Localizing Runtime Anomalies in Service-Oriented Systems

Abstract

In a distributed, dynamic and volatile operating environment, runtime anomalies occurring in service-oriented systems (SOSs) must be located and fixed in a timely manner in order to guarantee successful delivery of outcomes in response to user requests. Monitoring all component services constantly and inspecting the entire SOS upon a runtime anomaly are impractical due to excessive resource and time consumption required, especially in large-scale scenarios. We present a spectrum-based approach that goes through a five-phase process to quickly localize runtime anomalies occurring in SOSs based on end-to-end system delays. Upon runtime anomalies, our approach calculates the similarity coefficient for each basic component (BC) of the SOS to evaluate their suspiciousness of being faulty. Our approach also calculates the delay coefficients to evaluate each BC's contribution to the severity of the end-to-end system delays. Finally, the BCs are ranked by their similarity coefficient scores and delay coefficient scores to determine the order of them being inspected. Extensive experiments are conducted to evaluate the effectiveness and efficiency of the proposed approach. The results indicate that our approach significantly outperforms random inspection and the popular Ochiai-based inspection in localizing single and multiple runtime anomalies effectively. Thus, our approach can help save time and effort for localizing runtime anomalies occuring in SOSs.

Fault analysis of service‐oriented systems: a systematic literature review

“…This approach is applicable in localising single and multiple runtime anomalies. He et al [10] have proposed a spectrum‐based approach to localise runtime anomalies which calculate the similarity coefficient for each basic component to evaluate its suspiciousness of being faulty and then basic components are ranked by their similarity coefficient scores after that it calculates delay coefficient scores to determine the order of them being inspected. Ding et al [93] have also utilised the spectrum‐based fault localisation technique to locate the faulty components that cause the reliability reduction of the SOS.…”

“…Fault localisation and fault prediction metrics [8, 9] in traditional software design paradigm are commonly addressed topics for review. Fault localisation review papers [10, 11] with the comparative study, considering artificial intelligence (AI)‐based techniques and spectrum‐based techniques are proposed by the researchers.…”

A Trustable and Secure Usage-Based Insurance Policy Auction Mechanism and Platform Using Blockchain and Smart Contract Technologies

“…These examples showcase the framework’s versatility in enabling smart contract-based applications involving exchanging IoV data and cryptocurrencies. Furthermore, the paper conducts a thorough security analysis, evaluating the proposed framework against various attack scenarios, and presents comprehensive performance metrics from real-world implementation [ 39 ].…”

Effective Service Composition Approach based on Pruning Performance Bottlenecks

“…Many researchers have proposed models and mechanisms for monitoring component web services for dynamic reconfiguration of a CWS [21], but to reconfigure a web service composition in a timely manner when change events happen during its execution is an important issue and still an open question [7,8].…”

“…Moreover, a web services based system has not only to be correct and reliable, but it should also ensure that it remains optimal as the component web services evolve independently. The need to reconfigure a web service composition in a timely manner when change events happen during its execution is an important issue and still an open question [7,8].…”