In this world, there is fast growth in technology, as technology growth is there the human also move fast based on the growth in technology. New diseases also growing fast in the world. In this paper, a semi-supervised approach has been proposed for the classification of the COVID-19 and a study has been done to analyze the impact of the covid on Alzheimer’s disease patients. Coronavirus disease is a respiratory infection disease and Alzheimer’s disease is a brain disease. From the literature, it has been analyzed that, because of the coronavirus the immunity system will be affected in humans and there is a chance to affect the brain also. Classification and clustering have been done on the coronavirus dataset and validated using a 10-fold validation process. The classifiers applied are Naïve Bayes and Random Forest; the results obtained are 99.88% and 100% accuracy. Also, the clustering has been applied and 2 clusters are generated for grouping the classes. Then a study has been done for predicting the impact of the coronavirus on Alzheimer’s patients.
{"title":"Analysis of COVID-19 and its Impact on Alzheimer’s Patient using Machine Learning Techniques","authors":"R. Sivakani, M. Syed Masood","doi":"10.47839/ijc.21.4.2782","DOIUrl":"https://doi.org/10.47839/ijc.21.4.2782","url":null,"abstract":"In this world, there is fast growth in technology, as technology growth is there the human also move fast based on the growth in technology. New diseases also growing fast in the world. In this paper, a semi-supervised approach has been proposed for the classification of the COVID-19 and a study has been done to analyze the impact of the covid on Alzheimer’s disease patients. Coronavirus disease is a respiratory infection disease and Alzheimer’s disease is a brain disease. From the literature, it has been analyzed that, because of the coronavirus the immunity system will be affected in humans and there is a chance to affect the brain also. Classification and clustering have been done on the coronavirus dataset and validated using a 10-fold validation process. The classifiers applied are Naïve Bayes and Random Forest; the results obtained are 99.88% and 100% accuracy. Also, the clustering has been applied and 2 clusters are generated for grouping the classes. Then a study has been done for predicting the impact of the coronavirus on Alzheimer’s patients.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85474904","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}
Many quantum algorithms have been proposed which are drastically more efficient that the best of the non-quantum algorithms for solving the same problems. A natural question is: are these quantum algorithms already optimal – in some reasonable sense – or they can be further improved? In this paper, we review recent results showing that many known quantum algorithms are actually optimal. Several of these results are based on appropriate invariances (symmetries). Specifically, we show that the following algorithms are optimal: Grover’s algorithm for fast search in an unsorted array, teleportation algorithm – which is important for parallel quantum computations, and quantum annealing optimization algorithm. This covers many algorithms related to quantum computing. We also mention that algorithms for quantum communication and Deutsch-Josza algorithm – for fast checking whether a bit affect computation results – are optimal. In all these cases, optimality is shown not just for one specific optimality criterion, but for all possible optimality criteria that satisfy the natural invariance requirement.
{"title":"Many Known Quantum Algorithms Are Optimal: Symmetry-Based Proofs","authors":"V. Kreinovich, Oscar Galindo, O. Kosheleva","doi":"10.47839/ijc.21.4.2776","DOIUrl":"https://doi.org/10.47839/ijc.21.4.2776","url":null,"abstract":"Many quantum algorithms have been proposed which are drastically more efficient that the best of the non-quantum algorithms for solving the same problems. A natural question is: are these quantum algorithms already optimal – in some reasonable sense – or they can be further improved? In this paper, we review recent results showing that many known quantum algorithms are actually optimal. Several of these results are based on appropriate invariances (symmetries). Specifically, we show that the following algorithms are optimal: Grover’s algorithm for fast search in an unsorted array, teleportation algorithm – which is important for parallel quantum computations, and quantum annealing optimization algorithm. This covers many algorithms related to quantum computing. We also mention that algorithms for quantum communication and Deutsch-Josza algorithm – for fast checking whether a bit affect computation results – are optimal. In all these cases, optimality is shown not just for one specific optimality criterion, but for all possible optimality criteria that satisfy the natural invariance requirement.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72403686","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}
In recent years, the idea of software-defined networks (SDNs) has been proposed for better network management. This architecture has succeeded in optimizing network management functions and increased the ability to synchronize network equipment. Currently, one of the major issues in this architecture is the routing of packets flowing in the network. The main aim in the routing of packets is to increase the quality of services. Enhancement of the quality and productivity of these networks will increase user satisfaction. To this end, the present study proposes a mechanism for selecting the best route from among several existing routes to direct a flow on such a network. The proposed method examines the network parameters including bandwidth, delay, and packet loss on each link of the route by using artificial intelligence algorithms and changes the parameters reducing network productivity by means of fuzzy logic. Our evaluations show that the proposed method can select routes with high productivity and increase the quality of services on the network. Receiving feedback and modifying the fuzzy membership functions related to each mentioned criterion can maintain the effect of these parameters on an acceptable level after which all transmissions tend towards the optimum. Given the use of reinforcement learning methods which underpin some of the routing methods in SDNs, the proposed idea may gradually contribute to the provision of optimized services on the network.
{"title":"Traffic-aware Routing with Software-defined Networks Using Reinforcement Learning and Fuzzy Logic","authors":"Shohreh Jaafari, M. Nassiri, Reza Mohammadi","doi":"10.47839/ijc.21.3.2687","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2687","url":null,"abstract":"In recent years, the idea of software-defined networks (SDNs) has been proposed for better network management. This architecture has succeeded in optimizing network management functions and increased the ability to synchronize network equipment. Currently, one of the major issues in this architecture is the routing of packets flowing in the network. The main aim in the routing of packets is to increase the quality of services. Enhancement of the quality and productivity of these networks will increase user satisfaction. To this end, the present study proposes a mechanism for selecting the best route from among several existing routes to direct a flow on such a network. The proposed method examines the network parameters including bandwidth, delay, and packet loss on each link of the route by using artificial intelligence algorithms and changes the parameters reducing network productivity by means of fuzzy logic. Our evaluations show that the proposed method can select routes with high productivity and increase the quality of services on the network. Receiving feedback and modifying the fuzzy membership functions related to each mentioned criterion can maintain the effect of these parameters on an acceptable level after which all transmissions tend towards the optimum. Given the use of reinforcement learning methods which underpin some of the routing methods in SDNs, the proposed idea may gradually contribute to the provision of optimized services on the network.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81883431","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}
Serhii Voitenko, Volodymyr Druzhynin, Hanna Martyniuk, Tetiana Meleshko
This work deals with the identification of threats to wireless networks when considering an attacker from unmanned aerial vehicles. An analysis of heterogeneous networks built on 4 G technology, as objects of UAV attack, is performed. It is determined that the main problem of protecting wireless systems is the lack of protection of radio communication channels and the vulnerability of the base and subscriber station equipment. A model of the UAV as an intruder in the information security of wireless networks is built. The classification of various types of UAVs by targets and weapons of attack, methods of use and the ability to violate the criteria of protection of the information and telecommunication system is presented. A threat model that assesses the level of risks and losses in different types of attacks performed by different types of UAVs is built. It is expedient to use the received models as the basic ones when building a model of threats to a certain corporate network of the organization, developing ways and security means, estimating and controlling 4 G network protection against UAV.
{"title":"Unmanned Aerial Vehicles as a Source of Information Security Threats of Wireless Network","authors":"Serhii Voitenko, Volodymyr Druzhynin, Hanna Martyniuk, Tetiana Meleshko","doi":"10.47839/ijc.21.3.2695","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2695","url":null,"abstract":"This work deals with the identification of threats to wireless networks when considering an attacker from unmanned aerial vehicles. An analysis of heterogeneous networks built on 4 G technology, as objects of UAV attack, is performed. It is determined that the main problem of protecting wireless systems is the lack of protection of radio communication channels and the vulnerability of the base and subscriber station equipment. A model of the UAV as an intruder in the information security of wireless networks is built. The classification of various types of UAVs by targets and weapons of attack, methods of use and the ability to violate the criteria of protection of the information and telecommunication system is presented. A threat model that assesses the level of risks and losses in different types of attacks performed by different types of UAVs is built. It is expedient to use the received models as the basic ones when building a model of threats to a certain corporate network of the organization, developing ways and security means, estimating and controlling 4 G network protection against UAV.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76694142","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}
Hayder G. A. Altameemi, Ahmed A. Alani, A. Asmael, M. Al‐Obaidi
Over many years, in order to provide powerful techniques for protecting digital copyrights, digital watermarking techniques have been developed. This research focuses on proposing an efficient blind hybrid digital image watermarking technique based on the transformation of Daubechies wavelet (DW) and Block Bitmap modification (BBM). DW represents an effective multi-determination frequency domain for including the watermarks. The BBM is used to afford an enhanced capability of embedding and minimize distortion. Two layers of security have been added to the proposed technique for protecting digital images from theft by using the logistic chaotic mapping to select the position of the blocks for the embedding process and Lorenz chaotic mapping for scrambling the watermark image. In the experiments, high values of peak signal to noise ratio (PSNR) and structural similarity index (SSIM) are obtained, and all the obtained results illustrate that the presented technique is highly imperceptible, secure, and robust.
{"title":"A Competent Hybrid Digital Image Watermarking Technique Based on Daubechies Wavelet and Block Bitmap Modification","authors":"Hayder G. A. Altameemi, Ahmed A. Alani, A. Asmael, M. Al‐Obaidi","doi":"10.47839/ijc.21.3.2685","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2685","url":null,"abstract":"Over many years, in order to provide powerful techniques for protecting digital copyrights, digital watermarking techniques have been developed. This research focuses on proposing an efficient blind hybrid digital image watermarking technique based on the transformation of Daubechies wavelet (DW) and Block Bitmap modification (BBM). DW represents an effective multi-determination frequency domain for including the watermarks. The BBM is used to afford an enhanced capability of embedding and minimize distortion. Two layers of security have been added to the proposed technique for protecting digital images from theft by using the logistic chaotic mapping to select the position of the blocks for the embedding process and Lorenz chaotic mapping for scrambling the watermark image. In the experiments, high values of peak signal to noise ratio (PSNR) and structural similarity index (SSIM) are obtained, and all the obtained results illustrate that the presented technique is highly imperceptible, secure, and robust.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89331285","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 alarm management system with the Human Machine Interface in a process control system is used to alert an operator of any abnormal situation, so that corrective action can be taken to ensure safety and productivity of the plant and quality of the product. An alarm system reporting many alarms even during the normal state of the plant is due to chattering alarms, duplicated alarms, intermittent equipment problems and certain alarms configured in the system which may not have any importance. In such a situation the operator may miss certain critical alarms leading to undesirable outcomes. So, to have an optimum alarm system, the unwanted alarms have to be identified and eliminated. In this paper, we propose an offline method to identify repetitive, frequent sequences or patterns using PrefixSpan and Bi-Directional Extension algorithms. With the identified sequences or patterns, plant operation experts can improve the effectiveness of the alarm system through alarm rationalization so that this will help the operator in making the plant more safe, reliable and productive. The main objectives of this work are the following: (i) to use a definitive method to represent alarm data in an alarm log which is Temporal data as Itemsets without a need for complex mathematical, statistical or visual methods; (ii) to use data mining algorithms for identifying Frequent sequences which can be implemented on a normal computing resource such as Personal computer; (iii) to apply the method to the complete alarm data available no matter how big they are; (iv) to study and establish that the chosen method is possible to be applied to larger sized datasets.
{"title":"Alarm Pattern Recognition in Continuous Process Control Systems using Data Mining","authors":"Chetana Belavadi, V. Sardar, S. Chaudhari","doi":"10.47839/ijc.21.3.2689","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2689","url":null,"abstract":"An alarm management system with the Human Machine Interface in a process control system is used to alert an operator of any abnormal situation, so that corrective action can be taken to ensure safety and productivity of the plant and quality of the product. An alarm system reporting many alarms even during the normal state of the plant is due to chattering alarms, duplicated alarms, intermittent equipment problems and certain alarms configured in the system which may not have any importance. In such a situation the operator may miss certain critical alarms leading to undesirable outcomes. So, to have an optimum alarm system, the unwanted alarms have to be identified and eliminated. In this paper, we propose an offline method to identify repetitive, frequent sequences or patterns using PrefixSpan and Bi-Directional Extension algorithms. With the identified sequences or patterns, plant operation experts can improve the effectiveness of the alarm system through alarm rationalization so that this will help the operator in making the plant more safe, reliable and productive. The main objectives of this work are the following: (i) to use a definitive method to represent alarm data in an alarm log which is Temporal data as Itemsets without a need for complex mathematical, statistical or visual methods; (ii) to use data mining algorithms for identifying Frequent sequences which can be implemented on a normal computing resource such as Personal computer; (iii) to apply the method to the complete alarm data available no matter how big they are; (iv) to study and establish that the chosen method is possible to be applied to larger sized datasets.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80594793","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}
H. Al-Asadi, Huda A. Ahmed, Abdul-Hadi Al-Hassani, N. A. Ahmad Hambali
Because of the lack of fixed infrastructures, the existence of open media and diverse network topologies, internetworking networks and mobile ad hoc networks (MANET’s), the design of MANET protocols is complicated. In this paper, we propose an evolutionary trust mechanism imitating cognitive processes that uses sensitive information to avoid routing. Moreover, we propose an Enhanced Self-organizing Cooperation and Trust based (ESCT) Protocol, where the mobile nodes share self-reliance and interpret information from a cognitive point of view. Each node develops its information dynamically to eradicate malicious entities. The most attractive attribute of the proposed ESCT protocol, even if domestic attackers know how it operates, is to prevent infringements. In this paper, the efficiency of the proposed ESCT protocol is assessed for different routing disturbances and varying number of attackers. The results of a simulation show that, the proposed ESCT protocol supports diverse network platforms and provides an efficient routing method for MANET routers. The proposed ESCT protocol displays increased throughput, reduction in end-to-end delay and increase in packet delivery ratio when compared to the peers that were taken for comparison.
{"title":"A Novel and Enhanced Routing Protocol for Large Scale Disruption Tolerant Mobile Ad hoc Networks","authors":"H. Al-Asadi, Huda A. Ahmed, Abdul-Hadi Al-Hassani, N. A. Ahmad Hambali","doi":"10.47839/ijc.21.3.2688","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2688","url":null,"abstract":"Because of the lack of fixed infrastructures, the existence of open media and diverse network topologies, internetworking networks and mobile ad hoc networks (MANET’s), the design of MANET protocols is complicated. In this paper, we propose an evolutionary trust mechanism imitating cognitive processes that uses sensitive information to avoid routing. Moreover, we propose an Enhanced Self-organizing Cooperation and Trust based (ESCT) Protocol, where the mobile nodes share self-reliance and interpret information from a cognitive point of view. Each node develops its information dynamically to eradicate malicious entities. The most attractive attribute of the proposed ESCT protocol, even if domestic attackers know how it operates, is to prevent infringements. In this paper, the efficiency of the proposed ESCT protocol is assessed for different routing disturbances and varying number of attackers. The results of a simulation show that, the proposed ESCT protocol supports diverse network platforms and provides an efficient routing method for MANET routers. The proposed ESCT protocol displays increased throughput, reduction in end-to-end delay and increase in packet delivery ratio when compared to the peers that were taken for comparison.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86073648","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}
Approximate adders were proposed as feasible solution in error-tolerant applications to provide a proper trade-off with accuracy over other circuit-based metrics like energy, area, and delay. State of art of approximate adders are shown in this work to improve the operational features significantly. To acquire a most benefits of approximation, in this paper approximation at lower echelons is presented. Two speculative adders are proposed, one with approximate adder cell and other with Parallel prefix Adder cell. Gate level implementation of proposed model are designed and implemented. The cost functions are compared against various FPGA standard architectures. Results of proposed approach indicate an average of 46% improvement in Area Delay Product (ADP) and compared with existing approximate adders.
{"title":"High Speed Approximate Carry Speculative Adder in Error Tolerance Applications","authors":"Ajay Kumar Gottem, Arunmetha Sundaramoorthy, Aravindhan Alagarsamy","doi":"10.47839/ijc.21.3.2696","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2696","url":null,"abstract":"Approximate adders were proposed as feasible solution in error-tolerant applications to provide a proper trade-off with accuracy over other circuit-based metrics like energy, area, and delay. State of art of approximate adders are shown in this work to improve the operational features significantly. To acquire a most benefits of approximation, in this paper approximation at lower echelons is presented. Two speculative adders are proposed, one with approximate adder cell and other with Parallel prefix Adder cell. Gate level implementation of proposed model are designed and implemented. The cost functions are compared against various FPGA standard architectures. Results of proposed approach indicate an average of 46% improvement in Area Delay Product (ADP) and compared with existing approximate adders.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88685650","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}
Dmytro Polishchyk, V. Lysenko, Serhii Osadchiy, N. Zaiets
The article substantiates the management of the humidity and temperature regime of greenhouse complexes on the basis of a scenario-synergetic approach. The scenarios for controlling the temperature and humidity conditions in the greenhouse using the approach of fuzzy neural networks are formed. The structure of an automated control system for technological processes is developed, which provides automated collection and processing of information for the implementation of control actions in order to improve the efficiency of the greenhouse complex on the basis of a scenario-synergetic approach. The corresponding fuzzy neural networks are synthesized for a synergistic assessment of the interaction of technological parameters. Estimation of the root-mean-square error in the synthesis of fuzzy neural networks confirms the possibility of their use for the synergistic formation of scenarios for controlling the temperature and humidity regime in greenhouses to reveal the presence of a synergistic effect. Production rules for scenario management of temperature and humidity conditions are formed. It is shown that the use of fuzzy neural networks for the formation of scenarios for controlling the humidity and temperature regime provides the possibility of obtaining the appropriate scenarios for making managerial decisions and their prompt correction.
{"title":"Intellectual Scenario-synergetic Control of the Humidity and Temperature Regime of the Greenhouse Facilities","authors":"Dmytro Polishchyk, V. Lysenko, Serhii Osadchiy, N. Zaiets","doi":"10.47839/ijc.21.3.2686","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2686","url":null,"abstract":"The article substantiates the management of the humidity and temperature regime of greenhouse complexes on the basis of a scenario-synergetic approach. The scenarios for controlling the temperature and humidity conditions in the greenhouse using the approach of fuzzy neural networks are formed. The structure of an automated control system for technological processes is developed, which provides automated collection and processing of information for the implementation of control actions in order to improve the efficiency of the greenhouse complex on the basis of a scenario-synergetic approach. The corresponding fuzzy neural networks are synthesized for a synergistic assessment of the interaction of technological parameters. Estimation of the root-mean-square error in the synthesis of fuzzy neural networks confirms the possibility of their use for the synergistic formation of scenarios for controlling the temperature and humidity regime in greenhouses to reveal the presence of a synergistic effect. Production rules for scenario management of temperature and humidity conditions are formed. It is shown that the use of fuzzy neural networks for the formation of scenarios for controlling the humidity and temperature regime provides the possibility of obtaining the appropriate scenarios for making managerial decisions and their prompt correction.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72728543","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}
In recent years, the need for analytics on large volumes of data has become increasingly important. It turns out to be extremely useful in making strategic decisions about different applications. In this way, appropriate mechanisms must be designed to carry out data processing and integration with different platforms to take advantage of their best features. In this work, an architecture that works on cloud services is shown to migrate data stored in Big Query to an analytics engine such as Elasticsearch and take advantage of its potential in query, insert and display operations. This is accomplished through the use of Cloud Functions and Pub / Sub. The integration of these platforms through the proposed architecture showed 100% effectiveness when transferring data to another, maintaining an insertion rate of 4,138.30 documents per second, demonstrating its robustness, efficiency, and versatility when performing a data migration. This pretends to establish an architecture solution when it comes about handling a large amount of data as in the real world.
{"title":"A Cloud Pub/Sub Architecture to Integrate Google Big Query with Elasticsearch using Cloud Functions","authors":"Sergio Laureano Gutiérrez, Yasiel Pérez Vera","doi":"10.47839/ijc.21.3.2694","DOIUrl":"https://doi.org/10.47839/ijc.21.3.2694","url":null,"abstract":"In recent years, the need for analytics on large volumes of data has become increasingly important. It turns out to be extremely useful in making strategic decisions about different applications. In this way, appropriate mechanisms must be designed to carry out data processing and integration with different platforms to take advantage of their best features. In this work, an architecture that works on cloud services is shown to migrate data stored in Big Query to an analytics engine such as Elasticsearch and take advantage of its potential in query, insert and display operations. This is accomplished through the use of Cloud Functions and Pub / Sub. The integration of these platforms through the proposed architecture showed 100% effectiveness when transferring data to another, maintaining an insertion rate of 4,138.30 documents per second, demonstrating its robustness, efficiency, and versatility when performing a data migration. This pretends to establish an architecture solution when it comes about handling a large amount of data as in the real world.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81636795","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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