یک روش ترافیکآگاه برای دستهبندی بستهها با هدف کاهش تعداد دفعات دسترسی به حافظه
الموضوعات :سعید اسدروز 1 , محمد نصیری 2 , مهدی عباسی 3 , حاتم عبدلی 4
1 - دانشگاه بوعلی سینا
2 - دانشگاه بوعلی سینا
3 - دانشگاه بوعلی سینا همدان
4 - دانشگاه بوعلی سینا
الکلمات المفتاحية: ترافیکآگاهدرخت AVLدستهبندی بستههامحلیبودن مراجعات,
ملخص المقالة :
دستهبندی بستهها نقش بسزایی در بهبود عملکرد تجهیزات شبکهای از جمله مسیریابها، دیوارههای آتش و سیستمهای تشخیص نفوذ ایفا میکند. الگوریتمهای دستهبندی بسته عموماً مبتنی بر ساختار دادهای ایستا هستند که الگوی رفتاری ترافیک ورودی را در بهینهسازی ساختار جستجو در نظر نمیگیرند. در این پژوهش، ویژگیهای آماری ترافیک ورودی در نظر گرفته شده و از ساختمان دادههای کمکی ترافیکآگاه در کنار ساختارهای اصلی استفاده شده است. از آنجا که حجم غالب ترافیک اینترنت، مربوط به جریانهای بلندمدت است، برای مدتزمانی نه چندان کوتاه، اکثر مطابقتهای قوانین در زیردرختهای مشخصی از درخت جستجو قرار دارند. برای بهرهگیری از این ویژگی، در این پژوهش از ساختار داده درخت AVL برای نگهداری قوانین دستهبند و از حدهای بالا و پایین مجموعه قوانین به عنوان گرههای درخت جستجو استفاده شده است. ارزیابیها نشان میدهد که با افزایش چولگی بستههای آزمون، تعداد دفعات دسترسی به حافظه الگوریتم دستهبندی ترافیکآگاه نسبت به الگوریتم دستهبندی پایه کاهش قابل توجهی دارد. بر اساس ارزیابیها، دستهبندی بسته ترافیکآگاه با استفاده از قوانین پرتکرار میتواند میانگین کل تعداد دفعات دسترسی به حافظه و در نتیجه زمان جستجو را بیش از 40 درصد کاهش دهد.
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