Advances in Service-Oriented and Cloud Computing
International Workshops of ESOCC 2020, Heraklion, Crete, Greece, September 28–30, 2020, Revised Selected Papers
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Article
Open AccessSampleHST-X: A Point and Collective Anomaly-Aware Trace Sampling Pipeline with Approximate Half Space Trees
The storage requirement for distributed tracing can be reduced significantly by sampling only the anomalous or interesting traces that occur rarely at runtime. In this paper, we introduce an unsupervised sampl...
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Article
Open AccessSimTune: bridging the simulator reality gap for resource management in edge-cloud computing
Industries and services are undergoing an Internet of Things centric transformation globally, giving rise to an explosion of multi-modal data generated each second. This, with the requirement of low-latency re...
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Chapter and Conference Paper
LN: A Meta-solver for Layered Queueing Network Analysis
We overview LN, a novel solver introduced in the LINE software package to analyze layered queueing network (LQN) models. The novelty of the LN solver lies in its capability to analyze LQNs with a user-defined com...
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Chapter and Conference Paper
Enhancing Performance Modeling of Serverless Functions via Static Analysis
Serverless computing leverages the design of complex applications as the composition of small, individual functions to simplify development and operations. However, this flexibility complicates reasoning about...
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Book and Conference Proceedings
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Chapter and Conference Paper
Service Demand Distribution Estimation for Microservices Using Markovian Arrival Processes
Building performance models for microservices applications in DevOps is costly and error-prone. Accurate service demand distribution estimation is critical to performance model parameterization. However, tradi...
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Article
Open AccessCorrection to: Artificial neural networks based techniques for anomaly detection in Apache Spark
The original version of this article unfortunately contained a graphical mistake in Table 4. Table 4 shows a list of performance metrics associated to the DSM1, DSM2, DSM3, and DSM4 methods proposed in the pap...
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Article
Open AccessArtificial neural networks based techniques for anomaly detection in Apache Spark
Late detection and manual resolutions of performance anomalies in Cloud Computing and Big Data systems may lead to performance violations and financial penalties. Motivated by this issue, we propose an artific...
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Chapter and Conference Paper
Enhancing Big Data Application Design with the DICE Framework
The focus of the DICE project is to define a quality-driven framework for develo** Big data applications. DICE offers an Eclipse-based development environment, centered around a novel UML profile, to prototy...
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Chapter
Closing the Loop Between Ops and Dev
DevOps [1] is a recent trend in software engineering that bridges the gap between software development and operations, putting the developer in greater control of the operational environment in which the applicat...
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Chapter
QoS Assessment and SLA Management
Verifying that a software system shows certain non-functional properties is a primary concern for Cloud applications (In this chapter non-functional properties, QoS and non-functional requirements will be used...
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Chapter
Load Balancing for Multi-cloud
Load balancing is an integral part of software systems that require to serve requests with multiple concurrent computing resources such as servers, clusters, network links, central processing units or disk dri...
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Chapter and Conference Paper
Tulsa: A Tool for Transforming UML to Layered Queueing Networks for Performance Analysis of Data Intensive Applications
Motivated by the problem of detecting software performance anti-patterns in data-intensive applications (DIAs), we present a tool, Tulsa, for transforming software architecture models specified through UML int...
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Article
Open AccessOptiSpot: minimizing application deployment cost using spot cloud resources
The spot instance model is a virtual machine pricing scheme in which some resources of cloud providers are offered to the highest bidder. This leads to the formation of a spot price, whose fluctuations can det...
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Article
Open AccessQuality-of-service in cloud computing: modeling techniques and their applications
Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocatin...
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Article
Open AccessPerformance models of storage contention in cloud environments
We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. Model parameters can be deduced from measurements obt...
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Chapter and Conference Paper
AutoCAT: Automated Product-Form Solution of Stochastic Models
We introduce AutoCAT, a class of algorithms to automatically generate exact and approximate product-form solutions for large Markov processes that cannot be solved by direct numerical methods. Focusing on models ...
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Chapter and Conference Paper
Introduction
Research on performance evaluation over the past several years has resulted in a range of techniques and tools for modeling, analyzing, and optimizing performance of applications on parallel and distributed co...
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Chapter
Tools for Performance Evaluation of Computer Systems: Historical Evolution and Perspectives
The development of software tools for performance evaluation and modeling has been an active research area since the early years of computer science. In this paper, we offer a short overview of historical evol...
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Article
Open AccessSizing multi-tier systems with temporal dependence: benchmarks and analytic models
Temporal dependence, as a synonym for burstiness, is often found in workloads (i.e., arrival flows and/or service times) in enterprise systems that use the multi-tier paradigm. Despite the fact that burstiness...
