Design of an Optimal Deep Learning-Based Self-Healing Mechanism With Failure Prediction Model for Web Services

Design of an Optimal Deep Learning-Based Self-Healing Mechanism With Failure Prediction Model for Web Services

Rajeswari P., Jayashree K.
Copyright: © 2022 |Pages: 15
DOI: 10.4018/IJeC.304375
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Abstract

Recently, web service composition technology becomes familiar and it raise the quality offered by the systems designed followed by the service oriented architecture (SOA) framework. Web service composition mainly functioning in dynamic environment, susceptible to the incidence of unpredictable disruption and modifications which could influence the performance of the system. Therefore, the ability to self-healing and manage the execution of web service composition can enhance the reliability and fault tolerance of the system.This study develops an Optimal Deep Learning based Self Healing Mechanism with Failure Prediction (ODL-SHMFP) model for Web Services. The proposed ODL-SHMFP technique aims to accomplish a self healing model for minimizing the failure in web services.
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Introduction

Over the last few years, numerous efforts have been driven to develop the technologies of web service composition (WSC) architecture and to improve the quality transported by systems designed following the service-oriented architecture (SOA) model (Simmonds et al., 2013). Web Service Management System is a comprehensive framework for managing web service lifecycle which covers the development, deployment, publishing, discovery, composition, monitoring, and optimizing access to web services. As web services are being extensively deployed for business applications, the reliability of the services provided becomes an important criterion to enable the usage of such services (Jayashree et al., 2013) Internet users are increasing day by day, network requirement also increases to obtain good performance. Therefore, many online services demand a very large bandwidth and network performance (Rajeswari et al., 2018) The context of composite web services is very dynamic and several kinds of changes and faults may occur during and after deploying a composite service (Jayashree et al., 2015) Regarding any distributed systems, it becomes very complex to ensure the desired behaviour of web services (Sheng et al., 2014) The capacity to handle the implementation of WSC architecture might enhance the fault-tolerance and reliability of the deployed architecture. Developing mechanisms to recover from faults opens significant research opportunities (Madhan et al., 2020) The WSC architecture operates in dynamic environment, prone to the existence of unpredictable changes and disruptions which might affect the system performance. This problem could emerge at distinct stages of the WSC stack, ranging from faults at certain services to defect at the fundamental architecture (Papazoglou et al., 2007) The accessibility of the remotely placed service, the quality attribute transported by the service, and the functional state of the networks are inherent to SOA model and it might be the reason for failure.

Figure 1.

Self-healing architecture for web services

IJeC.304375.f01

As providing service can able to detect and correct faults, when conserving the run time execution with a minimum dependence of human intervention is the challenging problem. Similarly, failure recovery is critical for the effective and proper delivery of WSC functionality (Yu et al., 2008) The temporary inaccessibility of an essential components changes and service of the quality attribute provided by services are the example of failure. Categorizing faults in terms of WSC architecture is a step towards the description of effective SOA application (Neelakandan et al., 2021) Numerous classifications exists, adapting distinct criteria’s, involving dissimilar granularities of the composition, non-functional and functional factors (Malak et al., 2009) Many of this work suggest the usage of their taxonomy to describe self-healing mechanism for WSC architecture.

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