发布求助
文献互助 智能选刊 最新文献

International Journal of Grid and High Performance Computing最新文献

筛选
英文 中文
Performance Comparison of Various Algorithms During Software Fault Prediction 软件故障预测中各种算法的性能比较
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-04-01 DOI: 10.4018/IJGHPC.2021040105
Munish Khanna, Abhishek Toofani, Siddharth Bansal, M. Asif
{"title":"Performance Comparison of Various Algorithms During Software Fault Prediction","authors":"Munish Khanna, Abhishek Toofani, Siddharth Bansal, M. Asif","doi":"10.4018/IJGHPC.2021040105","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040105","url":null,"abstract":"Producing software of high quality is challenging in view of the large volume, size, and complexity of the developed software. Checking the software for faults in the early phases helps to bring down testing resources. This empirical study explores the performance of different machine learning model, fuzzy logic algorithms against the problem of predicting software fault proneness. The work experiments on the public domain KC1 NASA data set. Performance of different methods of fault prediction is evaluated using parameters such as receiver characteristics (ROC) analysis and RMS (root mean squared), etc. Comparison is made among different algorithms/models using such results which are presented in this paper.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"193 1","pages":"70-94"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83085124","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}
引用次数: 0
Network Blueprint for Maximizing the Lifetime of Smart Devices in Low Power IoT Networks 在低功耗物联网网络中最大化智能设备寿命的网络蓝图
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-04-01 DOI: 10.4018/IJGHPC.2021040102
P. Sarwesh, K. Chandrasekaran, S. Thamizharasan
{"title":"Network Blueprint for Maximizing the Lifetime of Smart Devices in Low Power IoT Networks","authors":"P. Sarwesh, K. Chandrasekaran, S. Thamizharasan","doi":"10.4018/IJGHPC.2021040102","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040102","url":null,"abstract":"In the modern communication and computation era, internet of things (IoT) is developing as the key technology that satisfies the requirements of various applications. Prolonging device lifetime and maintaining network reliability is the evident objective for IoT network. Therefore, the authors come up with the network architecture that integrates node placement technique and routing technique. In the architecture, node placement is implemented by varying the density of nodes, by varying battery level of nodes, and by varying transmission range of nodes. Energy efficient and reliable path computation is addressed by routing technique. Therefore, enhancing the features of routing and node placement technique and integrating them together in network architecture can efficiently prolong the network lifetime. From the results, the authors observed that the proposed network architecture prolongs the network lifetime two times better than the standard model and also outperforms EQSR protocol and maintains the reliable data transfer.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"15 1","pages":"21-38"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86009701","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}
引用次数: 0
Remote Health Patient Monitoring System for Early Detection of Heart Disease 用于心脏病早期检测的远程健康患者监测系统
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-04-01 DOI: 10.4018/IJGHPC.2021040107
Gokulnath Chandra Babu, Shantharajah S. Periyasamy
{"title":"Remote Health Patient Monitoring System for Early Detection of Heart Disease","authors":"Gokulnath Chandra Babu, Shantharajah S. Periyasamy","doi":"10.4018/IJGHPC.2021040107","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040107","url":null,"abstract":"This paper presents a heart disease prediction model. Among the recent technology, internet of things-enabled healthcare plays a vital role. The medical sensors used in healthcare provide a huge volume of medical data in a continuous manner. The speed of data generation in IoT healthcare is high so the volume of data is also high. In order to overcome this problem, the proposed model is a novel three-step process to store and analyze the large volumes of data. The first step focuses on a collection of data from sensor devices. In Step 2, HBase has been used to store the large volume of medical sensor data from a wearable device to the cloud. Step 3 uses Mahout for devolving logistic regression-based prediction model. At last, ROC curve is used to find the parameters that cause heart disease.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"4 1","pages":"118-130"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72938044","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}
引用次数: 7
Neural Network Inversion-Based Model for Predicting an Optimal Hardware Configuration: Solving Computationally Intensive Problems 基于神经网络的预测最优硬件配置模型:解决计算密集型问题
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-04-01 DOI: 10.4018/IJGHPC.2021040106
M. M. Al-Qutt, H. Khaled, Rania El-Gohary
{"title":"Neural Network Inversion-Based Model for Predicting an Optimal Hardware Configuration: Solving Computationally Intensive Problems","authors":"M. M. Al-Qutt, H. Khaled, Rania El-Gohary","doi":"10.4018/IJGHPC.2021040106","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040106","url":null,"abstract":"Deciding the number of processors that can efficiently speed-up solving a computationally intensive problem while perceiving efficient power consumption constitutes a major challenge to researcher in the HPC high performance computing realm. This paper exploits machine learning techniques to propose and implement a recommender system that recommends the optimal HPC architecture given the problem size. An approach for multi-objective function optimization based on neural network (neural network inversion) is employed. The neural network inversion approach is used for forward problem optimization. The objective functions in concern are maximizing the speedup and minimizing the power consumption. The recommendations of the proposed prediction systems achieved more than 89% accuracy for both validation and testing set. The experiments were conducted on 2500 CUDA core on Tesla K20 Kepler GPU Accelerator and Intel(R) Xeon(R) CPU E5-2695 v2.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"87 1","pages":"95-117"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84559494","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}
引用次数: 1
Cloud Computing for Malicious Encrypted Traffic Analysis and Collaboration 基于云计算的恶意加密流量分析与协作
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/IJGHPC.2021070102
Tzung-Han Jeng, Wen-Yang Luo, Chuan-Chiang Huang, Chien-Chih Chen, Kuang-Hung Chang, Yi-Ming Chen
{"title":"Cloud Computing for Malicious Encrypted Traffic Analysis and Collaboration","authors":"Tzung-Han Jeng, Wen-Yang Luo, Chuan-Chiang Huang, Chien-Chih Chen, Kuang-Hung Chang, Yi-Ming Chen","doi":"10.4018/IJGHPC.2021070102","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021070102","url":null,"abstract":"As the application of network encryption technology expands, malicious attacks will also be protected by encryption mechanism, increasing the difficulty of detection. This paper focuses on the analysis of encrypted traffic in the network by hosting long-day encrypted traffic, coupled with a weighted algorithm commonly used in information retrieval and SSL/TLS fingerprint to detect malicious encrypted links. The experimental results show that the system proposed in this paper can identify potential malicious SSL/TLS fingerprints and malicious IP which cannot be recognized by other external threat information providers. The network packet decryption is not required to help clarify the full picture of the security incident and provide the basis of digital identification. Finally, the new threat intelligence obtained from the correlation analysis of this paper can be applied to regional joint defense or intelligence exchange between organizations. In addition, the framework adopts Google cloud platform and microservice technology to form an integrated serverless computing architecture.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"299 1","pages":"12-29"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73175852","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}
引用次数: 3
Remote Access NVMe SSD via NTB 通过NTB远程访问NVMe SSD
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/IJGHPC.2021070103
Yu-sheng Lin, Chi-Lung Wang, Chao-Tang Lee
{"title":"Remote Access NVMe SSD via NTB","authors":"Yu-sheng Lin, Chi-Lung Wang, Chao-Tang Lee","doi":"10.4018/IJGHPC.2021070103","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021070103","url":null,"abstract":"NVMe SSDs are deployed in data centers for applications with high performance, but its capacity and bandwidth are often underutilized. Remote access NVMe SSD enables flexible scaling and high utilization of Flash capacity and bandwidth within data centers. The current issue of remote access NVMe SSD has significant performance overheads. The research focuses on remote access NVMe SSD via NTB (non-transparent bridge). NTB is a type of PCI-Express; its memory mapping technology can allow to access memory belonging to peer servers. NVMe SSD supports multiple I/O queues to maximize the I/O parallel processing of flash; hence, NVMe SSD can provide significant performance when comparing with traditional hard drives. The research proposes a novel design based on features of NTB memory mapping and NVMe SSD multiple I/O queues. The remote and local servers can access the same NVMe SSD concurrently. The experimental results show the performance of remote access NVMe SSD can approach the local access. It is significantly excellent and proved feasible.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"2002 16","pages":"30-42"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72400464","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}
引用次数: 0
Modeling of Two-Level Checkpointing With Silent and Fail-Stop Errors in Grid Computing Systems 网格计算系统中具有静止和故障停止错误的两级检查点建模
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/ijghpc.2021010104
Rahaf Maher Ghazal, S. Jafar, M. Alhamad
{"title":"Modeling of Two-Level Checkpointing With Silent and Fail-Stop Errors in Grid Computing Systems","authors":"Rahaf Maher Ghazal, S. Jafar, M. Alhamad","doi":"10.4018/ijghpc.2021010104","DOIUrl":"https://doi.org/10.4018/ijghpc.2021010104","url":null,"abstract":"With the increase in high-performance computing platform size, it makes the system reliability more challenging, and system mean time between failures (MTBF) may be too short to supply a total fault-free run. Thereby, to achieve greater benefit from these systems, the applications must include fault tolerance mechanisms to satisfy the required reliability. This manuscript focuses on grid computing platform that exposes to two types of threats: crash and silent data corruption faults, which cause the application's failure. This manuscript also addresses the problem of modeling resource availability and aims to minimize the overhead of checkpoint/recovery-fault tolerance techniques. Modeling resources faults has commonly been addressed with exponential distribution, but that isn't fully realistic for the transient errors, which appear randomly. In the manuscript, the authors use Weibull distribution to express these random faults to create the optimal time to save checkpoints.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"67 1","pages":"65-81"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87800606","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}
引用次数: 0
An Automated Self-Healing Cloud Computing Framework for Resource Scheduling 一种用于资源调度的自动化自修复云计算框架
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/ijghpc.2021010103
B. Dewangan, M. Venkatadri, A. Agarwal, Ashutosh Pasricha, T. Choudhury
{"title":"An Automated Self-Healing Cloud Computing Framework for Resource Scheduling","authors":"B. Dewangan, M. Venkatadri, A. Agarwal, Ashutosh Pasricha, T. Choudhury","doi":"10.4018/ijghpc.2021010103","DOIUrl":"https://doi.org/10.4018/ijghpc.2021010103","url":null,"abstract":"In cloud computing, applications, administrations, and assets have a place with various associations with various goals. Elements in the cloud are self-sufficient and self-adjusting. In such a collaborative environment, the scheduling decision on available resources is a challenge given the decentralized nature of the environment. Fault tolerance is an utmost challenge in the task scheduling of available resources. In this paper, self-healing fault tolerance techniques have been introducing to detect the faulty resources and measured the best resource value through CPU, RAM, and bandwidth utilization of each resource. Through the self-healing method, less than threshold values have been considering as a faulty resource and separate from the resource pool. The workloads submitted by the user have been assigned to the available best resource. The proposed method has been simulated in cloudsim and compared the multi-objective performance metrics with existing methods, and it is observed that the proposed method performs utmost.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"1 1","pages":"47-64"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76183684","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}
引用次数: 7
An Efficient Threshold-Fuzzy-Based Algorithm for VM Consolidation in Cloud Datacenter 一种基于阈值模糊的云数据中心虚拟机整合算法
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/ijghpc.2021010102
N. Baskaran, R. Eswari
{"title":"An Efficient Threshold-Fuzzy-Based Algorithm for VM Consolidation in Cloud Datacenter","authors":"N. Baskaran, R. Eswari","doi":"10.4018/ijghpc.2021010102","DOIUrl":"https://doi.org/10.4018/ijghpc.2021010102","url":null,"abstract":"Cloud computing has grown exponentially in the recent years. Data growth is increasing day by day, which increases the demand for cloud storage, which leads to setting up cloud data centers. But they consume enormous amounts of power, use the resources inefficiently, and also violate service-level agreements. In this paper, an adaptive fuzzy-based VM selection algorithm (AFT_FS) is proposed to address these problems. The proposed algorithm uses four thresholds to detect overloaded host and fuzzy-based approach to select VM for migration. The algorithm is experimentally tested for real-world data, and the performance is compared with existing algorithms for various metrics. The simulation results testify to the proposed AFT_FS method is the utmost energy efficient and minimizes the SLA rate compared to other algorithms.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"57 1","pages":"18-46"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88007859","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}
引用次数: 1
An Ensemble Deep Neural Network Model for Onion-Routed Traffic Detection to Boost Cloud Security 基于集成深度神经网络的洋葱路由流量检测模型提高云安全
IF 1
International Journal of Grid and High Performance Computing Pub Date : 2021-01-01 DOI: 10.4018/ijghpc.2021010101
Shamik Tiwari
{"title":"An Ensemble Deep Neural Network Model for Onion-Routed Traffic Detection to Boost Cloud Security","authors":"Shamik Tiwari","doi":"10.4018/ijghpc.2021010101","DOIUrl":"https://doi.org/10.4018/ijghpc.2021010101","url":null,"abstract":"Anonymous network communication using onion routing networks such as Tor are used to guard the privacy of sender by encrypting all messages in the overlapped network. These days most of the onion routed communications are not only used for decent cause but also cyber offenders are ill-using onion routings for scanning the ports, hacking, exfiltration of theft data, and other types of online frauds. These cyber-crime attempts are very vulnerable for cloud security. Deep learning is highly effective machine learning method for prediction and classification. Ensembling multiple models is an influential approach to increase the efficiency of learning models. In this work, an ensemble deep learning-based classification model is proposed to detect communication through Tor and non-Tor network. Three different deep learning models are combined to achieve the ensemble model. The proposed model is also compared with other machine learning models. Classification results shows the superiority of the proposed model than other models.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"4 1","pages":"1-17"},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78759697","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}
引用次数: 4
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信