J. S. Manjaly, T. Subbulakshmi^*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3083-3108, 2023, DOI:10.32604/csse.2023.036320

Abstract The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs. This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator (YARN) scheduler, called the Adaptive Node and Container Aware Scheduler (ANACRAC), that aligns cluster resources to the demands of the applications in the real world. The approach performs to leverage the user-provided configurations as a unique design to apportion nodes, or containers within the nodes, to application thresholds. Additionally, it provides the flexibility to the applications for selecting and choosing which node’s resources they… More >

Adnan Ali¹, Nada Masood Mirza^1,2, Mohamad Khairi Ishak^1,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 913-928, 2023, DOI:10.32604/csse.2023.036400

Abstract In the Big Data era, numerous sources and environments generate massive amounts of data. This enormous amount of data necessitates specialized advanced tools and procedures that effectively evaluate the information and anticipate decisions for future changes. Hadoop is used to process this kind of data. It is known to handle vast volumes of data more efficiently than tiny amounts, which results in inefficiency in the framework. This study proposes a novel solution to the problem by applying the Enhanced Best Fit Merging algorithm (EBFM) that merges files depending on predefined parameters (type and size). Implementing this algorithm will ensure that… More >

Keungyeup Ji, Youngmi Kwon^*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 201-214, 2023, DOI:10.32604/csse.2023.031270

Abstract As the importance of email increases, the amount of malicious email is also increasing, so the need for malicious email filtering is growing. Since it is more economical to combine commodity hardware consisting of a medium server or PC with a virtual environment to use as a single server resource and filter malicious email using machine learning techniques, we used a Hadoop MapReduce framework and Naïve Bayes among machine learning methods for malicious email filtering. Naïve Bayes was selected because it is one of the top machine learning methods(Support Vector Machine (SVM), Naïve Bayes, K-Nearest Neighbor(KNN), and Decision Tree) in… More >

Jin Wang^1,2, Yaqiong Yang¹, Jingyu Zhang^1,3,*, Xiaofeng Yu⁴, Osama Alfarraj⁵, Amr Tolba^5,6

Computer Systems Science and Engineering, Vol.35, No.6, pp. 523-532, 2020, DOI:10.32604/csse.2020.35.523

Abstract In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost hardwares. HDFS nodes communicate with… More >