BSSACH: A Big Slot Scheduling Algorithm with Channel Hopping for Dynamic Wireless Sensor Networks

2017 ◽  
pp. 359-366
Author(s):  
Chi Trung Ngo ◽  
Quy Lam Hoang ◽  
Hoon Oh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Scheduling Algorithm ◽  
Wireless Sensor ◽  
Channel Hopping ◽  
Slot Scheduling

scholarly journals TSCH and RPL Joining Time Model for Industrial Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3904
Author(s):  
Jose Vera-Pérez ◽  
Javier Silvestre-Blanes ◽  
Víctor Sempere-Payá
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Industry 4.0 ◽  
Wireless Sensor ◽  
Lossy Networks ◽  
Industrial Wireless Sensor Networks ◽  
Time Model ◽  
Industrial Internet ◽  
Channel Hopping ◽  
Definition Of

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.

Formal Probabilistic Analysis of Detection Properties in Wireless Sensor Networks

2015 ◽  
pp. 228-258
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probabilistic Analysis ◽  
Detection Probability ◽  
Scheduling Algorithm ◽  
Wireless Sensor ◽  
Higher Order Logic ◽  
Security Monitoring ◽  
Detection Delay ◽  
Mission Critical

In the context of Wireless Sensor Networks (WSNs), the ability to detect an intrusion event is the most desired characteristic. Due to the randomness in nodes scheduling algorithm and sensor deployment, probabilistic techniques are used to analyze the detection properties of WSNs. However, traditional probabilistic analysis techniques, such as simulation and model checking, do not ensure accurate results, which is a severe limitation considering the mission-critical nature of most of the WSNs. In this chapter, the authors overcome these limitations by using higher-order-logic theorem proving to formally analyze the detection properties of randomly deployed WSNs using the randomized scheduling of nodes. Based on the probability theory, described in Chapters 5, they first formally reason about the intrusion period of any occurring event. This characteristic is then built upon to develop the fundamental formalizations of the key detection metrics: the detection probability and the detection delay. For illustration purposes, the authors formally analyze the detection performance of a WSN deployed for border security monitoring.

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