پایان نامه الگوریتم های خوشه بندی در شبکه های حسگر بی سیم
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)
پروژه ی کارشناسی مهندسی فناوری اطلاعات - الگوریتم های خوشه بندی (clusterig) در شبکه های حسگر بی سیم
در این پروژه از ترجمه و خلاصه ی چندین مقاله ی ISI استفاده شده است .
این پروژه ۱۲۵ صفحه می باشد که فرمت آن نیز متناسب با فرمت پروژه های دانشگاهی است.
برای ارائه این پروژه فایل پاورپوینتی نیز در نظر گرفته شده است.
چکیده: شبکه های حسگر بی سیم شامل تعداد زیادی از سنسورهای کوچک است که که می توانند یک ابزار قوی برای جمع آوری داده در انواع محیط های داده ای متنوع باشند.داده های جمع آوری شده توسط هر حسگر به ایستگاه اصلی منتقل می شود تا به کاربر نهایی ارائه می شود.یكی از عمده ترین چالشها در این نوع شبكه ها، محدودیت مصرف انرژی است كه مستقیما طول عمر شبكه حسگر را تحت تأثیر قرار میدهد ، خوشه بندی بعنوان یكی از روشهای شناخته شده ای است كه بطور گسترده ای برای مواجه شدن با این چالش مورد استفاده قرار میگیرد. خوشه بندی به شبکه های حسگر بی سیم معرفی شده است چرا که طبق آزمایشات انجام شده ،روشی موثر برای ارائه ی بهتر تجمع داده ها و مقیاس پذیری برای شبکه های حسگر بی سیم بزرگ است. خوشه بندی همچنین منابع انرژی محدود حسگرها را محافظت کرده و باعث صرفه جویی در مصرف انرژی می شود.