scholarly journals Geographic Routing in Duty-Cycled Industrial Wireless Sensor Networks With Radio Irregularity

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 9043-9052 ◽  
Author(s):  
Lei Shu ◽  
Mithun Mukherjee ◽  
Likun Hu ◽  
Neil Bergmann ◽  
Chunsheng Zhu
Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 196 ◽  
Author(s):  
Xing Hu ◽  
Linhua Ma ◽  
Yongqiang Ding ◽  
Jin Xu ◽  
Yan Li ◽  
...  

The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.


2021 ◽  
Author(s):  
Khanh-Van Nguyen ◽  
Chi-Hieu Nguyen ◽  
Phi Le Nguyen ◽  
Tien Van Do ◽  
Imrich Chlamtac

AbstractA quest for geographic routing schemes of wireless sensor networks when sensor nodes are deployed in areas with obstacles has resulted in numerous ingenious proposals and techniques. However, there is a lack of solutions for complicated cases wherein the source or the sink nodes are located close to a specific hole, especially in cavern-like regions of large complex-shaped holes. In this paper, we propose a geographic routing scheme to deal with the existence of complicated-shape holes in an effective manner. Our proposed routing scheme achieves routes around holes with the (1+$$\epsilon$$ ϵ )-stretch. Experimental results show that our routing scheme yields the highest load balancing and the most extended network lifetime compared to other well-known routing algorithms as well.


2006 ◽  
Vol 2 (2) ◽  
pp. 221-262 ◽  
Author(s):  
Gang Zhou ◽  
Tian He ◽  
Sudha Krishnamurthy ◽  
John A. Stankovic

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3904
Author(s):  
Jose Vera-Pérez ◽  
Javier Silvestre-Blanes ◽  
Víctor Sempere-Payá

Wireless sensor networks (WSNs) play a key role in the ecosystem of the Industrial Internet of Things (IIoT) and the definition of today’s Industry 4.0. These WSNs have the ability to sensor large amounts of data, thanks to their easy scalability. WSNs allow the deployment of a large number of self-configuring nodes and the ability to automatically reorganize in case of any change in the topology. This huge sensorization capacity, together with its interoperability with IP-based networks, allows the systems of Industry 4.0 to be equipped with a powerful tool with which to digitalize a huge amount of variables in the different industrial processes. The IEEE 802.15.4e standard, together with the access mechanism to the Time Slotted Channel Hopping medium (TSCH) and the dynamic Routing Protocol for Low-Power and Lossy Networks (RPL), allow deployment of networks with the high levels of robustness and reliability necessary in industrial scenarios. However, these configurations have some disadvantages in the deployment and synchronization phases of the networks, since the time it takes to synchronize the nodes is penalized compared to other solutions in which access to the medium is done randomly and without channel hopping. This article proposes an analytical model to characterize the behavior of this type of network, based on TSCH and RPL during the phases of deployment along with synchronization and connection to the RPL network. Through this model, validated by simulation and real tests, it is possible to parameterize different configurations of a WSN network based on TSCH and RPL.


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