Forthcoming articles

International Journal of System of Systems Engineering

International Journal of System of Systems Engineering (IJSSE)

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International Journal of System of Systems Engineering (7 papers in press)

Regular Issues

  • AN EMPIRICAL HYBRID DBN-EL SYSTEM MODEL FOR STOCK MARKET PREDICTION WITH BIG DATA   Order a copy of this article
    by Ishwarappa K, Anuradha Jagadeesan 
    Abstract: Recent years, big data analytics have become the prominent aspect for different sectors for the prediction of large datasets. The stock market is also the important exertions in the field of business in which big data play an important role for the prediction of stocks. For this reason, the big data and hybrid Deep Belief Network-Ensemble Learning (DBN-EL) model is proposed for analysis of large stock market data in order to improve the performance of its prediction. Here, the Hive based distributed database with MapReduce technique for storing and mapping of data into other for fast processing. Furthermore, the hybrid DBN-EL system model will be used as classifier for stock market prediction. The stock futures dataset is used for analysis. The simulation results shows that the proposed model outperforms by predicting the stock futures trend upto 98% when compared with other existing techniques in terms of precision, recall, and F-Measure.
    Keywords: Stock Market Prediction; Deep Belief Network (DBN); Ensemble Learning (EL); National Stock Exchange (NSE); Big Data; MapReduce.
    DOI: 10.1504/IJSSE.2021.10033298
     
  • PERFORMANCE ANALYSIS OF HYBRID CLASSIFICATION SYSTEM MODEL FOR BIG DATA STREAM USING INTERNET OF THINGS   Order a copy of this article
    by Gayathri Devi N, Manikandan K 
    Abstract: Big data and IoT have become the world’s prominent technology and reached a high impact on millions of people’s daily life that helps in managing environmental and physical systems processed in real-time. In this research, we proposed a hybrid classification system model named Multi-Output Regression with Deep Belief Networks (MOR-DBN) to improve the performance of the classifier when huge amount of streaming data is transferred from IoT devices. Moreover, the improved Privacy-Preserving Rotation based Condensation Algorithm (P2RoCAl) with Geometric Transformation is also used for obtaining high utility for data streaming to protect from various kinds of attacks during data reconstruction. The simulation results show that proposed framework obtains a high accuracy when compared with other existing algorithms in terms of precision, recall, and F-measure. Overall the proposed MOR_DBN model outperforms by obtaining a 96.21% for SSDS dataset, 97.89% for FRDS dataset, 95.7% for HPDS dataset, and 99.23% for ESDS dataset.
    Keywords: Multi-Output Regression (MOR); Deep Belief Network (DBN); Privacy Preserving Rotation based Condensation Algorithm (P2RoCAl); Geometric Transformation; Data Streaming; Big Data; Internet of Things.
    DOI: 10.1504/IJSSE.2021.10034877
     
  • An Efficient Vote Casting System with Aadhar Verification through Blockchain   Order a copy of this article
    by Kuppani Sathish, Basetty Mallikarjuna, J. Gitanjali, Venkata Krishna 
    Abstract: In the recent past security for vote casting system plays a vital role in the autonomous constitutional authority of election. A democratic country like India highly depends on the fail proof voting system to elect the government. The many security systems have evolved to ensure the electronic voting system to avoid malpractice during election. This paper describes an electoral system for the Indian election on blockchain technology and Aadhaar verification. The proposed system provides optimal security for the voting system and preserves votes stored in the Electronic Voting Machine (EVM). The technology behind blockchain and Aadhaar verification are used to simplify the process of the voting system. The Aadhaar number has to be fetched and verified with the database after entering every vote on the machine. The information has to be verified for the vote of an individual to be accepted by EVM and stored in block chain ledger.
    Keywords: Aadhar verification; Electronic Voting Machine (EVM); Cyber-attack; Blockchain; IoT.
    DOI: 10.1504/IJSSE.2021.10034938
     
  • Fog and Edge Computing Simulators Systems: Research Challenges and an Overview   Order a copy of this article
    by Sathish Kumar, IYAPPARAJA M 
    Abstract: To support the requirement of geographically data scale, low latency, heterogeneous applications two new computing paradigms have been introduced namely, fog and edge computing. Discrete Event Simulation (DES) and Discrete Time Simulation (DTS) are the two types of simulation, where DES approach is applied to the problem where the application requires more scalability and DTS is the simulation model it is applied to the system when there is a higher possibility of inaccuracy. There is a wide number of simulators available for cloud, however the simulators for fog and edge computing are limited. An overview of fog and edge computing simulators like iFogSim, CloudSimSDN, and YAFS has be analyzed in this paper. Finally resource consumption metrics and fault tolerance metrics are analyzed and results has shown that that resource consumption metrics increases when the complexity of the scenario increases.
    Keywords: Fog Computing; Simulation; CDN; iFogSim; CloudSimSDN; YAFS; EMUFOG.
    DOI: 10.1504/IJSSE.2021.10034939
     
  • Design and Implementation of Novel Secure User Authentication System over Internet of Drones   Order a copy of this article
    by Subhadra Perumalla, Santanu Chatterjee, Siva Kumar A. P 
    Abstract: In recent years, edge related to internet of drone (IoD) is an emerging concept in computing system which is used to describe future technical implementations via different drone/node communication Provide different user services with respect to computing facilities For efficient communication between different nodes/drones in data transmission, avoid solution from different potential based adversary attacks in wireless IoD environment Traditionally different approaches are described with respect to secure data transmission, they are not efficient in secure communication with increase of quality of service parameters in wireless IoD So that in this paper, we propose a novel Elliptic curve cryptographic based Chebyshev polynomial Source Authentication System (ECCCPSAS) For linear data communication, we use the Chebyshev polynomials over with different characteristics, one-way communication with different characteristic vulnerabilities in wireless communication Also use Elliptic curve cryptography for secure authentication to each node to share session key with similar secure channel to transmit data
    Keywords: Internet of things; Internet of Drones; Internet security protocol; data transmission; global positioning system and Unmanned Aerial Vehicles (UAVs).
    DOI: 10.1504/IJSSE.2021.10038004
     
  • Enriching Module Dependency Graphs for Improved Software Clustering   Order a copy of this article
    by Harleen Kaur, Geeta Sikka 
    Abstract: The requirements for systems change over time and as the software systems evolve their designs degenerate, making it necessary to restructure the system to recoup with the apprehension that was lost. Without complete cognizance to a software system, a software maintainer may find it difficult to modify the system. The process of reverse engineering starts with an analysis phase where a system is analyzed by extracting its structure using automated tools. It is crucial for the developers to understand the system structure before making an attempt to modify it. The discovered structure can be viewed as a directed Module dependency graph. In this paper we enrich the MDG for a better understanding of the system structure by assigning different weights to different kind of code dependencies. To each kind of coupling relation distinctive weights are assigned. A naive function has been defined to generate weighted MDG's.
    Keywords: MDG; Dependency; Clustering.
    DOI: 10.1504/IJSSE.2022.10038005
     
  • Game Theory for Systems Engineering: A Survey   Order a copy of this article
    by Gayane Grigoryan, Andrew Collins 
    Abstract: It is possible to model any system that involves the interaction between multiple stakeholders as a game, whether they are in competition or they wish to coordinate. In these settings game theory is a useful modeling approach to describe the conflicting parties, their decision-making process, and the impact of their decisions on the overall system performance. In this paper, we review the use of game theory models in the systems engineering domain. Our approach was to conduct an extensive literature review in systems engineering related journals on game theory and systems engineering content. We have identified that major application areas of game theory, within systems engineering, as electricity markets, conflict and security systems, and supply chain; which we discuss in detail. This paper aggregates notable research to date to provide an overview of the models and highlights the potential contribution that game theory brings to solving systems engineering problems.
    Keywords: systems; engineering; game theory; cooperative game theory; non-cooperative game theory.
    DOI: 10.1504/IJSSE.2021.10038011