Low Power coder for Wireless Sensor Networks

Author(s):  
Priya B ◽  
Radhamani V
2018 ◽  
pp. 14-1-14-23
Author(s):  
Brian P. Otis ◽  
Yuen Hui Chee ◽  
Richard Lu ◽  
Nathan M. Pletcher ◽  
Jan M. Rabaey ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6111
Author(s):  
Sangjun Lee ◽  
Kyunghwan Cho ◽  
Jihye Kim ◽  
Jongho Park ◽  
Inhwan Lee ◽  
...  

Cryptographic circuits generally are used for applications of wireless sensor networks to ensure security and must be tested in a manufacturing process to guarantee their quality. Therefore, a scan architecture is widely used for testing the circuits in the manufacturing test to improve testability. However, during scan testing, test-power consumption becomes more serious as the number of transistors and the complexity of chips increase. Hence, the scan chain reordering method is widely applied in a low-power architecture because of its ability to achieve high power reduction with a simple architecture. However, achieving a significant power reduction without excessive computational time remains challenging. In this paper, a novel scan correlation-aware scan cluster reordering is proposed to solve this problem. The proposed method uses a new scan correlation-aware clustering in order to place highly correlated scan cells adjacent to each other. The experimental results demonstrate that the proposed method achieves a significant power reduction with a relatively fast computational time compared with previous methods. Therefore, by improving the reliability of cryptography circuits in wireless sensor networks (WSNs) through significant test-power reduction, the proposed method can ensure the security and integrity of information in WSNs.


Author(s):  
Mehdi Amiri Nasab ◽  
Shahaboddin Shamshirband ◽  
Anthony Theodore Chronopoulos ◽  
Amir Mosavi ◽  
Narjes Nabipur

The radio operation in wireless sensor networks (WSN) in the Internet of Things (IoT) applications are the most common source for power consumption. However, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. ContikiMAC is a low-power Radio Duty-Cycle protocol in Contiki OS used in WakeUp mode, which is a clear channel assessment (CCA) to check radio status periodically. The time spent to check the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in Radio Duty-Cycles and ContikiMAC. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Then, we propose lightweight CCA (LW-CCA) as an extension to ContikiMAC to reduce the percentage of Radio Duty-Cycles in false WakeUps and idle listenings by using dynamic received signal strength indicators (RSSI) status check time. The simulation results in the Cooja simulator show that LW-CCA reduces about 8% energy consumption in nodes while maintaining up to 99% of the packet delivery rate (PDR).


Author(s):  
Maytham Safar ◽  
Hasan Al-Hamadi ◽  
Dariush Ebrahimi

Wireless sensor networks (WSN) have emerged in many applications as a platform to collect data and monitor a specified area with minimal human intervention. The initial deployment of WSN sensors forms a network that consists of randomly distributed devices/nodes in a known space. Advancements have been made in low-power micro-electronic circuits, which have allowed WSN to be a feasible platform for many applications. However, there are two major concerns that govern the efficiency, availability, and functionality of the network—power consumption and fault tolerance. This paper introduces a new algorithm called Power Efficient Cluster Algorithm (PECA). The proposed algorithm reduces the power consumption required to setup the network. This is accomplished by effectively reducing the total number of radio transmission required in the network setup (deployment) phase. As a fault tolerance approach, the algorithm stores information about each node for easier recovery of the network should any node fail. The proposed algorithm is compared with the Self Organizing Sensor (SOS) algorithm; results show that PECA consumes significantly less power than SOS.


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