Fusion: Practice and Applications
FPA
2692-4048
2770-0070
10.54216/FPA
https://www.americaspg.com/journals/show/2040
2018
2018
Design of High-Performance Intelligent WSN based-IoT using Time Synchronized Channel Hopping and Spatial Correlation Model
Biomedical Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Hillah 51001, Babil, Iraq
Hamza
Hamza
Commissions of Persons with Disabilities and Special Needs, Ministry of Labor and Social Affairs, Baghdad, Iraq; Information and Communication Engineering, Al-Nahrain University, Baghdad, Iraq
Refed Adnan
Jaleel
Wireless Sensor Network (WSN) is one of the most significant contributors to the Internet of Things (IoT), and it plays a significant role in the lives of individuals. There are three main problems in the design of traditional WSN based-IoT. First problem about data; the WSN transmits a huge volume of data to the IoT for processing. The second problem is the energy; since sensor nodes rely on their limited battery, conserving energy is crucial, and the third problem about efficiency of transmission. This paper presents new WSN based IoT framework that integrate important techniques to solve these problems; To increase the effectiveness of data processing and storing, the intelligent Adaptive Boosting stochastic algorithm is applied. IEEE 802.15.4e time slotted channel hopping (TSCH) protocol is used because it has the benefits such as collision-free transmission and multi-hop transmission. Data reduction at the Gateway (GW) level of the network is achieved through spatial correlation between sensors with the goal of conserving energy. Principle idea of this new framework is to identify the advantages of integrating the important techniques; intelligent Adaptive Boosting Stochastic diffusion search algorithm, TSCH, and Special correlation model. As a result, the proposed framework can thereby satisfy the need for a long battery life of low-rate applications and at the same time, the need for high throughput for high-rate uses also for testing it in achieved efficient classification of data, the important performance measures are used.
2023
2023
49
58
10.54216/FPA.130104
https://www.americaspg.com/articleinfo/3/show/2040