Publications

Also listed on DBLP. [AAM] (author accepted manuscript) and [OA] (open access) are locally hosted copies for personal non-commercial use.

Research theme: AllQoS managementModelling and simulationDependability

228Diameter-independent reinforcement learning for the control of state-dependent queues. Perform. Evaluation, to appear, 2026. Cite
227Monotone performance measures in closed multiclass queueing networks. Perform. Evaluation, to appear, 2026. Cite
226The component queues method for quasi-birth-death process fitting and analysis. Proc. of QEST/FORMATS 2026, accepted, 2026. Cite
225A family of multiclass LCFS networks with a novel product-form solution. Queueing Syst. Theory Appl., vol. 110, no. 2, pp. 32, 2026. Cite
224CARSS: Leveraging online arrival forecasting and co-simulation for adaptive scheduling. IEEE Trans. Parallel Distributed Syst., accepted, 2026. Cite
223Fine-grained Tracing for Performance Anomaly Diagnosis of Serverless Functions. ACM Trans. Auton. Adapt. Syst., vol. 21, no. 1, pp. 5:1-5:29, 2026. Cite
222LLMRCA: Multilevel root cause analysis for LLM applications using multimodal observability data. ACM Trans. Softw. Eng. Methodol., accepted, 2026. Cite
221SQUAD: Scalable Quorum Adaptive Decisions via ensemble of early exit neural networks. arXiv preprint, vol. abs/2601.22711, 2026. Cite
220Competitive Analysis of Vehicle-Sharing Systems With Cournot Queueing Games. IEEE Trans. Intell. Transp. Syst., vol. 26, no. 8, pp. 12039-12048, 2025. Cite
219SELA: Smart Edge LLM Agent to Optimize Response Trade-offs of AI Assistants. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., vol. 9, no. 3, pp. 130:1-130:18, 2025. Cite
218TBI: Transient Hierarchical Modeling of Large-Scale Vehicle Sharing Systems. IEEE Trans. Intell. Transp. Syst., vol. 26, no. 11, pp. 19720-19729, 2025. Cite
217Towards Cost-Optimal Policies for DAGs to Utilize IaaS Clouds With Online Learning. IEEE Trans. Serv. Comput., vol. 18, no. 4, pp. 2439-2455, 2025. Cite
216CEED: Collaborative Early Exit Neural Network Inference at the Edge. Proc. of INFOCOM, pp. 1-10, 2025. Cite
215Deep Surrogate Models of Serverless Batch Processing Services. Proc. of ESOCC, pp. 155-170, 2025. Cite
214DeepBAT: Performance and Cost Optimization of Serverless Inference Using Transformers. Proc. of IPDPS, pp. 335-346, 2025. Cite
213Enhanced Training of Response Time Anomaly Detectors Using Diffusion Models. Proc. of MASCOTS, pp. 1-8, 2025. Cite
212A Product-form Network for Systems with Job Stealing Policies. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 9, no. 2, pp. 6:1-6:26, 2024. Cite
211LN: A Flexible Algorithmic Framework for Layered Queueing Network Analysis. ACM Trans. Model. Comput. Simul., vol. 34, no. 3, pp. 17:1-17:26, 2024. Cite
210Neural Density Estimation of Response Times in Layered Software Systems. IEEE Trans. Software Eng., vol. 50, no. 3, pp. 636-650, 2024. Cite
209Performance Modeling of Distributed Data Processing in Microservice Applications. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 9, no. 4, pp. 14:1-14:30, 2024. Cite
208PreGAN+: Semi-Supervised Fault Prediction and Preemptive Migration in Dynamic Mobile Edge Environments. IEEE Trans. Mob. Comput., vol. 23, no. 6, pp. 6881-6895, 2024. Cite
207RADF: Architecture decomposition for function as a service. Softw. Pract. Exp., vol. 54, no. 4, pp. 566-594, 2024. Cite
206SampleHST-X: A Point and Collective Anomaly-Aware Trace Sampling Pipeline with Approximate Half Space Trees. J. Netw. Syst. Manag., vol. 32, no. 3, pp. 44, 2024. Cite
205Scheduling Inputs in Early Exit Neural Networks. IEEE Trans. Computers, vol. 73, no. 2, pp. 451-465, 2024. Cite
204Approximating Closed Queueing Networks in Semi-Markov Random Environments. Proc. of MASCOTS, pp. 1-8, 2024. Cite
203Approximating Fork-Join Systems via Mixed Model Transformations. Proc. of ICPE (Companion), pp. 273-280, 2024. Cite
202Bayesian Optimization for Clinical Pathway Decomposition From Aggregate Data. Proc. of WSC, pp. 952-963, 2024. Cite
201ChainNet: A Customized Graph Neural Network Model for Loss-Aware Edge AI Service Deployment. Proc. of DSN, pp. 238-251, 2024. Cite
200Cournot Queueing Games with Applications to Mobility Systems. Proc. of AAMAS, pp. 2462-2464, 2024. Cite
199Matrix Network Analyzer: A New Decomposition Algorithm for Phase-type Queueing Networks (Work In Progress Paper). Proc. of ICPE (Companion), pp. 34-39, 2024. Cite
198Optimizing Edge AI: Performance Engineering in Resource-Constrained Environments. Proc. of ICPE, pp. 223, 2024. Cite
197AI augmented Edge and Fog computing: Trends and challenges. J. Netw. Comput. Appl., vol. 216, pp. 103648, 2023. Cite
196CILP: Co-Simulation-Based Imitation Learner for Dynamic Resource Provisioning in Cloud Computing Environments. IEEE Trans. Netw. Serv. Manag., vol. 20, no. 4, pp. 4448-4460, 2023. Cite
195Delay and Price Differentiation in Cloud Computing: A Service Model, Supporting Architectures, and Performance. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 8, no. 3, pp. 1-40, 2023. Cite
194DRAGON: Decentralized Fault Tolerance in Edge Federations. IEEE Trans. Netw. Serv. Manag., vol. 20, no. 1, pp. 276-291, 2023. Cite
193Estimating Multiclass Service Demand Distributions Using Markovian Arrival Processes. ACM Trans. Model. Comput. Simul., vol. 33, no. 1-2, pp. 2:1-2:26, 2023. Cite
192Fitting with matrix exponential mixtures generated by discrete probabilistic scaling. SIGMETRICS Perform. Evaluation Rev., vol. 51, no. 2, pp. 15-17, 2023. Cite
191Learning to Dynamically Select Cost Optimal Schedulers in Cloud Computing Environments. SIGMETRICS Perform. Evaluation Rev., vol. 50, no. 4, pp. 29-31, 2023. Cite
190Performance evaluation teaching in the age of cloud computing. SIGMETRICS Perform. Evaluation Rev., vol. 51, no. 2, pp. 45-49, 2023. Cite
189Redundancy Planning for Cost Efficient Resilience to Cyber Attacks. IEEE Trans. Dependable Secur. Comput., vol. 20, no. 2, pp. 1154-1168, 2023. Cite
188SciNet: Codesign of Resource Management in Cloud Computing Environments. IEEE Trans. Computers, vol. 72, no. 12, pp. 3590-3602, 2023. Cite
187SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments. IEEE Trans. Mob. Comput., vol. 22, no. 9, pp. 5539-5554, 2023. Cite
186START: Straggler Prediction and Mitigation for Cloud Computing Environments Using Encoder LSTM Networks. IEEE Trans. Serv. Comput., vol. 16, no. 1, pp. 615-627, 2023. Cite
185Clinical Pathway Clustering Using Surrogate Likelihoods and Replayability Validation. Proc. of WSC, pp. 1220-1231, 2023. Cite
184Coupling QoS Co-Simulation with Online Adaptive Arrival Forecasting. Proc. of CNSM, pp. 1-9, 2023. Cite
183DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model. Proc. of INFOCOM, pp. 1-10, 2023. Cite
182SampleHST: Efficient On-the-Fly Selection of Distributed Traces. Proc. of NOMS, pp. 1-9, 2023. Cite
181COSCO: Container Orchestration Using Co-Simulation and Gradient Based Optimization for Fog Computing Environments. IEEE Trans. Parallel Distributed Syst., vol. 33, no. 1, pp. 101-116, 2022. Cite
180Facilitating Load-Dependent Queueing Analysis Through Factorization (Extended Abstract). SIGMETRICS Perform. Evaluation Rev., vol. 49, no. 3, pp. 51-52, 2022. Cite
179GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing Environments. IEEE Trans. Parallel Distributed Syst., vol. 33, no. 11, pp. 2821-2833, 2022. Cite
178HUNTER: AI based holistic resource management for sustainable cloud computing. J. Syst. Softw., vol. 184, pp. 111124, 2022. Cite
177MCDS: AI Augmented Workflow Scheduling in Mobile Edge Cloud Computing Systems. IEEE Trans. Parallel Distributed Syst., vol. 33, no. 11, pp. 2794-2807, 2022. Cite
176SimTune: bridging the simulator reality gap for resource management in edge-cloud computing. Scientific Reports, vol. 12, pp. 19158, 2022. Cite
175TauSSA: Simulating Markovian Queueing Networks with Tau Leaping. SIGMETRICS Perform. Evaluation Rev., vol. 49, no. 4, pp. 70-75, 2022. Cite
174TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data. Proc. VLDB Endow., vol. 15, no. 6, pp. 1201-1214, 2022. Cite
173CAROL: Confidence-Aware Resilience Model for Edge Federations. Proc. of DSN, pp. 28-40, 2022. Cite
172Enhancing Performance Modeling of Serverless Functions via Static Analysis. Proc. of ICSOC, pp. 71-88, 2022. Cite
171JCSP: Joint Caching and Service Placement for Edge Computing Systems. Proc. of IWQoS, pp. 1-10, 2022. Cite
170LN: A Meta-solver for Layered Queueing Network Analysis. Proc. of QEST, pp. 232-254, 2022. Cite
169MetaNet: Automated Dynamic Selection of Scheduling Policies in Cloud Environments. Proc. of CLOUD, pp. 331-341, 2022. Cite
168Optimizing the Performance of Fog Computing Environments Using AI and Co-Simulation. Proc. of ICPE (Companion), pp. 25-28, 2022. Cite
167PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing. Proc. of INFOCOM, pp. 670-679, 2022. Cite
166Facilitating load-dependent queueing analysis through factorization. Perform. Evaluation, vol. 152, pp. 102241, 2021. Cite
165Performance Analysis Methods for List-Based Caches With Non-Uniform Access. IEEE/ACM Trans. Netw., vol. 29, no. 2, pp. 651-664, 2021. Cite
164Quality-Aware DevOps Research: Where Do We Stand?. IEEE Access, vol. 9, pp. 44476-44489, 2021. Cite
163Variational inference for Markovian queueing networks. Advances in Applied Probability, vol. 53, no. 3, pp. 687-715, 2021. Cite
162AI-driven performance management in data-intensive applications. Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning, Wiley-IEEE Press, pp. 199-222, 2021. Cite
161A Mixture Density Network Approach to Predicting Response Times in Layered Systems. Proc. of MASCOTS, pp. 1-8, 2021. Cite
160Deep Learning Models for Automated Identification of Scheduling Policies. Proc. of MASCOTS, pp. 1-8, 2021. Cite
159MEAD: Model-Based Vertical Auto-Scaling for Data Stream Processing. Proc. of CCGRID, pp. 314-323, 2021. Cite
158RDOF: Deployment Optimization for Function as a Service. Proc. of CLOUD, pp. 508-514, 2021. Cite
157Service Demand Distribution Estimation for Microservices Using Markovian Arrival Processes. Proc. of QEST, pp. 310-328, 2021. Cite
156Generative Optimization Networks for Memory Efficient Data Generation. arXiv preprint, vol. abs/2110.02912, 2021. Cite
155Artificial neural networks based techniques for anomaly detection in Apache Spark. Clust. Comput., vol. 23, no. 2, pp. 1345-1360, 2020. Cite
154Correction to: Artificial neural networks based techniques for anomaly detection in Apache Spark. Clust. Comput., vol. 23, no. 2, pp. 1361-1362, 2020. Cite
153Fluid approximation of closed queueing networks with discriminatory processor sharing. Perform. Evaluation, vol. 139, pp. 102094, 2020. Cite
152iThermoFog: IoT-Fog based automatic thermal profile creation for cloud data centers using artificial intelligence techniques. Internet Technol. Lett., vol. 3, no. 5, 2020. Cite
151RADON: rational decomposition and orchestration for serverless computing. SICS Softw.-Intensive Cyber Phys. Syst., vol. 35, no. 1-2, pp. 77-87, 2020. Cite
150TRACK-Plus: Optimizing Artificial Neural Networks for Hybrid Anomaly Detection in Data Streaming Systems. IEEE Access, vol. 8, pp. 146613-146626, 2020. Cite
149COCOA: Cold Start Aware Capacity Planning for Function-as-a-Service Platforms. Proc. of MASCOTS, pp. 1-8, 2020. Cite
148Integrated Performance Evaluation of Extended Queueing Network Models with Line. Proc. of WSC, pp. 2377-2388, 2020. Cite
147Performance Engineering for Microservices and Serverless Applications: The RADON Approach. Proc. of ICPE Companion, pp. 46-49, 2020. Cite
146TRACK: Optimizing Artificial Neural Networks for Anomaly Detection in Spark Streaming Systems. Proc. of VALUETOOLS, pp. 188-191, 2020. Cite
145A Framework for Allocating Server Time to Spot and On-Demand Services in Cloud Computing. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 4, no. 4, pp. 20:1-20:31, 2019. Cite
144A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade. ACM Comput. Surv., vol. 51, no. 5, pp. 105:1-105:38, 2019. Cite
143Cognitive Distance and Research Output in Computing Education: A Case-Study. IEEE Trans. Educ., vol. 62, no. 2, pp. 99-107, 2019. Cite
142Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge. J. Syst. Softw., vol. 155, pp. 104-129, 2019. Cite
141Novel Solutions for Closed Queueing Networks with Load-Dependent Stations. SIGMETRICS Perform. Evaluation Rev., vol. 47, no. 2, pp. 30-32, 2019. Cite
140ATOM: Model-Driven Autoscaling for Microservices. Proc. of ICDCS, pp. 1994-2004, 2019. Cite
139Automated Multi-paradigm Analysis of Extended and Layered Queueing Models with LINE. Proc. of ICPE Companion, pp. 37-38, 2019. Cite
138SD: A Divergence-Based Estimation Method for Service Demands in Cloud Systems. Proc. of FiCloud, pp. 197-204, 2019. Cite
137QMLE: A Methodology for Statistical Inference of Service Demands from Queueing Data. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 3, no. 4, pp. 17:1-17:28, 2018. Cite
136A Neural-Network Driven Methodology for Anomaly Detection in Apache Spark. Proc. of QUATIC, pp. 201-209, 2018. Cite
135Analyzing Replacement Policies in List-Based Caches with Non-Uniform Access Costs. Proc. of INFOCOM, pp. 432-440, 2018. Cite
134Anomaly Detection for Big Data Technologies. Proc. of ICCSW, pp. 8:1-8:1, 2018. Cite
133PAX: Partition-aware autoscaling for the Cassandra NoSQL database. Proc. of NOMS, pp. 1-9, 2018. Cite
132Approximate Bayesian inference with queueing networks and coupled jump processes. arXiv preprint, vol. abs/1807.08673, 2018. Cite
131Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. ACM Meas. Anal. Comput. Syst., vol. 1, no. 1, pp. 8:1-8:25, 2017. Cite
130Line: Evaluating Software Applications in Unreliable Environments. IEEE Trans. Reliab., vol. 66, no. 3, pp. 837-853, 2017. Cite
129Modelling and Simulation Challenges in Internet of Things. IEEE Cloud Comput., vol. 4, no. 1, pp. 62-69, 2017. Cite
128Performance Evaluation with Java Modelling Tools: : A Hands-on Introduction. SIGMETRICS Perform. Evaluation Rev., vol. 45, no. 3, pp. 246-247, 2017. Cite
127Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. of SIGMETRICS (Abstracts), pp. 64, 2017. Cite
126Energy-efficient resource allocation and provisioning for in-memory database clusters. Proc. of IM, pp. 19-27, 2017. Cite
125Enhancing Big Data Application Design with the DICE Framework. Proc. of ESOCC Workshops, pp. 164-168, 2017. Cite
124Generalized Synchronizations and Capacity Constraints for Java Modelling Tools. Proc. of ICPE, pp. 169-170, 2017. Cite
123How to Supercharge the Amazon T2: Observations and Suggestions. Proc. of CLOUD, pp. 278-285, 2017. Cite
122Performance-aware refactoring of cloud-based big data applications. Proc. of CSCI 2017, pp. 1505-1510, 2017. Cite
121Tulsa: A Tool for Transforming UML to Layered Queueing Networks for Performance Analysis of Data Intensive Applications. Proc. of QEST, pp. 295-299, 2017. Cite
120A note on integrating products of linear forms over the unit simplex. arXiv preprint, vol. abs/1704.05867, 2017. Cite
119A Bayesian Approach to Parameter Inference in Queueing Networks. ACM Trans. Model. Comput. Simul., vol. 27, no. 1, pp. 2, 2016. Cite
118Compact Markov-modulated models for multiclass trace fitting. Eur. J. Oper. Res., vol. 255, no. 3, pp. 822-833, 2016. Cite
117Contention-Aware Workload Placement for In-Memory Databases in Cloud Environments. ACM Trans. Model. Perform. Evaluation Comput. Syst., vol. 2, no. 1, pp. 1:1-1:29, 2016. Cite
116OptiSpot: minimizing application deployment cost using spot cloud resources. Clust. Comput., vol. 19, no. 2, pp. 893-909, 2016. Cite
115QRF: An Optimization-Based Framework for Evaluating Complex Stochastic Networks. ACM Trans. Model. Comput. Simul., vol. 26, no. 3, pp. 15:1-15:24, 2016. Cite
114A Queueing Network Model for Performance Prediction of Apache Cassandra. Proc. of VALUETOOLS, 2016. Cite
113An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems. Proc. of MASCOTS, pp. 39-48, 2016. Cite
112Automated Parameterization of Performance Models from Measurements. Proc. of ICPE, pp. 325-326, 2016. Cite
111Current and Future Challenges of Software Engineering for Services and Applications. Proc. of Cloud Forward, pp. 34-42, 2016. Cite
110Efficient Memory Occupancy Models for In-memory Databases. Proc. of MASCOTS, pp. 430-432, 2016. Cite
109Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data. Proc. of ICPE, pp. 3-14, 2016. Cite
108Model-Driven Application Refactoring to Minimize Deployment Costs in Preemptible Cloud Resources. Proc. of CLOUD, pp. 335-342, 2016. Cite
107Performance Engineering for In-Memory Databases: Models, Experiments and Optimization. Proc. of ICPE Companion, pp. 13, 2016. Cite
106Performance Prediction for Burstable Cloud Resources. Proc. of VALUETOOLS, 2016. Cite
105Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases. Proc. of QRS, pp. 286-297, 2016. Cite
104Estimating Computational Requirements in Multi-Threaded Applications. IEEE Trans. Software Eng., vol. 41, no. 3, pp. 264-278, 2015. Cite
103Evaluating approaches to resource demand estimation. Perform. Evaluation, vol. 92, pp. 51-71, 2015. Cite
102Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data. SIGMETRICS Perform. Evaluation Rev., vol. 43, no. 2, pp. 45-47, 2015. Cite
101QD-AMVA: Evaluating systems with queue-dependent service requirements. Perform. Evaluation, vol. 91, pp. 80-98, 2015. Cite
100Autonomic Provisioning and Application Mapping on Spot Cloud Resources. Proc. of ICCAC, pp. 57-68, 2015. Cite
99DICE: Quality-Driven Development of Data-Intensive Cloud Applications. Proc. of MiSE@ICSE, pp. 78-83, 2015. Cite
98Experiments or simulation? A characterization of evaluation methods for in-memory databases. Proc. of CNSM, pp. 201-209, 2015. Cite
97Filling the gap: a tool to automate parameter estimation for software performance models. Proc. of QUDOS@SIGSOFT FSE, pp. 31-32, 2015. Cite
96Less Can Be More: Micro-managing VMs in Amazon EC2. Proc. of CLOUD, pp. 317-324, 2015. Cite
95Towards a DevOps Approach for Software Quality Engineering. Proc. of WOSP-C@ICPE, pp. 5-10, 2015. Cite
94Blending randomness in closed queueing network models. Perform. Evaluation, vol. 82, pp. 15-38, 2014. Cite
93Quality-of-service in cloud computing: modeling techniques and their applications. J. Internet Serv. Appl., vol. 5, no. 1, pp. 11:1-11:17, 2014. Cite
92Evaluating Weighted Round Robin Load Balancing for Cloud Web Services. Proc. of SYNASC, pp. 393-400, 2014. Cite
91LibReDE: a library for resource demand estimation. Proc. of ICPE, pp. 227-228, 2014. Cite
90Memory-aware sizing for in-memory databases. Proc. of NOMS, pp. 1-9, 2014. Cite
89Towards Multi-Clouds engineering. Proc. of INFOCOM Workshops, pp. 1-6, 2014. Cite
88Heavy-traffic revenue maximization in parallel multiclass queues. Perform. Evaluation, vol. 70, no. 10, pp. 806-821, 2013. Cite
87Modelling exogenous variability in cloud deployments. SIGMETRICS Perform. Evaluation Rev., vol. 40, no. 4, pp. 73-82, 2013. Cite
86Performance models of storage contention in cloud environments. Softw. Syst. Model., vol. 12, no. 4, pp. 681-704, 2013. Cite
85A Feasibility Study of Host-Level Contention Detection by Guest Virtual Machines. Proc. of CloudCom (2), pp. 152-157, 2013. Cite
84An Offline Demand Estimation Method for Multi-threaded Applications. Proc. of MASCOTS, pp. 21-30, 2013. Cite
83Assessing SLA Compliance from Palladio Component Models. Proc. of SYNASC, pp. 409-416, 2013. Cite
82Bayesian Service Demand Estimation Using Gibbs Sampling. Proc. of MASCOTS, pp. 567-576, 2013. Cite
81Fitting second-order acyclic Marked Markovian Arrival Processes. Proc. of DSN, pp. 1-12, 2013. Cite
80RPO: Runtime web server optimization under simultaneous multithreading. Proc. of IM, pp. 85-92, 2013. Cite
79Supporting the Development and Operation of Multi-cloud Applications: The MODAClouds Approach. Proc. of SYNASC, pp. 417-423, 2013. Cite
78Towards a monitoring feedback loop for cloud applications. Proc. of MultiCloud@ICPE, pp. 43-44, 2013. Cite
77ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads. IEEE Trans. Netw. Serv. Manag., vol. 9, no. 2, pp. 198-212, 2012. Cite
76BURN: Enabling Workload Burstiness in Customized Service Benchmarks. IEEE Trans. Software Eng., vol. 38, no. 4, pp. 778-793, 2012. Cite
75Dealing with Burstiness in Multi-Tier Applications: Models and Their Parameterization. IEEE Trans. Software Eng., vol. 38, no. 5, pp. 1040-1053, 2012. Cite
74KPC-toolbox: fitting Markovian arrival processes and phase-type distributions with MATLAB. SIGMETRICS Perform. Evaluation Rev., vol. 39, no. 4, pp. 47, 2012. Cite
73Product-form approximation of queueing networks with phase-type service. SIGMETRICS Perform. Evaluation Rev., vol. 39, no. 4, pp. 36, 2012. Cite
72A class of tractable models for run-time performance evaluation. Proc. of ICPE, pp. 63-74, 2012. Cite
71MODAClouds: a model-driven approach for the design and execution of applications on multiple clouds. Proc. of MiSE, pp. 50-56, 2012. Cite
70OFBench: An Enterprise Application Benchmark for Cloud Resource Management Studies. Proc. of SYNASC, pp. 393-399, 2012. Cite
69WIQ: Work-Intensive Query Scheduling for In-Memory Database Systems. Proc. of IEEE CLOUD, pp. 33-40, 2012. Cite
68A generalized method of moments for closed queueing networks. Perform. Evaluation, vol. 68, no. 2, pp. 180-200, 2011. Cite
67Exact analysis of performance models by the Method of Moments. Perform. Evaluation, vol. 68, no. 6, pp. 487-506, 2011. Cite
66IO performance prediction in consolidated virtualized environments (abstracts only). SIGMETRICS Perform. Evaluation Rev., vol. 39, no. 3, pp. 17-18, 2011. Cite
65A Model of Storage I/O Performance Interference in Virtualized Systems. Proc. of ICDCS Workshops, pp. 34-39, 2011. Cite
64Approximate analysis of blocking queueing networks with temporal dependence. Proc. of DSN, pp. 574-585, 2011. Cite
63AutoCAT: Automated Product-Form Solution of Stochastic Models. Proc. of MAM, pp. 57-85, 2011. Cite
62Building accurate workload models using Markovian arrival processes. Proc. of SIGMETRICS, pp. 357-358, 2011. Cite
61Efficient parallelization of the Method of Moments for queueing networks using multi-modular algebra. Proc. of VALUETOOLS, pp. 176-185, 2011. Cite
60Fluid Analysis of Queueing in Two-Stage Random Environments. Proc. of QEST, pp. 21-30, 2011. Cite
59IO performance prediction in consolidated virtualized environments. Proc. of ICPE, pp. 295-306, 2011. Cite
58Markovian Workload Characterization for QoS Prediction in the Cloud. Proc. of IEEE CLOUD, pp. 147-154, 2011. Cite
57Quantitative system evaluation with Java modeling tools. Proc. of ICPE, pp. 449-454, 2011. Cite
56Approximating passage time distributions in queueing models by Bayesian expansion. Perform. Evaluation, vol. 67, no. 11, pp. 1076-1091, 2010. Cite
55KPC-Toolbox: Best recipes for automatic trace fitting using Markovian Arrival Processes. Perform. Evaluation, vol. 67, no. 9, pp. 873-896, 2010. Cite
54Model-Driven System Capacity Planning under Workload Burstiness. IEEE Trans. Computers, vol. 59, no. 1, pp. 66-80, 2010. Cite
53Sizing multi-tier systems with temporal dependence: benchmarks and analytic models. J. Internet Serv. Appl., vol. 1, no. 2, pp. 117-134, 2010. Cite
52Trace data characterization and fitting for Markov modeling. Perform. Evaluation, vol. 67, no. 2, pp. 61-79, 2010. Cite
51BAP: a benchmark-driven algebraic method for the performance engineering of customized services. Proc. of WOSP/SIPEW, pp. 3-14, 2010. Cite
50CWS: a model-driven scheduling policy for correlated workloads. Proc. of SIGMETRICS, pp. 251-262, 2010. Cite
49SLA-driven planning and optimization of enterprise applications. Proc. of WOSP/SIPEW, pp. 117-128, 2010. Cite
48Tools for Performance Evaluation of Computer Systems: Historical Evolution and Perspectives. Proc. of PERFORM, pp. 24-37, 2010. Cite
47Process-algebraic modelling of priority queueing networks. Proc. of PASTA 2010 workshop, 2010. Cite
46Product-form approximation of tandem queues via matrix-geometric methods. Proc. of NSMC 2010 workshop, 2010. Cite
45Automatically generating bursty benchmarks for multitier systems. SIGMETRICS Perform. Evaluation Rev., vol. 37, no. 3, pp. 32-37, 2009. Cite
44CoMoM: Efficient Class-Oriented Evaluation of Multiclass Performance Models. IEEE Trans. Software Eng., vol. 35, no. 2, pp. 162-177, 2009. Cite
43Feasibility regions: exploiting tradeoffs between power and performance in disk drives. SIGMETRICS Perform. Evaluation Rev., vol. 37, no. 3, pp. 43-48, 2009. Cite
42JMT: performance engineering tools for system modeling. SIGMETRICS Perform. Evaluation Rev., vol. 36, no. 4, pp. 10-15, 2009. Cite
41Autocorrelation-driven load control in distributed systems. Proc. of MASCOTS, pp. 1-10, 2009. Cite
40Automatic Stress Testing of Multi-tier Systems by Dynamic Bottleneck Switch Generation. Proc. of Middleware, pp. 393-413, 2009. Cite
39Estimating service resource consumption from response time measurements. Proc. of VALUETOOLS, pp. 48, 2009. Cite
38Injecting realistic burstiness to a traditional client-server benchmark. Proc. of ICAC, pp. 149-158, 2009. Cite
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