Below is a list of recent research publications and brief summaries. A complete list can be found in my CV and on DBLP.
- X. Wu, F. De Pellegrini, G. Gao, G. Casale. A Framework for Allocating Server Time to Spot and On-demand Services in Cloud Computing, ACM Trans. on Modeling and Perform. Eval. Comp. Sys., to appear.
- A new framework to provision spot and on-demand resources in cloud computing.
- S. S. Gill, P. Garraghan, V. Stankovski, G. Casale, et al. Holistic Resource Management for Sustainable and Reliable Cloud Computing: An Innovative Solution to Global Challenge, Journal of Systems and Software, Elsevier, May 2019.
- The paper presents a holistic resource management method for cloud systems taking into account reliability and energy efficiency.
- A. Gias, G. Casale, M. Woodside. ATOM: Model-Driven Autoscaling for Microservices, in Proc. of IEEE ICDCS, 11 pages, Jul 2019.
- The paper presents an auto-scaling method for microservices based architectures.
- G. Casale. Automated multi-paradigm analysis of extended and layered queueing models with LINE, in Proc. of ICPE, 2019. Best Demo Award.
- This a demo paper presenting version 2.0 of the LINE solver.
- G. Casale, P.G. Harrison, O.W. Hong. Novel Solutions for Closed Queueing Networks with Load-Dependent Stations, Proc. of MAMA workshop 2019.
- This is an extended abstract presenting new exact and approximate results for the analysis of load-dependent closed queueing networks.
- R. Buyya, S. N. Srirama, G. Casale, R. Calheiros, Y. Simmhan, B. Varghese, et al. A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade, ACM Computing Surveys, to appear.
- The paper surveys open and future problems in cloud computing to define a research agenda for the next decade.
- W. Wang, G. Casale, A. Kattepur, and M. Nambiar. QMLE: a Methodology for Statistical Inference of Service Demands from Queueing Data, ACM Trans. on Modeling and Perform. Eval. Comp. Sys., to appear.
- A methodology to infer service demands at resources based on queueing data.
- D. Tamburri, G. Casale. Cognitive Distance and Research Output in Computing Education: A Case-Study, IEEE Trans. on Education, to appear.
- A study on cognitive distance in doctoral education that hinders the quality and variety of research outputs from doctoral students.
- S. Dipietro, R. Buyya, G. Casale. PAX: Partition-Aware Autoscaling for the Cassandra NoSQL Database, in Proc. of IEEE/IFIP NOMS, Apr 2018.
- An autoscaling algorithm for runtime control of the Apache Cassandra NoSQL database.
- G. Casale. Analyzing replacement policies in list-based caches with non-uniform access costs, in Proc. of IEEE INFOCOM, Apr 2018. Best-in-Session Presentation Award. [acc. rate: 19.2%].
- Exact and approximate performance analysis of multi-level caches with first-come first-served and randomized replacement policies.
- J. Wen, L. Ren, F. Yan, D. J. Dubois, G. Casale, and E. Smirni. How to Supercharge the Amazon T2: Observations and Suggestions, IEEE CLOUD 2017.
- The paper proposes a methodology to increase the performance benefits of T2 instances on Amazon EC2.
- G. Casale. Accelerating Performance Inference over Closed Systems by Asymptotic Methods. ACM SIGMETRICS, Best paper award, June 2017.
- J. F. Pérez and G. Casale. LINE: Evaluating Software Applications in Unreliable Environments. IEEE Transactions on Reliability, 2017.
- A tool for performance and reliability analysis of layered queueing network in time-varying environments.
- K. Molka, G. Casale. Energy-Efficient Resource Allocation and Provisioning for In-Memory Database Clusters. IFIP/IEEE IM, May 2017. Best student paper award.
- An energy-aware consolidation algorithm for the SAP HANA in-memory database clusters
- D. Dubois, G. Casale. Performance Prediction for Burstable Cloud Resources. VALUETOOLS 2016 (tool paper).
- A tool for predicting performance metrics such as resource utilizations, request response times, and credit usage in burstable cloud VMs.
- S. Dipietro, G. Casale, G. Serazzi. A Queueing Network Model for Performance Prediction of Apache Cassandra. VALUETOOLS 2016.
- A multiclass simulation model for NoSQL capacity planning.
- G. Casale, A. Sansottera, P. Cremonesi. Compact Markov-Modulated Models for Multiclass Trace Fitting, INFORMS European J. of Operational Research (EJOR), 2016.
- A fitting methodology for marked Markovian arrival processes (MMAPs) and a novel method to avoid state-space explosion in their superposition.
- W. Wang, G. Casale, C. Sutton. A Bayesian Approach to Parameter Inference in Queueing Networks, ACM Trans. on Modeling and Computer Simulation (TOMACS), 2016.
- A method to obtain service demands in closed product-form queueing networks based on observations of unfinished work at the queueing stations (queue-length samples).
- D. J. Dubois, G. Casale. OptiSpot: Minimizing Application Deployment Cost using Spot Cloud Resources, Cluster Computing, Springer, 2016
- An heuristic to minimize deployment costs on Amazon EC2 spot VMs, taking into account workloads, system topology, and quality-of-service requirements.
- G. Casale, V. de Nitto-Personé, E. Smirni. QRF: An Optimization-Based Framework for Evaluating Complex Stochastic Networks, ACM Trans. on Modeling and Computer Simulation (TOMACS), 26(3):15, Jan 2016.
- Optimization-based algorithm to bound performance measures in queueing networks with bursty workloads and finite capacity buffers.
- R. Osman, J. F. Peréz, G. Casale. Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases, in Proc. of IEEE QRS, Aug 2016
- A method to characterize the performance of Amazon Relational Database Service (RDS) deployments when scaling the underpinning compute resources.
- D. Dubois, C. Trubiani, G. Casale. Model-driven Application Refactoring to Minimize Deployment Costs in Preemptible Cloud Resources, in Proc. of IEEE CLOUD, Jun 2016.
- A method to improve the deployment of a cloud application on Amazon EC2 spot instances through atomic refactoring actions.
- W. Wang, G. Casale, A. Kattepur, M. Nambiar. Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data, in Proc. of ACM/SPEC ICPE, Mar 2016. Best paper award.
- Maximum-likelihood estimators for service demands in closed queueing network models, including those with load-dependent stations.
- J.F. Pérez, G. Casale, S. Pacheco-Sanchez. Estimating Computational Requirements in Multi-Threaded Applications, IEEE Trans. on Software Engineering, 41(3):264–278, Mar 2015
- A method to estimate CPU requirements of CPU jobs using response time data.
- S. Spinner, G. Casale, F. Brosig, S. Kounev. Evaluating Approaches to Resource Demand Estimation, Performance Evaluation, Elsevier 92:51-71, Oct 2015.
- A survey and experimental comparison on demand estimation methods used in capacity planning, resource management and performance modelling.
- G. Casale, J. F. Pérez, W. Wang. QD-AMVA: Evaluating Systems with Queue-Dependent Service Requirements, Performance Evaluation, Elsevier, 91:80-98, Sep 2015. Also presented at IFIP Performance 2015.
- An efficient heuristic for the analysis of closed queueing networks where stations have service rates that depend on the current number or mix of requests at the station.
- K. Molka, G. Casale. Experiments or Simulation? A Characterization of Evaluation Methods for In-Memory Databases, in Proc. of IFIP/IEEE CNSM, Nov 2015.
- A comparison of the relative merits of design-of-experiments and simulation in the performance evaluation of SAP HANA.
- D. J. Dubois, G. Casale. Autonomic Provisioning and Application Mapping on Spot Cloud Resources, in Proc. of IEEE ICCAC, Sep 2015. Best paper award.
- An heuristic to minimize deployment costs on Amazon EC2 spot VMs, taking into account the workload and topology of the application and subject to quality of services requirements.
- J. Wen, L. Lu, G. Casale, E. Smirni. Less can be More: micro-Managing VMs in Amazon EC2, in Proc. of IEEE CLOUD, Jun 2015. Best paper award.
- A characterization of micro-VMs on Amazon EC2 and a proposal for CPU throttling methods.
2003-2014: see CV