجاد درخت‌های مسیریابی وزن‌دار و بهره‌گیری توأم از نمونه‌برداری فشرده، داده‌های گره‌های هر مسیر را تجمیع و برای گره چاهک ارسال می‌کند. در الگوریتم WCDG با در نظر گرفتن قابلیت کنترل توان در گره‌های حسگر، مسیرهای کارآمدی انتخاب می‌شوند. نتایج شبیه‌سازی‌ها حاکی از آن است که روش پیشنهادی در مقایسه با سایر روش‌ها به طور قابل توجهی عملکرد بهتری از نظر میزان مصرف انرژی و تعادل بار در شبکه دارد.
Wireless senor networks (WSNs) are widely used for the monitoring purposes. One of the most challenges in designing these networks is minimizing the data transmission cost with accurate data recovery. Data aggregation using the theory of compressive sampling is an effective way to reduce the cost of communication in the sink node. The existing data aggregation methods based on compressive sampling require to a large number of nodes for each measurement sample leading to inefficient energy consumption in wireless sensor network. To solve this problem, we propose a new scheme by using sparse random measurement matrix. In this scheme, the formation of routing trees with low cost and fair distribution of load on the network significantly reduces energy consumption. Toward this goal, a new algorithm called “weighted compressive data gathering (WCDG)” is suggested in which by creating weighted routing trees and using the compressive sampling, the data belong to all of nodes of each path is aggregated and then, sent to the sink node. Considering the power control ability in sensor nodes, efficient paths are selected in this algorithm. Numerical results demonstrate the efficiency of the proposed algorithm with compared to the conventional data aggregation schemes in terms of energy consumption, load balancing, and network lifetime.
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