ENERGY EFFICIENCY WITH COMPRESSIVE SLEEPING AND SCHEDULING SCHEME FOR BODY SENSOR NETWORK

ELSA NUR FITRI ASTUTI

Informasi Umum

Kode

20.05.121

Klasifikasi

621.382 - Communication Engineering, signal processing, network protocol, signal processing, communication network analysis

Jenis

Karya Ilmiah - Thesis (S2) - Reference

Subjek

Telecommunication - Engineering

Dilihat

36 kali

Informasi Lainnya

Abstraksi

Body Sensor Network is one of the sensor networks that are needed in the medical field. In this network, there are sensor technology, information processing, realtime communication and pervasive computing. These technologies use a lot of energy in its implementation, such as the use of sensors for sensing information, realtime communication, transmission of information from the sensors to the fusion center and others. Therefore, energy consumption is an important concern for the Body Sensor Network (BSN). The use of compressive sleeping and scheduling methods is very important in selecting active sensors and transmission the right data, so as to reduce energy consumption. This study aims to design a compressive sleeping algorithm that adopts the Compressive Sensing (CS) method, which is used to select several sensors that are active and inactive at the specified time.In addition, the scheduling method will be used in processing data transmission obtained from the active sensor. The method to be used in this study is the Sensor-Medium Access Control (S-MAC) method, which can reduce energy consumption by scheduling to prevent collisions between information sent by sensors to the fusion center. S-MAC aims to set the sensor in the data transmission (time data transmission), so that sensor know the time for the data transmission and no. Sensors that is transmitting data will be enter a period of listen and the sensor that is not transmitting data will be enter a period of rest. After the scheduling process, data sensor will be transmit to the fusion center and perform CS recontruction process. The results of this study, the comparison of the value of energy consumption in BSN which applying the proposed method with BSN without applying the proposed method. Keywords: Body Sensor Network, Compressive Sensing, Scheduling, S-MAC, Energy Efficiency.