Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497216
Thian-Li Lim, A. Lee
The use of Information and Communication Technology (ICT) in everyday life of an individual has expanded in recent years. The much-needed skills for 21st century are creativity, able to think critically, communication and collaboration skills. By equipping students with these skills, it will able to prepare students for the challenges in life and work environments in 21st century. The advancement of technology has led to e-learning in education. E-learning refers to online learning, which provides students with a virtual environment in which students engage in several activities. However, even with the increasingly utilise of e-learning platform, research has proven that the issues of students were not fully utilise the functions of e-learning platforms in their learning process still exist. It is just act as a supporting tool for them and lack of communication support provided by learning management system (LMS) has leads to using other platform for communication purposes. Pervasive tools in education such as mobile devices, wearable technology, and RFID has proven to have positive impact on student learning outcome, however its application in higher education settings is still relatively little. Hence with the limitations of current teaching practice with limitations of study focusing on utilizing pervasive tools, therefore the aim of this study is to investigate the important factors which affect the user behaviour of IT devices (pervasive tools). To achieve this, theories of technology acceptance model (TAM) and task technology fit (TTF) was used. Along with TAM and TTF characteristics, factors of enjoyment, usefulness, convenience, compatibility, social influence, computer self-efficacy, and mobility were also considered. This study provides a framework to better understand the factors affect the acceptance of pervasive tools in private universities in Malaysia.
{"title":"Extended TAM and TTF Model: A Framework for the 21st Century Teaching and Learning","authors":"Thian-Li Lim, A. Lee","doi":"10.1109/ICCOINS49721.2021.9497216","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497216","url":null,"abstract":"The use of Information and Communication Technology (ICT) in everyday life of an individual has expanded in recent years. The much-needed skills for 21st century are creativity, able to think critically, communication and collaboration skills. By equipping students with these skills, it will able to prepare students for the challenges in life and work environments in 21st century. The advancement of technology has led to e-learning in education. E-learning refers to online learning, which provides students with a virtual environment in which students engage in several activities. However, even with the increasingly utilise of e-learning platform, research has proven that the issues of students were not fully utilise the functions of e-learning platforms in their learning process still exist. It is just act as a supporting tool for them and lack of communication support provided by learning management system (LMS) has leads to using other platform for communication purposes. Pervasive tools in education such as mobile devices, wearable technology, and RFID has proven to have positive impact on student learning outcome, however its application in higher education settings is still relatively little. Hence with the limitations of current teaching practice with limitations of study focusing on utilizing pervasive tools, therefore the aim of this study is to investigate the important factors which affect the user behaviour of IT devices (pervasive tools). To achieve this, theories of technology acceptance model (TAM) and task technology fit (TTF) was used. Along with TAM and TTF characteristics, factors of enjoyment, usefulness, convenience, compatibility, social influence, computer self-efficacy, and mobility were also considered. This study provides a framework to better understand the factors affect the acceptance of pervasive tools in private universities in Malaysia.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122497135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497213
Siti Nadzirah Khairuddin, A. Sarlan, Rohiza Ahmad
Most researchers, if not all, would agree that regardless of software development methodology used for constructing software, the need to deal with requirements is real. Multiple studies have highlighted that erroneous in requirements is one of the major contributions for unsuccessful software development process (SDP). Hence, this paper intends to share findings from Structured Literature Review (SLR) that have been conducted, which studies some of the challenges arise in requirement management which could be seen as negatively impacting the requirement management (RM) process in context of SDP. Two main databases, i.e., Scopus and ScienceDirect have been used for extracting relevant papers dated between 2015 and 2021. From the result of frequency analysis performed on the papers, nine challenging activities are identified; with the top five being requirement engineering; the knowledge transfer between process; response toward changes; maintaining communication between stakeholders; and documentation. With the findings, it can be said that, whilst requirement management is an established activity, there are still factors that may contribute to failure if not properly attended.
{"title":"Challenges in Requirement Management Process: An Overview","authors":"Siti Nadzirah Khairuddin, A. Sarlan, Rohiza Ahmad","doi":"10.1109/ICCOINS49721.2021.9497213","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497213","url":null,"abstract":"Most researchers, if not all, would agree that regardless of software development methodology used for constructing software, the need to deal with requirements is real. Multiple studies have highlighted that erroneous in requirements is one of the major contributions for unsuccessful software development process (SDP). Hence, this paper intends to share findings from Structured Literature Review (SLR) that have been conducted, which studies some of the challenges arise in requirement management which could be seen as negatively impacting the requirement management (RM) process in context of SDP. Two main databases, i.e., Scopus and ScienceDirect have been used for extracting relevant papers dated between 2015 and 2021. From the result of frequency analysis performed on the papers, nine challenging activities are identified; with the top five being requirement engineering; the knowledge transfer between process; response toward changes; maintaining communication between stakeholders; and documentation. With the findings, it can be said that, whilst requirement management is an established activity, there are still factors that may contribute to failure if not properly attended.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125062058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/iccoins49721.2021.9497226
{"title":"[ICCOINS 2021 Front cover]","authors":"","doi":"10.1109/iccoins49721.2021.9497226","DOIUrl":"https://doi.org/10.1109/iccoins49721.2021.9497226","url":null,"abstract":"","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133958903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497209
N. Kamarudin, A. Azahari, M. H. M. Halip, Syarifah Bahiyah Rahayu, Arniyati Ahmad
The present paper discloses a patent framework of iNavig (Smart System for Inventory Management, Stock Item Locator and Navigation) for locating stock items stored in a building and navigating to the stock items on shelves. The enhanced system comprises a plurality of weight sensors for detecting a weight of the stock items placed on a storing platform, a video camera assembly to provide a real-time video data of the stock items and a visual appearance of the stock items. A service processing module for receiving a service request from a user via a portable computing device to procure one of the stock items is also presented. A plurality of anchor nodes comprising node microcontrollers (NodeMCU) is deployed in a vicinity of the stock items on the storing platform at a predefined set of locations. For smart navigation features, the system is equipped with an AR navigation map using a camera assembly of the portable computing device itself. Moreover, a stock item indicator utilizing fog computing decentralized system which implements machine learning and intelligent of things will be provided in terms of visual and/or audio notification to the user upon arrival at the said one of the stock items location.
本论文公开了iNavig (Smart System for Inventory Management, Stock Item Locator and Navigation)的专利框架，用于定位存储在建筑物中的库存物品并导航到货架上的库存物品。增强型系统包括用于检测放置在存储平台上的库存物品的重量的多个重量传感器、用于提供库存物品的实时视频数据的摄像机组件和库存物品的视觉外观。还提出了一种服务处理模块，用于通过便携式计算设备接收来自用户的服务请求以获取所述库存项目之一。包含节点微控制器(NodeMCU)的多个锚节点部署在存储平台上一组预定义位置的库存项目附近。对于智能导航功能，该系统配备了AR导航地图，使用便携式计算设备本身的相机组件。此外，利用雾计算分散系统实现机器学习和物联网的库存项目指示器将在用户到达所述库存项目位置时以视觉和/或音频通知的方式提供给用户。
{"title":"A New Framework of Smart System For Inventory Management, Stock Item Locator And Navigation","authors":"N. Kamarudin, A. Azahari, M. H. M. Halip, Syarifah Bahiyah Rahayu, Arniyati Ahmad","doi":"10.1109/ICCOINS49721.2021.9497209","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497209","url":null,"abstract":"The present paper discloses a patent framework of iNavig (Smart System for Inventory Management, Stock Item Locator and Navigation) for locating stock items stored in a building and navigating to the stock items on shelves. The enhanced system comprises a plurality of weight sensors for detecting a weight of the stock items placed on a storing platform, a video camera assembly to provide a real-time video data of the stock items and a visual appearance of the stock items. A service processing module for receiving a service request from a user via a portable computing device to procure one of the stock items is also presented. A plurality of anchor nodes comprising node microcontrollers (NodeMCU) is deployed in a vicinity of the stock items on the storing platform at a predefined set of locations. For smart navigation features, the system is equipped with an AR navigation map using a camera assembly of the portable computing device itself. Moreover, a stock item indicator utilizing fog computing decentralized system which implements machine learning and intelligent of things will be provided in terms of visual and/or audio notification to the user upon arrival at the said one of the stock items location.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116211747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497186
Y. Abiodun, U. I. Bature, D. Sani, J. N. Lawrence, N. M. Tahir
This paper presents the design and implementation of the mobile student handbook for the Department of Computer and Communications Engineering (DCCE), Abubakar Tafawa Balewa University (ATBU). The book was aimed at providing students with specific information for the curriculum of the department that indicates their structures as given by the Minimum Academic Standard of the National Universities Commission (NUC-MAS) Nigeria. It provides information on the brief history of the department, entry requirement, grading system, graduation requirements among many. The Conventional student handbook is a hard copy that is not easy to carry alone all the time, hard to manage, prone to damage, and easy to being misplaced. To address this setback, a software application of a student handbook is developed using Android SDK. This will help to provide an easy-to-use, interactive, and portable means for simple access to the department’s curriculum structure that will assist students during their academic pursuits. The user evaluation process was employed to validate the application, this involved installations of the application to the mobile phone of 100 students and 20 staff. Results were recorded and shown in both graphs and tabular format. This application provides basic features of the DCCE’s curriculum like the courses and their pre-requisites for all levels, grading system, degree nomenclature, graduation requirements, and examination guidelines, etc. Moreover, it is an all-in-one offline mobile application that was meant to resolve basic issues. In the future, the link to the university website should be incorporated for further access to information.
{"title":"Mobile Application for Student Handbook Based on the Android Operating System","authors":"Y. Abiodun, U. I. Bature, D. Sani, J. N. Lawrence, N. M. Tahir","doi":"10.1109/ICCOINS49721.2021.9497186","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497186","url":null,"abstract":"This paper presents the design and implementation of the mobile student handbook for the Department of Computer and Communications Engineering (DCCE), Abubakar Tafawa Balewa University (ATBU). The book was aimed at providing students with specific information for the curriculum of the department that indicates their structures as given by the Minimum Academic Standard of the National Universities Commission (NUC-MAS) Nigeria. It provides information on the brief history of the department, entry requirement, grading system, graduation requirements among many. The Conventional student handbook is a hard copy that is not easy to carry alone all the time, hard to manage, prone to damage, and easy to being misplaced. To address this setback, a software application of a student handbook is developed using Android SDK. This will help to provide an easy-to-use, interactive, and portable means for simple access to the department’s curriculum structure that will assist students during their academic pursuits. The user evaluation process was employed to validate the application, this involved installations of the application to the mobile phone of 100 students and 20 staff. Results were recorded and shown in both graphs and tabular format. This application provides basic features of the DCCE’s curriculum like the courses and their pre-requisites for all levels, grading system, degree nomenclature, graduation requirements, and examination guidelines, etc. Moreover, it is an all-in-one offline mobile application that was meant to resolve basic issues. In the future, the link to the university website should be incorporated for further access to information.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"48 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114741906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497179
Monther M. Elaish, Mahmood H. Hussein, Liyana Shuib, W. F. Wan Ahmad, K. Becker
Research interest in gamification is currently enjoying global attention. However, while game design is often the focus of these gamification systems, interface design is overlooked. This is due to the expectations of field stakeholders and experts who consider interface to be only a minor element of the gamification experience. The aim of this paper is to propose a classification method that categorizes the gamification element into tangible and intangible. This new classification would provide a clear perspective about the elements before the design and development of an educational game has even begun. The proposed new method of classification would save researcher’s time and effort by assisting in the selection of the most appropriate gamification elements for the situation at hand.
{"title":"A Proposed Gamification Elements of Educational Games","authors":"Monther M. Elaish, Mahmood H. Hussein, Liyana Shuib, W. F. Wan Ahmad, K. Becker","doi":"10.1109/ICCOINS49721.2021.9497179","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497179","url":null,"abstract":"Research interest in gamification is currently enjoying global attention. However, while game design is often the focus of these gamification systems, interface design is overlooked. This is due to the expectations of field stakeholders and experts who consider interface to be only a minor element of the gamification experience. The aim of this paper is to propose a classification method that categorizes the gamification element into tangible and intangible. This new classification would provide a clear perspective about the elements before the design and development of an educational game has even begun. The proposed new method of classification would save researcher’s time and effort by assisting in the selection of the most appropriate gamification elements for the situation at hand.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128331059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497134
L. M. Choong, Wei Cheng
Failure Analysis is a systematic process of collect and analyze data to determine the cause of failure, and identify effective corrective actions. It is an important discipline in many manufacturing industry, and when apply correctly can help to save money, resources and prevent further damages. Common failure analysis techniques in manufacturing include Ishikawa Cause-and Effect analysis a.k.a. Fishbone Analysis and Failure Mode and Effects Analysis (FMEA) are also used in optical transceiver manufacturing. While both methods are effective in providing high level assessment of failure causes, they may be visually cluttering when more complex defects are involved and the interrelationships between causes are not easily identifiable. This paper examines the application of Supervised Machine Learning in defect detection, quality assurance and throughput improvement. Machine learning helps manufacturers visualize previously impenetrable problems and reveal those that they never knew existed, including hidden bottlenecks or unprofitable production lines [1], further enhancing Failure Analysis methods in manufacturing.
{"title":"Machine Learning in Failure Analysis of Optical Transceiver Manufacturing Process","authors":"L. M. Choong, Wei Cheng","doi":"10.1109/ICCOINS49721.2021.9497134","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497134","url":null,"abstract":"Failure Analysis is a systematic process of collect and analyze data to determine the cause of failure, and identify effective corrective actions. It is an important discipline in many manufacturing industry, and when apply correctly can help to save money, resources and prevent further damages. Common failure analysis techniques in manufacturing include Ishikawa Cause-and Effect analysis a.k.a. Fishbone Analysis and Failure Mode and Effects Analysis (FMEA) are also used in optical transceiver manufacturing. While both methods are effective in providing high level assessment of failure causes, they may be visually cluttering when more complex defects are involved and the interrelationships between causes are not easily identifiable. This paper examines the application of Supervised Machine Learning in defect detection, quality assurance and throughput improvement. Machine learning helps manufacturers visualize previously impenetrable problems and reveal those that they never knew existed, including hidden bottlenecks or unprofitable production lines [1], further enhancing Failure Analysis methods in manufacturing.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129360815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497233
Hoong-Cheng Soong, R. Ayyasamy, R. Akbar
Due to the advent of Web 2.0 and Internet boom, social media is essential to generate vast amount of data that can be analyzed for various purposes. For instance, we can use the vast amount of data for sentiment analysis and opinion mining. Nowadays, it is prevalent to find out the sentiments of the customers regarding products or services offered specially to increase the sales with proper actions taken from the predictions. In short, it is to determine how people feel about a specific topic. Although sentiment analysis and opinion mining are slightly different, there are often used interchangeably under the text mining and natural language processing fields. Two approaches for the sentiment analysis: lexicon analysis or machine learning. For the machine learning approaches, there are supervised, unsupervised and semi-supervised learning approaches. Deep learning is a new era of machine learning techniques that overcome the weaknesses of earlier machine learning techniques that is Artificial Neural Network (ANN) and Deep Neural Network (DNN). DNN has Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). In this paper, the deep learning techniques will be surveyed to discuss the importance from moving towards from machine learning to deep learning for the classification.
{"title":"A Review Towards Deep Learning for Sentiment Analysis","authors":"Hoong-Cheng Soong, R. Ayyasamy, R. Akbar","doi":"10.1109/ICCOINS49721.2021.9497233","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497233","url":null,"abstract":"Due to the advent of Web 2.0 and Internet boom, social media is essential to generate vast amount of data that can be analyzed for various purposes. For instance, we can use the vast amount of data for sentiment analysis and opinion mining. Nowadays, it is prevalent to find out the sentiments of the customers regarding products or services offered specially to increase the sales with proper actions taken from the predictions. In short, it is to determine how people feel about a specific topic. Although sentiment analysis and opinion mining are slightly different, there are often used interchangeably under the text mining and natural language processing fields. Two approaches for the sentiment analysis: lexicon analysis or machine learning. For the machine learning approaches, there are supervised, unsupervised and semi-supervised learning approaches. Deep learning is a new era of machine learning techniques that overcome the weaknesses of earlier machine learning techniques that is Artificial Neural Network (ANN) and Deep Neural Network (DNN). DNN has Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). In this paper, the deep learning techniques will be surveyed to discuss the importance from moving towards from machine learning to deep learning for the classification.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116162087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497205
Zan-Wai Kong, T. Tan, B. Ooi, S. Liew
IoT gateways are deployed among the sensor networks with huge number of nodes to facilitate manageability and deployment cost of IoT system. Efficient gateway placement can establish a mesh network between gateways to achieve fault-tolerance, load balancing and further reduce deployment and operational cost. However, existing gateway placement schemes do not take wireless interference between gateways into account, which may cause great performance impact to wireless network traffic and thus affect overall throughput. This work proposed an interference-aware IoT gateway placement scheme which take network interference, fault-tolerance and deployment cost into account. We have proposed to implement the scheme using a metaheuristic approach – Genetic Algorithm. In order to adapt gateway placement problem to be solved by genetic algorithm, the constraints are required to be further formulated and modeled. The main contribution of this work is to fabricate the mentioned model and consequently assess its performance against existing solutions from different aspect. The results are promising.
{"title":"Interference-aware Wireless Internet of Things Gateway Placement Scheme","authors":"Zan-Wai Kong, T. Tan, B. Ooi, S. Liew","doi":"10.1109/ICCOINS49721.2021.9497205","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497205","url":null,"abstract":"IoT gateways are deployed among the sensor networks with huge number of nodes to facilitate manageability and deployment cost of IoT system. Efficient gateway placement can establish a mesh network between gateways to achieve fault-tolerance, load balancing and further reduce deployment and operational cost. However, existing gateway placement schemes do not take wireless interference between gateways into account, which may cause great performance impact to wireless network traffic and thus affect overall throughput. This work proposed an interference-aware IoT gateway placement scheme which take network interference, fault-tolerance and deployment cost into account. We have proposed to implement the scheme using a metaheuristic approach – Genetic Algorithm. In order to adapt gateway placement problem to be solved by genetic algorithm, the constraints are required to be further formulated and modeled. The main contribution of this work is to fabricate the mentioned model and consequently assess its performance against existing solutions from different aspect. The results are promising.","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116599870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICCOINS49721.2021.9497136
Joseph Mabor Agany Manyiel, Yew Kwang Hooi, Mohamed Nordin b. Zakaria
Genetic algorithm (GA) is a metaheuristic method that has been widely adopted for solving the Rich Vehicle Routing Problems (RVRP) due to its ability to find quality approximate solutions, even for large-scale instances of the problem, in a reasonable time. However, GA is stochastic in nature and does not guarantee a good solution all the time, a problem primarily due to premature convergence. In this paper we present Multi-population Genetic Algorithm for Rich Vehicle Routing Problems (MPGA-RVRP) to provide diversity and delay premature convergence in GA by making use of multiple populations that each evolves independently optimizing a single objective while sharing potential solutions. MPGA-RVRP is applied in RVRP with three objectives:- total route distance, total route duration and total route cost. Results from the experiments show that MPGA-RVRP performs considerably better compared to benchmark, multi-objective Genetic Algorithm (MOGA).
{"title":"Multi-Population Genetic Algorithm for Rich Vehicle Routing Problems","authors":"Joseph Mabor Agany Manyiel, Yew Kwang Hooi, Mohamed Nordin b. Zakaria","doi":"10.1109/ICCOINS49721.2021.9497136","DOIUrl":"https://doi.org/10.1109/ICCOINS49721.2021.9497136","url":null,"abstract":"Genetic algorithm (GA) is a metaheuristic method that has been widely adopted for solving the Rich Vehicle Routing Problems (RVRP) due to its ability to find quality approximate solutions, even for large-scale instances of the problem, in a reasonable time. However, GA is stochastic in nature and does not guarantee a good solution all the time, a problem primarily due to premature convergence. In this paper we present Multi-population Genetic Algorithm for Rich Vehicle Routing Problems (MPGA-RVRP) to provide diversity and delay premature convergence in GA by making use of multiple populations that each evolves independently optimizing a single objective while sharing potential solutions. MPGA-RVRP is applied in RVRP with three objectives:- total route distance, total route duration and total route cost. Results from the experiments show that MPGA-RVRP performs considerably better compared to benchmark, multi-objective Genetic Algorithm (MOGA).","PeriodicalId":245662,"journal":{"name":"2021 International Conference on Computer & Information Sciences (ICCOINS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124946361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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