scholarly journals Wireless Sensor Network in Agriculture: Model of Cyber Security

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6747
Author(s):  
Radomir Prodanović ◽  
Dejan Rančić ◽  
Ivan Vulić ◽  
Nenad Zorić ◽  
Dušan Bogićević ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Cyber Security ◽  
Data Security ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Security Model ◽  
Proposed Model ◽  
Save Energy ◽  
Secured Data ◽  
The Cost

Nowadays, wireless sensor networks (WSN) are widely used in agriculture monitoring to improve the quality and productivity of farming. In this application, sensors gather different types of data (i.e., humidity, carbon dioxide level, and temperature) in real-time scenarios. Thus, data gathering, transmission, and rapid response to new circumstances require a secured data mechanism to avoid malicious adversaries. Therefore, this paper focuses on data security from the data origin source to the end-user, and proposes a general data security model that is independent of the network topology and structure, and can be widely used in the agriculture monitoring application. The developed model considers practical aspects, the architecture of the sensor node, as well as the necessity to save energy while ensuring data security, and optimize the model through the application of organizational and technical measures. The model evaluation is conducted through simulation in terms of energy consumption. The result shows that the proposed model ensures good data security at the cost of a slight increase in energy consumption at receiver and sender nodes, and energy consumption per bit, up to 2%, 7%, and 1.3%, respectively, due to overhead added for authentication in the network.

Secured data aggregation in wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Sathya D. ◽  
Ganesh Kumar P.
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Computation Time ◽  
Wireless Sensor ◽  
Content Type ◽  
Homomorphic Cryptosystem ◽  
Secured Data ◽  
Time And Energy

PurposeThis study aims to provide a secured data aggregation with reduced energy consumption in WSN. Data aggregation is the process of reducing communication overhead in wireless sensor networks (WSNs). Presently, securing data aggregation is an important research issue in WSNs due to two facts: sensor nodes deployed in the sensitive and open environment are easily targeted by adversaries, and the leakage of aggregated data causes damage in the networks, and these data cannot be retrieved in a short span of time. Most of the traditional cryptographic algorithms provide security for data aggregation, but they do not reduce energy consumption.Design/methodology/approachNowadays, the homomorphic cryptosystem is used widely to provide security with low energy consumption, as the aggregation is performed on the ciphertext without decryption at the cluster head. In the present paper, the Paillier additive homomorphic cryptosystem and Bonehet al.’s aggregate signature method are used to encrypt and to verify aggregate data at the base station.FindingsThe combination of the two algorithms reduces computation time and energy consumption when compared with the state-of-the-art techniques.Practical implicationsThe secured data aggregation is useful in health-related applications, military applications, etc.Originality/valueThe new combination of encryption and signature methods provides confidentiality and integrity. In addition, it consumes less computation time and energy consumption than existing methods.

scholarly journals Reducing the Energy Budget in WSN Using Time Series Models

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Felicia Engmann ◽  
Ferdinand Apietu Katsriku ◽  
Jamal-Deen Abdulai ◽  
Kofi Sarpong Adu-Manu
Keyword(s):  
Data Transmission ◽  
Energy Savings ◽  
Data Driven ◽  
Wireless Sensor ◽  
Time Series Models ◽  
Duty Cycling ◽  
Data Driven Approach ◽  
Save Energy ◽  
The Cost ◽  
Prediction Approach

Energy conservation is critical in the design of wireless sensor networks since it determines its lifetime. Reducing the frequency of transmission is one way of reducing the cost, but it must not tamper with the reliability of the data received at the sink. In this paper, duty cycling and data-driven approaches have been used together to influence the prediction approach used in reducing data transmission. While duty cycling ensures nodes that are inactive for longer periods to save energy, the data-driven approach ensures features of the data that are used in predicting the data that the network needs during such inactive periods. Using the grey series model, a modified rolling GM(1,1) is proposed to improve the prediction accuracy of the model. Simulations suggest a 150% energy savings while not compromising on the reliability of the data received.

Two-Level Data Collection for an Energy-Efficient Solution in Wireless Sensor Networks

2016 ◽  
Vol 7 (4) ◽  
pp. 50-67 ◽  
Author(s):  
Besma Benaziz ◽  
Okba Kazar ◽  
Laid Kahloul ◽  
Ilham Kitouni ◽  
Samir Bourekkache
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Timed Automata ◽  
High Energy ◽  
Wireless Sensor ◽  
Data Collection Strategy ◽  
Level Data ◽  
Consumption Data ◽  
The Cost

Density in sensor networks often causes data redundancy, which is often the origin of high energy consumption. Data collection techniques are proposed to avoid retransmission of the same data by several sensors. In this paper, the authors propose a new data collection strategy based on static agents and clustering nodes in wireless sensor network (WSN) for an efficient energy consumption called: Two-Level Data Collection Strategy (TLDC). It consists in two-level hierarchy of nodes grouping. The technique is based on an experience building to perform a reorganization of the groups. Cooperation between agents can be used to reduce the communication cost significantly, by managing the data collection smartly. In order to validate the proposed scheme, the authors use the timed automata (TA) model and UPPAAL engine to validate the proposed strategy; the results after and before reorganization are compared. They establish that the proposed approach reduces the cost of communication in the group and thus minimizes the consumed energy.

scholarly journals Novel Energy-Efficient Data Gathering Scheme Exploiting Spatial-Temporal Correlation for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ying Zhou ◽  
Lihua Yang ◽  
Longxiang Yang ◽  
Meng Ni
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Data Gathering ◽  
Temporal Correlation ◽  
Wireless Sensor ◽  
Selection Scheme ◽  
Efficient Data ◽  
Transmission Energy Consumption

A novel energy-efficient data gathering scheme that exploits spatial-temporal correlation is proposed for clustered wireless sensor networks in this paper. In the proposed method, dual prediction is used in the intracluster transmission to reduce the temporal redundancy, and hybrid compressed sensing is employed in the intercluster transmission to reduce the spatial redundancy. Moreover, an error threshold selection scheme is presented for the prediction model by optimizing the relationship between the energy consumption and the recovery accuracy, which makes the proposed method well suitable for different application environments. In addition, the transmission energy consumption is derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the existing schemes, and the sink can recover measurements with reasonable accuracy by using the proposed method.

An Efficient Sleeping Scheduling for Save Energy Consumption in Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 2288-2293
Author(s):  
Shu Guang Jia ◽  
Li Peng Lu ◽  
Ling Dong Su ◽  
Gui Lan Xing ◽  
Ming Yue Zhai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Round Robin ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Active Sensors ◽  
Save Energy ◽  
Battery Energy

Smart grid has become one hot topic at home and abroad in recent years. Wireless Sensor Networks (WSNs) has applied to lots of fields of smart grid, such as monitoring and controlling. We should ensure that there are enough active sensors to satisfy the service request. But, the sensor nodes have limited battery energy, so, how to reduce energy consumption in WSNs is a key challenging. Based on this problem, we propose a sleeping scheduling model. In this model, firstly, the sensor nodes round robin is used to let as little as possible active nodes while all the targets in the power grid are monitored; Secondly, for removing the redundant active nodes, the sensor nodes round robin is further optimized. Simulation result indicates that this sleep mechanism can save the energy consumption of every sensor node.

Lifetime Maximization Routing Based on Genetic Algorithm for Wireless Sensor Networks

2011 ◽  
Vol 230-232 ◽  
pp. 283-287
Author(s):  
You Rong Chen ◽  
Tiao Juan Ren ◽  
Zhang Quan Wang ◽  
Yi Feng Ping
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Gathering ◽  
Transmission Probability ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Lifetime Maximization

To prolong network lifetime, lifetime maximization routing based on genetic algorithm (GALMR) for wireless sensor networks is proposed. Energy consumption model and node transmission probability are used to calculate the total energy consumption of nodes in a data gathering cycle. Then, lifetime maximization routing is formulated as maximization optimization problem. The select, crosss, and mutation operations in genetic algorithm are used to find the optimal network lifetime and node transmission probability. Simulation results show that GALMR algorithm are convergence and can prolong network lifetime. Under certain conditions, GALMR outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.

scholarly journals Energy-efficient chain-based data gathering applied to communicating concrete

2020 ◽  
Vol 16 (8) ◽  
pp. 155014772093902
Author(s):  
Hang Wan ◽  
Michael David ◽  
William Derigent
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Hot Spot ◽  
Data Gathering ◽  
Information Modeling ◽  
Wireless Sensor ◽  
Energy Models

Wireless Sensor Networks are very convenient to monitor structures or even materials, as in McBIM project (Materials communicating with the Building Information Modeling). This project aims to develop the concept of “communicating concretes,” which are concrete elements embedding wireless sensor networks, for applications dedicated to Structure Health Monitoring in the construction industry. Due to applicative constraints, the topology of the wireless sensor network follows a chain-based structure. Node batteries cannot be replaced or easily recharged, it is crucial to evaluate the energy consumed by each node during the monitoring process. This area has been extensively studied leading to different energy models to evaluate energy consumption for chain-based structures. However, no simple, practical, and analytical network energy models have yet been proposed. Energy evaluation models of periodic data collection for chain-based structures are proposed. These models are compared and evaluated with an Arduino XBee–based platform. Experimental results show the mean prediction error of our models is 5%. Realizing aggregation at nodes significantly reduces energy consumption and avoids hot-spot problem with homogeneous consumptions along the chain. Models give an approximate lifetime of the wireless sensor network and communicating concretes services. They can also be used online by nodes for a self-assessment of their energy consumptions.

Privacy Preserving Data Gathering in Wireless Sensor Network

2011 ◽  
pp. 237-251
Author(s):  
Md. Golam Kaosar ◽  
Xun Yi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Perturbation Technique ◽  
Data Gathering ◽  
Real Life ◽  
Privacy Preserving ◽  
Wireless Sensor ◽  
Individual Data ◽  
Data Collection Process ◽  
Proposed Model

Sensor devices provide sophisticated services in collecting data in various applications, some of which are privacy sensitive; others are ordinary. This chapter emphasizes the necessity and some mechanisms of privacy preserving data gathering techniques in wireless sensor network communication. It also introduces a new solution for privacy preserving data gathering in wireless sensor networks. By using perturbation technique in a semi-trusted server model, this new solution is capable of reducing a significant amount of computation in data collection process. In this technique, data of a sensor is perturbed into two components which are unified into two semi-trusted servers. Servers are assumed not to collude each other. Neither of them have possession of any individual data. Therefore, they cannot discover individual data. There are many real life applications in which the proposed model can be applied. Moreover, this chapter also shows a technique to collect grouped data from distributed sources keeping the privacy preserved. Security proofs show that any of the servers or any individual sensor neither can discover any individual data nor can associate any data to an individual sensor. Thus, the privacy of individual data is preserved.

A Robust Lightweight Data Security Model for Cloud Data Access and Storage

2021 ◽  
Vol 16 (3) ◽  
pp. 39-53
Author(s):  
Pajany M. ◽  
Zayaraz G.
Keyword(s):  
Data Storage ◽  
Data Security ◽  
Data Access ◽  
Data Retrieval ◽  
Security Model ◽  
Cloud Data ◽  
Data Merging ◽  
Major Benefit ◽  
Proposed Model ◽  
And Storage

In this paper, an efficient lightweight cloud-based data security model (LCDS) is proposed for building a secured cloud database with the assistance of intelligent rules, data storage, information collection, and security techniques. The major intention of this study is to introduce a new encryption algorithm to secure intellectual data, proposing a new data aggregation algorithm for effective data storage and improved security, developing an intelligent data merging algorithm for accessing encrypted and original datasets. The major benefit of the proposed model is that it is fast in the encryption process at the time of data storage and reduced decryption time during data retrieval. In this work, the authors proposed an enhanced version of the hybrid crypto algorithm (HCA) for cloud data access and storage. The proposed system provides secured storage for storing data within the cloud.

Two-Level Data Collection for an Energy-Efficient Solution in Wireless Sensor Networks

2020 ◽  
pp. 194-213
Author(s):  
Besma Benaziz ◽  
Okba Kazar ◽  
Laid Kahloul ◽  
Ilham Kitouni ◽  
Samir Bourekkache
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Timed Automata ◽  
High Energy ◽  
Wireless Sensor ◽  
Data Collection Strategy ◽  
Level Data ◽  
Consumption Data ◽  
The Cost

Density in sensor networks often causes data redundancy, which is often the origin of high energy consumption. Data collection techniques are proposed to avoid retransmission of the same data by several sensors. In this paper, the authors propose a new data collection strategy based on static agents and clustering nodes in wireless sensor network (WSN) for an efficient energy consumption called: Two-Level Data Collection Strategy (TLDC). It consists in two-level hierarchy of nodes grouping. The technique is based on an experience building to perform a reorganization of the groups. Cooperation between agents can be used to reduce the communication cost significantly, by managing the data collection smartly. In order to validate the proposed scheme, the authors use the timed automata (TA) model and UPPAAL engine to validate the proposed strategy; the results after and before reorganization are compared. They establish that the proposed approach reduces the cost of communication in the group and thus minimizes the consumed energy.

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