scholarly journals Performance Analysis of IoT-Based Health and Environment WSN Deployment

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5923
Author(s):  
Maryam Shakeri ◽  
Abolghasem Sadeghi-Niaraki ◽  
Soo-Mi Choi ◽  
S. M. Riazul Islam
Keyword(s):  
Routing Protocol ◽  
Smart Home ◽  
Minimum Spanning Tree ◽  
Pso Algorithm ◽  
Bees Algorithm ◽  
Objective Functions ◽  
Fire Monitoring ◽  
Lower Complexity ◽  
Total Network ◽  
Health Applications

With the development of Internet of Things (IoT) applications, applying the potential and benefits of IoT technology in the health and environment services is increasing to improve the service quality using sensors and devices. This paper aims to apply GIS-based optimization algorithms for optimizing IoT-based network deployment through the use of wireless sensor networks (WSNs) and smart connected sensors for environmental and health applications. First, the WSN deployment research studies in health and environment applications are reviewed including fire monitoring, precise agriculture, telemonitoring, smart home, and hospital. Second, the WSN deployment process is modeled to optimize two conflict objectives, coverage and lifetime, by applying Minimum Spanning Tree (MST) routing protocol with minimum total network lengths. Third, the performance of the Bees Algorithm (BA) and Particle Swarm Optimization (PSO) algorithms are compared for the evaluation of GIS-based WSN deployment in health and environment applications. The algorithms were compared using convergence rate, constancy repeatability, and modeling complexity criteria. The results showed that the PSO algorithm converged to higher values of objective functions gradually while BA found better fitness values and was faster in the first iterations. The levels of stability and repeatability were high with 0.0150 of standard deviation for PSO and 0.0375 for BA. The PSO also had lower complexity than BA. Therefore, the PSO algorithm obtained better performance for IoT-based sensor network deployment.

Design and Performance Analysis of Objective Functions for RPL Routing Protocol

2022 ◽  
Author(s):  
Ibtissem Zaatouri ◽  
Nouha Alyaoui ◽  
Awatef Benfradj Guiloufi ◽  
Francoise Sailhan ◽  
Abdennaceur Kachouri
Keyword(s):  
Performance Analysis ◽  
Routing Protocol ◽  
Objective Functions ◽  
And Performance

scholarly journals Performance of Static Iot Networks using RPL Objective Functions

2019 ◽  
Vol 8 (4) ◽  
pp. 8972-8977 ◽  
Keyword(s):  
Objective Function ◽  
Routing Protocol ◽  
Routing Algorithms ◽  
Transmission Protocol ◽  
Objective Functions ◽  
Lossy Networks ◽  
Hop Count ◽  
Efficient Data ◽  
Selection Of ◽  
Better Than

Internet of Things, abbreviated as IoT is a network used mainly for the communication where different devices are connected for the retrieval, examination and execution of the necessary task. One of IoT’s biggest challenge is that, they are resource-constrained. Hence, it is essential to use an efficient data transmission protocol for routing. An effective routing protocol for static IoT network is the Routing protocol for Low Power and Lossy Networks (RPL). It is essential to assess the effectiveness of the RPL with the selection of best objective function for different static model. In this paper, the performance of different routing algorithms is compared in connection with different static topologies. Hence, the objective function’s performance is compared for different topologies i.e., Butterfly, Ring and Umbrella topologies. We consider two objective functions: namely Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OF0). MRHOF considers Expected Transmission Count (ETX) as its metric and the metric considered under OF0 is hop count. It is observed that the objective function OF0 performs better than MRHOF for the metric of energy and successful receiving of data.

scholarly journals Fractional order PID controller tuned by bat algorithm for robot trajectory control

2021 ◽  
Vol 21 (1) ◽  
pp. 74
Author(s):  
Mohammad A. Faraj ◽  
Abdulsalam Mohammed Abbood
Keyword(s):  
Fractional Order ◽  
Tracking Control ◽  
Bat Algorithm ◽  
Robotic Manipulators ◽  
Pso Algorithm ◽  
Objective Functions ◽  
Trajectory Tracking Control ◽  
Robot Trajectory ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

<span>This paper deals with implementing the tuning process of the gains of fractional order proportional-integral-derivative (FOPID) controller designed for trajectory tracking control for two-link robotic manipulators by using a Bat algorithm. Two objective functions with weight values assigned has been utilized for achieving the minimization operation of errors in joint positions and torque outputs values of robotic manipulators. To show the effectiveness of using a Bat algorithm in tuning FOPID parameters, a comparison has been made with particle swarm optimization algorithm (PSO). The validity of the proposed controllers has been examined in case of presence of disturbance and friction. The results of simulations have clearly explained the efficiency of FOPID controller tuned by Bat algorithm as compared with FOPID controller tuned by PSO algorithm. </span>

scholarly journals Using particle swarm optimization to solve test functions problems

2021 ◽  
Vol 10 (6) ◽  
pp. 3422-3431
Author(s):  
Issa Ahmed Abed ◽  
May Mohammed Ali ◽  
Afrah Abood Abdul Kadhim
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Standard Deviation ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Speed Of Convergence ◽  
Test Functions ◽  
Objective Functions ◽  
Swarm Optimization ◽  
Engineering Problems

In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.

Maximum Integration Capacity Analysis of Distributed Generator in Distribution Power System

2014 ◽  
Vol 672-674 ◽  
pp. 1032-1036
Author(s):  
Feng Zhou ◽  
Zai Lin Piao ◽  
Ke Yan Liu ◽  
Wan Xing Sheng ◽  
Jia Meng
Keyword(s):  
Power System ◽  
Stability Index ◽  
Pso Algorithm ◽  
Test System ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Distributed Generator ◽  
Inertia Weight ◽  
Network Losses

The integration of distributed generator (DG) will bring a series of influence in distribution power system. With the trend of a large number of DG penetration, researches on the maximum integration capacity of DG become a hot research topic. A multi-objective optimization model with objective functions of the maximum DG output, network losses and voltage stability index are formulated. Particle swarm optimization (PSO) algorithm is adopted with variable inertia weight to calculate the maximum DG output. IEEE 33-bus test system with DG units is taken as one example to compute the maximum integration capacity. The results show that the proposed method is reasonable and effective.

scholarly journals A Comprehensive Survey on Node Metrics of RPL Protocol for IoT

2019 ◽  
Vol 13 (12) ◽  
pp. 1
Author(s):  
Adeeb Saaidah ◽  
Omar Almomani ◽  
Laila Al-Qaisi. ◽  
Nesreen Alsharman ◽  
Faisal Alzyoud
Keyword(s):  
Internet Of Things ◽  
Routing Protocol ◽  
Optimal Path ◽  
Objective Functions ◽  
Relevant Research ◽  
Resource Limitations ◽  
Critical Issues ◽  
Comprehensive Survey ◽  
Resource Constrained Devices ◽  
Constrained Devices

Internet of Things (IOT) system often consists of thousands of constrained connected devices. Resource-constrained devices one of critical issues in a low- power and lossy network LLNs. RPL is IPv6 routing protocol. It&rsquo;s designed by IETF to be simple and inter-operable networking protocol to overcome these resource limitations. The RPL carries out Objective Functions (OFs) in the aim of finding the best path. The OFs chooses the best parent nodes aiming to build the route and optimize it. The metrics used to build the OF must be selected in an effective and accurate manner for finding the optimal path and meets all constraints. A survey about node metrics which can be utilized in OFs of RPL is presented, and node metrics calculations are explained then discussed thoroughly. The researcher displays the most relevant research efforts regarding the RPL OFs existing in literature.

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