A brain tumor is an abnormal development of cells in the brain that are either benign or malignant. Magnetic resonance imaging (MRI) is used to identify tumors. Manual evaluation of brain tumors from MRI images by a radiologist is a challenging task. Hence, this paper proposes VGG-19 Convolutional Neural Networks (CNN)-based deep learning model for the classification of brain tumors. Initially, in the proposed model, contrast stretching technique is employed for noises removal. Next, a deep neural network is employed for rich feature extract. Further, these learning features are combined with classifier models of CNN for training and validation. performance analysis of the proposed methodology and experiments have been carried out using publicly available MRI images in Figshare dataset of 3064 slices from 233 subjects. The proposed model has achieved 99.83% accuracy. Moreover, the proposed model obtained precision 96.32%, 98.26%, and 98.56%, recall of 97.82%, 98.62%, 98.87%, and specificity of 98.72%, 99.51%, and 99.43% for the Glioma, Meningioma, and Pituitary tumors respectively.
{"title":"CNN-Based Deep Learning Technique for the Brain Tumor Identification and Classification in MRI Images","authors":"Anil Kumar Mandle, S. Sahu, Govind P. Gupta","doi":"10.4018/ijssci.304438","DOIUrl":"https://doi.org/10.4018/ijssci.304438","url":null,"abstract":"A brain tumor is an abnormal development of cells in the brain that are either benign or malignant. Magnetic resonance imaging (MRI) is used to identify tumors. Manual evaluation of brain tumors from MRI images by a radiologist is a challenging task. Hence, this paper proposes VGG-19 Convolutional Neural Networks (CNN)-based deep learning model for the classification of brain tumors. Initially, in the proposed model, contrast stretching technique is employed for noises removal. Next, a deep neural network is employed for rich feature extract. Further, these learning features are combined with classifier models of CNN for training and validation. performance analysis of the proposed methodology and experiments have been carried out using publicly available MRI images in Figshare dataset of 3064 slices from 233 subjects. The proposed model has achieved 99.83% accuracy. Moreover, the proposed model obtained precision 96.32%, 98.26%, and 98.56%, recall of 97.82%, 98.62%, 98.87%, and specificity of 98.72%, 99.51%, and 99.43% for the Glioma, Meningioma, and Pituitary tumors respectively.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130902583","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}
Magagi Ali Bachir, Ismail Jellouli, E. Said, Souad Amjad
In a modern information system adaptation, optimization is a crucial aspect. Systems adaptation problematics have been explored in a large set of research, which have not been able to fix every single issue, leaving therefore so many challenges to be explored. It for this reason this paper presents a method, through a UML profile, to ensure the optimization of the performance of a production system. In the first place, a state of the art is presented to clarify the context of the study. This method consists in setting up a UML profile which will allow the real value of the production to be constantly assessed, the reaction take place when production is not satisfactory. The productivity assessment performs through the application of the simple algorithm, the simplex constraints are integrated through the OCL language. A code generator, based on acceleo, has been developed to propose code generation.
{"title":"Model-Based Method for Optimisation of an Adaptive System","authors":"Magagi Ali Bachir, Ismail Jellouli, E. Said, Souad Amjad","doi":"10.4018/ijssci.301269","DOIUrl":"https://doi.org/10.4018/ijssci.301269","url":null,"abstract":"In a modern information system adaptation, optimization is a crucial aspect. Systems adaptation problematics have been explored in a large set of research, which have not been able to fix every single issue, leaving therefore so many challenges to be explored. It for this reason this paper presents a method, through a UML profile, to ensure the optimization of the performance of a production system. In the first place, a state of the art is presented to clarify the context of the study. This method consists in setting up a UML profile which will allow the real value of the production to be constantly assessed, the reaction take place when production is not satisfactory. The productivity assessment performs through the application of the simple algorithm, the simplex constraints are integrated through the OCL language. A code generator, based on acceleo, has been developed to propose code generation.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001057","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}
J. K. Appati, Prince Kofi Nartey, Winfred Yaokumah, J. Abdulai
Biometric authentication is gaining ground in security-related issues in business, corporate management, and other settings. A considerable amount of research has been conducted in this area, yet further research into its betterment is still an emerging trend. This article presents a study of the published empirical research on some fingerprint recognition techniques widely in use. The study is limited to articles that explicitly discuss techniques used in recognizing a person's fingerprint. It employs a systematic mapping design, which proposes a categorical system to classify the research results based on the selected articles' topics. The categories include work distribution by year of publication, datasets used, fingerprint recognition approaches, metrics, and evaluation. This study shows the direction of currently performed empirical research on fingerprint recognition by comparing the selected published work to the classification criteria and evaluating them.
{"title":"A Systematic Review of Fingerprint Recognition System Development","authors":"J. K. Appati, Prince Kofi Nartey, Winfred Yaokumah, J. Abdulai","doi":"10.4018/ijssci.300358","DOIUrl":"https://doi.org/10.4018/ijssci.300358","url":null,"abstract":"Biometric authentication is gaining ground in security-related issues in business, corporate management, and other settings. A considerable amount of research has been conducted in this area, yet further research into its betterment is still an emerging trend. This article presents a study of the published empirical research on some fingerprint recognition techniques widely in use. The study is limited to articles that explicitly discuss techniques used in recognizing a person's fingerprint. It employs a systematic mapping design, which proposes a categorical system to classify the research results based on the selected articles' topics. The categories include work distribution by year of publication, datasets used, fingerprint recognition approaches, metrics, and evaluation. This study shows the direction of currently performed empirical research on fingerprint recognition by comparing the selected published work to the classification criteria and evaluating them.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124848896","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}
Akshat Gaurav, Konstantinos E. Psannis, D. Peraković
In this digital era expectations for medical quality have increased. As the number of patients continues to increase, conventional health care methods are having to deal with new complications. In light of these observations, researchers suggested a hybrid combination of conventional health care methods with IoT technology and develop MIoT. The goal of IoMT is to ensure that patients can respond more effectively and efficiently to their treatment. But preserving user privacy is a critical issue when it comes to collecting and handling highly sensitive personal health data. However, IoMTs have limited processing power; hence, they can only implement minimal security techniques. Consequently, throughout the health data transfer through MIoT, patient’s data is at risk of data leakage. This manuscript per the authors emphasizes the need of implementing suitable security measures to increase the IoMT's resilience to cyberattacks. Additionally, this manuscript per the authors discusses the main security and privacy issues associated with IoMT and provide an overview of existing techniques.
{"title":"Security of Cloud-Based Medical Internet of Things (MIoTs): A Survey","authors":"Akshat Gaurav, Konstantinos E. Psannis, D. Peraković","doi":"10.4018/ijssci.285593","DOIUrl":"https://doi.org/10.4018/ijssci.285593","url":null,"abstract":"In this digital era expectations for medical quality have increased. As the number of patients continues to increase, conventional health care methods are having to deal with new complications. In light of these observations, researchers suggested a hybrid combination of conventional health care methods with IoT technology and develop MIoT. The goal of IoMT is to ensure that patients can respond more effectively and efficiently to their treatment. But preserving user privacy is a critical issue when it comes to collecting and handling highly sensitive personal health data. However, IoMTs have limited processing power; hence, they can only implement minimal security techniques. Consequently, throughout the health data transfer through MIoT, patient’s data is at risk of data leakage. This manuscript per the authors emphasizes the need of implementing suitable security measures to increase the IoMT's resilience to cyberattacks. Additionally, this manuscript per the authors discusses the main security and privacy issues associated with IoMT and provide an overview of existing techniques.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130084558","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}
Khadidja Benmoussa, D. Hamdadou, Zine El Abidine Roukh
The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.
{"title":"GIS-Based Multi-Criteria Decision-Support System and Machine Learning for Hospital Site Selection: Case Study Oran, Algeria","authors":"Khadidja Benmoussa, D. Hamdadou, Zine El Abidine Roukh","doi":"10.4018/ijssci.285592","DOIUrl":"https://doi.org/10.4018/ijssci.285592","url":null,"abstract":"The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"1040 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123140251","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}
Operational safety is at the center of all companies' concerns because increasing productivity is the top priority. Moreover, the high cost of breakdowns invests in a maintenance strategy, one of the most critical aspects of a manufacturing system. In the digital age, e-maintenance platforms can interoperate technically but fail to achieve semantic interoperability. The results are ambiguities and misunderstandings that can lead to equipment shutdowns or inefficient use of material resources. However, as formal knowledge specifications, ontologies have successfully integrated heterogeneous systems for some time. Therefore, the authors developed a core industrial maintenance ontology that is both generic and capable of extending and refining to meet semantic information repository requirements. Ontologies can unite and merge different datasets without adapting new ontologies. Only the core ontology needs to be modified according to the new semantics. A detailed description of the development process is provided, beginning with the definition of requirements and ending with the evaluation.
{"title":"A Core Industrial Maintenance Ontology Development Process","authors":"Leila Zemmouchi-Ghomari, Badreddine Midoune, Nadhir Djamiai","doi":"10.4018/ijssci.312555","DOIUrl":"https://doi.org/10.4018/ijssci.312555","url":null,"abstract":"Operational safety is at the center of all companies' concerns because increasing productivity is the top priority. Moreover, the high cost of breakdowns invests in a maintenance strategy, one of the most critical aspects of a manufacturing system. In the digital age, e-maintenance platforms can interoperate technically but fail to achieve semantic interoperability. The results are ambiguities and misunderstandings that can lead to equipment shutdowns or inefficient use of material resources. However, as formal knowledge specifications, ontologies have successfully integrated heterogeneous systems for some time. Therefore, the authors developed a core industrial maintenance ontology that is both generic and capable of extending and refining to meet semantic information repository requirements. Ontologies can unite and merge different datasets without adapting new ontologies. Only the core ontology needs to be modified according to the new semantics. A detailed description of the development process is provided, beginning with the definition of requirements and ending with the evaluation.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128376511","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}
Xiangnan Pan, S. Yamaguchi, Takumi Kageyama, Mohd Hafizuddin Bin Kamilin
This article proposes a white-hat worm launcher based on machine learning (ML) adaptable to large-scale IoT network for Botnet Defense System (BDS). BDS is a cyber-security system that uses white-hat worms to exterminate malicious botnets. White-hat worms defend an IoT system against malicious bots, the BDS decides the number of white-hat worms, but there is no discussion on the white-hat worms' deployment in IoT network. Therefore, the authors propose a machine-learning-based launcher to launch the white-hat worms effectively along with a divide and conquer algorithm to deploy the launcher to large-scale IoT networks. Then the authors modeled BDS and the launcher with agent-oriented Petri net and confirmed the effect through the simulation of the PN2 model. The result showed that the proposed launcher can reduce the number of infected devices by about 30-40%.
{"title":"Machine-Learning-Based White-Hat Worm Launcher in Botnet Defense System","authors":"Xiangnan Pan, S. Yamaguchi, Takumi Kageyama, Mohd Hafizuddin Bin Kamilin","doi":"10.4018/ijssci.291713","DOIUrl":"https://doi.org/10.4018/ijssci.291713","url":null,"abstract":"This article proposes a white-hat worm launcher based on machine learning (ML) adaptable to large-scale IoT network for Botnet Defense System (BDS). BDS is a cyber-security system that uses white-hat worms to exterminate malicious botnets. White-hat worms defend an IoT system against malicious bots, the BDS decides the number of white-hat worms, but there is no discussion on the white-hat worms' deployment in IoT network. Therefore, the authors propose a machine-learning-based launcher to launch the white-hat worms effectively along with a divide and conquer algorithm to deploy the launcher to large-scale IoT networks. Then the authors modeled BDS and the launcher with agent-oriented Petri net and confirmed the effect through the simulation of the PN2 model. The result showed that the proposed launcher can reduce the number of infected devices by about 30-40%.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121044162","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}
The Light Detection and Ranging (LiDAR) sensor is utilized to track each sensed obstructions at their respective locations with their relative distance, speed, and direction; such sensitive information forwards to the cloud server to predict the vehicle-hit, traffic congestion and road damages. Learn the behaviour of the state to produce an appropriate reward as the recommendation to avoid tragedy. Deep Reinforcement Learning and Q-network predict the complexity and uncertainty of the environment to generate optimal reward to states. Consequently, it activates automatic emergency braking and safe parking assistance to the vehicles. In addition, the proposed work provides safer transport for pedestrians and independent vehicles. Compared to the newer methods, the proposed system experimental results achieved 92.15% higher prediction rate accuracy. Finally, the proposed system saves many humans, animal lives from the vehicle hit, suggests drivers for rerouting to avoid unpredictable traffic, saves fuel consumption, and avoids carbon emission.
{"title":"Deep Reinforcement Learning-Based Pedestrian and Independent Vehicle Safety Fortification Using Intelligent Perception","authors":"P. Vijayakumar, L. Deborah, S. Rajkumar","doi":"10.4018/ijssci.291712","DOIUrl":"https://doi.org/10.4018/ijssci.291712","url":null,"abstract":"The Light Detection and Ranging (LiDAR) sensor is utilized to track each sensed obstructions at their respective locations with their relative distance, speed, and direction; such sensitive information forwards to the cloud server to predict the vehicle-hit, traffic congestion and road damages. Learn the behaviour of the state to produce an appropriate reward as the recommendation to avoid tragedy. Deep Reinforcement Learning and Q-network predict the complexity and uncertainty of the environment to generate optimal reward to states. Consequently, it activates automatic emergency braking and safe parking assistance to the vehicles. In addition, the proposed work provides safer transport for pedestrians and independent vehicles. Compared to the newer methods, the proposed system experimental results achieved 92.15% higher prediction rate accuracy. Finally, the proposed system saves many humans, animal lives from the vehicle hit, suggests drivers for rerouting to avoid unpredictable traffic, saves fuel consumption, and avoids carbon emission.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133660936","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}
An IoT is a complex system of interconnected electronic devices that exchange data over the network. Due to the sensitive nature of the data involved in this new technological paradigm, security measures must be taken with great care. Researchers can better understand the threats and weaknesses of the IoT if attacks are categorized to facilitate the development of a more robust defense system. This study discusses various attacks and statistical data related to IoT. These attacks are divided into two categories: physical and cyber-attacks. Based on the literature review, the authors found that social engineering and DoS are the most common attacks in the physical and cyber categories. This study demonstrates the security solutions inherent to securing the IoT environment. Cryptography, blockchain, software-defined networks, and machine learning techniques were reviewed. They also discussed steps that should be taken to make a safe IoT environment.
{"title":"Attacks on Resource-Constrained IoT Devices and Security Solutions","authors":"Ravi Sharma, Nonita Sharma","doi":"10.4018/ijssci.310943","DOIUrl":"https://doi.org/10.4018/ijssci.310943","url":null,"abstract":"An IoT is a complex system of interconnected electronic devices that exchange data over the network. Due to the sensitive nature of the data involved in this new technological paradigm, security measures must be taken with great care. Researchers can better understand the threats and weaknesses of the IoT if attacks are categorized to facilitate the development of a more robust defense system. This study discusses various attacks and statistical data related to IoT. These attacks are divided into two categories: physical and cyber-attacks. Based on the literature review, the authors found that social engineering and DoS are the most common attacks in the physical and cyber categories. This study demonstrates the security solutions inherent to securing the IoT environment. Cryptography, blockchain, software-defined networks, and machine learning techniques were reviewed. They also discussed steps that should be taken to make a safe IoT environment.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132905638","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}
The popularization of the cloud and its need to solve complex engineering application have alarmed energy and environmental concerns among the researchers. Achieving energy efficiency has become one of the most essential aims of the data center, offering more services with minimal energy consumption (EC). VM consolidation aims at adjusting the VMs to fewer PMs by live migration of VMs and then switching off the inactive servers, achieving energy efficiency. However, uncontrolled consolidation could violate the SLA. The paper contributes by considering the optimization problem targeting the EC and the number of VM migrations. Dynamic double threshold with enhanced search and rescue (DDT-ESAR) optimization has been introduced utilizing two thresholds; the first value defines the upper and lower bound for host classification, whereas the other is used to make migration decision. For migration, ESAR has been adopted for the most appropriate PM- VM mapping. The experimental analysis proves the efficiency where EC is computed to be 0.384kWh, SLA violations to be 6.33% and 64 number of migrations.
{"title":"Multi-Objective Energy-Efficient Virtual Machine Consolidation Using Dynamic Double Threshold-Enhanced Search and Rescue-Based Optimization","authors":"Sweta Singh, R. Kumar, U. P. Rao","doi":"10.4018/ijssci.315006","DOIUrl":"https://doi.org/10.4018/ijssci.315006","url":null,"abstract":"The popularization of the cloud and its need to solve complex engineering application have alarmed energy and environmental concerns among the researchers. Achieving energy efficiency has become one of the most essential aims of the data center, offering more services with minimal energy consumption (EC). VM consolidation aims at adjusting the VMs to fewer PMs by live migration of VMs and then switching off the inactive servers, achieving energy efficiency. However, uncontrolled consolidation could violate the SLA. The paper contributes by considering the optimization problem targeting the EC and the number of VM migrations. Dynamic double threshold with enhanced search and rescue (DDT-ESAR) optimization has been introduced utilizing two thresholds; the first value defines the upper and lower bound for host classification, whereas the other is used to make migration decision. For migration, ESAR has been adopted for the most appropriate PM- VM mapping. The experimental analysis proves the efficiency where EC is computed to be 0.384kWh, SLA violations to be 6.33% and 64 number of migrations.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133727297","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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