Multiresolution Abnormal Trace Detection Using Varied-Length $n$-Grams and Automata

Jiang, Guofei; Chen, Haifeng; Ungureanu, Cristian; Yoshihira, Kenji

doi:10.1109/tsmcc.2006.871569

Cited by 17 publications

(11 citation statements)

References 12 publications

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“…Another significant work [10] makes use of variable length n-grams to model call and return order between components in distributed systems. In our opinion, such a method is not suitable for the service model since in services composition, concurrent services are called and return data at the same time (e.g.…”

Section: Related Work In Service Composition Learningmentioning

confidence: 99%

Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks

Geyik

Bulut

Szymanski

2012

2012 IEEE Ninth International Conference on Services Computing

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Abstract-Service composition in sensor networks combines elementary services with a specific functionality to create a service with higher level functionality. The previous efforts in automating composition were sending full information about all services across the entire sensor network, creating a security risk and imposing significant communication overhead. Furthermore, learning based composition or error detection methods do not consider global information, leading to inefficiencies in the generated composition graphs. In this paper, we propose a probabilistic context-free grammar (PCFG) based modeling technique to construct service compositions. The successful compositions created for the given application are treated as statements belonging to an efficient composition PCFG of this application. The given set of such compositions is used to derive this PCFG automatically. Future composition could be then easily constructed with the help of such PCFG. We present our methodology for achieving such modeling and provide examples of its use to demonstrate its advantage over previous work. We also evaluate the resulting improvements in performance of compositions and in the costs of their creation.Index Terms-sensor networks; service composition; PCFGs;I. INTRODUCTION Service oriented architecture (SOA) for wireless sensor networks (WSN) have recently been proposed as a means to abstract the sensor network as a set of services (programs integrated within sensor nodes) that provide a certain functionality. In this context, the task of service composition is to efficiently combine a set of services so that a more complex functionality can be realized. In our initial work for SOA for WSN [1], we showed how to represent a composition as a graph of connection of services and how to automatically combine services in an efficient way. While such an automated scheme improves energy efficiency of the solution, during composition creation this scheme suffers from communication overhead and a security problem because metadata about services are sent between all potential services. Since the metada may include mission critical information, in domains such as military applications, the user may not want such information to be moved around freely. Manual connection of services by the user is a possible solution to this problem that has been followed in the literature. However, such a method becomes error-prone with the increasing composition size.

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Section: Related Work In Service Composition Learningmentioning

confidence: 99%

Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks

Geyik

Bulut

Szymanski

2012

2012 IEEE Ninth International Conference on Services Computing

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“…Mirgorodskiy et al used k-nearest neighbor approach on per function time profile to identify potential failure traces in distributed systems [14]. Jiang et al used training data to construct automata to characterize normal traces of distributed system and then used it to detect abnormal traces [9]. Yuan et al applied support vector machines classifiers to categorize system event traces and correlated them to known system problem to determine root causes [21].…”

Section: Related Workmentioning

confidence: 99%

ELT: Efficient Log-based Troubleshooting System for Cloud Computing Infrastructures

2011

2011 IEEE 30th International Symposium on Reliable Distributed Systems

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Abstract-We present an Efficient Log-based Troubleshooting(ELT) system for cloud computing infrastructures. ELT adopts a novel hybrid log mining approach that combines coarse-grained and fine-grained log features to achieve both high accuracy and low overhead. Moreover, ELT can automatically extract key log messages and perform invariant checking to greatly simplify the troubleshooting task for the system administrator. We have implemented a prototype of the ELT system and conducted an extensive experimental study using real management console logs of a production cloud system and a Hadoop cluster. Our experimental results show that ELT can achieve more efficient and powerful troubleshooting support than existing schemes. More importantly, ELT can find software bugs that cannot be detected by current cloud system management practice.

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“…a fault in the overall system is detected if at least one diagnoser (sub-automaton) recognizes a faulty situation in a locally recorded sequence of events [18]. Decentralized fault diagnosis, as well as necessary and sufficient conditions for diagnosability in distributed systems has been a significant research direction in the area of distributed discrete event dynamical systems [2,5,8,12,26,32].…”

Section: Syntactic Analysis Using Fuzzy Automatamentioning

confidence: 99%

Fault detection and isolation based on fuzzy automata

Rigatos

2009

Information Sciences

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Multiresolution Abnormal Trace Detection Using Varied-Length $n$-Grams and Automata

Cited by 17 publications

References 12 publications

Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks

Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks

ELT: Efficient Log-based Troubleshooting System for Cloud Computing Infrastructures

Fault detection and isolation based on fuzzy automata

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