scholarly journals A Self-Adaptive Wireless Sensor Network Coverage Method for Intrusion Tolerance Based on Trust Value

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zuo Chen ◽  
Xue Li ◽  
Bing Yang ◽  
Qian Zhang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Secure Communication ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Intrusion Tolerance ◽  
Trust Value ◽  
Coverage Optimization ◽  
Simulation Results ◽  
Value Model

The sensor is quite easily attacked or invaded during the process of the node coverage optimization. It is a great challenge to make sure that the wireless sensor network could still carry out a secure communication and reliable coverage under the condition of being attacked. Therefore, this paper proposes a network coverage method for intrusion tolerance based on trust value of nodes by combining the trust value model with the reliable coverage optimization. It first estimates trust value of nodes through which to regulate the perception radius and decision-making radius. Furthermore, this algorithm also combines the classical methods of wireless network coverage, such as GSO and PSO, to realize the networks coverage of invasive tolerant sensor. After comparing with the conventional single cover mechanism, it can improve the security and coverage rate of network under the condition of invasion. The simulation results verify the effectiveness of the algorithm.

scholarly journals Coverage Optimization Algorithm of Wireless Sensor Network Based on Mobile Nodes

2016 ◽  
Vol 12 (08) ◽  
pp. 45 ◽  
Author(s):  
Li Zhu ◽  
Chunxiao Fan ◽  
Huarui Wu ◽  
Zhigang Wen
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Optimization Algorithm ◽  
Quantitative Relationship ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Mobile Nodes ◽  
Coverage Optimization ◽  
Blind Zone

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; -ms-layout-grid-mode: line; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">To reduce the blind zone in network coverage, we propose a coverage optimization algorithm of wireless sensor network based on mobile nodes. This algorithm calculates the irregularity of blind zone in network coverage and obtains the minimum approximate numerical solution by utilizing the quantitative relationship between energy consumption of related nodes and the position of the mobile nodes. After determining the optimal relative position of the mobile nodes, the problem of blind zone between the static nodes is addressed. Simulation result shows that the proposed algorithm has high dynamic adaptability and can address the problem of blind zone maximally. Besides increasing the network coverage, the algorithm also reduces the network energy consumption, optimizes network coverage control and exhibits high convergence. </span>

scholarly journals Wireless Sensor Network Coverage Optimization Based on Fruit Fly Algorithm

2018 ◽  
Vol 14 (06) ◽  
pp. 58 ◽  
Author(s):  
Ren Song ◽  
Zhichao Xu ◽  
Yang Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Fruit Fly ◽  
Effective Radius ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fruit Fly Optimization Algorithm ◽  
Network Coverage ◽  
Coverage Optimization ◽  
Improved Algorithm

<p class="0abstract"><span lang="EN-US">To solve the defect of traditional node deployment strategy, the improved <a name="_Hlk502130691"></a>fruit fly algorithm was combined with wireless sensor network. The optimization of network coverage was implemented. </span><span lang="EN-US">Based on a new type of intelligent algorithm, the change step of fruit fly optimization algorithm (CSFOA)</span><span lang="EN-US">was proposed. At the same time, the mathematical modeling of two network models was carried out respectively. The grid coverage model was used. The network coverage and redundancy were transformed into corresponding mathematical variables by means of grid partition.</span><span lang="EN-US">Among them, the maximum effective radius of sensor nodes was fixed in mobile node wireless sensor network. The location of nodes was randomly cast. The location of sensor nodes was placed in fixed position nodes. The effective radius of nodes can be changed dynamically.</span><span lang="EN-US">Finally, combined with the corresponding network model, the improved algorithm was applied to wireless sensor network.</span><span lang="EN-US">The combination of the optimal solution of the node position and the perceptual radius was found through the algorithm. The maximum network coverage was achieved.</span><span lang="EN-US">The two models were simulated and verified. The results showed that the improved algorithm was effective and superior to the coverage optimization of wireless sensor networks.</span></p>

Empowered AODV Protocol in Wireless Sensor Network using Three Variable RSA Cryptosystem

2020 ◽  
Vol 13 (4) ◽  
pp. 718-724
Author(s):  
Amit K. Agarwal ◽  
Munesh Chandra ◽  
S.S. Sarangdevot
Keyword(s):  
Black Hole ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Secure Communication ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Rsa Cryptosystem ◽  
Simulation Results ◽  
Aodv Routing Protocol

Background: The Wireless Sensor Network (WSN) is a type of networks which primarily designed for the purpose of monitoring in remote areas. It consists of communicating nodes (called sensor's) which communicate each other to share their data and passing the information to the central node. In many applications like defence requires the secure communication of information. However, due to the numerous characteristics of WSN such as open shared communication channel, limited memory, and processing power of sensors, etc. these networks are vulnerable to various attacks such as black hole, gray hole, etc. Objective: The objective of the paper is to secure the AODV routing protocol in WSN using cryptography techniques. Methods: In this paper, the Ad hoc On-demand Distance Vector (AODV) routing protocol has been chosen for information routing because of their lightweight processing capability. To provide secure communication in WSN, the AODV routing protocol is secured by utilizing the RSA key generation algorithm. Here, RSA with three variables (three prime numbers) is employed instead of two variables. Results: The effectiveness of the proposed approach in handling black hole attack is being verified through the simulation results obtained from the experiments conducted using Network Simulator tool (NS2). The three popular performance metrics namely Average End-to-End Delay, Packet Delivery Ratio, and Average Throughput are used for evaluation purpose. These results are observed under different pose time and varying number of malicious nodes. Conclusion: In this paper, a new three variable RSA cryptosystem-based security model is proposed to protect the communication against the Black Hole (BH) attack in wireless sensor networks. The use of three variables instead of two variables allows our model to provide more security as compared to other methods. Simulation results obtained from the experiments carried out using NS2 tool evident the performance of the proposed model over original AODV and other previous models.

scholarly journals Wireless sensor network coverage optimization based on whale group algorithm

2018 ◽  
Vol 15 (3) ◽  
pp. 569-583 ◽  
Author(s):  
Lei Wang ◽  
Weihua Wu ◽  
Junyan Qi ◽  
Zongpu Jia
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Performance ◽  
Mathematic Model ◽  
Initial Distribution ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Coverage Optimization

For all of types of applications in wireless sensor networks (WSNs), coverage is a fundamental and hot topic research issue. To monitor the interest field and obtain the valid data, the paper proposes a wireless sensor network coverage optimization model based on improved whale algorithm. The mathematic model of node coverage in wireless sensor networks is developed to achieve full coverage for the interest area. For the model, the idea of reverse learning is introduced into the original whale swarm optimization algorithm to optimize the initial distribution of the population. This method enhances the node search capability and speeds up the global search. The experiment shows that this algorithm can effectively improve the coverage of nodes in wireless sensor networks and optimize the network performance.

scholarly journals Coverage Optimization Strategy for WSN based on Energy-aware

2016 ◽  
Vol 11 (6) ◽  
pp. 877 ◽  
Author(s):  
Li Zhu ◽  
Chunxiao Fan ◽  
Zhigang Wen ◽  
Huarun Wu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Path Loss ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Network Coverage ◽  
Energy Aware ◽  
Coverage Optimization

In order to optimize the wireless sensor network coverage, this paper designs a coverage optimization strategy for wireless sensor network (EACS) based on energy-aware. Under the assumption that the geographic positions of sensor nodes are available, the proposed strategy consists of energy-aware and network coverage adjustment. It is restricted to conditions such as path loss, residual capacity and monitored area and according to awareness ability of sensors, it would adjust the monitored area, repair network hole and kick out the redundant coverage. The purpose is to balance the energy distribution of working nodes, reduce the number of “dead” nodes and balance network energy consumption. As a result, the network lifetime is expanded. Simulation results show that: EACS effectively reduces the number of working nodes, improves network coverage, lowers network energy consumption while ensuring the wireless sensor network coverage and connectivity, so as to balance network energy consumption.

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