Forthcoming and Online First Articles

International Journal of Big Data Intelligence

International Journal of Big Data Intelligence (IJBDI)

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International Journal of Big Data Intelligence (5 papers in press)

Regular Issues

  • Map reduce-based scalable Lempel-Ziv and application in route prediction   Order a copy of this article
    by Vishnu Shankar Tiwari, Sudha Chaturvedi, Arti Arya 
    Abstract: Prediction of route based on historical trip observation of users is widely employed in location-based services. This work concentrates on building a route prediction system using Lempel-Ziv technique applied to a historical corpus of user travel data. Huge continuous logs of historical GPS traces representing the user’s location in past are decomposed into smaller logical units known as trips. User trips are converted into sequences of road network edges using a process known as map matching. Lempel-Ziv is applied on road network edges to build the prediction model that captures the user’s travel pattern in the past. A two-phased model is proposed using a map reduce framework without losing accuracy and efficiency. Model is then used to predict the user’s end-to-end route given a partial route travelled by the user at any point in time. The objective of the proposed work is to build a Route Prediction system in which model building and prediction both are horizontally scalable.
    Keywords: Lempel-Ziv; route prediction; horizontally scalable; map reduce; distributed computing.
    DOI: 10.1504/IJBDI.2022.10047952
  • Resource monitoring framework for big raw data processing   Order a copy of this article
    by Mayank Patel, Minal Bhise 
    Abstract: Scientific experiments, simulations, and modern applications generate large amounts of data. Analysing resources required to process such big datasets is essential to identify application running costs for cloud or in-house deployments. Researchers have proposed keeping data in raw formats to avoid upfront utilisation of resources. However, it poses reparsing issues for frequently accessed data. The paper discusses detailed comparative analysis of resources required by in-situ engines and traditional database management systems to process a real-world scientific dataset. A resource monitoring framework has been developed and incorporated into the raw data query processing framework to achieve this goal. The work identified different query types best suited to a given data processing tool in terms of data to result time and resource requirements. The analysis of resource utilisation patterns has led to the development of query complexity aware (QCA) and resource utilisation aware (RUA) data partitioning techniques to process big raw data efficiently. Resource utilisation data have been analysed to estimate the data processing capacity of a given machine.
    Keywords: big raw data; database management systems; DBMSs; in-situ engines; query processing; resource monitoring.
    DOI: 10.1504/IJBDI.2023.10053408
  • On large automata processing: towards a high level distributed graph language   Order a copy of this article
    by Alpha Mouhamadou Diop, Cheikh BA 
    Abstract: Large graphs or automata have their data that cannot fit in a single machine, or may take unreasonable time to be processed. We implement with MapReduce and Giraph two algorithms for intersecting and minimising large and distributed automata. We provide some comparative analysis, and the experiment results are depicted in figures. Our work experimentally validates our propositions as long as it shows that our choice, in comparison with MapReduce one, is not only more suitable for graph-oriented algorithms, but also speeds the executions up. This work is one of the first steps of a long-term goal that consists in a high level distributed graph processing language.
    Keywords: big data; large graphs and automata; distributed computing; MapReduce; bulk synchronous parallel; BSP.
    DOI: 10.1504/IJBDI.2023.10059910
  • To be intelligent or not to be? That is the question - reflection and insights about big knowledge systems: definition, model and semantics   Order a copy of this article
    by Ruqian Lu 
    Abstract: This paper aims to share the author’s vision on possible research directions for big knowledge-based AI. A renewed definition of big knowledge (BK) and big knowledge systems (BKS) is first introduced. Then the first BKS model, called cloud knowledge social intelligence (CKEI) is provided with a hierarchy of knowledge as a service (KAAS). At last, a new semantics, the big-and-broad step axiomatic structural operational semantics (BBASOS) for applications on BKS is introduced and discussed with a practical distributed BKS model knowledge graph network KGN and a mini example.
    Keywords: big knowledge system; BKS; CKEI model; cloud knowledge as a service; CKaaS; social intelligence; crowd intelligence; big and broad axiomatic structural operational semantics; KGN model; KGN-Prolog language.
    DOI: 10.1504/IJBDI.2023.10061439
  • Hybrid encryption of fernet and initialisation vector with attribute-based encryption: a secure and flexible approach for data protection   Order a copy of this article
    by Madhavi Sadu 
    Abstract: The continuous growth and importance of data, the need for strong data protection becomes crucial. Encryption plays a vital role in preserving the confidentiality of data, and attribute-based encryption (ABE) offers a meticulous access control system based on attributes. This study investigates the integration of Fernet encryption with initialisation vector (IV) and ABE, resulting in a hybrid encryption approach that enhances both security and flexibility. By combining the advantages of Fernet encryption and IV-based encryption, the hybrid encryption scheme establishes an effective and robust mechanism for safeguarding data. Fernet encryption, renowned for its simplicity and efficiency, provides authenticated encryption, guaranteeing both the confidentiality and integrity of the data. The incorporation of an initialisation vector (IV) introduces an element of randomness into the encryption process, thereby strengthening the overall security measures. This research paper discusses the advantages and drawbacks of the hybrid encryption of Fernet and IV with ABE.
    Keywords: hybrid encryption; fernet; initialisation vector; IV; attribute-based encryption; ABE; data protection; access control; security.
    DOI: 10.1504/IJBDI.2023.10062285