عرض تفاصيل البحث

ادناه جميع التفاصيل الخاصة بالبحث المطلوب عرضه. توفر هذه المنصة معلومات اساسية حول البحث, لمزيد من التفاصيل يرجى متابعة التصفح من خلال الضغط على الرابط الاصلي للبحث او رابط DOI.

عنوان البحث
Maximizing The Underwater Wireless Sensor Networks’ Lifespan Using Btc And Mnp5 Compression Techniques
عنوان المجلة
Annals Of Telecommunications
ISSN-1958-9395
تفاصيل النشر
سنة النشر - 2022 / الفهرس الاصلي للمجلة - 77 : 10 (عدد الصفحات 21)
تصنيف البحث
Computer Science - المجموعة العلمية
رابط DOI
doi.org/10.1007/s12243-021-00903-6
رابط البحث
فتح في موقع المجلة الرسمي
البحث والاستدامة
الهدف 9– الصناعة والابتكار والبنية التحتية   المزيد حول هذا الهدف
البحث والمجتمع
نعم , يدعم
الكلمات المفتاحية
Data compression, UWSN, Block truncation coding, MNP5 ,Energy saving, Lifespan

اسم الباحثجهة الانتساببلد الباحث
غفران علي محمد جامعة بابل كلية العلوم للبنات العراق
علي كاظم محمد الغرابي جامعة بابل كلية العلوم للبنات العراق
علي كاظم ادريس جامعة بابل كلية العلوم للبنات العراق

The sending/receiving of data is the biggest energy user in the underwater wireless sensor networks (UWSNs). The energy supplied by the battery is the most critical resource in the sensor node affecting UWSN’s lifetime. At sensor nodes, energy is used in several forms, such as data reception and transmission, sensing, and processing. In all these, the transmission of data is very expensive in terms of power depletion, whereas data processing demand is known to be much smaller. Therefore, to save energy and boost the lifespan of UWSN, it is crucial to reduce data sending/receiving. In this paper, a two-level data compression method is proposed to work at two levels of the network that are sensor nodes and the gateway. At the sensor nodes level, we introduced a compression-based block truncation coding (CBBTC) strategy to minimize the amount of transferred data, reduce the energy used, and thereby prolong the network lifetime while attempting to keep the accuracy of the data reaching the base station at the best possible level. At the gateway (i.e., cluster head (CH)) level, a lossless compression algorithm called MNP5 is proposed to compress the obtained data sets. The MNP5 method is a double-staged procedure that consists of run-length (RLE) and adaptive frequency encodings. Using extensive simulation experiments, the assessment of proposed approaches is performed. Compared to prefix frequency filtering (PFF) and Harb protocols, the results of the simulation prove effectiveness, i.e., overhead reduction of up to 98% in residual data and 98% in energy consumption while preserving the accuracy of sent data above 90%.