scholarly journals A Delayed Epidemic Model for Propagation of Malicious Codes in Wireless Sensor Network

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 396 ◽  
Author(s):  
Zizhen Zhang ◽  
Soumen Kundu ◽  
Ruibin Wei
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Epidemic Model ◽  
Dynamical Behavior ◽  
Sufficient Conditions ◽  
Wireless Sensor ◽  
Feasible Region ◽  
Proposed Model ◽  
Malicious Codes ◽  
Theoretical Results

In this paper, we investigate a delayed SEIQRS-V epidemic model for propagation of malicious codes in a wireless sensor network. The communication radius and distributed density of nodes is considered in the proposed model. With this model, first we find a feasible region which is invariant and where the solutions of our model are positive. To show that the system is locally asymptotically stable, a Lyapunov function is constructed. After that, sufficient conditions for local stability and existence of Hopf bifurcation are derived by analyzing the distribution of the roots of the corresponding characteristic equation. Finally, numerical simulations are presented to verify the obtained theoretical results and to analyze the effects of some parameters on the dynamical behavior of the proposed model in the paper.

A Study of Malware Propagation Dynamics in Wireless Sensor Network using Spatially Correlated Security Model

2020 ◽  
Vol 13 ◽  
Author(s):  
Satya Ranjan Biswal ◽  
Santosh Kumar Swain
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Network ◽  
Spatial Correlation ◽  
Malicious Code ◽  
Wireless Sensor ◽  
Epidemic Theory ◽  
Malware Propagation ◽  
Proposed Model ◽  
Propagation Dynamics

: Security is one of the important concern in both types of the network. The network may be wired or wireless. In case of wireless network security provisioning is more difficult in comparison to wired network. Wireless Sensor Network (WSN) is also a type of wireless network. And due to resource constraints WSN is vulnerable against malware attacks. Initially, the malware (virus, worm, malicious code, etc.) targets a single node of WSN for attack. When a node of WSN gets infected then automatically start to spread in the network. If nodes are strongly correlated the malware spreads quickly in the network. On the other hand, if nodes are weakly correlated the speed of malware spread is slow. A mathematical model is proposed for the study of malware propagation dynamics in WSN with combination of spatial correlation and epidemic theory. This model is based on epidemic theory with spatial correlation. The proposed model is Susceptible-Exposed-Infectious-Recover-Dead (SEIRD) with spatial correlation. We deduced the expression of basic reproduction number. It helps in the study of malware propagation dynamics in WSN. The stability analysis of the network has been investigated through proposed model. This model also helps in reduction of redundant information and saving of sensor nodes’ energy in WSN. The theoretical investigation verified by simulation results. A spatial correlation based epidemic model has been formulated for the study of dynamic behaviour of malware attacks in WSN.

Cross layer design with extensive virtual MIMO: FS-MUP optimization model for wireless sensor network

2020 ◽  
pp. 1-16
Author(s):  
Monali Prajapati ◽  
Dr. Jay Joshi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Input Multiple Output ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Virtual Mimo ◽  
Proposed Model ◽  
Multiple Input ◽  
Input Multiple Output

In the wireless sensor network (WSN), wireless communication is said to be the dominant power-consuming operation and it is a challenging one. Virtual Multiple-Input–Multiple-Output (V-MIMO) technology is considered to be the energy-saving method in the WSN. In this paper, a novel multihop virtual MIMO communication protocol is designed in the WSN via cross-layer design to enhance the energy efficiency, reliability, and end-to-end (ETE) and Quality of Service (QoS) provisioning. On the basis of the proposed protocol, the optimal set of parameters concerning the transmission and the overall consumed energy by each of the packets is found. Furthermore, the modeling of ETE latency and throughput of the protocol takes place with respect to the bit-error-rate (BER). A novel hybrid optimization algorithm referred as Flight Straight Moth Updated Particle Swarm Optimization (FS-MUP) is introduced to find the optimal BER that meets the QoS, ETE requirements of each link with lower power consumption. Finally, the performance of the proposed model is evaluated over the extant models in terms of Energy Consumption and BER as well.

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.

scholarly journals An Efficient Multitask Scheduling Model for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hongsheng Yin ◽  
Honggang Qi ◽  
Jingwen Xu ◽  
Xin Huang ◽  
Anping He
Keyword(s):  
Wireless Sensor Network ◽  
Data Processing ◽  
Sensor Network ◽  
Queuing Theory ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Queuing Model ◽  
Average Delay ◽  
Data Packets ◽  
Proposed Model

The sensor nodes of multitask wireless network are constrained in performance-driven computation. Theoretical studies on the data processing model of wireless sensor nodes suggest satisfying the requirements of high qualities of service (QoS) of multiple application networks, thus improving the efficiency of network. In this paper, we present the priority based data processing model for multitask sensor nodes in the architecture of multitask wireless sensor network. The proposed model is deduced with the M/M/1 queuing model based on the queuing theory where the average delay of data packets passing by sensor nodes is estimated. The model is validated with the real data from the Huoerxinhe Coal Mine. By applying the proposed priority based data processing model in the multitask wireless sensor network, the average delay of data packets in a sensor nodes is reduced nearly to 50%. The simulation results show that the proposed model can improve the throughput of network efficiently.

scholarly journals Dynamical Behavior of a Stochastic SIRC Model for Influenza A

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 745 ◽  
Author(s):  
Tongqian Zhang ◽  
Tingting Ding ◽  
Ning Gao ◽  
Yi Song
Keyword(s):  
Lyapunov Function ◽  
Numerical Simulations ◽  
Positive Solution ◽  
Epidemic Model ◽  
Influenza A ◽  
Dynamical Behavior ◽  
Sufficient Conditions ◽  
Global Positive Solution ◽  
Theoretical Results ◽  
Stochastic Lyapunov Function

In this paper, a stochastic SIRC epidemic model for Influenza A is proposed and investigated. First, we prove that the system exists a unique global positive solution. Second, the extinction of the disease is explored and the sufficient conditions for extinction of the disease are derived. And then the existence of a unique ergodic stationary distribution of the positive solutions for the system is discussed by constructing stochastic Lyapunov function. Furthermore, numerical simulations are employed to illustrate the theoretical results. Finally, we give some further discussions about the system.

scholarly journals Bifurcation Analysis for an SEIRS-V Model with Delays on the Transmission of Worms in a Wireless Sensor Network

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Zizhen Zhang ◽  
Yougang Wang
Keyword(s):  
Wireless Sensor Network ◽  
Hopf Bifurcation ◽  
Sensor Network ◽  
Center Manifold ◽  
Wireless Sensor ◽  
Bifurcation Parameter ◽  
Normal Form Theory ◽  
Center Manifold Theorem ◽  
Form Theory ◽  
Theoretical Results

Hopf bifurcation for an SEIRS-V model with delays on the transmission of worms in a wireless sensor network is investigated. We focus on existence of the Hopf bifurcation by regarding the diverse delay as a bifurcation parameter. The results show that propagation of worms in the wireless sensor network can be controlled when the delay is suitably small under some certain conditions. Then, we study properties of the Hopf bifurcation by using the normal form theory and center manifold theorem. Finally, we give a numerical example to support the theoretical results.

scholarly journals An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Belal Al-Fuhaidi ◽  
Abdulqader M. Mohsen ◽  
Abdulkhabeer Ghazi ◽  
Walid M. Yousef
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Coverage Ratio ◽  
Proposed Model ◽  
Heterogeneous Wireless Sensor Network

Due to the increase of Wireless Sensor Network (WSN) technologies demand, the optimal sensor node deployment is considered as one of the most important factors that directly affect the network coverage. Most researches in WSNs that solved the problem of coverage in homogeneous and heterogeneous cases are suffering from many drawbacks such as consumed energy and high cost. In this paper, we propose an efficient deployment model based on probabilistic sensing model (PSM) and harmony search algorithm (HSA) to achieve the balance between the network coverage performance and the network cost in a heterogeneous wireless sensor network (HEWSN). The HSA is used for deployment optimization of HEWSN nodes which makes a balance between the coverage and financial cost. The PSM is used to solve the overlapping problem among the sensors. The performance of the proposed model is analyzed in terms of coverage ratio and cost evaluations. The simulation results showed the capability of the proposed heterogeneous deployment model to achieve maximum coverage and a minimum number of sensors compared to homogeneous deployment. Furthermore, a comparative study with a meta-heuristic genetic-based algorithm in HEWSN has also been conducted, and its results confirm the superiority of the proposed model.

scholarly journals Pollination Inspired Clustering Model for Wireless Sensor Network Optimization

2021 ◽  
Vol 3 (3) ◽  
pp. 196-207
Author(s):  
Subarna Shakya
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Fault Tolerance ◽  
Sensor Network ◽  
Network Lifetime ◽  
Data Transmission ◽  
Management Strategy ◽  
Wireless Sensor ◽  
Clustering Model ◽  
Proposed Model

Remote and dangerous fields that are expensive, complex, and unreachable to reach human insights are examined with ease using the Wireless Sensor Network (WSN) applications. Due to the use of non-renewable sources of energy, challenges with respect to the network lifetime, fault tolerance and energy consumption are faced by the self-managed networks. An efficient fault tolerance technique has been provided in this paper as an effective management strategy. Using the network and communication nodes, revitalization and fault recognition techniques are used for handling diverse levels of faults in this framework. At the network nodes, the fault tolerance capability is increased by the proposed protocol model and management strategy. This enhances the corresponding data transmission in the network. When compared to the conventional techniques, the proposed model increases the network lifetime by five times. It is observed from the validation results that, with a 10% increase in the network lifetime, there is a 2% decrease in the fault tolerance proficiency of the network. The network lifetime and data transmission rate are improved while the network energy consumption is reduced significantly. The MATLAB environment is used for simulation purpose. In terms of energy consumption, network lifetime and fault tolerance, the proposed model offers optimal results.

Privacy Preserving Data Gathering in Wireless Sensor Network

2012 ◽  
pp. 239-253 ◽  
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.

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