Green Computing for Industrial Wireless Sensor Networks: Energy oriented Cross Layer Modelling

2021 ◽  
Vol 15 ◽  
Author(s):  
Mahendra Ram ◽  
Sushil Kumar ◽  
Arvind Kumar ◽  
Rupak Kharel
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Dissemination ◽  
Physical Layer ◽  
Green Computing ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Industrial Environment ◽  
Industrial Wireless Sensor Network ◽  
Network Environments

Background: Enabling industrial environment with automation is growing trend due to the recent developments as industry 4.0 centric production. The industrial wireless sensor network environments have a number of constraints, including densely deployed nodes, delay constraint for mechanical operation, and access constraints due to node position within instruments. The related literature have applied existing models of wireless sensor network in industrial environment without appropriate updating in the different layers of communication, which results in performance degradation in realistic industrial scenario. Method: This paper presents a framework for Energy Oriented Cross Layer Data Dissemination Path (E-CLD2 P) towards enabling green computing in industrial wireless sensor network environments. It is a cross-layer design approach considering deployment of sensors at the physical layer up to data dissemination at the network layer and smart services at application layer. In particular, an energy centric virtual circular deployment visualization model is presented focusing on physical layer signal transmission characteristics in industrial WSNs scenario. A delay centric angular striping is designed for cluster based angular transmission to support deadline constrained industrial operation in the WSNs environments. Algorithms for energy centric delivery path formulation and node’s role transfer are developed to support green computing in restricted access industrial WSNs scenario. Results: The green computing framework is implemented to evaluate the performance in a realistic industrial WSNs environment. Conclusion: The performance evaluation attests the benefits in terms of number of metrics in realistic industrial constrained environments.

Self-Correcting Time Synchronization Based on Cross Layer for Wireless Sensor Network

2012 ◽  
Vol 220-223 ◽  
pp. 1871-1876
Author(s):  
Feng Mei Liang ◽  
Bin Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Time Synchronization ◽  
Mac Protocol ◽  
Physical Layer ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Synchronization Mechanism ◽  
Synchronization Algorithm ◽  
Crystal Oscillation

Due to energy restrictions, node distribution density and hardware computing power etc., the traditional time synchronization mechanism is not suitable for wireless sensor network. The paper discussed the main reason that caused asynchronization and proposed an improved time synchronization algorithm based on cross layer optimization for wireless sensor network. Considering the stability of crystal oscillation and the linearity of crystal deviation in the physical layer, the improved time synchronization mechanism implemented a self-correction by the cross-layer MAC protocol. Estimating the crystal oscillation drift, the crystal deviation had been self-corrected just by a few times data broadcast. The experiment on the MCU Si1000 physical layer platform has demonstrated the practicability of the algorithm. The synchronization algorithm is able to keep a stable network operation in the way of extending the synchronization period and reducing the synchronization cost. The synchronization mechanism is applicable to the active acquisition network, especially the realtime one.

Cross-Layer Cooperative Protocol for Industrial Wireless Sensor Network

2017 ◽  
pp. 218-241
Author(s):  
Bilal Muhammad Khan ◽  
Rabia Bilal
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Performance Metrics ◽  
Data Communication ◽  
Reliable Data ◽  
Wireless Sensor ◽  
Harsh Environment ◽  
Cross Layer ◽  
Minimum Delay ◽  
Industrial Wireless Sensor Network

Robustness and reliability are two essential network parameters to be given priority in Industrial Wireless Sensor Network. But at the same time it is difficult to achieve gain in these performance metrics. Since in industries these networks are used for monitoring, control and automation processes, therefore, it also requires robust communication with minimum delay. Considering the need of high QoS in Industrial WSN, protocols and standards were developed to fulfil the requirement of reliable data communication in harsh environment. In year 2007, HART community designed a Wireless HART standard for efficient industrial communication. This standard gain high reputation soon after its implementation and still being used as a universal solution for industries. In 2009, another standard ISA100.11a was developed, it also gives promised results but fails to eliminate WHART. Both these standards are still competing in industry and the results of these standards are more reliable in comparison to other wireless industrial protocols that exists.

Cross-Layer Cooperative Protocol for Industrial Wireless Sensor Network

2020 ◽  
pp. 532-555
Author(s):  
Bilal Muhammad Khan ◽  
Rabia Bilal
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Performance Metrics ◽  
Data Communication ◽  
Reliable Data ◽  
Wireless Sensor ◽  
Harsh Environment ◽  
Cross Layer ◽  
Minimum Delay ◽  
Industrial Wireless Sensor Network

Robustness and reliability are two essential network parameters to be given priority in Industrial Wireless Sensor Network. But at the same time it is difficult to achieve gain in these performance metrics. Since in industries these networks are used for monitoring, control and automation processes, therefore, it also requires robust communication with minimum delay. Considering the need of high QoS in Industrial WSN, protocols and standards were developed to fulfil the requirement of reliable data communication in harsh environment. In year 2007, HART community designed a Wireless HART standard for efficient industrial communication. This standard gain high reputation soon after its implementation and still being used as a universal solution for industries. In 2009, another standard ISA100.11a was developed, it also gives promised results but fails to eliminate WHART. Both these standards are still competing in industry and the results of these standards are more reliable in comparison to other wireless industrial protocols that exists.

Cross layer design with extensive virtual MIMO: FS-MUP optimization model for wireless sensor network

2020 ◽  
pp. 1-16
Author(s):  
Monali Prajapati ◽  
Dr. Jay Joshi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Input Multiple Output ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Virtual Mimo ◽  
Proposed Model ◽  
Multiple Input ◽  
Input Multiple Output

In the wireless sensor network (WSN), wireless communication is said to be the dominant power-consuming operation and it is a challenging one. Virtual Multiple-Input–Multiple-Output (V-MIMO) technology is considered to be the energy-saving method in the WSN. In this paper, a novel multihop virtual MIMO communication protocol is designed in the WSN via cross-layer design to enhance the energy efficiency, reliability, and end-to-end (ETE) and Quality of Service (QoS) provisioning. On the basis of the proposed protocol, the optimal set of parameters concerning the transmission and the overall consumed energy by each of the packets is found. Furthermore, the modeling of ETE latency and throughput of the protocol takes place with respect to the bit-error-rate (BER). A novel hybrid optimization algorithm referred as Flight Straight Moth Updated Particle Swarm Optimization (FS-MUP) is introduced to find the optimal BER that meets the QoS, ETE requirements of each link with lower power consumption. Finally, the performance of the proposed model is evaluated over the extant models in terms of Energy Consumption and BER as well.

Sign in / Sign up

Export Citation Format

Share Document