SIMSIZ SENSOR TARMOQLARI UCHUN MASHINAVIY O‘RGANISH ASOSIDAGI ENERGIYA TEJAMKOR MARSHRUTLASH PROTOKOLI
Kalit so'zlar
https://doi.org/10.47390/ts-v3i12y2025N14Kalit so'zlar
Mashinaviy o‘rganish, noravshan mantiq, Q-o‘qitish, klaster bosh tuguni tanlash, kuchaytirilgan o‘rganish.Annotasiya
Simsiz sensor tarmoqlari (SST) atrof-muhit monitoringi, sanoatni avtomatlashtirish, qishloq xo‘jaligi monitoringi shuningdek, ko‘plab rivojlanayotgan IoT tizimlarida tobora muhim rol o‘ynamoqda. Sensor tugunlarining energiya bo‘yicha cheklovlari tufayli energiya tejamkor marshrutlash protokollarini ishlab chiqish ushbu sohadagi eng dolzarb muammolardan biri bo‘lib qolmoqda. LEACH, HEED va PEGASIS kabi an’anaviy marshrutlash protokollari statik qoidalarga asoslanadi va ko‘pincha dinamik tarmoq sharoitlariga moslasha olmaydi, natijada energiyaning nomutanosib sarflanishi va tugunlarning muddatidan oldin ishdan chiqishi kuzatiladi.Ushbu maqolada mashina o‘rganish asosidagi energiya tejamkor marshrutlash protokoli (ML-EERP) taklif etilmoqda. Mazkur protokol noravshan mantiqqa asoslangan klaster-bosh (KB) tugunini tanlash va Q-o‘qitishga asoslangan ko‘p oraliqli marshrutni optimallashtirishni birlashtiruvchi gibrid protokoldir. Noravshan mantiq tizimi qoldiq energiya, tugun zichligi, aloqa sifatini va bazaviy stansiyaga bo‘lgan masofani KB tugunni tanlash jarayoniga birlashtiradi.
Klasterlar shakllantirilgandan so‘ng, tugunlar uzatish energiyasini kamaytirgan holda ishonchlilikni saqlab turish uchun keyingi optimal tugunni tanlashdda Q-o‘qitishdan foydalanadi. MATLAB va Python dasturlash muhitlarida birinchi tartibli radio energiya modeli asosida o‘tkazilgan simulyatsiyalar ML-EERP protokoli LEACH va HEED protokollaridan sezilarli darajada ustun ekanligini ko‘rsatadi. Taklif etilayotgan protokol tarmoqning yashovchanligini uzaytiradi, umumiy energiya sarfini kamaytiradi va paketlar yetkazib berish koeffitsiyentini oshiradi.
Manbalar
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