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Routing in Internet of Things Using Cellular Automata 3rd

Routing in Internet of Things Using Cellular Automata

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3rd international conference on Innovative computing and Communication, ICICC 2020

作者： Heidari, Ehsan Movaghar, Ali Motameni, Homayun Homayun, Esmaeil Department of Computer Engineering Sari Branch Islamic Azad University Sari Iran Department of Computer Engineering Sharif University of Technology Tehran Iran Department of Computer Engineering Doroud Branch Islamic Azad University Doroud Iran

ISBN: (纸本)9789811551123

The Internet of Things (IoT) is a new model that contributes to connect heterogeneous objects and devices. It can share information with any device globally. Furthermore, the sensor technologies, communications, networks, and cloud computing technology in the IoT are expected to be integrated into large-scale monitored spaces. The main infrastructure of monitoring in the IoT is based on wireless sensor networks. Saving energy and expanding the lifetime are significant properties of the sensor’s nodes in these systems. The efficient energy saving projects should develop appropriate energy consumption’s algorithms to improve the lifetime of the networks in the IoT systems. In this paper, a routing algorithm is proposed to calculate the distributed cluster using cellular learning automata technology, which aims to reduce energy consumptions and can efficiently increase the network lifetime in the IoT system. The key objective of this project is reducing the data transmission distance from sensor nodes using the properties of the cluster structure. According to the cluster architecture, the data transmission distance between the sensors nodes can be reduced by balancing the network load, thereby reducing energy consumption and, consequently, enhancing the network lifetime. Simulation experiments revealed the superiority of this approach in the IoT to the previous ones with regard to energy consumptions and network lifetime. © 2021, Springer Nature Singapore Pte Ltd.

关键词： sensor nodes

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Determination of Optimal distributed Generation Penetration Level in Distribution Networks based on Normalized Impact Factor Score

Determination of Optimal Distributed Generation Penetration ...

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Power Engineering Application (ICPEA), ieee international conference in

作者： Muhammad Syahir Turiman Mohd Khairun Nizam Mohd Sarmin Nira Saadun Mohd Fahri Zamri Hamdan Ali Qawizamshah Mohammad Dept. of Transmission and Distribution TNB Research Selangor Malaysia Distribution Network Divison Tenaga Nasional Berhad Selangor Malaysia

The penetration level of renewable energy (RE) including distributed generation (DG) integrated in the distribution network has been increasing in many countries. This follows widespread encouragement to use renewable energy to minimize reliance on conventional power plants to achieve net zero emissions. Malaysian energy transition targets and carbon neutral goals set by the government, lower cost of ownership of solar PV systems, and more efficient government renewable energy initiatives including Net Energy Metering (NEM) 3.0, Green Investment Tax (GITA), Large Scale Solar (LSS), and most recently the Corporate Green Power Program (CGPP) have driven the rapid development of renewable energy in the country. However, the high penetration level of distributed generation including solar PV, mini- hydro, and bio-energy has introduced several technical impacts on the operation of the distribution network including increased fault levels, voltage limit violation, reverse power flow, distribution network losses, and transformer losses. This paper analyzes the technical impacts of the high penetration level of distributed generation in medium voltage (MV) substations of the distribution network using DigSILENT PowerFactory simulation software. From the results obtained through the simulation analysis, the impact factors of fault level, voltage limit violations, reverse power flow, distribution network losses, and transformer losses have been formulated. The optimal distributed generation penetration level in distribution networks is then determined based on the highest score value of the normalized impact factor from all penetration levels.

关键词： Renewable energy sources Analytical models Green products Government Distribution networks Voltage Transformers

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A consumer-based approach to the design of distributed energy systems with solar photovoltaic generation 3

A consumer-based approach to the design of distributed energ...

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3rd international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2021

作者： Perez-Moscote, Daniel A. Tyagunov, Mikhail G. Institute of Hydropower and Renewable Energy National Research University MPEI Moscow Russia

ISBN: (纸本)9781728183985

This paper describes how the design of distributed energy systems (DES) with renewable energy sources, particularly solar photovoltaic (PV) generation, could be improved with an approach based on the management of electricity consumption and behavior of end-users. With the use of HOMER Grid software, a grid-connected DES with three different load profiles has been designed, simulated, and compared in terms of performance and cost-effectiveness. Using demand flexibility to shift consumer loads throughout the day to better match the availability of renewable energy sources could represent a valuable key to enhancing DES development with regulated customers by increasing the penetration of renewables in the energy mix and subsequently increasing savings on utility bills. © 2021 ieee.

关键词： Cost effectiveness

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Underwater Wireless sensor Networks Using distributed Fusion of Optimally Quantized Estimations from Local Trackers

Underwater Wireless Sensor Networks Using Distributed Fusion...

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Pervasive computing and Social Networking (ICPCSN), international conference on

作者： Yogesh Pal Ravi Mohan Ganga Rama Koteswara Rao Suresh kumar. A Ravi Rastogi Mohd Asif Shah SCSET Bennett University Greater Noida Uttar Pradesh India Electronics & Communication Engineering Shri Ram Institute of Technology Madhotaal Jabalpur Madhya Pradesh India Department of CSIT Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India Department of CSE Rathinam Technical Campus Coimbatore Tamilnadu India NIELIT Gorakhpur Uttar Pradesh India University School of Business Chandigarh University Mohali Punjab India

Underwater wireless sensor networks (UWSNs) have come to rely heavily on localization technology due to their usefulness in a wide variety of contexts. Multi-sensor underwater surveillance has been an important area of study for both military and civilian uses. UWSNs employ measurement quantization to send data from individual sensors to the fusion Centre in order to accomplish centralized tracking/fusion despite bandwidth constraints. Yet, due to its non-linear nature, azimuth information is difficult to quantify at the measurement level. This work presents a solution by distributing the tracking and quantizing the local estimates in order to increase available bandwidth and decrease the computational burden. Yet, underwater acoustic communications have a very low bandwidth because of the temporal and geographical diversity of sound channels. Data quantization helps decrease the length of information sent from local sensors to the fusion Centre, which can help alleviate network congestion. Although quantization might lessen the burden on a network's budget, the information loss that ensues from the process also leads to subpar tracking performance. This work presents a target tracking system based on optimum quantization to address this issue. Namely, it reduces the extra covariance introduced by quantization in low-bit quantized measurements, hence enhancing their tracking efficiency. The simulation results show that our method outperforms the standard uniform quantization-based target tracking technique and that the increase in data length has a negligible impact on its performance. The proposed technique has been tested in simulation and shown to effectively reduce localization errors and reduce the burden of data transfer in massive 3D submerged sensor nodes.

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False Data Injection Attacks Against High Voltage Transmission systems

False Data Injection Attacks Against High Voltage Transmissi...

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international conference on distributed computing in sensor systems (DCOSS)

作者： Panagiotis Radoglou-Grammatikis Magda Zafeiropoulou Maria Atanasova Pencho Zlatev Sofia Giannakidou Thomas Lagkas Vasileios Argyriou Evangelos K. Markakis Ioannis Moscholios Panagiotis Sarigiannidis Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Innovative Energy and Information Technologies LTD (IEIT BIC-IZOT Sofia Bulgaria K3Y Ltd Sofia Bulgaria Department of Computer Science International Hellenic University Kavala Campus Greece Department of Networks and Digital Media Kingston University London Surrey UK Department of Electrical and Computer Engineering Hellenic Mediterranean University Crete Greece Department of Informatics & Telecommunications University of Peloponnese Tripolis Greece

The digitisation of the smart electrical grid provides several advantages and valuable services, such as self-monitoring, pervasive control and smart healing. However, despite the benefits of this progression, critical cybersecurity and privacy issues are raised due to the vulnerabilities of legacy Electrical Power and Energy systems (EPES) and the evolution of stealthy cyberthreats and malware. In this paper, we give emphasis to False Data Injection Attacks (FDIAs) that can affect the EPES State Estimation (SE). In particular, we investigate two FDIA categories, namely: (a) Global Positioning System (GPS) Spoofing Attacks and (b) ieee C37.118 FDIAs against an actual testbed emulating a high-voltage ieee 9-Bus transmission grid. Finally, we provide a relevant Intrusion Detection System (IDS) capable of detecting the aforementioned FDIAs. The evaluation analysis demonstrates the impact of the above FDIAs and the efficiency of the proposed IDS.

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Cloud-based Parallel computing System Via Single-Client Multi-Hash Single-Server Multi-Thread 3

Cloud-based Parallel Computing System Via Single-Client Mult...

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3rd international conference on Advance of Sustainable Engineering and its Application, ICASEA 2021

作者： Rashid, Zryan Najat Zeebaree, Subhi R. M. Sadeeq, Mohammed A. M. Zebari, Rizgar R. Shukur, Hanan M. Alkhayyat, Ahmed Sulaimani Polytechnic University Information Technology Dept. Sulemani Iraq Duhok Polytechnic University Technical College of Engineering Energy Department Duhok Iraq Duhok Polytechnic University Technical College of Administration Information Technology Mangement Department Duhok Iraq Nawroz University Computer Science Dept. Duhok Iraq Al-Kitab University Dept. Computer Engineering Kirkuk Iraq Islamic University Najaf Technical Engineering Dept. Najaf Iraq

ISBN: (纸本)9781665497367

Parallel distributed Processing is a relatively new method. distributed cloud connects data and applications delivered by utilizing cloud computing technologies from several geographical locations. When something is distributed in IT, it is transferred among multiple systems located across diverse areas. The expanse of information besides the interval it takes towards analyzing adding to monitoring projected results efficiently and effectively has been dramatically enhanced. This paper presented a system to assist users in doing composite tasks interactively with the least processing time. distributed-Parallel-Processing (DPP) and Cloudcomputing (CC) are the two most great technologies, can process and answer the user problem quickly. Developing a suggested system used several sources (source generators, under-test load, computing machines, and processing units) and (webservers) through the cloud. Hash codes are generated on the client-side and sent towards the webserver. The webserver delivers these does to cracking servers that have been specified. It has been verified that while employing light load (single hash-code) with multi-servers and multiprocessors, the suggested system gives improved efficiency (in terms of Kernel-burst, User-bust, and Total-execution) timings. Although it has been demonstrated that employing large loads (many under-testing codes) with many computing machines using multiprocessors improves the system's performance. The suggested computational system outperforms it in terms of parallel processing. The proposed method took these situations into account due to the code-breaking influences by two precarious criteria (minimal breaking-time besides cost-effective usage of computer resources). © 2021 ieee.

关键词： distributed cloud

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Automatic defense against distributed denial of service using anomaly based method in machine learning 3

Automatic defense against distributed denial of service usin...

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3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Hakak, Riyan Ahmad, Manzoor University of Kashmir Department of Computer Science Srinagar India

ISBN: (纸本)9780738111834

Security of the network is biggest challenge in modern world. Big companies like Google, Microsoft, Amazon etc. need to have their network secured all the time as they host public information on their servers. DDoS attacks poses a serious threat to many organizations. One need to be alert always to identify such attacks as they come from various distributed sources and every time hackers try to attack differently, so filtering by hand to avoid DDoS attack is a difficult task. Goal of this paper is to train a machine to classify the packets into malicious packet or legitimate packet. This is achieved by training our machine with KDD CUP dataset. This dataset is divided into two halves containing 20% of original dataset and 10% of original dataset which is used for training ANN and testing ANN, respectively. The dataset is chosen uniformly from the original dataset set so that normal and malicious instances are approximately same in number in each dataset. © 2021 ieee.

关键词： Personal computing

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Optimization of Node Deployment in Underwater sensor Networks Using Maximum Coverage and Connectivity Self-Deployment Algorithm Based on Particle Swarm Optimization

Optimization of Node Deployment in Underwater Sensor Network...

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Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： G. Renuka V. Gurumurthy Raed Hameed P. K. Chidambaram Sudhakar Chinnakathiyan Department of Electronics and Communication Engineering Anurag University Hyderabad India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Mechanical Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai India Department of Electronics and Communication Engineering Dhanalakshmi Srinivasan University Trichy India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

In recent years, Underwater Wireless sensor Networks (UWSNs) monitor underwater environment such as aquatic life. Moreover, to enhance network efficiently, sensor nodes are strategically placed in a 3D underwater space. However, underwater networks failed to find the optimal depth for each sensor in a 3D underwater network and failed in maintaining the connectivity to the surface station. Further, this research proposes a Maximum Coverage and Connectivity self-deployment algorithm based on Particle Swarm Optimization namely (MCC-PSO) for maximum coverage of water surface. Initially, the system models such as Network Scenario and Coverage Model are designed to optimize node deployment in UWSNs by simulating realistic environments. Then the problem identified that the optimal depth for N sensors deployed on a water surface to maximize network coverage and ensure connectivity to the surface station. To address this, a MCC and Connectivity Scheme is designed, Further, the MCC-PSO enhanced for optimizing the node development and PSO optimizes moving particles in search space by dynamic adaptation to environmental factors, such as node distribution and communication range. From the results, proposed MCC-PSO achieves a 50% higher maximum coverage rate compared to the existing Growth Ring Style Uneven Node Depth-Adjustment Self-Deployment Optimization Algorithm (GRSUNDSOA).

关键词： Integrated circuits Wireless sensor networks Three-dimensional displays Heuristic algorithms Environmental factors Real-time systems Reliability Particle swarm optimization Optimization Monitoring

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Quality of Power Improved by DSTATCOM for $3-\phi$ Grid-tied Solar Photo-Voltaic System

Quality of Power Improved by DSTATCOM for $3-\phi$ Grid-tied...

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international conference on Electrical Power and Energy systems (ICEPES)

作者： Rahul Kumar Mukesh Kirar Department of Electrical Engineering MANIT Bhopal M.P. India

ISBN: (数字)9798350390728

ISBN: (纸本)9798350390735

In this paper the design and working of $\mathbf{3}-\boldsymbol{\phi}$ Solar-PV integrated with distributed static compensator (DSTATCOM) are present for mitigating the power quality issues, under non-linear, unbalanced and dynamic loads. In general for non-linear loads DSTATCOM injects harmonic current component in opposite direction into the system there after the harmonics in source current is compensated. This paper applied for reduce rating of DC current, mitigate harmonics from source current, reactive power compensation, improve voltage regulation and load balancing. In this paper DSTATCOM also perform the function of extracting power from PV array. Proportional Integral controller based technique (or Unit template) with Hysteresis current controller is used in this work for controlling the VSC (DSTATCOM) and for extraction of maximum power from PV, MPPT technique is used. The performances of this system are evaluated using MATLAB software with its Simulink and power system block set toolboxes.

关键词： Reactive power Software packages Power system dynamics Power quality Switching loss Power system harmonics Harmonic analysis

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Advanced Water Quality Assessment with IOT WSN and Multivariate Machine Learning Techniques

Advanced Water Quality Assessment with IOT WSN and Multivari...

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Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Shofia Priyadharshini D G.P. Ramesh Department of Electronics and communication engineering St.Peter's Institute of Higher Education and Research Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Ensuring clean and safe water is a critical global challenge, necessitating advanced monitoring techniques for early detection of contamination. This research presents an loT-driven water quality monitoring framework that integrates wireless sensor networks (WSNs) with multivariate machine learning models to assess key water parameters in real time. The proposed system collects and transmits data to a cloud platform for analysis, employing predictive algorithms to estimate E. coli levels. Six machine learning models-Ridge Regression, Random Forest Regressor, Stochastic Gradient Boosting, Support Vector Machine, k-Nearest Neighbors, and AdaBoost-were evaluated for their predictive accuracy. Among these, AdaBoost demonstrated the highest reliability, achieving the lowest mean absolute error (MAE) of 14.37 counts per 100 mL, while Stochastic Gradient Boosting showed the least accuracy. The study further identifies an optimal set of water quality parameters (Set A) comprising pH, conductivity, chloride, turbidity, nitrates, and chlorophyll, which enhances predictive efficiency. These findings highlight the potential of AI-driven water monitoring systems as early-warning tools, providing a cost-effective approach to ensuring water safety and public health.

关键词： Support vector machines Wireless sensor networks Accuracy Stochastic processes Escherichia coli Water quality Boosting Water pollution Real-time systems Random forests

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