Adaptive Active Immune Policy for Sensor Nodes in Internet of Things

Author(s):  
Cheng Zhong ◽  
Pengcheng Lu ◽  
Shaoyong Guo ◽  
Song Kang
2021 ◽  
Vol 24 (3) ◽  
pp. 5-8
Author(s):  
Kai Geissdoerfer ◽  
Mikołaj Chwalisz ◽  
Marco Zimmerling

Collaboration of batteryless devices is essential to their success in replacing traditional battery-based systems. Without significant energy storage, spatio-temporal fluctuations of ambient energy availability become critical for the correct functioning of these systems. We present Shepherd, a testbed for the batteryless Internet of Things (IoT) that can record and reproduce spatio-temporal characteristics of real energy environments to obtain insights into the challenges and opportunities of operating groups of batteryless sensor nodes.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7449
Author(s):  
Fangqiuzi He ◽  
Junfeng Xu ◽  
Jinglin Zhong ◽  
Guang Chen ◽  
Shixin Peng

In order to realize the intelligent management of a power materials warehouse, the Internet of Things based on wireless sensor networks (WSNs) is a promising effective solution. Considering the limited battery capacity of sensor nodes, the optimization of the topology control and the determination of the amount of collected data are critical for prolonging the survival time of WSNs and increasing the satisfaction of the warehouse supplier. Therefore, in this paper, an optimization problem on sensor association and acquisition data satisfaction is proposed, and the subproblem of the sensor association is modeled as the knapsack problem. To cope with it, the block coordinate descent method is used to obtain the suboptimal solution. A sensor association scheme based on the ant colony algorithm (ACO) is proposed, and the upper and lower bounds of this optimization problem are also obtained. After this, a cluster head selection algorithm is given to find the optimal cluster head. Finally, the experimental simulations show that the algorithms proposed in this paper can effectively improve the energy utilization of WSNs to ensure the intelligent management of a power materials warehouse.


2017 ◽  
Vol 4 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Amol V. Dhumane ◽  
Rajesh S. Prasad ◽  
Jayashree R. Prasad

In Internet of things and its relevant technologies the routing of data plays one of the major roles. In this paper, a routing algorithm is presented for the networks consisting of smart objects, so that the Internet of Things and its enabling technologies can provide high reliability while the transmitting the data. The proposed technique executes in two stages. In first stage, the sensor nodes are clustered and an optimal cluster head is selected by using k-means clustering algorithm. The clustering is performed based on energy of sensor nodes. Then the energy cost of the cluster head and the trust level of the sensor nodes are determined. At second stage, an optimal path will be selected by using the Genetic Algorithm (GA). The genetic algorithm is based on the energy cost at cluster head, trust level at sensor nodes and path length. The resultant optimal path provides high reliability, better speed and more lifetimes.


2018 ◽  
Vol 7 (3.12) ◽  
pp. 1317 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav Ji Nigam

Internet of Things is the mainstay of the new era since its application becomes the future of day-to-day life. This work targets the IoT network assisted by WSN to prevent forest fire. We propose two-layer architecture of sensor network assisted by IoT enabled UAVs. The data flows in the proposed architecture in bottom-up fashion i.e., data is sensed by the nodes, which are deployed in the forest area (and sense temperature continuously). This data is transmitted to upper layer consisting of UAVs, which take appropriate action (to sprinkle water to bring temperature down to prevent fire). All the UAVs are interconnected to each other as well as to base station. The sensor nodes are clustered using two-step clustering algorithm, which takes care of the isolated nodes. The scheme has been equated to another WSN assisted IoT clustering technique. The proposed scheme outperforms the existing in terms of congestion at the UAV stations, number of alive nodes and remaining energy of the network.  


2012 ◽  
Vol 197 ◽  
pp. 649-655
Author(s):  
Jian Hua Liu ◽  
Wei Qin Tong

Internet of things applications using RFID sensors are a challenging task due to the limited capacity of batteries. Thus, energy efficient updating and maintenance have become more critical design with RFID sensor network. This paper is dedicated to combine energy harvesting and maintenance, sensor network, and resource discovery to develop a rechargeable sensor energy maintenance scheme. To deal with key sensor nodes and low energy path maintenance, the proposed approach consists of the following:(1)key point energy maintenance for RFID sensor through multi-path similarity analysis;(2)path energy maintenance for RFID sink through energy resource discovery. Use case application and simulation results show that the proposed methods reduce key sensor nodes energy maintenance time and energy maintenance path length for sensor nodes energy updating and maintenance.


Author(s):  
Zhiyao Fan ◽  
Tianhong Pan ◽  
Li Ma

In order to increase the management efficiency and decrease the maintenance costs in the traditional dust monitoring system, a novel real-time remote monitoring system using the Internet of Things and cloud server is proposed in this paper. The system includes several sensor nodes, a sink node and Cloud Server. The high-precision dust probe, temperature and humidity sensors, water flow sensors and hydrogen transmitters are integrated together into a sensor node to access the metal polished environmental information. Then, the collected information is transmitted to sink-node using the 2.4G wireless network. The sink-node uploads data to the Cloud Server through the 4G network and TCP Socket. Based on the Browser/Server (B/S) model, a remote monitoring system is developed by using Tencent Cloud Server, C# language, and SQL database. As a result, the on-site metal polishing environmental information is obtained via the App and Web page.


2017 ◽  
Vol 13 (10) ◽  
pp. 21 ◽  
Author(s):  
Xijuan Wang

<p style="margin: 1em 0px;"><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">To realize the remote monitoring and intelligent management of the home environment, intelligent home remote monitoring system is developed based on the Internet of things technology. By using RF transceiver chip and GPRS technology, a smart home system scheme for wireless networks is established. The hardware and software design of sensor nodes and GPRS wireless communication base station is completed. Sensor nodes are used to monitor the acquisition of field data. Based on GPRS technology, the wireless communication base station realizes the uploading of monitoring data. The wireless communication between the node and the base station is realized by radio frequency transceiver chip SI4432. The results show that the system reaches the aim of expected design function. Therefore, it can be concluded that the system can meet the intelligent monitoring of the home environment.</span></span></p>


2012 ◽  
Vol 468-471 ◽  
pp. 60-63
Author(s):  
Xiao Fan Wu ◽  
Jia Jun Bu ◽  
Chun Chen

Due to the rapid development of Internet of Things (IoT), kinds of sensor nodes have been introduced to the different applications. Because of the variety of MCUs, sensors and radio modules, it’s challenging to reuse the device drivers between different sensor node platforms. To address this issue, a reusable device driver framework is proposed in this paper. Comparing with existed work, our framework is flexible, efficient, and easy to learn. The flexibility is achieved by layered encapsulation, which decouples the device driver with the sensor node operating system kernel. Our framework gives the reusability at the source code level, so it’s efficient. At the end, our framework is implemented in C programming language, which is the most common tool adopted by embedded system developing. This framework has applied to SenSpire OS, a micro-kernel real-time operating system for IoT sensor nodes.


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