样式: 排序: IF: - GO 导出 标记为已读
-
Federated computation: a survey of concepts and challenges Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-11-23 Akash Bharadwaj, Graham Cormode
-
Balanced parallel triangle enumeration with an adaptive algorithm Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-07-13 Abir Farouzi, Xiantian Zhou, Ladjel Bellatreche, Mimoun Malki, Carlos Ordonez
-
SimCost: cost-effective resource provision prediction and recommendation for spark workloads Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-06-22 Yuxing Chen, Mohammad A. Hoque, Pengfei Xu, Jiaheng Lu, Sasu Tarkoma
-
Scalable top-k query on information networks with hierarchical inheritance relations Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-06-03 Fubao Wu, Lixin Gao
-
Multi-model query languages: taming the variety of big data Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-31 Qingsong Guo, Chao Zhang, Shuxun Zhang, Jiaheng Lu
-
Performance models of data parallel DAG workflows for large scale data analytics Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-23 Juwei Shi, Jiaheng Lu
-
On combining system and machine learning performance tuning for distributed data stream applications Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-17 Lambros Odysseos, Herodotos Herodotou
-
Adaptive update handling for graph HTAP Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-14 Muhammad Attahir Jibril, Alexander Baumstark, Kai-Uwe Sattler
-
GTraclus: a novel algorithm for local trajectory clustering on GPUs Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-13 Hamza Mustafa, Clark Barrus, Eleazar Leal, Le Gruenwald
-
DOE: database offloading engine for accelerating SQL processing Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-13 Hao Kong, Wenyan Lu, Yan Chen, Jingya Wu, Yu Zhang, Guihai Yan, Xiaowei Li
-
Adaptive query compilation in graph databases Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-12 Alexander Baumstark, Muhammad Attahir Jibril, Kai-Uwe Sattler
-
BOUNCE: memory-efficient SIMD approach for lightweight integer compression Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-10 Juliana Hildebrandt, Dirk Habich, Wolfgang Lehner
-
Out-of-the-box library support for DBMS operations on GPUs Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-05-10 Harish Kumar Harihara Subramanian, Bala Gurumurthy, Gabriel Campero Durand, David Broneske, Gunter Saake
-
Novel insights on atomic synchronization for sort-based group-by on GPUs Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-04-24 Bala Gurumurthy, David Broneske, Martin Schäler, Thilo Pionteck, Gunter Saake
-
STIF: Intuitionistic fuzzy Gaussian membership function with statistical transformation weight of evidence and information value for private information preservation Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-04-21 G. Sathish Kumar, K. Premalatha
-
S3QLRDF: distributed SPARQL query processing using Apache Spark—a comparative performance study Distrib. Parallel. Databases (IF 1.2) Pub Date : 2023-01-24 Mahmudul Hassan, Srividya Bansal
-
Challenges and future directions for energy, latency, and lifetime improvements in NVMs Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-09-21 Saeed Kargar, Faisal Nawab
-
Four node graphlet and triad enumeration on distributed platforms Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-30 Yudi Santoso, Xiaozhou Liu, Venkatesh Srinivasan, Alex Thomo
-
Scalable probabilistic truss decomposition using central limit theorem and H-index Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-25 Fatemeh Esfahani, Mahsa Daneshmand, Venkatesh Srinivasan, Alex Thomo, Kui Wu
-
Structured data transformation algebra (SDTA) and its applications Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-20 Jie Song, George Alter, H. V. Jagadish
-
ReSKY: Efficient Subarray Skyline Computation in Array Databases Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-17 Dalsu Choi, Hyunsik Yoon, Yon Dohn Chung
-
Bio-SODA UX: enabling natural language question answering over knowledge graphs with user disambiguation Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-16 Ana Claudia Sima, Tarcisio Mendes de Farias, Maria Anisimova, Christophe Dessimoz, Marc Robinson-Rechavi, Erich Zbinden, Kurt Stockinger
-
Recursive SQL and GPU-support for in-database machine learning Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-07-09 Maximilian E. Schüle, Harald Lang, Maximilian Springer, Alfons Kemper, Thomas Neumann, Stephan Günnemann
-
Searching semantically diverse paths Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-06-15 Xu Teng, Goce Trajcevski, Andreas Züfle
-
Cob: a leaderless protocol for parallel Byzantine agreement in incomplete networks Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-05-28 Andrea Flamini, Riccardo Longo, Alessio Meneghetti
-
An SGX-based execution framework for smart contracts upon permissioned blockchain Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-05-23 Min Fang, Zhao Zhang, Cheqing Jin, Aoying Zhou
-
BlockGraph: a scalable secure distributed ledger that exploits locality Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-05-21 Seth Copen Goldstein, Sixiang Gao, Zhenbo Sun
-
OptSmart: a space efficient Optimistic concurrent execution of Smart contracts Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-05-09 Parwat Singh Anjana, Sweta Kumari, Sathya Peri, Sachin Rathor, Archit Somani
-
BBoxDB streams: scalable processing of multi-dimensional data streams Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-05-02 Jan Kristof Nidzwetzki, Ralf Hartmut Güting
-
Subscribing to big data at scale Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-04-07 Xikui Wang, Michael J. Carey, Vassilis J. Tsotras
-
MICAR: multi-inhabitant context-aware activity recognition in home environments Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-04-05 Luca Arrotta, Claudio Bettini, Gabriele Civitarese
-
A novel role-mapping algorithm for enhancing highly collaborative access control system Distrib. Parallel. Databases (IF 1.2) Pub Date : 2022-03-31 Doaa Abdelfattah, Hesham A. Hassan, Fatma A. Omara
-
Virtual machines pre-copy live migration cost modeling and prediction: a survey Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-12-06 Mohamed Esam Elsaid, Hazem M. Abbas, Christoph Meinel
Live migration is an essential feature in virtual infrastructure and cloud computing datacenters. Using live migration, virtual machines can be online migrated from a physical machine to another with negligible service interruption. Load balance, power saving, dynamic resource allocation, and high availability algorithms in virtual data-centers and cloud computing environments are dependent on live
-
HTD: heterogeneous throughput-driven task scheduling algorithm in MapReduce Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-10-28 Xite Wang, Chaojin Wang, Mei Bai, Qian Ma, Guanyu Li
As one of the most popular parallel data processing models, data analysis system MapReduce has been widely used in many fields. Task scheduling is the core module in MapReduce system, and the quality of the scheduling algorithm directly affects the processing capacity of the system. Since new nodes need to be continuously added in the cluster to improve the processing capacity of the cluster, objectively
-
MISS: finding optimal sample sizes for approximate analytics Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-10-21 Xuebin Su, Hongzhi Wang
Nowadays, sampling-based Approximate Query Processing (AQP) is widely regarded as a promising way to achieve interactivity in big data analytics. To build such an AQP system, finding the minimal sample size for a query regarding given error constraints in general, called Sample Size Optimization (SSO), is an essential yet unsolved problem. Ideally, the goal of solving the SSO problem is to achieve
-
A framework for discovering popular paths using transactional modeling and pattern mining Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-09-20 P. Revanth Rathan, P. Krishna Reddy, Anirban Mondal
While the problems of finding the shortest path and k-shortest paths have been extensively researched, the research community has been shifting its focus towards discovering and identifying paths based on user preferences. Since users naturally follow some of the paths more than other paths, the popularity of a given path often reflects such user preferences. Given a set of user traversals in a road
-
Mutual-contained access delegation scheme for the Internet of Things user services Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-09-03 N. Panneerselvam, S. Krithiga
Internet of Things (IoT) has gained significance in different real-time applications due to its pervasive access response to user demands. This is a heterogeneous and open platform in which the data provenance, access permissions, and concealed data sharing features are exposed to external threats. Several methods that have been designed compromise with either complexity or limited security in delivering
-
Double layer secure secret images sharing scheme for biometrics Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-25 Gunasekaran, Elavarasi, Muthuraman, Vanitha
Biometric strategy is primarily followed for authentication which incorporates the distinct recognition of the individual depending on their physical or behavioral features. Among all the biometrics techniques, ‘Iris scanning’ is touted to be the most secure technique due to its uniqueness and constancy. However, it is challenging to safely store the iris template in database since it can be stolen
-
FIGS-DEAF: an novel implementation of hybrid deep learning algorithm to predict autism spectrum disorders using facial fused gait features Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-24 Saranya, A., Anandan, R.
Autism spectrum disorder (A.S.D.) is considered a heterogeneous mental disorder, which is notoriously difficult to identify for a better diagnosis, especially among children. The current diagnosis methodology is purely based on the behavioural observation of symptoms prone to misdiagnosis. Several hybrid methods were explored, which also needs its improvisation in better prediction and diagnosis to
-
Deep learning-based computer aided diagnosis model for skin cancer detection and classification Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-23 Adla, Devakishan, Reddy, G. Venkata Rami, Nayak, Padmalaya, Karuna, G.
Skin cancer is a commonly occurring disease, which affects people of all age groups. Automated detection of skin cancer is needed to decrease the death rate by identifying the diseases at the initial stage. The visual inspection during the medical examination of skin lesions is a tedious process as the resemblance among the lesions exists. Recently, imaging-based Computer Aided Diagnosis (CAD) model
-
Detection of breast cancer using the infinite feature selection with genetic algorithm and deep neural network Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-07 Ittannavar, S. S., Havaldar, R. H.
The breast cancer is a major health issue worldwide, so the early detection of abnormalities decreases the mortality rate. For the early detection of breast cancer, a new model is proposed in this research using mammogram images which is an effective technique used for screening and detecting the breast cancer. At first, the images are acquired from the digital database for screening mammography and
-
Application of machine learning (ML) and internet of things (IoT) in healthcare to predict and tackle pandemic situation Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-07 Sitharthan, R., Rajesh, M.
The pandemic situation has pretentious the habitual life of the human, it also has surpassed the regional, social, business activities and forced human society to live in a limited boundary. In this paper, the application of the internet of things (IoT) and machine learning (ML) based system to combat pandemic situation in health care application has been discussed. The developed ML and IoT based monitoring
-
Super-resolution reconstruction algorithm for aerial image data management based on deep learning Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-06 Xie, Bing, Niu, Fengjuan
Deep learning aims to learn the internal laws and representation levels of sample data. The information obtained in the learning process is of great help in the interpretation of data such as text, images and sounds. With the continuous development of modern technology, vision-based autonomous navigation technology, as the core of UAV technology, has received extensive attention worldwide. However
-
Research on network abnormal data flow mining based on improved cluster analysis Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-04 Jia, Xiaoqiang
Aiming at the problems of traditional methods that cannot adapt to the interference of noise or abnormal data, the data mining time is long, and the data mining accuracy is low, a network abnormal data stream mining method based on improved clustering analysis is proposed. By establishing a preprocessing model for abnormal network data flow, real-time data flow query is realized. Construct a network
-
Optimization method of machining parameters based on intelligent algorithm Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-03 Cai, Jie, Zhang, Wei, Deng, Jinlian, Zhao, Weisheng
The processing parameters have a particularly significant impact on the quality and efficiency of processing. Selecting the correct processing parameters can greatly improve the processing performance of the machine tool. To this end, by improving the chromosome structure and genetic operators of the GA algorithm, a new GA-BP neural network algorithm is proposed and combined BP neural network method
-
DLFPM-SSO-PE: privacy-preserving and security of intermediate data in cloud storage Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-08-02 V., Sarala, Shanmugapriya, P.
Nowadays, cloud computing has played a vital role in most data-intensive applications to store the data in the intermediated dataset. This effective cloud storage process helps to minimize the storage and processing cost while performing recomputing. Although the cloud provides numerous services, resources maintaining cost, outsourced user data protection from unauthorized users, the privacy of sensitive
-
Immersive online biometric authentication algorithm for online guiding based on face recognition and cloud-based mobile edge computing Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-16 Peng Su
The Internet deconstructs and reshapes the traditional classroom organization, the status of teachers, the authority of teaching materials and the role of students. Online Ideological and political education with the help of the Internet has become an inevitable trend of Ideological and political education. Mobile edge computing solves the high delay barrier when traditional cloud computing center
-
Improved data clustering methods and integrated A-FP algorithm for crop yield prediction Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-15 P. Suvitha Vani, S. Rathi
Big data analysis is the process of gathering, managing and analyzing a large volume of data to determine patterns and other valuable information. Agricultural data can be a significant area of big data applications. The big data analysis for agricultural data can comprise the various data from both internal systems and outside sources like weather data, soil data, and crop data. Though big data analysis
-
Multiple ground/aerial parcel delivery problem: a Weighted Road Network Voronoi Diagram based approach Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-12 Po-wei Harn, Ji Zhang, Ting Shen, Wenlu Wang, Xunfei Jiang, Wei-Shinn Ku, Min-Te Sun, Yao-Yi Chiang
The Multiple Ground/Aerial Parcel Delivery Problem (MGAPDP), an extension of the Ground/Aerial Parcel Delivery Problem (GAPDP), aims to find an optimal partition that minimizes the overall delivery time of all trucks by serving all destinations once and returning to the distribution center. This paper presents two heuristic solutions to the MGAPDP based on the Weighted Road Network Voronoi Diagram
-
An early warning model for the stuck-in medical drilling process based on the artificial fish swarm algorithm and SVM Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-07 Zhongyan Xian, Hai Yang
To avoid the considerable challenges and losses caused by stuck drilling to normal drilling operations, this article analyses the mechanism of stuck drilling, then combines the artificial fish swarm algorithm (AFSA) and support vector machine (SVM), and finally proposes an early warning model for the stuck-in medical drilling process based on the AFSA and SVM. The model realizes real-time sticking
-
Dynamic Multilevel Scheduling Strategy (MSS) mechanism for commercial multi-cloud surroundings Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-02 D. Selvapandian, R. Santhosh
An assortment of virtualized assets that makes planning a basic segment is dealt in Cloud Computing (CC). Cloud manufacturing is another concept worldview that has pulled in a lot of examination interest around the world. Cloud manufacturing conveys on-request fabricating administrations to customers over the Internet. One of the basic methods is planning for accomplishing the point of cloud fabricating
-
CTRV: resource based task consolidation approach in cloud for green computing Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-07-01 M. S. Mekala, P. Viswanathan
Dynamic resource provisioning is a main challenge in cloud computing due to distinct task resource requirements. An abnormal workload creates resource famine, resource wastage, haphazard resource and task allocation that influence task scheduling, and machine resource usage leads to SLA violation. To cope-up this issue, we propose a strategy Categorization of a Task with a Resource to assign VM (CTRV)
-
Detection of Alzheimer’s disease using grey wolf optimization based clustering algorithm and deep neural network from magnetic resonance images Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-06-26 Halebeedu Subbaraya Suresha, Srirangapatna Sampathkumaran Parthasarathy
The automated magnetic resonance imaging (MRI) processing techniques are gaining more importance in Alzheimer disease (AD) recognition, because it effectively diagnosis the pathology of the brain. Currently, computer aided diagnosis based on image analysis is an emerging tool to support AD diagnosis. In this research study, a new system is developed for enhancing the performance of AD recognition.
-
Healthcare Cramér Generative Adversarial Network (HCGAN) Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-06-25 R. Indhumathi, S. Sathiya Devi
Medical data is shared with a wide range for various research purposes and an extensive amount of research has been developed in the data privacy community for anonymization. Unfortunately, Data anonymization techniques do not provide data privacy guarantees and synthetic data generation is an alternative approach in data anonymization. Deep learning has recently achieved more reputation for its high
-
Remote sensing imaging analysis and ubiquitous cloud-based mobile edge computing based intelligent forecast of forest tourism demand Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-06-03 Zhang Rui, Zhang Jingran, Wang Wukui
With the development of society and the improvement of people's living standards, ecotourism based on forest ecological environment has become an urgent need of urban and rural people. Forest leisure tourism is different from traditional sightseeing tourism. The differences between them are not only reflected in consumption purpose, consumption behavior, consumption grade and consumption form, but
-
A distributed submerged object detection and classification enhancement with deep learning Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-05-22 E. S. Madhan, K. S. Kannan, P. Shobha Rani, J. Vakula Rani, Dinesh Kumar Anguraj
Research in the autonomous underwater detection system has become rapidly increasing in Ocean Technology. In a recent object detection research study, there a need to enhance the quality, which needs to handle submerged object image processing techniques and a lot of demand to develop an intelligent vision system to improve the Blurred Images and low-quality illumination. Manual research in undersea
-
Multi-objective swarm-based model for deploying virtual machines on cloud physical servers Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-05-20 D. Saravanan, R. Rajakumar, M. Sreedevi, K. Dinesh, S. V. Sudha, Dinesh Kumar Anguraj, Azath Mubarakali
The physical cloud servers consists of \(n\) number of machines for serving the requirements posted via Virtual Machines by the users. The allocation of requested Virtual Machines to appropriate Physical Servers is one among the challenging task exists in Cloud Computing. During the deployment phase several objectives needs to be considered which includes the total power consumption, the resource wastage
-
A novel resource management framework in a cloud computing environment using hybrid cat swarm BAT (HCSBAT) algorithm Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-05-11 A. M. Senthil Kumar, K. Padmanaban, A. K. Velmurugan, X. S. Asha Shiny, Dinesh Kumar Anguraj
Resource management is an important issue in the cloud computing paradigm. The maximum Utilization of resources leads the service providers to get maximum profit. The suitable resources in the cloud data centre are needed to satisfy the user needs. The selection of the right resource is very essential in the data centre. Metaheuristic algorithms are used to perform the task allocation in the cloud
-
Self-adapting data migration in the context of schema evolution in NoSQL databases Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-04-30 Andrea Hillenbrand, Uta Störl, Shamil Nabiyev, Meike Klettke
When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, data is routinely stored in different versions. The management of versioned data leads to an overhead potentially impeding the software development. Several data migration strategies exist that handle legacy data differently during data accesses, each of which can be characterized
-
Security and privacy issue in multi-cloud accommodating Intrusion Detection System Distrib. Parallel. Databases (IF 1.2) Pub Date : 2021-04-28 T. Mohanraj, R. Santhosh
Cloud Computing (CC) is an innovative worldview technique that allows for the registration of resources. Some examples of computing resources are an organization, stockpiling, applications, and administrations when there is an interesting perspective. In CC, the assets are shared by Cloud customers. A registered framework is given by the cloud which is an advanced stage on which clients can build up