Development of a programmable sensor interface for wireless network nodes

2005 ◽  
Author(s):  
V. Mattoli
Keyword(s):  
Wireless Network ◽  
Sensor Interface ◽  
Network Nodes

Analysis of Existing Trust Based Routing Schemes Used in Wireless Network

2016 ◽  
Vol 10 (2) ◽  
pp. 26-40 ◽  
Author(s):  
Kajal S. Patel ◽  
Jagdish S. Shah
Keyword(s):  
Wireless Network ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Battery Life ◽  
Delayed Response ◽  
Error Message ◽  
Trust Value ◽  
Network Nodes ◽  
Routing Schemes

Wireless networks are vulnerable to many security attacks as they use wireless media and a node has to depend on unknown intermediate nodes for data transmission. Cryptographic algorithms used for wired network cannot work efficiently in wireless network, as in wireless network nodes are mobile and battery operated. Nodes may also have limited resources available. So, to detect malicious activities on node and improve stability of route while routing in mobile ad hoc network, trust-based routing is used. Communication parameters used in calculating trust value in most of existing trust based protocol (wireless network) are number of successful session or packet forwarded between two nodes, number of packet dropped or delayed, response time, battery life, mobility of node etc. This paper provides analysis of existing trust based routing by surveying current “sate of the art” work in this area. This paper also proposed a new parameter (number of route error message sent by a node) of a wireless node which can affect the network performance and can be used to calculate trust value.

scholarly journals Simulation of a vessel sensor network of ZigBee standard

2021 ◽  
Vol 2061 (1) ◽  
pp. 012075
Author(s):  
I I Buzenkov ◽  
Iu V Redkin ◽  
A A Tyufanova ◽  
E P Khaleeva
Keyword(s):  
Sensor Network ◽  
Wireless Network ◽  
Simulation Modeling ◽  
Local Network ◽  
Network Nodes ◽  
Packet Delivery ◽  
Delivery Delay ◽  
The Subject ◽  
Network Application ◽  
A Chain

Abstract The subject of the paper is a vessel sensor network designed to collect data from wireless sensors for various purposes. The peculiarity of this network application is the presence of a large number of premises, wireless communication between which is complicated. One of the possible approaches to solving this problem is to use coordinators connected by a switch into a local network, and a large number of routers that provide data relaying along the chain. Studies of the proposed vessel wireless network in the OMNeT ++ simulation modeling environment using Castalia framework are carried out in the paper. The process of modeling both the network itself and its individual components, and various modes of their operation is shown. The interaction of network nodes through intermediate routers is considered. Estimation of losses during packet delivery along a chain of routers, the time spent on processing packets in routers and delays in packet delivery to the network coordinator from the sending node is based on the compiled model. It is concluded that with the increasing complexity of the network structure (growth in the number of routers), there is a proportional rise of the packets delivery delay over the wireless network to the vessel local network. However, all transmitted packets are delivered to the addressee.

Using Spreadsheet Maps for the Placement of Low Altitude Platform (LAP) Wireless Network Nodes After Disasters

2021 ◽  
Vol 4 (1) ◽  
pp. 31-46
Author(s):  
Larry J. LeBlanc ◽  
Michael R. Bartolacci ◽  
Thomas A. Grossman
Keyword(s):  
Wireless Network ◽  
Network Connectivity ◽  
Propagation Model ◽  
Additional Contribution ◽  
Weight Restrictions ◽  
Network Nodes ◽  
Emergency Responders ◽  
Standard Models ◽  
Low Altitude ◽  
Fixed Wireless

Low altitude platform (LAP) architectures are an emerging platform for providing temporary wireless network connectivity to areas with a damaged fixed wireless network infrastructure. The authors propose a spreadsheet-based approach for practitioners to locate LAP nodes in the field. This approach does not require radio frequency propagation expertise and incorporates standard models to display the coverage areas for the placement of LAP aerial devices. The proposed tool allows the transmission range for a given aerial device to be visually optimized during deployment. The spreadsheet-based tool the authors are proposing is expressly suited for battery-powered LAP architecture devices with payload weight restrictions, such as those utilizing balloons or kites, that can be quickly deployed by emergency responders. An additional contribution of this work is the development of a hybrid propagation model for LAP device transmissions for deployments above 200 meters which is absent in the literature. This model is a linear combination of two existing models for free space radio propagation.

Optimization of wireless network node deployment in smart city based on adaptive particle swarm optimization

2020 ◽  
Vol 39 (4) ◽  
pp. 4959-4969
Author(s):  
Weiqiang Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Wireless Network ◽  
Smart City ◽  
Smart Cities ◽  
Particle Swarm ◽  
Network Node ◽  
Swarm Optimization ◽  
Network Nodes ◽  
Node Deployment ◽  
Multi Objective

In smart city wireless network infrastructure, network node deployment directly affects network service quality. This problem can be attributed to deploying a suitable ordinary AP node as a wireless terminal access node on a given geometric plane, and deploying a special node as a gateway to aggregate. Traffic from ordinary nodes is to the wired network. In this paper, Pareto multi-objective optimization strategy is introduced into the wireless sensor network node security deployment, and an improved multi-objective particle swarm coverage algorithm based on secure connection is designed. Firstly, based on the mathematical model of Pareto multi-objective optimization, the multi-target node security deployment model is established, and the security connectivity and node network coverage are taken as the objective functions, and the problems of wireless sensor network security and network coverage quality are considered. The multi-objective particle swarm optimization algorithm is improved by adaptively adjusting the inertia weight and particle velocity update. At the same time, the elite archive strategy is used to dynamically maintain the optimal solution set. The high-frequency simulation software Matlab and simulation platform data interaction are used to realize the automatic modeling, simulation analysis, parameter prediction and iterative optimization of wireless network node deployment in smart city based on adaptive particle swarm optimization. Under the premise of meeting the performance requirements of wireless network nodes in smart cities, the experimental results show that although the proposed algorithm could not achieve the accuracy of using only particle swarm optimization algorithm to optimize the parameters of wireless network nodes in smart cities, the algorithm is completed. The antenna parameter optimization process takes less time and the optimization efficiency is higher.

scholarly journals Optimization Algorithm of Control Channel Selection for Wireless Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Jian Chen ◽  
Huahui Yu ◽  
Jingyu Hua ◽  
Xiaoyan Zhang
Keyword(s):  
Wireless Network ◽  
Channel Selection ◽  
Control Channel ◽  
Network Nodes ◽  
Data Channel ◽  
Bandwidth Requirement ◽  
Simulation Results ◽  
Selection For ◽  
Limited Spectrum ◽  
Optimal Set

Control channel is used to transmit protocol or signal information between wireless network nodes and is a key component of wireless network. Compared with data information, protocol or signal information is usually much less, so the spectrum bandwidth requirement of control channel is also much less than that of data channel. In order to optimize the usage of the limited spectrum resources, this paper focuses on the issue of control channel selection. We propose a greedy algorithm which minimizes the total spectrum bandwidth of the set of control channels. Theoretical analysis proves that the proposed algorithm can achieve the optimal set of control whose sum of the spectrum bandwidth is the minimum. Simulation results also show that the proposed algorithm consumes less spectrum resources than other algorithms in the same wireless network environment.

scholarly journals On-Demand Scheduling of Command and Responses for Low-Power Multihop Wireless Networks

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 738
Author(s):  
Mingyu Park ◽  
Jeongyeup Paek
Keyword(s):  
Wireless Networks ◽  
Low Power ◽  
Wireless Network ◽  
Information Exchange ◽  
Time Synchronization ◽  
Multihop Wireless ◽  
Network Nodes ◽  
On Demand ◽  
Time Required ◽  
Low Power Wireless Networks

Many IoT applications require a mechanism to disseminate commands and collect responses over a wireless network in order to control and collect data from multiple embedded devices. However, severe collisions may occur if a large number of nodes attempt to respond simultaneously and promptly, not only among the responses, but also with the dissemination of commands. This is because low-power wireless network protocols for dissemination and collection have been designed separately. Tuning the parameters of one side of the protocol has clear trade-off between reliability and latency. To address this challenge, we propose SCoRe, an on-demand scheme for joint scheduling of command and responses on multihop low-power wireless networks to improve both reliability and latency simultaneously at runtime. SCoRe gathers the amount of time required by network nodes for dissemination and collection, and allocates relative timeslots to each node recursively over multihop on-demand when (and only when) disseminating a command. While doing so, information exchange occurs only between local neighbor nodes without a need for global routing table nor time synchronization. We implement SCoRe on a low-power embedded platform, and compare with well-known dissemination and collection schemes through both simulations and testbed experiments on 30 devices. Our evaluation results show that SCoRe can improve both latency and reliability without tuning the parameters for one metric, while the legacy schemes require careful parameter selection to match only one side of SCoRe, never both.

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