Danlami Gabi, Nasiru Muhammad Dankolo, A. Ismail, A. Zainal, Z. Zakaria
With exponential growth in the number of customers accessing the cloud services, scheduling tasks at cloud datacenter poses the greatest challenge in meeting end-user’s quality of service (QoS) expectations in terms of time and cost. Recent research makes use of metaheuristic task scheduling techniques in addressing this concern. However, metaheuristic techniques are attributed with certain limitation such as premature convergence, global and local imbalance which causes insufficient task allocation across cloud virtual machines. Thus, resulting in inefficient QoS expectation. To address these concerns while meeting end-users QoS expectation, this paper puts forward a non-preemptive chaotic cat swarm optimization (NCCSO) scheme as an ideal solution. In the developed scheme, chaotic process is introduced to reduce entrapment at local optima and overcome premature convergence and Pareto dominant strategy is used to address optimality problem. The developed scheme is implemented in the CloudSim simulator tool and simulation results show the developed NCCSO scheme compared to the benchmarked schemes adopted in this paper can achieve 42.87%, 35.47% and 25.49% reduction in term of execution time, and also 38.62%, 35.32%, 25.56% in term of execution cost. Finally, we also unveiled that a statistical significance on 95% confidential interval has shown that our developed NCCSO scheme can provide a remarkable performance that can meet end-user QoS expectations.
{"title":"Non-preemptive chaotic cat swarm optimization scheme for task scheduling on cloud computing environment","authors":"Danlami Gabi, Nasiru Muhammad Dankolo, A. Ismail, A. Zainal, Z. Zakaria","doi":"10.19101/IJACR.PID29","DOIUrl":"https://doi.org/10.19101/IJACR.PID29","url":null,"abstract":"With exponential growth in the number of customers accessing the cloud services, scheduling tasks at cloud datacenter poses the greatest challenge in meeting end-user’s quality of service (QoS) expectations in terms of time and cost. Recent research makes use of metaheuristic task scheduling techniques in addressing this concern. However, metaheuristic techniques are attributed with certain limitation such as premature convergence, global and local imbalance which causes insufficient task allocation across cloud virtual machines. Thus, resulting in inefficient QoS expectation. To address these concerns while meeting end-users QoS expectation, this paper puts forward a non-preemptive chaotic cat swarm optimization (NCCSO) scheme as an ideal solution. In the developed scheme, chaotic process is introduced to reduce entrapment at local optima and overcome premature convergence and Pareto dominant strategy is used to address optimality problem. The developed scheme is implemented in the CloudSim simulator tool and simulation results show the developed NCCSO scheme compared to the benchmarked schemes adopted in this paper can achieve 42.87%, 35.47% and 25.49% reduction in term of execution time, and also 38.62%, 35.32%, 25.56% in term of execution cost. Finally, we also unveiled that a statistical significance on 95% confidential interval has shown that our developed NCCSO scheme can provide a remarkable performance that can meet end-user QoS expectations.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086496","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 mobile cloud computing as an excellent paradigm offers on-demand services, whereas users can be confident once using them. Nevertheless, the existing cloud virtualization systems are not secure enough regarding the mediocre degree of data protection, which avoids individuals and organizations to engage with this technology. Therefore, the security of sensitive data may be affected when mobile users move it out to the cloud exactly during the processing in virtual machines (VMs). Many studies show that sensitive data of legitimate users’ VMs may be the target of malicious users, which lead to violating VMs’ confidentiality and privacy. The current approaches offer various solutions for this security issue. However, they are suffering from many inconveniences such as unauthorized distributed VM access behavior and robust strategies that ensure strong protection of communication of sensitive data among distributed VMs. The purpose of this paper is to present a new security proxy-based approach that contains three policies based on secured hashed DiffieHellman keys for user access control and VM deployment and communication control management in order to defend against three well-known attacks on the mobile cloud environment (co-resident attacks, hypervisor attacks and distributed attacks). The related attacks lead to unauthorized access to sensitive data between different distributed mobile applications while using the cloud as a third party for sharing resources. The proposed approach is illustrated using a healthcare case study. Including the experimental results that show interesting high-efficiency protection and accurate attacks identification.
{"title":"A new secure proxy-based distributed virtual machines management in mobile cloud computing","authors":"Boubakeur Annane, O. Ghazali, A. Alti","doi":"10.19101/IJACR.PID10","DOIUrl":"https://doi.org/10.19101/IJACR.PID10","url":null,"abstract":"The mobile cloud computing as an excellent paradigm offers on-demand services, whereas users can be confident once using them. Nevertheless, the existing cloud virtualization systems are not secure enough regarding the mediocre degree \u0000of data protection, which avoids individuals and organizations to engage with this technology. Therefore, the security of sensitive data may be affected when mobile users move it out to the cloud exactly during the processing in virtual \u0000machines (VMs). Many studies show that sensitive data of legitimate users’ VMs may be the target of malicious users, which lead to violating VMs’ confidentiality and privacy. The current approaches offer various solutions for this security issue. However, they are suffering from many inconveniences such as unauthorized distributed VM access behavior and robust strategies that ensure strong protection of communication of sensitive data among distributed VMs. The purpose of this paper is to present a new security proxy-based approach that contains three policies based on secured hashed DiffieHellman keys for user access control and VM deployment and communication control management in order to defend against three well-known attacks on the mobile cloud environment (co-resident attacks, hypervisor attacks and distributed attacks). The related attacks lead to unauthorized access to sensitive data between different distributed mobile applications while using the cloud as a third party for sharing resources. The proposed approach is illustrated using a healthcare case study. Including the experimental results that show interesting high-efficiency protection and accurate attacks identification.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114253654","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}
It has been reported that the construction of emotion profiling models using supervised machine learning involves data acquisition, signal pre-processing, feature extraction and classification. However, almost all papers do not address the issue of profiling emotion using supervised machine learning on the interrupted encephalogram (EEG) signals. Based on a preliminary study, emotion profiling on interrupted EEG signals produces low classification accuracy, using multilayer perceptron (MLP). Furthermore, lower emotion classification accuracy is produced from interrupted EEG signals with higher number of segments. Thus, the objective of this paper is to propose a technique and present the outcomes of handling interrupted EEG signals for emotion profiling. This is done by the suppression and interpolation of originally interrupted EEG signals at pre-process stage. As a result, emotion classification using MLP on interpolated data improves
{"title":"Emotional profiling through supervised machine learning of interrupted EEG interpolation","authors":"H. Yaacob, H. Omar, D. Handayani, R. Hassan","doi":"10.19101/IJACR.PID17","DOIUrl":"https://doi.org/10.19101/IJACR.PID17","url":null,"abstract":"It has been reported that the construction of emotion profiling models using supervised machine learning involves data acquisition, signal pre-processing, feature extraction and classification. However, almost all papers do not address the issue of profiling emotion using supervised machine learning on the interrupted encephalogram (EEG) signals. Based on a preliminary study, emotion profiling on interrupted EEG signals produces low classification accuracy, using multilayer perceptron (MLP). Furthermore, lower emotion classification accuracy is produced from interrupted EEG signals with higher number of segments. Thus, the objective of this paper is to propose a technique and present the outcomes of handling interrupted EEG signals for emotion profiling. This is done by the suppression and interpolation of originally interrupted EEG signals at pre-process stage. As a result, emotion classification using MLP on interpolated data improves","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131873922","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}
Integration of technologies and smart services is an essential need in most pervasive smart automation systems, especially those requiring agile situation management such as a smart home. Ontology reasoning is an efficient technique for identifying the situation of such systems by capturing the context and optimizing connected object lifecycle. It is based on common-sense knowledge for interpreting a huge number of events from different and heterogeneous connected objects. The ontology-driven approach may be used to solve the parallel incoming events using new combination operators in order to achieve high accuracy rates. This paper presents a flexible, modular and hierarchical loosely coupled framework based on open semantic services in order to identify highly complex events to hold the situations with high efficiency. The proposed approach is evaluated on smart domains use cases and compared with other existing methods. Results show interesting ratios of situation identification accuracy with low execution time.
{"title":"A semantic event based framework for complex situations modeling and identification in smart environments","authors":"Abderrahim Lakehal, A. Alti, P. Roose","doi":"10.19101/IJACR.PID33","DOIUrl":"https://doi.org/10.19101/IJACR.PID33","url":null,"abstract":"Integration of technologies and smart services is an essential need in most pervasive smart automation systems, especially those requiring agile situation management such as a smart home. Ontology reasoning is an efficient technique for identifying the situation of such systems by capturing the context and optimizing connected object lifecycle. It is based on common-sense knowledge for interpreting a huge number of events from different and heterogeneous connected objects. The ontology-driven approach may be used to solve the parallel incoming events using new combination operators in order to achieve high accuracy rates. This paper presents a flexible, modular and hierarchical loosely coupled framework based on open semantic services in order to identify highly complex events to hold the situations with high efficiency. The proposed approach is evaluated on smart domains use cases and compared with other existing methods. Results show interesting ratios of situation identification accuracy with low execution time.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115453135","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 : 2019-05-18DOI: 10.19101/IJACR.2019.940004
Tariq Tashan, Ekhlas H. Karam, Eman Falah Mohsin
This paper presents different structures of immune proportional-integral-derivative (PID) control system, to regulate the heart rate. It is based on Yanagihara, Noma, and Irisawa (YNI) model that represent the mathematical model of the heart. Three structure designs have been proposed to emphasize the optimality in the control process. In this work differential evolution (DE) algorithm is considered to optimize the controller parameters. The performance of the proposed three controllers has been compared to traditional PID methods. The comparison results show best improvement when using the proposed structure-III with 0% maximum overshoot, a reduction of 98.9%, 96.8% and 30.8% in rising time, settling time, and steady state error respectively.
{"title":"Immune PID controller based on differential evolution algorithm for heart rate regulation","authors":"Tariq Tashan, Ekhlas H. Karam, Eman Falah Mohsin","doi":"10.19101/IJACR.2019.940004","DOIUrl":"https://doi.org/10.19101/IJACR.2019.940004","url":null,"abstract":"This paper presents different structures of immune proportional-integral-derivative (PID) control system, to regulate the heart rate. It is based on Yanagihara, Noma, and Irisawa (YNI) model that represent the mathematical model of the heart. Three structure designs have been proposed to emphasize the optimality in the control process. In this work differential evolution (DE) algorithm is considered to optimize the controller parameters. The performance of the proposed three controllers has been compared to traditional PID methods. The comparison results show best improvement when using the proposed structure-III with 0% maximum overshoot, a reduction of 98.9%, 96.8% and 30.8% in rising time, settling time, and steady state error respectively.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115880659","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 : 2019-05-18DOI: 10.19101/IJACR.2019.940030
Xinlu Wang, W. Meng, Mingchuan Zhang
{"title":"A novel information retrieval method based on R-tree index for smart hospital information system","authors":"Xinlu Wang, W. Meng, Mingchuan Zhang","doi":"10.19101/IJACR.2019.940030","DOIUrl":"https://doi.org/10.19101/IJACR.2019.940030","url":null,"abstract":"","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123793035","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 : 2019-05-18DOI: 10.19101/IJACR.2019.940029
Priyanka Gupta, M. Gaur
{"title":"A comprehensive study of process calculi with routing tables","authors":"Priyanka Gupta, M. Gaur","doi":"10.19101/IJACR.2019.940029","DOIUrl":"https://doi.org/10.19101/IJACR.2019.940029","url":null,"abstract":"","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116390787","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 : 2019-05-18DOI: 10.19101/IJACR.2018.839037
Layla H. Abood, Ekhlas H. Karam, Abbas H. Issa
Monitoring depth of anesthesia (DOA) is a significant point in general anesthesia (GA). It can be obtained from the assessment of the drug dose carefully and preciously. As a benefit of drug delivery automation, closed-loop method will present several advantages. It may prevent excessive dose amount or less needed dose and the controlled feedback system can decrease the cost of the healthcare by reducing the patient recovery period. This paper addresses the use of adaptive sliding mode controllers (ASMC) for calculating the depth of anesthesia by administrating a dose of propofol drug and measure patient state according to the monitoring device the bispectral index (BIS). In this study, we suggest a simple nonlinear control strategy consists of an ASMC combined with single neuron self-tune neural controller. It is used for maintaining DOA and reducing the effect of the nonlinear element. The adaptive controller uses the BIS value measured as a reference tracking value and propofol dose rate as a control signal. The parameters of the controller are tuned using a procedure based on the biogeography-based optimization (BBO) algorithm. The results indicate that including adaptive parts of the controller and tune its gains needed by BBO algorithm may enable optimal and stable performance for controller for all patients. It also provides fast reach to the induction phase and stay in a stable value in maintenance phase, which reflects the efficient response of the suggested controller if it compared to other nonlinear controllers. It is also justified by the results obtained that the suggested controller gives a very good response.
{"title":"Design of adaptive neuro sliding mode controller for anesthesia drug delivery based on biogeography based optimization","authors":"Layla H. Abood, Ekhlas H. Karam, Abbas H. Issa","doi":"10.19101/IJACR.2018.839037","DOIUrl":"https://doi.org/10.19101/IJACR.2018.839037","url":null,"abstract":"Monitoring depth of anesthesia (DOA) is a significant point in general anesthesia (GA). It can be obtained from the assessment of the drug dose carefully and preciously. As a benefit of drug delivery automation, closed-loop method will present several advantages. It may prevent excessive dose amount or less needed dose and the controlled feedback system can decrease the cost of the healthcare by reducing the patient recovery period. This paper addresses the use of adaptive sliding mode controllers (ASMC) for calculating the depth of anesthesia by administrating a dose of propofol drug and measure patient state according to the monitoring device the bispectral index (BIS). In this study, we suggest a simple nonlinear control strategy consists of an ASMC combined with single neuron self-tune neural controller. It is used for maintaining DOA and reducing the effect of the nonlinear element. The adaptive controller uses the BIS value measured as a reference tracking value and propofol dose rate as a control signal. The parameters of the controller are tuned using a procedure based on the biogeography-based optimization (BBO) algorithm. The results indicate that including adaptive parts of the controller and tune its gains needed by BBO algorithm may enable optimal and stable performance for controller for all patients. It also provides fast reach to the induction phase and stay in a stable value in maintenance phase, which reflects the efficient response of the suggested controller if it compared to other nonlinear controllers. It is also justified by the results obtained that the suggested controller gives a very good response.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133156951","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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