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Enhancing Network Lifetime of WSNs through the Implementation of a modified ant colony optimization Algorithm

Procedia Computer Science 2023年 230卷 368-376页

作者： Malathi Murugesan Kanimozhi R Dharani K G Devi D Assoc. Professor Dept. of Electronics and Communication Engineering E. G. S. Pillay Engineering College Nagapattinam - 611002 Asst. Professor Dept. of Computer Science and Engineering Bharathiyar Institute of Engineering for Women Deviyakurichi Assoc. Professor Dept. of Electronics and Communication Engineering Akshaya College of Engineering & Technology Coimbatore Asst. Professor Dept. of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology

Energy efficient routing has been the mainstay of research in wireless sensor networks. With rising utility of WSNs in a broad range of applications, a significant volume of research contributions are targeted towards obtaining an energy efficient routing with a good quality of service (QoS) metric. In recent times, the utility of evolutionary algorithm for such multi-objective problems has been on the rising trend as evolutionary models closely mimic the real time scenario of any problem optimization. In this research work, a modified ant colony optimization (M-ACO) has been proposed and implemented for optimization in terms of energy conservation and thereby to extend the network lifetime of the network

关键词： WSN Intelligent Routing Energy Efficiency modified ant colony optimization Hierarchical protocols

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Topographical design of stiffener layout for plates against blast loading using a modified ant colony optimization algorithm

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STRUCTURAL AND MULTIDISCIPLINARY optimization 2019年第2期59卷 335-350页

作者： Liu, Tangying Sun, Guangyong Fang, Jianguang Zhang, Jingtao Li, Qing Hunan Univ State Key Lab Adv Design & Manufacture Vehicle Bo Changsha 410082 Hunan Peoples R China Univ Sydney Sch Aerosp Mech & Mechatron Engn Sydney NSW 2006 Australia Univ Technol Sydney Sch Civil & Environm Engn Ctr Built Infrastruct Res Sydney NSW 2007 Australia

The stiffened plates are of demonstrable advantages and potential in offering high resistance to such extreme loading scenarios as blast. Since the distribution of the stiffeners has considerable effect on their performance, its design signifies an important topic of research. However, existing research has mainly focused on empirical design, and the configurations were largely experience based, which limits structural explosion-proof capacity. In order to improve the performance of stiffened plates against blast loading, we introduced here two new structural configurations of stiffened plates. In this study, the modified ant colony optimization (MACO) algorithm which introduces the mass constraint factor to the pheromone update function and integrates the idea of crossover and mutation was used to design the subjected to given working conditions. Specifically, material distribution of stiffeners is taken to be the design variables, and minimization of the maximum deflection of the center point of the plate to be the design objective under predetermined mass constraints. Compared with the baseline structure, the optimal designs largely improved the explosion-proof performance through distributing stiffener topology on the plates. The results showed that the optimum designs all present the reinforcement stiffeners to link with the fixed boundaries against the deformation. Moreover, the optimum designs placed more reinforcement materials in the central regions instead of four angles, and with the increase of the mass fraction, the reinforcement placement gradually extends from the center to the edges. The proposed method and new topological configurations are expected to provide some insights into design for novel protective structures.

关键词： Stiffened plates modified ant colony optimization Explosion-proof performance Topography optimization ant colony optimization

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Feature Selection Using modified ant colony optimization for Wireless Capsule Endoscopy 7

Feature Selection Using Modified Ant Colony Optimization for...

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7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (IEEE UEMCON)

作者： Mohammed, Shahed K. Deeba, Farah Bui, Francis M. Wahid, Khan A. Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK Canada

ISBN: (纸本)9781509014965

In this study, a modified ant colony optimization algorithm has been proposed to find a feature subset most relevant to the classification task. The algorithm incorporates a new heuristic information component based on classification accuracy. The proposed methodology has been applied in a multiclass classification problem of capsule endoscopic images, where image regions will be classified as bleeding, non-bleeding and uninformative regions. 75 dimensional features extracted from five color spaces have been investigated in the experiments. The proposed MACO algorithm efficiently finds the optimum feature subset over the five color spaces including RGB, HSV, Lab, YCbCr, and CMYK, resulting in a feature subset outperforming those obtained individually from each color space. The comparative study with state-of-the-art methods of feature selection demonstrated that MACO can provide the most relevant features and improve the performance in terms of accuracy, sensitivity and computational time.

关键词： modified ant colony optimization Support Vector Machine Feature Selection Wireless Capsule Endoscopy

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Mobile Robot Motion Planning by Point to Point Based on modified ant colony optimization and Voronoi Diagram

Mobile Robot Motion Planning by Point to Point Based on Modi...

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International Seminar on Intelligent Technology and Its Applications (ISITIA) - Recent Trends in Intelligent Computational Technologies for Sustainable Energy

作者： Habib, Nukman Purwanto, Djoko Soeprijanto, Adi Inst Teknol Sepuluh Nopember Dept Elect Engn Surabaya Indonesia

ISBN: (纸本)9781509017096

The bask purpose of mobile robot motion planning (MRMP) is discover the shortest path safely from beginning to the end position in the environment without crash some obstacles. In this paper, we proposed a combined method between Voronoi diagram (VD) and the modified ant colony optimization (M-ACO) algorithm for MRMP. The Voronoi diagram generate edges and vertices in the obstacles-filled space, then M-ACO choose the nodes (the generated vertices by VD) to form the safely shortest path by point to point (PTP) motion planning. The proposed approach to solve this MRMP problem indicate that it could make a safely planning shortest path.

关键词： point to point mobile robot motion planning modified ant colony optimization voronoi diagram

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Enhancing the Route optimization Using Hybrid MAF optimization Algorithm for the Internet of Vehicle

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WIRELESS PERSONAL COMMUNICATIONS 2022年第2期125卷 1715-1735页

作者： Dhanare, Ritesh Nagwanshi, Kapil Kumar Varma, Sunita Amity Univ Rajasthan Dept Comp Sci & Engn ASET Jaipur Rajasthan India Shri GS Inst Technol & Sci Commuter Technol & Applicat Indore India

A smart city involves different types of sensors and electronic devices that collect data to develop sustainable growth in the urban area. The development of internet-based driving is referred to as the IoV in the new modern era of the IoT. In IoV, real-time data is collected and the vehicles communicate with each other to transmit the data. However, there are some issues, like finding the shortest route between a travelling source and a destination, high packet delivery ratios, congestion, low connectivity probability, and high delays. To overcome these parameter issues, this paper proposes a hybrid optimization approach that combines modified ant colony and Firefly optimization techniques (MAF) to calculate the average speed and find the best route to the destination. The MAF algorithm combined attractiveness and pheromones to find the optimal path and reduce the travelling time. The proposed MAF algorithm for shortest route selection is compared to recent state-of-the-art methods such as RAVP, ECRA, EECM, and AISM. Two simulators, NS2 and SUMO, were used to conduct this experiment. These simulation findings reveal that the performance of the proposed MAF optimization is increased in terms of increased connectivity probability, reduced delays, and increased packet delivery ratio of the vehicles when the entire system was considered.

关键词： modified ant colony optimization Firefly optimization Internet of vehicles Routing Vehicular ad hoc network

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An improved distance-based ant colony optimization routing for vehicular ad hoc networks

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2020年第14期33卷 e4502-e4502页

作者： Ramamoorthy, Raghu Thangavelu, Menakadevi Adhiyamaan Coll Engn Dept Informat Technol Hosur 635109 Tamilnadu India Adhiyamaan Coll Engn Dept Elect & Commun Engn Hosur 635109 Tamilnadu India

Vehicular ad hoc network (VANET) has earned tremendous attraction in the recent period due to its usage in a wireless intelligent transportation system. VANET is a unique form of mobile ad hoc network (MANET). Routing issues such as high mobility of nodes, frequent path breaks, the blind broadcasting of messages, and bandwidth constraints in VANET increase communication cost, frequent path failure, and overhead and decrease efficiency in routing, and shortest path in routing provides solutions to overcome all these problems. Finding the shortest path between source and destination in the VANET road scenario is a challenging task. Long path increases network overhead, communication cost, and frequent path failure and decreases routing efficiency. To increase efficiency in routing a novel, improved distance-based ant colony optimization routing (IDBACOR) is proposed. The proposed IDBACOR determines intervehicular distance, and it is triggered by modified ant colony optimization (modified ACO). The modified ACO method is a metaheuristic approach, motivated by the natural behavior of ants. The simulation result indicates that the overall performance of our proposed scheme is better than ant colony optimization (ACO), opposition-based ant colony optimization (OACO), and greedy routing with ant colony optimization (GRACO) in terms of throughput, average communication cost, average propagation delay, average routing overhead, and average packet delivery ratio.

关键词： distance-based approach modified ant colony optimization pheromone probabilistic model shortest path VANET

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A Novel Intelligent Controller for Improved Transient Performance of SEIG-based Wave Energy Conversion System 2

A Novel Intelligent Controller for Improved Transient Perfor...

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2nd IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (IEEE ECBIOS) - Biomedical Engineering, Healthcare and Sustainability

作者： Lu, Kai-Hung Hong, Chih-Ming Gong, Xin Horng, Mong-Fong Cao, Yu Beijing Inst Technol Sch Informat Technol Zhuhai 519088 Peoples R China Natl Kaohsiung Univ Sci & Technol Dept Elect Engn Kaohsiung 80778 Taiwan

ISBN: (纸本)9781728187129

This study presented the devise of a novel intelligent controller (NIC) for the stability of self-excited induction generator (SEIG)-based wells turbine. The proposed NIC consisted of a recurrent wavelet based Elman neural network (RWENN) and modified ant colony optimization (MACO). A MACO method is used to regulate the learning rates and enhance the learning capability of RWENN. The intelligent control strategy is realized to preserve balance between generator output and grid power, to maintain the constant voltage of alternating current line, and DC-Link stable during variable load and speed. The innovative control strategy in this study improves the power regulation and dynamic capability of wave energy in a large range of working status.

关键词： Recurrent Wavelet based Elman Neural Network modified ant colony optimization Ocean Wave Energy Self-Excited Induction Generator

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Makespan Efficient Task Scheduling in Cloud Computing

Makespan Efficient Task Scheduling in Cloud Computing

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Springer International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS)

作者： Raju, Y. Home Prasanna Devarakonda, Nagaraju Acharya Nagarjuna Univ Dept CSE Guntur 522510 Andhra Pradesh India Lakireddy Bali Reddy Coll Engn Dept IT Vijayawada 521230 Andhra Pradesh India

ISBN: (纸本)9789811319518;9789811319501

Cloud computing is an emerging technology in modern era of online processing of customizable resources gathered commonly for several remote server accesses through on-demand access. Cloud Service Provider (CSP) renders cloud computing infrastructure in pay per use scheme in various formats. Thus, CSP provides a major role in optimization of Task Scheduling (TS) in trade off with cost afford by the end user. In proposed scheme, to create efficient utilization of resources and balanced cost of rendering service to end user, modified Fuzzy Clustering Means algorithm (MFCM) along with modified ant colony optimization (MACO) technique is used thereby minimizing the cost of using a cloud computing structure and with reduced makespan along with load balancing capability. Proposed strategy provides better results than existing strategies of various modifications on ACO alone that concentrates on optimizing lineup of Virtual Machine (VM).

关键词： Cloud service provider modified ant colony optimization modified fuzzy clustering means Task scheduling Virtual machine

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POSITIONAL GROUP ENHANCEMENT WITH NOVEL ROUTING SCHEME FOR SENSOR NODE LINKS IN WIRELESS DOMAIN

POSITIONAL GROUP ENHANCEMENT WITH NOVEL ROUTING SCHEME FOR S...

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International Conference on Signal Processing, Communication, Power and Embedded System

作者： Suresh Shanmugasundaram Boopathi Gopalakrishnan Botho University

ISBN: (纸本)9781509046218

The advancement of research ameliorates the interest of researchers to find solutions routing issues in Wireless Sensor Networks (WSN) and largely of the other routing schemes for WSN consider uniform nodes wherein, all sensor nodes have the same capabilities in terms of sensing, announcement and calculation capabilities. However, deployment of a homogeneous sensor node link may suffer from poor performance. Grouping is an effective method for resource administration regarding performance of the node link, design of routing scheme, Quality of Service etc. In this paper, a novel Position Enhanced Group based QoS routing scheme is suggested to know the best possible routing schemes, depending on multiple optimization goals. This scheme locates the nodes and formation of group and group head selection is processed by modified K means grouping algorithm. Then a modified ant colony optimization (MACO) technique is suggested for optimal routing which is in insensible to preliminary position, thus preeminent in the situation of Wireless Sensor Node link (WSNs). We propose a position enhanced Assemblage for group formation. Our scheme utilizes limited position information acquired by elegant antennas to determine routes and create direction-finding decisions for the grouped WSNs. The key feature of the scheme is its ability to meet different QoS requirements posed by dissimilar kind of traffic generated due to various natures of nodes thus maximizing node link performance and consumption. Simulation results suggest a considerable increase in the performance of suggested scheme over existing scheme.

关键词： Assemblage modified ant colony optimization Routing Wireless Sensor Node links

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Modifying ant colony optimization by Introducing the Concept of Perception Radius

Modifying Ant Colony Optimization by Introducing the Concept...

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International Conference on optimization, Reliability, and Information Technology (ICROIT)

作者： Arora, Geetika Rana, Satakshi Panchal, V. K. Banasthali Univ Jaipur Rajasthan India Manipal Inst Technol Manipal Karnataka India DRDO Def Terrain Res Lab New Delhi India

ISBN: (纸本)9781479929955

The main motive of ant colony optimization (ACO) is to fi? d the shortest path from the ants' nest to the food source by sensmg the amount of pheromone (a chemical secreted by ants which is used as the communication system) on the different paths available. In this paper, we propose a novel methodology which solves the problem of an ant facing an obstacle in its path from the nest to the food source, in which case the conventional ACO may fail. This work proposes a modified ant colony optimization by introducing the concept of perception radius, for enabling the ants to find the path to the food source even if there is any break in the pheromone trail. The Travelling Salesman Problem, as an example, is solved using the proposed modified ACO and the results obtained are compared with Dijkstra's algorithm. It is clearly demonstrated that our methodology not only works well when breaks or hurdles are encountered by ants but also provides efficient results.

关键词： ACO modified ant colony optimization Perception Radius

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