Browsing by Author "Ratneshwer Gupta"

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A fault propagation approach for SOA fault management using Petri Nets
(Institute of Electrical and Electronics Engineers Inc., 2017) Guru Prasad Bhandari; Ratneshwer Gupta
A fault situation occurs in a SOA (Service Oriented Architecture) to a service, needs to be detected to repair it. It is challenging to guarantee the reliability of service composition in a distributed concurrent, dynamic and complex environment. This paper aims to present fault propagation approach of SOA (Service Oriented Architecture) using Petri Nets. The presented approach extends discrete state space techniques to simulate the concurrent and distributed behavior through Petri nets for the SOA systems in the case of faulty situation. Through the performance analysis of our approach, the results demonstrate the feasibility of the approach. © 2017 IEEE.
An approach for fault prediction in SOA-based systems using machine learning techniques
(Emerald Publishing, 2019) Guru Prasad Bhandari; Ratneshwer Gupta; Satyanshu Kumar Upadhyay
Purpose: Software fault prediction is an important concept that can be applied at an early stage of the software life cycle. Effective prediction of faults may improve the reliability and testability of software systems. As service-oriented architecture (SOA)-based systems become more and more complex, the interaction between participating services increases frequently. The component services may generate enormous reports and fault information. Although considerable research has stressed on developing fault-proneness prediction models in service-oriented systems (SOS) using machine learning (ML) techniques, there has been little work on assessing how effective the source code metrics are for fault prediction. The paper aims to discuss this issue. Design/methodology/approach: In this paper, the authors have proposed a fault prediction framework to investigate fault prediction in SOS using metrics of web services. The effectiveness of the model has been explored by applying six ML techniques, namely, Naïve Bayes, Artificial Networks (ANN), Adaptive Boosting (AdaBoost), decision tree, Random Forests and Support Vector Machine (SVM), along with five feature selection techniques to extract the essential metrics. The authors have explored accuracy, precision, recall, f-measure and receiver operating characteristic curves of the area under curve values as performance measures. Findings: The experimental results show that the proposed system can classify the fault-proneness of web services, whether the service is faulty or non-faulty, as a binary-valued output automatically and effectively. Research limitations/implications: One possible threat to internal validity in the study is the unknown effects of undiscovered faults. Specifically, the authors have injected possible faults into the classes using Java C3.0 tool and only fixed faults are injected into the classes. However, considering the Java C3.0 community of development, testing and use, the authors can generalize that the undiscovered faults should be few and have less impact on the results presented in this study, and that the results may be limited to the investigated complexity metrics and the used ML techniques. Originality/value: In the literature, only few studies have been observed to directly concentrate on metrics-based fault-proneness prediction of SOS using ML techniques. However, most of the contributions are regarding the fault prediction of the general systems rather than SOS. A majority of them have considered reliability, changeability, maintainability using a logging/history-based approach and mathematical modeling rather than fault prediction in SOS using metrics. Thus, the authors have extended the above contributions further by applying supervised ML techniques over web services metrics and measured their capability by employing fault injection methods. © 2019, Emerald Publishing Limited.
An Overview of Cloud and Edge Computing Architecture and Its Current Issues and Challenges
(IGI Global, 2021) Guru Prasad Bhandari; Ratneshwer Gupta
Edge computing is a technique of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data in the systems. And, cloud computing is a service that delivers on-demand self-service, broad network access, resource pooling, rapid elasticity or expansion, which is trending in today’s technology-driven world. With the advantage of flexibility, storage, sharing, and easy accessibility, cloud is being used by major players in IT (information technology). This chapter highlights cloud/edge computing architecture and its current issues and challenges from technological and organizational aspects. A brief introduction of edge computing architecture with similar technologies along with its service models is discussed. A few counterexamples of cloud computing architecture are showed. Organizational aspects of cloud computing architecture, as well as IBM and Oracle reference cloud architecture, are briefly presented. Some emerging issues and challenges associated with cloud/ edge computing on its utilization are also elaborated. © 2021, IGI Global.
Colored Petri Nets based fault diagnosis in service oriented architecture
(IGI Global, 2018) Guru Prasad Bhandari; Ratneshwer Gupta; Satyanshu K. Upadhyay
Diagnosing faults in a service-oriented architecture (SOA) is a difficult task due to limited accessibility of software services. Probabilistic approaches of diagnostic faults may be insufficient due to the blackbox nature of services. In SOA, software services may be obtained by different service providers and get composed at run-time. This is the reason why there are diagnosis faults at execution time, and is a costly affair. The authors have demonstrated a Color Petri Nets (CPN)-based approach to model different faults that may occur at execution time. Some heuristics are proposed to diagnose faults from the CPN modeling. CPN behavioral properties have also been used for fault diagnosis. The model may be helpful for dependability enhancement of an SOA-based systems. Copyright © 2018, IGI Global.
Congestion control for high-speed wired network: A systematic literature review
(Academic Press, 2014) Vandana Kushwaha; Ratneshwer Gupta
This paper presents a survey of congestion control approaches in high speed wired network by taking into account both directions of congestion control research: source based and router based congestion control. Various survey papers reported in the literature, regarding congestion control approaches, have considered source based approach and router based approach independent to each other and take either of them into account. Both research directions are closely related to each other for a particular network domain and are equally important. It is a practicable idea to take a holistic view and study both the approaches together. The main motivation of this work is to summarize both approaches, interaction between both approaches, identify major issue and challenges in congestion control and motivate further research on this topic. © 2014 Elsevier Ltd.
Dependency modeling of a SOA based system through colored Petri Nets
(University of Zagreb, 2016) Pawan Kumar; Ratneshwer Gupta
Dependency relationships play an important role in testing, maintenance and configuration management of software systems. The informal dependency representations fail to observe behavioral connections among subsystems and cause ambiguity in representing different types of dependency relationships. Therefore, dependency in a software system requires a formal and unambiguous representation so that its correct effects can be visualized. In this paper, we present a Colored Petri Net based dependency analysis of a Service Oriented Architecture (SOA) based system that represents specification of dependency relationships and models the dependencies in a SOA based system at conceptual level. Different types of dependency relations are represented in a formal manner by using Service Algebra. A module SOA based system 'Online Bookshop' has been developed and used for the purpose of modeling and example demonstration. Such modeling can help in identification of inconsistency among services, and web services can be verified for safety and reliability.
Extended fault taxonomy of SOA-based systems
(University of Zagreb, 2017) Guru Prasad Bhandari; Ratneshwer Gupta
Service Oriented Architecture (SOA) is considered as a standard for enterprise software development. The main characteristics of SOA are dynamic discovery and composition of software services in a heterogeneous environment. These properties pose newer challenges in fault management of SOA-based systems (SBS). A proper understanding of different faults in an SBS is very necessary for effective fault handling. A comprehensive three-fold fault taxonomy is presented here that covers distributed, SOA specific and nonfunctional faults in a holistic manner. A comprehensive fault taxonomy is a key starting point for providing techniques and methods for accessing the quality of a given system. In this paper, an attempt has been made to outline several SBSs faults into a well-structured taxonomy that may assist developers in planing suitable fault repairing strategies. Some commonly emphasized fault recovery strategies are also discussed. Some challenges that may occur during fault handling of SBSs are also mentioned.
Fault analysis of service-oriented systems: A systematic literature review
(Institution of Engineering and Technology, 2018) Guru Prasad Bhandari; Ratneshwer Gupta
Due to the increasing scale and complexity of service-oriented systems (SOSs) understanding fault and its recovery mechanism is a tedious task so there is a strong demand for a summary of the SOSs fault analysis knowledge that can assist further developers and researchers to plan appropriate action and guidelines for SOSs development. The objective of this systematic literature review (SLR) is to summarise the current state-of-the-art of fault analysis in SOSs. The authors have used the predefined SLR method employing a manual search of 11 highly reputed international journals and three conference proceedings. The categorisation and organisation were done according to the research questions regarding approaches, fault types, current issues and challenges and tools of fault analysis on SOSs. After applying selection criteria, this SLR includes 123 papers published between January 2008 and April 2017, 65 papers address SOSs-fault handling approaches, 35 papers report SOS-specific faults and 51 papers address SOS issues, challenges, and testing and 17 papers are of tooling. They have discussed the main approaches, techniques, concepts, contributions and research methods used for fault analysis of SOSs. Through the paper, a comprehensive review work has been presented that provides empirical evidence for establishing future research agendas. © The Institution of Engineering and Technology 2018.
Fault diagnosis in service-oriented computing through partially observed stochastic Petri nets
(Springer, 2020) Guru Prasad Bhandari; Ratneshwer Gupta
Service composition, interoperability, loose coupling and distributed nature make service-oriented computing (SOC) enhanced for small-scale to large and complex software systems, though it tends to increase the vulnerability of faults. The properties of SOC pose newer challenges in fault diagnosis. To deal with this problem, we need to enhance the understandability that assists in fault analysis of SOC. In this paper, we have proposed a model-based fault diagnosis approach for SOC adopting the concept of partially observed stochastic Petri nets. In this work, Web services are transformed into Petri nets and stochastic Petri nets using the existing constructs. Then, the calculated reachability graph of the modeled Petri nets is used to diagnose the fault in the observable sequence with the help of labeled Petri nets. Experiments are conducted for the illustration of the proposed fault diagnosis model. The analyzed performance of the proposed model guarantees the accessibility of our approach and suggests the inspection of the model into real-world environments. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Fault prediction in SOA-based systems using deep learning techniques
(IGI Global, 2020) Guru Prasad Bhandari; Ratneshwer Gupta
Fault prediction in Service Oriented Architecture (SOA) based systems is one of the important tasks to minimize the computation cost and time of the software system development. Predicting the faults and discovering their locations in the early stage of the system development lifecycle makes maintenance processes easy and improves the resource utilization. In this paper, the authors proposed the fault prediction model for SOA-based systems by utilizing the deep learning techniques. Twentyone source code metrics are applied to different web services projects. The web services datasets are constructed by injecting the faults into it, and metrics are extracted for both faulty and nonfaulty data for training and testing purpose. Moreover, different deep learning techniques are inspected for fault prediction of web services and performance of different methods are compared by using standard performance measures. From the experimental results, it is observed that deep learning techniques provide effective results and applicable to the real-world SOA-based systems. Copyright © 2020, IGI Global.
Machine learning based software fault prediction utilizing source code metrics
(Institute of Electrical and Electronics Engineers Inc., 2018) Guru Prasad Bhandari; Ratneshwer Gupta
In the conventional techniques, it requires prior knowledge of faults or a special structure, which may not be realistic in practice while detecting the software faults. To deal with this problem, in this work, the proposed approach aims to predict the faults of the software utilizing the source code metrics. In addition, the purpose of this paper is to measure the capability of the software fault predictability in terms of accuracy, f-measure, precision, recall, Area Under ROC (Receiver Operating Characteristic) Curve (AUC). The study investigates the effect of the feature selection techniques for software fault prediction. As an experimental analysis, our proposed approach is validated from four publicly available datasets. The result predicted from Random Forest technique outperforms the other machine learning techniques in most of the cases. The effect of the feature selection techniques has increased the performance in few cases, however, in the maximum cases it is negligible or even the worse. © 2018 IEEE.
Measuring the Fault Predictability of Software using Deep Learning Techniques with Software Metrics
(Institute of Electrical and Electronics Engineers Inc., 2018) Guru Prasad Bhandari; Ratneshwer Gupta
Minimization of failures is the major expectation from reliable software. Predicting the software faults supports in identifying the location in the faulty modules for detailed testing to increase the maintainability. This paper presents fault prediction using some of the deep learning techniques utilizing source code metrics of the software. Accuracy, f-measure, recall, precision, receiver operating characteristic (ROC) curves and area under curve (AUC) values are considered to measure the performance of the deep learning methods. Experimental analysis on five NASA public benchmarked datasets depict Convolutional Neural Network (CNN) classifier as a more robust software fault prediction model achieving the highest accuracy rates. CNN is followed by Artificial Neural Network (ANN) and then Self-Organizing Map (SOM). Learning Vector Quantization (LVQ) version 3 and MultiLVQ have the worst performance on software fault prediction using software metrics. © 2018 IEEE.
Safety-critical, dependable, and fault-tolerant cyber- physical systems
(IGI Global, 2018) Guru Prasad Bhandari; Ratneshwer Gupta
Cyber-physical systems (CPSs) are co-engineered integrating with physical and computational components networks. Additionally, a CPS is a mechanism controlled or monitored by computer-based algorithms, tightly interacting with the internet and its users. This chapter presents the definitions relating to dependability, safety-critical and fault-tolerance of CPSs. These definitions are supplemented by other definitions like reliability, availability, safety, maintainability, integrity. Threats to dependability and security like faults, errors, failures are also discussed. Taxonomy of different faults and attacks in CPSs are also presented in this chapter. The main objective of this chapter is to give the general information about secure CPS to the learners for the further enhancement in the field of CPSs. © 2018, IGI Global.
Some Studies on Factors Influencing Maximum Association Number of Wi-Fi Access Point
(Springer, 2019) Haribansh Mishra; Ratneshwer Gupta
Wi-Fi, which is standardized by IEEE as 802.11, is most popular wireless network protocol of the present time for WLAN deployment. In a professionally deployed WLAN, there are many Access Points (APs) placed at well-determined locations to provide good wireless connectivity. The decision of placement of APs is dependent on many factors. For successful WLAN deployment and maintenance, it is pertinent to know that what factors influence the maximum count of stations that can be connected to one single AP. This study tries to explore all the aspects that are responsible for deciding the maximum number of devices that can be connected to single AP without degrading the performance of network significantly. Such information will play pertinent role in placement of APs in different geographical locations in a cost-effective manner. © 2019, Springer Nature Singapore Pte Ltd.
Systematic review of congestion handling techniques for 802.11 wireless networks
(John Wiley and Sons Ltd, 2020) Haribansh Mishra; Ratneshwer Gupta; Satyanshu Kumar Upadhyay
IEEE 802.11 is a matured standard for wireless local area networks (WLANs). The cellular network providers had made every possible effort to offload their traffic over WLANs whenever it was possible, owing to the benefits that this technology provides. IEEE 802.11 is gaining greater prominence with the arrival of 802.11ax standard, which is backed by the Wi-Fi alliance by branding as Wi-Fi 6. The issue of congestion has been studied well for various networks. Particularly, in wireless networks, it needs to be tackled in a peculiar manner owing to the uncertain nature of the wireless medium. This study explores and evaluates the improvements done at various protocol layers to handle the problem of congestion in 802.11-based wireless networks. An attempt is made to understand the implication of different parameters and the significance of cross-layer interaction. Further, an endeavor is made to assess the influence on congestion control mechanisms in the different architectures of 802.11 networks. Lastly, the challenges that might be confronted at different protocol layers, while dealing with the issue of congestion, are classified. © 2019 John Wiley & Sons, Ltd.