Actuator Task Assignment Based on Auction Method in Wireless Sensor and Actuator Networks

2013 ◽  
Vol 373-375 ◽  
pp. 306-310 ◽  
Author(s):  
Ping Deng ◽  
Ke Li Zhang
Keyword(s):  
Wireless Sensor Network ◽  
Utility Function ◽  
Sensor Network ◽  
Assignment Problem ◽  
Task Assignment ◽  
Wireless Sensor ◽  
Proper Action ◽  
New Challenges ◽  
Simulation Results ◽  
Task Assignment Problem

A typical Wireless Sensor Network (WSN) only performs the action of sensing the environment, the needs of smart interaction with the environment have led to the emergence of Wireless Sensor and Actuator Network (WSAN). With the presence of actuators, WSAN is heterogeneous, which brings about new challenges that need to be addressed. In this paper, the task assignment of actuators in overlapping area is studied. Firstly, a new utility function is defined, which is the standard to choose the proper action actuators in overlapping area. Then, based on the new utility function, a distributed solution called localized auction method to solve task assignment problem in overlapping area is proposed. Simulation results demonstrate that the proposed auction method can assign tasks to the unique actuator and meet the action completion bound.

Modelling a Deep Learning-Based Wireless Sensor Network Task Assignment Algorithm

2020 ◽  
pp. 84-109
Author(s):  
Titus Issac ◽  
Salaja Silas ◽  
Elijah Blessing Rajsingh
Keyword(s):  
Deep Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Task Assignment ◽  
Human Interaction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Feed Forward Neural Network ◽  
Functional Capabilities ◽  
Assignment Algorithm

The 21st century is witnessing the emergence of a wide variety of wireless sensor network (WSN) applications ranging from simple environmental monitoring to complex satellite monitoring applications. The advent of complex WSN applications has led to a massive transition in the development, functioning, and capabilities of wireless sensor nodes. The contemporary nodes have multi-functional capabilities enabling the heterogeneous WSN applications. The future of WSN task assignment envisions WSN to be heterogeneous network with minimal human interaction. This led to the investigative model of a deep learning-based task assignment algorithm. The algorithm employs a multilayer feed forward neural network (MLFFNN) trained by particle swarm optimization (PSO) for solving task assignment problem in a dynamic centralized heterogeneous WSN. The analyses include the study of hidden layers and effectiveness of the task assignment algorithms. The chapter would be highly beneficial to a wide range of audiences employing the machine and deep learning in WSN.

scholarly journals Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy

2019 ◽  
Vol 8 (1) ◽  
pp. 57 ◽  
Author(s):  
Shaymaa Al Hayali ◽  
Osman Ucan ◽  
Javad Rahebi ◽  
Oguz Bayat
Keyword(s):  
Genetic Algorithms ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Development ◽  
Wireless Sensor ◽  
Optimal Routing ◽  
Fuzzy Function ◽  
Renewable Energy Development ◽  
Multi Agent ◽  
Simulation Results

In this paper an individual - suitable function calculating design for WSNs is conferred. A multi-agent- located construction for WSNs is planned and an analytical type of the active combination is built for the function appropriation difficulty. The purpose of this study is to identify the threats identified by clustering genetic algorithms in clustering networks, which will prolong network lifetime. In addition, optimal routing is done using the fuzzy function. Simulation results show that the simulated genetic algorithm improves diagnostic speed and improves energy consumption.©2019. CBIORE-IJRED. All rights reservedArticle History: Received May 16th 2018; Received in revised form Octiber 6th 2018; Accepted Jnauary 6th 2019; Available onlineHow to Cite This Article: Al-Hayali, S., Ucan, O., Rahebi, J. and Bayat, O. (2019) Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy. International Journal of Renewable Energy Development, 8(1), 57-64.https://doi.org/10.14710/ijred.8.1.57-64

scholarly journals A Data Transmission Algorithm Based on Dynamic Grid Division for Coal Goaf Temperature Monitoring

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Qingsong Hu ◽  
Lixin Wu ◽  
Fei Geng ◽  
Can Cao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Field Data ◽  
Temperature Monitoring ◽  
Wireless Sensor ◽  
Dynamic Features ◽  
Transmission Scheme ◽  
Simulation Results ◽  
Grid Division

WSN (wireless sensor network) is a perfect tool of temperature monitoring in coal goaf. Based on the three-zone theory of goaf, the GtmWSN model is proposed, and its dynamic features are analyzed. Accordingly, a data transmission scheme, named DTDGD, is worked out. Firstly, sink nodes conduct dynamic grid division on the GtmWSN according to virtual semicircle. Secondly, each node will confirm to which grid it belongs based on grid number. Finally, data will be delivered to sink nodes with greedy forward and hole avoidance. Simulation results and field data showed that the GtmWSN and DTDGD satisfied the lifetime need of goaf temperature monitoring.

scholarly journals Multi-UAV Reconnaissance Task Assignment for Heterogeneous Targets Based on Modified Symbiotic Organisms Search Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 734 ◽  
Author(s):  
Hao-Xiang Chen ◽  
Ying Nan ◽  
Yi Yang
Keyword(s):  
Assignment Problem ◽  
Time Window ◽  
Search Algorithm ◽  
Task Assignment ◽  
Multiple Time ◽  
Nsga Ii ◽  
Symbiotic Organisms Search ◽  
Simulation Results ◽  
Symbiotic Organisms ◽  
Task Assignment Problem

This paper considers a reconnaissance task assignment problem for multiple unmanned aerial vehicles (UAVs) with different sensor capacities. A modified Multi-Objective Symbiotic Organisms Search algorithm (MOSOS) is adopted to optimize UAVs’ task sequence. A time-window based task model is built for heterogeneous targets. Then, the basic task assignment problem is formulated as a Multiple Time-Window based Dubins Travelling Salesmen Problem (MTWDTSP). Double-chain encoding rules and several criteria are established for the task assignment problem under logical and physical constraints. Pareto dominance determination and global adaptive scaling factors is introduced to improve the performance of original MOSOS. Numerical simulation and Monte-Carlo simulation results for the task assignment problem are also presented in this paper, whereas comparisons with non-dominated sorting genetic algorithm (NSGA-II) and original MOSOS are made to verify the superiority of the proposed method. The simulation results demonstrate that modified SOS outperforms the original MOSOS and NSGA-II in terms of optimality and efficiency of the assignment results in MTWDTSP.

Maximizing the Lifetime of Sliding Wireless Sensors in Barrier Coverage

2012 ◽  
Vol 157-158 ◽  
pp. 503-506 ◽  
Author(s):  
Tao Yang ◽  
Pan Guo Fan ◽  
De Jun Mu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Wireless Sensors ◽  
Specific Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Barrier Coverage ◽  
Coverage Ratio ◽  
Simulation Results

Wireless sensor network is always deployed in specific area for intrusion detection and environmental monitoring. The sensor nodes suffer mostly from their limited battery capacity.Maximizing the lifetime of the entire networks is mainly necessary considered in the design. Sliding the sensors in different barriers under the optimal barrier construction is a good solution for both maximizing network lifetime and providing predetermined coverage ratio. The simulation results demonstrate that the scheme can effectively reduce the energy consumption of the wireless sensor network and increase the network lifetime.

A DEPLOYMENT ALGORITHM FOR UNDERWATER SENSOR NETWORKS IN OCEAN ENVIRONMENT

2011 ◽  
Vol 20 (06) ◽  
pp. 1051-1066 ◽  
Author(s):  
LINFENG LIU
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Wireless Sensor ◽  
Underwater Sensor Networks ◽  
Cluster Shape ◽  
Simulation Results ◽  
Ocean Environment ◽  
Near Future

Underwater sensor networks will find many oceanic applications in near future, and the deployment problem in 3D sensor networks has not been paid enough attention at present. In order to maximize the network lifetime, a deployment algorithm (UDA) for underwater sensor networks in ocean environment is proposed. UDA can determine and select the best cluster shape, then partition the space into layers and clusters while maintaining full coverage and full connectivity. In addition, nodes closer to sinks are possible to bear a heavier data-relaying mission. UDA sets different node deployment densities at different layers in response to the potential relay discrepancy. The simulation results suggest UDA can choose the proper cluster shape to get the maximum underwater wireless sensor network lifetime approximately.

The Analysis of Probability Detection CSMA Protocol for Wireless Sensor Network Based on the Request-Response Mechanism

2014 ◽  
Vol 543-547 ◽  
pp. 3511-3515
Author(s):  
Hong Wei Ding ◽  
Ying Ying Guo ◽  
Jia Guo ◽  
Yuan Long Chen ◽  
Yi Fan Zhao
Keyword(s):  
Mathematical Model ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Mac Protocol ◽  
Mathematical Expression ◽  
Wireless Sensor ◽  
Response Mechanism ◽  
Transmission Quality ◽  
Simulation Results ◽  
Mathematical Derivation

This paper presents a new MAC protocol the probability detection CSMA protocol for wireless sensor network based on the request-response mechanism. Builds the corresponding mathematical model using the average cycle method, and get the mathematical expression of systemic throughput through a rigorous mathematical derivation and makes the computer simulations. Simulation results show the correctness of the theoretical analysis and the effectiveness of the protocol; meanwhile, the protocol this paper presents increases the reliability and stability of the system through increasing RTS-CTS request-response mechanism and ACK handshake signal, thereby improving the systems transmission quality.

scholarly journals Routing of emergency data in a wireless sensor network for mining applications

2021 ◽  
Author(s):  
Mandana Jafarian
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Residual Energy ◽  
Mesh Network ◽  
Wireless Sensor ◽  
End To End Delay ◽  
Simulation Results ◽  
End To End

Emergency situations in mines result in loss of precious human lives. In this thesis we discussed architecture of a Wireless Sensor Network (WSN) that can be deployed in mines, which takes care of severe geographical and environmental constraints found inside mines. The proposed architecture is a two-level hierarchy of small sized WSNs that employs a wireless Mesh network as the backbone connecting small sized WSNs scattered inside mines. We proposed a routing protocol for that WSN that is optimized for both emergency and non-emergency data routing. Since our main goal is to provide safety in the mining environment, the main consideration of the routing protocol is to provide reliability and reduce the end-to-end delay for vital emergency traffic while optimizing for network longevity for non-emergency traffic. We present a new cost-based routing protocol called MDML, which provides Minimum Delay and Maximum Lifetime routing for such networks. The proposed MDML routing defines separate cost metrics for emergency and non-emergency traffic. It finds the least-cost path for the reliable delay-constrained emergency traffic with regards to link error rate but also gives secondary consideration to nodes' residual energy. It is an energy efficient routing scheme for non-emergency or regular data traffic routing that maximizes the network lifetime. However, for emergency traffic energy efficiency is compromised to achieving minimal delay. Regular traffic is generated through periodic monitoring and is delay-insensitive. For regular traffic delivery, a shortest path routinig algorithm is employed which uses link costs that reflect both the communication energy consumption rates and the residual energy levels at the two end nodes. Simulation results show that using the proposed emergency routes reduces the end-to-end delay for emergency traffic. The effect of protocol update cycle on increasing the network lifetime is verified true simulation. MDML is also compared with a simulated non-MDML approach to compare the lifetime and delay performance. Simulation results have demonstrated the effectiveness of our approach.

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