scholarly journals Simulation Study of Topological Structures and Node Coordinations for Deterministic WSN with TSCH

2017 ◽  
Vol 1 (4) ◽  
pp. 115 ◽  
Author(s):  
Vijaya Perumalla ◽  
B. Seetha Ramanjaneyulu ◽  
Ashok Kolli
Keyword(s):  
Simulation Study ◽  
Time Delays ◽  
Frequency Hopping ◽  
Multihop Networks ◽  
Wireless Sensor ◽  
Multiple Channels ◽  
Promising Technique ◽  
Different Types ◽  
Channel Hopping ◽  
Multiple Frequencies

Time-Slotted Channel hopping (TSCH) that was introduced in IEEE802.15.4e is a promising technique to offer deterministic data deliveries in Wireless Sensor Networks (WSN). Its main strength lies in using multiple channels for the transmissions, using frequency hopping method. However, it takes more time for initializing the network, as beacons have to be released on multiple frequencies and scanning needs to be carried out by the devices in all those frequencies for joining the network. In this work, a simulation study is carried out to investigate the effect of these delays for different types of multihop networks. The benefit of introducing multiple coordinators in reducing these time delays is also studied. It is found that the delays are increasing linearly with the number of hops in the network and adding an additional coordinator can bring down the initialization time by half.

scholarly journals Block Design-Based Asynchronous Neighbor Discovery Protocol for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Sangil Choi ◽  
Wooksik Lee ◽  
Teukseob Song ◽  
Jong-Hoon Youn
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Simulation Study ◽  
Mathematical Proof ◽  
Block Design ◽  
Wireless Sensor ◽  
Neighbor Discovery ◽  
Block Designs ◽  
Worst Case ◽  
Neighbor Discovery Protocol

Neighbor discovery is a significant research topic in wireless sensor networks. After wireless sensor devices are deployed in specific areas, they attempt to determine neighbors within their communication range. This paper proposes a new Block design-based Asynchronous Neighbor Discovery protocol for sensor networks calledBAND. We borrow the concept of combinatorial block designs for neighbor discovery. First, we summarize a practical challenge and difficulty of using the original block designs. To address this challenge, we create a new block generation technique for neighbor discovery schedules and provide a mathematical proof of the proposed concept. A key aspect of the proposed protocol is that it combines two block designs in order to construct a new block for neighbor discovery. We analyze the worst-case neighbor discovery latency numerically between our protocol and some well-known protocols in the literature. Our protocol reveals that the worst-case latency is much lower than others. Finally, we evaluate the performance ofBANDand existing representative protocols through the simulation study. The results of our simulation study show that the average and maximum latency ofBANDis about 40% lower than that of existing protocols. Furthermore,BANDspends approximately 30% less energy than others during the neighbor discovery process.

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.

Exponential lag function projective synchronization of memristor-based multidirectional associative memory neural networks via hybrid control

2018 ◽  
Vol 32 (09) ◽  
pp. 1850116 ◽  
Author(s):  
Manman Yuan ◽  
Weiping Wang ◽  
Xiong Luo ◽  
Lixiang Li ◽  
Jürgen Kurths ◽  
...  
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Time Delays ◽  
Hybrid Control ◽  
Projective Synchronization ◽  
Mixed Delays ◽  
Time Varying ◽  
Function Projective Synchronization ◽  
Different Types ◽  
Discrete Delays

This paper is concerned with the exponential lag function projective synchronization of memristive multidirectional associative memory neural networks (MMAMNNs). First, we propose a new model of MMAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying discrete delays and distributed time delays. Second, we design two kinds of hybrid controllers. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the controllers are carefully designed to confirm the process of different types of synchronization in the MMAMNNs. Third, sufficient criteria guaranteeing the synchronization of system are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

An Automated Optimize Utilization of Water and Crop Monitoring in Agriculture Using IoT

2021 ◽  
pp. 37-45
Author(s):  
Ajith Krishna R ◽  
◽  
◽  
◽  
Ankit Kumar ◽  
...  
Keyword(s):  
Soil Analysis ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Leaf Wetness ◽  
Productivity Analysis ◽  
Factors Affecting ◽  
Crop Monitoring ◽  
Different Types ◽  
Smart Agriculture ◽  
Climate Analysis

Agriculture is the primary occupation in our country for ages. But now due to migration of people from rural to urban there is hindrance in agriculture. So, to overcome this problem we go for smart agriculture techniques using IoT. This paper includes various features like GPS based remote controlled monitoring, moisture & temperature sensing, intruders scaring, security, leaf wetness and proper irrigation facilities. It makes use of wireless sensor networks for noting the soil properties and environmental factors continuously. Various sensor nodes are deployed at different locations in the farm. Controlling these parameters are through any remote device or internet services and the operations are performed by interfacing sensors, Wi-Fi, camera with microcontroller. This concept is created as a product and given to the farmer’s welfare. AI Solution for Farmers perform soil analysis, climate analysis, and productivity analysis using linear regression. It helps farmers to understand about the crop to be sown as well as the factors affecting their productivity with the help of different types of graphs and tables. Farmers need not to do anything on the application as it is highly interactive as by using speech API.

Application of Computational Intelligence Techniques in Managing Wireless Sensor Networks

2010 ◽  
pp. 39-72
Author(s):  
Ibrahiem Mahmoud Mohamed El Emary
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Management ◽  
Computational Intelligence ◽  
Critical Issue ◽  
Human Interaction ◽  
Wireless Sensor ◽  
Hierarchical Architecture ◽  
Different Types ◽  
Management Functions

This chapter gives a brief background on network management and how it is integrated into sensor network as well as the application of computational intelligence techniques in managing wireless sensor networks. Also discussed how Genetic Algorithms work in common and how they can be applied to sensor networks. Among the major management tasks rely on consumption power management, so there are many challenges associated with sensor networks but the primary challenge is energy consumption. Sensor networks are typically have little human interaction and are installed with limited battery supplies. This makes energy conservation a critical issue in deployed WSNs. All types of networks require monitoring and maintenance. A service that supplies a set of tools and applications that assist a network manager with these tasks is network management. It includes the administration of networks and all associated components. While all networks require some form of network management, different types of networks may stress certain aspects of network management. Some networks may also impose new tasks on network management. There are different types of network management architectures: centralized, hierarchical and distributed. In a centralized approach, one central server performs the role of the network management application. A hierarchical architecture will include multiple platforms, typically one server and several clients, performing network management functions.

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