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KPIs (key performance indicators) reflect the operational state of Cloud services and infrastructure. With the rapid development of cloud services, many dimensional KPIs are constantly generated during service operations. Recently, deep-learning-...

A grand challenge in personalised federated learning (PFL) is the data heterogeneity. Although various methods tried to address this challenge, they are either inefficient or show low generalisation capability. In this work, we propose a PFL ...

Stream join is a fundamental operation in stream processing and has attracted extensive research due to its large resource consumption and serious impact on system performance. As the theoretical basis of stream join systems, the stream join model ...

Quality of Service (QoS) prediction is a crucial aspect in service management. However, the existing QoS prediction methods face several limitations, such as loss of information during encoding, incomplete feature extraction and neglect of the ...

We devise in this paper a Multilevel Adaptive Reduction Technique (MART) for time series data. MART extracts the main features of a time series and encodes them in a reduced data structure called reduct. The extracted features are ...

We propose in this paper a partial order framework for clustering incomplete data. The paramount feature of this framework is that it spans over a partial order that can be leveraged to establish data similarity. We present the underlying ...

Stream processing is an emerging in-memory computing paradigm to handle massive amounts of real-time data. It is vital to have a mechanism to propose proper parallelism for the operators to handle streaming data efficiently. Previous research has ...

This paper focuses on the issue of robust stability analysis for recurrent neural networks (RNNs) with leakage delay. By constructing a novel Lyapunov---Krasovskii functional together with the reciprocally convex approach and the free-weighting matrix ...

Reliability is critical for choosing, ranking and composing Web services. However, some common situations, such as fault-tolerant strategies and the dynamic operational profile, are not considered in existing reliability analysis. To solve these ...

This paper is concerned with the guaranteed generalized $${\mathcal {H}}_{2}$$H2 performance state estimation for a class of static neural networks with a time-varying delay. A more general Arcak-type state estimator rather than the Luenberger-type ...

In this paper, based on the discrete Wirtinger inequality, a novel summation inequality is established which extends the Jensen inequality. By the technique of the novel inequality, a sufficient criterion on asymptotic stability of discrete neural ...

In this paper, the problem of stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay is investigated. By constructing a new Lyapunov-Krasovskii functional and employing a novel summation inequality which is ...

In the software testing process, many factors can affected the failure distribution, such as the testing strategy, running environment and resource allocation, etc. Once these factors are transformed during testing phase, they could result in the ...

In the software testing process, many factors can affected the failure distribution, such as the testing strategy, running environment and resource allocation, etc. Once these factors are transformed during testing phase, they could result in the ...

HighlightsWe use a log-logistic distribution to model fault introduction during debugging.We propose a log-logistic distribution fault content function.Fault introduction rate per fault exhibits increasing and decreasing characteristics. Numerous ...

In general, an assumption of perfect debugging is used to build a software reliability model in the software testing process. However, it is not in accordance with the realistic testing situation. In practice, software testing is a complicated process ...

In the software testing process, the effective development of software reliability models can be quantified to assess the software reliability. Most of the current software reliability models developed are the parametric models, and assuming that the ...

The increasing popularity of power constrained mobile computers applications drives the need for evaluating and analyzing power in all components of a system. Software constitutes a major component of systems where power is a constraint. Most of ...

A robust dynamic inversion control law based on nonlinear disturbance observer is proposed for the integrated guidance and control of missile. Firstly the pitch channel of integrated guidance and control model was established. According to this model, a ...

The fault correction process is very important in software testing, and it has been considered into some software reliability growth models (SRGMs). In these models, the time-delay functions are often used to describe the dependency of the fault ...