Obtaining Models for Realistic Mobile Network Simulations using Real Traces

Dı́az, A. Navas; Merino, Pedro; Salmerón, Alberto

doi:10.1109/lcomm.2011.060111.102514

Cited by 6 publications

(8 citation statements)

References 8 publications

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“…We have also surveyed the trace diagnostics support in the tools that were contestants of the "offline monitoring" track of the 2014 and 2015 international Competition on Software for Runtime Verification (CSRV 2014 [3] and CSRV 2015 [22]). Four of the tools (STePr, AgMon [29], LogFire [27], OptySim [8]) are not publicly available; another tool RiTHM-v2.0 [34], is available but does not work when executed by following the instructions specified in the README file on its GitHub page [39]; the remaining tools that we analyzed are: Breach [10], MonPoly [5], QEA [37], SOLOIST+ZOT [7], and RV-Monitor [33]. Table 2 summarizes our findings, indicating whether a tool produces a boolean output (column "boolean"), whether it takes into account all the (events leading to) violations in a trace (column "positions"), whether it provides detailed diagnostic information, such as the cause of a violation (column "cause"), and whether it is based on MDE technologies (column "MDE").…”

Section: Related Workmentioning

confidence: 99%

Model-Driven Trace Diagnostics for Pattern-based Temporal Specifications

Wei

Bianculli

Briand

2018

Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

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Offline trace checking tools check whether a specification holds on a log of events recorded at run time; they yield a verification verdict (typically a boolean value) when the checking process ends. When the verdict is false, a software engineer needs to diagnose the property violations found in the trace in order to understand their cause and, if needed, decide for corrective actions to be performed on the system. However, a boolean verdict may not be informative enough to perform trace diagnostics, since it does not provide any useful information about the cause of the violation and because a property can be violated for multiple reasons. The goal of this paper is to provide a practical and scalable solution to solve the trace diagnostics problem, in the settings of model-driven trace checking of temporal properties expressed in TemPsy, a pattern-based specification language. The main contributions of the paper are: a model-driven approach for trace diagnostics of pattern-based temporal properties expressed in TemPsy, which relies on the evaluation of OCL queries on an instance of a trace meta-model; the implementation of this trace diagnostics procedure in the TemPsy-Report tool; the evaluation of the scalability of TemPsy-Report, when used for the diagnostics of violations of real properties derived from a case study of our industrial partner. The results show that TemPsy-Report is able to collect diagnostic information from large traces (with one million events) in less than ten seconds; TemPsy-Report scales linearly with respect to the length of the trace and keeps approximately constant performance as the number of violations increases.

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Section: Related Workmentioning

confidence: 99%

Model-Driven Trace Diagnostics for Pattern-based Temporal Specifications

Wei

Bianculli

Briand

2018

Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

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“…We have implemented a version of the analyzer using the S pin model checker, and have applied it to ns-2 network simulations 31,32,37,38 and Java programs. 33 In later sections we will present the particular implementation for ns-2 and several case studies regarding performance, reliability and validation analysis.…”

Section: Analysis and Optimization Frameworkmentioning

confidence: 99%

“…The property we used for this validation case study is similar to the one we had previously used in another application of our framework: configuring jitter simulation models to conform to real network traffic. 32…”

Section: Validation Of E-model Extensionmentioning

confidence: 99%

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Integrating model checking and simulation for protocol optimization

Salmerón

Merino

2014

SIMULATION

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Simulation models of communication protocols are widely used in the field of protocol engineering. Some methods have been proposed to ensure the correctness of these models, or to tune their parameters for performance. However, these aspects have usually been considered separately. This paper presents OptySim, a uniform framework to perform correctness analysis and performance evaluation over execution traces of communication protocols. The same protocol models can be tested for correctness before being used for performance evaluation, using this uniform framework. The exploration of the scenarios is controlled by performance or correctness objectives set by the user, using rich formalisms such as temporal logic and automata. Each execution trace is analyzed on the fly, stopping simulations as soon as the objectives are met or violated. The controlled exploration of the parameter space and the associated execution traces can help uncover errors or configurations that may have been otherwise missed with other exhaustive methods or human analysis. Our framework separates the analyzer from the system under analysis using a communication protocol that enables easier adaptation to new systems. We have implemented our framework with the Spin model checker to analyze ns-2 network simulations, and demonstrated the usefulness of our approach with two case studies: video streaming and VoIP call quality in mobile environments.

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“…In general, low 2 values have been obtained (0.7 or less) with the equations used, which exposes the complexity of the relationships between the cross-layer parameters analyzed. In future work, we will apply objective-driven simulations [28] to obtain more accurate patterns between cross-layer parameters under study.…”

Section: Harq and Packet Lossesmentioning

confidence: 99%

Obtaining More Realistic Cross-Layer QoS Measurements: A VoIP over LTE Use Case

Rivas¹,

Dı́az

Merino³

2013

Journal of Computer Networks and Communications

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We introduce a real-time experimentation testbed in this paper which enables more realistic analysis of quality of service (QoS) in LTE networks. This testbed is envisioned for the improvement of QoS and quality of experience (QoE) through the experimentation with real devices, services, and radio configurations. Radio configurations suggested in the literature typically arise from simulations; the testbed provides a real and controlled testing environment where such configurations can be validated. The added value of this testbed goes a long way not only in the provision of more realistic results but also in the provision of QoS and QoE cross-layer measurements through the correlation of information collected at different layers: from service and IP levels to radio and protocol parameters. Analyzing the interlayer dependencies will allow us to identify optimal settings for the radio access network and service parameters. This information can be used to suggest new cross-layer optimizations to further improve quality of experience of mobile subscribers. As a use case, we examine VoIP service over LTE, which is currently an open issue.

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Obtaining Models for Realistic Mobile Network Simulations using Real Traces

Cited by 6 publications

References 8 publications

Model-Driven Trace Diagnostics for Pattern-based Temporal Specifications

Model-Driven Trace Diagnostics for Pattern-based Temporal Specifications

Integrating model checking and simulation for protocol optimization

Obtaining More Realistic Cross-Layer QoS Measurements: A VoIP over LTE Use Case

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