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
Distributed Energy-Efficient Data Reduction Approach Based On Prediction And Compression To Reduce Data Transmission In Iot Networks
عنوان المجلة
International Journal Of Communication Systems
ISSN-1099-1131
تفاصيل النشر
سنة النشر - 2022 / الفهرس الاصلي للمجلة - 35 : 15 (عدد الصفحات 8)
تصنيف البحث
Computer Science - المجموعة العلمية
رابط DOI
https://doi.org/10.1002/dac.5282
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, data reduction, IoT, network lifetime, prediction, sensor networks

اسم الباحثجهة الانتساببلد الباحث
احمد محمد حسين جامعة بابل كلية العلوم للبنات العراق
د. علي كاظم ادريس جامعة بابل كلية التكنولوجيا المعلومات العراق
Raphael Couturier Universite Bourgogne Franche Comte

In the modern world, it will be necessary to deploy a large number of sensor devices to sense everything around us in order to detect changes, risks, and hazards and to mitigate them. This increasing number of sensor devices represents an essential data provider in the Internet of Things (IoT). The devices generate and transmit a huge amounts of data which requires a large amount of storage and high processing power to come real-time processing and speed up the network. It also leads to an increase in high energy consumption. Thus, it is important to remove redundant data to reduce the data transmission before sending it to the gateway while maintaining a good level of data quality. In this paper, a distributed energy-efficient data reduction (DEDaR) approach based on prediction and compression to minimize the data transmission in IoT Networks is proposed. The DEDaR is used in periods to make decision. In each period, the autoregressive prediction (ARP) is used to predict the data of the next period and make a decision on whether to send the data of the current period to the gateway or not. In the case of data transmission, the redundant data are eliminated using an efficient compression approach based on adaptive piecewise constant approximation (APCA), symbolic aggregate approximation (SAX), and finally fixed code dictionary (FCD) based on Huffman encoding. The simulation results based on real-sensed data show that the proposed DEDaR approach outperforms the other recent methods in terms of data reduction percentage, transmitted data size, energy consumption, and data accuracy.