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The number of linked data sources and the size of the linked open data graph keep growing every day. As a consequence, semantic RDF services are more and more confronted to various "big data" problems. Query processing is one of them and…

Databases · Computer Science 2016-11-04 Hubert Naacke , Olivier Curé , Bernd Amann

Priority queues are fundamental data structures with widespread applications in various domains, including graph algorithms and network simulations. Their performance critically impacts the overall efficiency of these algorithms.…

Data Structures and Algorithms · Computer Science 2023-11-27 Kiarash Parvizi

The computation of the skyline provides a mechanism for utilizing multiple location-based criteria to identify optimal data points. However, the efficiency of these computations diminishes and becomes more challenging as the input data…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-05 Chen Li , Ye Zhu , Yang Cao , Jinli Zhang , Annisa Annisa , Debo Cheng , Yasuhiko Morimoto

The increase in the use of the Internet and web services and the advent of the fifth generation of cellular network technology (5G) along with ever-growing Internet of Things (IoT) data traffic will grow global internet usage. To ensure the…

Networking and Internet Architecture · Computer Science 2022-12-13 Ramin Atefinia , Mahmood Ahmadi

Consensus protocols are the foundation for building fault-tolerant, distributed systems, and services. They are also widely acknowledged as performance bottlenecks. Several recent systems have proposed accelerating these protocols using the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-28 Huynh Tu Dang , Pietro Bressana , Han Wang , Ki Suh Lee , Noa Zilberman , Hakim Weatherspoon , Marco Canini , Fernando Pedone , Robert Soulé

In the most popular distributed stream processing frameworks (DSPFs), programs are modeled as a directed acyclic graph. This model allows a DSPF to benefit from the parallelism power of distributed clusters. However, choosing the proper…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-03 Hamid Nasiri , Saeed Nasehi , Arman Divband , Maziar Goudarzi

The general increase in data size and data sharing motivates the adoption of Big Data strategies in several scientific disciplines. However, while several options are available, no particular guidelines exist for selecting a Big Data…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-04 Mathieu Dugré , Valérie Hayot-Sasson , Tristan Glatard

Clustering of image is one of the important steps of mining satellite images. In our experiment we have simultaneously run multiple K-means algorithms with different initial centroids and values of k in the same iteration of MapReduce jobs.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-09 Tapan Sharma , Dr. Vinod Shokeen , Dr. Sunil Mathur

Apriori is one of the key algorithms to generate frequent itemsets. Analyzing frequent itemset is a crucial step in analysing structured data and in finding association relationship between items. This stands as an elementary foundation to…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-12-20 Anjan K. Koundinya , Srinath N. K. , K. A. K. Sharma , Kiran Kumar , Madhu M. N. , Kiran U. Shanbag

With the overwhelming amount of complex and heterogeneous data pouring from any-where, any-time, and any-device, there is undeniably an era of Big Data. The emergence of the Big Data as a disruptive technology for next generation of…

Databases · Computer Science 2019-03-01 Ravi Ranjan , Aditi Sharma

Sheer increase in volume of data over the last decade has triggered research in cluster computing frameworks that enable web enterprises to extract big insights from big data. While Apache Spark is gaining popularity for exhibiting superior…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-03 Ahsan Javed Awan , Mats Brorsson , Vladimir Vlassov , Eduard Ayguade

The goal of ranking and selection (R&S) procedures is to identify the best stochastic system from among a finite set of competing alternatives. Such procedures require constructing estimates of each system's performance, which can be…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-17 Eric C. Ni , Dragos F. Ciocan , Shane G. Henderson , Susan R. Hunter

Parallel computing is the fundamental base for MapReduce framework in Hadoop. Each data chunk is replicated over 3 servers for increasing availability of data and decreasing probability of data loss. Hence, the 3 servers that have Map task…

Performance · Computer Science 2020-07-21 Amirali Daghighi , Jim Q. Chen

Recently, MapReduce based spatial query systems have emerged as a cost effective and scalable solution to large scale spatial data processing and analytics. MapReduce based systems achieve massive scalability by partitioning the data and…

Databases · Computer Science 2015-09-04 Ablimit Aji , Vo Hoang , Fusheng Wang

In the big data era of observational oceanography, passive acoustics datasets are becoming too high volume to be processed on local computers due to their processor and memory limitations. As a result there is a current need for our…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-10 Paul Nguyen Hong Duc , Dorian Cazau

In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-27 Noopur Gupta , Rakesh K. Lenka , Rabindra K. Barik , Harishchandra Dubey

The paradigm of big data is characterized by the need to collect and process data sets of great volume, arriving at the systems with great velocity, in a variety of formats. Spark is a widely used big data processing system that can be…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-29 Duarte M. Nascimento , Miguel Ferreira , Miguel L. Pardal

Nowadays, the size of the Internet is experiencing rapid growth. As of December 2014, the number of global Internet websites has more than 1 billion and all kinds of information resources are integrated together on the Internet, however,the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-02 Qingpei Guo , Chao Xu , Yang Song

The accelerated evolution and explosion of the Internet and social media is generating voluminous quantities of data (on zettabyte scales). Paramount amongst the desires to manipulate and extract actionable intelligence from vast big data…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-31 Dillon Mark Rose , Jean Michel Rouly , Rana Haber , Nenad Mijatovic , Adrian M. Peter

In a typical Internet-of-Things setting that involves scientific applications, a target computation can be evaluated in many different ways depending on the split of computations among various devices. On the one hand, different…

Performance · Computer Science 2022-08-09 Aravind Sankaran , Paolo Bientinesi
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