Research topic
This topic page groups Naser Ezzati-Jivan research papers related to resource analysis. Each linked record provides the paper's problem, method, findings, limitations, keywords, and authoritative source links.
Related search terms: resource analysis
17 papers in this topic, ordered newest first. The detailed paper records contain the evidence-grounded methods, tools, datasets, findings, and citation guidance.
2024 · The 37th Canadian Conference on Artificial Intelligence
The paper uses gradient boosting and feature importance to reduce the amount of trace data needed for microservice performance modeling.
Keywords: trace data volume · feature importance · CPU demand · memory demand · Alibaba microservices
2024 · 2024 IEEE International Conference on Collaborative Advances in Software and COmputiNg (CASCON)
MemAdapt forecasts memory behavior under irregular sampling and uses the forecast to choose an adaptive monitoring rate that balances estimation quality with collection overhead.
Keywords: memory monitoring · irregular sampling · adaptive monitoring · time series · memory usage
2023 · IEEE International Conference on Big Data
AltOOM combines early memory-pressure forecasting with selective process-level profiling to identify the process most responsible for an impending out-of-memory event.
Keywords: out-of-memory · OOM diagnosis · data-driven RCA · resource analysis · memory pressure forecasting
2021 · IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
The paper characterizes container workloads from host-level LTTng traces by selecting important threads and clustering execution-state behavior without instrumenting the containers internally.
Keywords: container workloads · host tracing · LTTng · pid_ns · tid
2021 · 2021 IEEE International Conference on Big Data (BigData)
The paper presents a low-intrusion heap monitor that records allocation call stacks and uses persistent heap-growth filtering plus trace correlation to identify likely memory-leak roots.
Keywords: heap monitoring · memory leaks · root-cause analysis · memory management · BigData 2021
2021 · 2021 IEEE International Systems Conference (SysCon)
The work bridges kernel-level hardware-counter sampling and user-space interpreter state so execution-path profiling can attribute performance evidence to interpreted code.
Keywords: execution paths · hardware performance counters · critical-path profiling · CPython · PyPMU
2021 · Journal of Hardware and Systems Security
The paper proposes a cloud-side anomaly detector that combines traffic, virtual-machine resource, and kernel-level indicators to identify several DDoS classes through change-point evidence.
Keywords: DDoS attacks · cloud environment · CUSUM · bandwidth exhaustion · application exhaustion
2020 · IEEE Internet of Things, GreenCom, CPSCom and SmartData
The paper correlates LTTng traces across OpenStack services, QEMU/KVM, network components, and host kernels to diagnose cloud-platform performance problems.
Keywords: cloud platforms · multi-level execution tracing · LTTng · LTTng-UST · OpenStack Nova
2019 · Journal of Hardware and Systems Security
The paper combines execution-trace and virtual-machine metrics with machine learning to detect EDoS behavior and restrict resource expansion to apparently normal VMs.
Keywords: Economic Denial of Sustainability · EDoS · DDoS · cloud computing · execution trace analysis
2017 · IEEE High Performance Extreme Computing Conference (HPEC)
The paper introduces a kernel-resident dynamic sampler that tracks virtual and physical memory usage while reducing the event volume generated by high-frequency memory activity.
Keywords: memory usage · dynamic sampling · enterprise applications · trace overhead · LTTng
2016 · IEEE BigData Congress
eSHT redesigns the State History Tree to store and query highly parallel trace intervals more compactly and with shallower trees.
Keywords: Enhanced State History Tree · eSHT · State History Tree · interval data · external-memory indexing
2016 · IEEE Future Internet of Things and Cloud Workshops (FiCloudW)
The paper fuses synchronized host and virtual-machine kernel traces into a Fused Virtual Machine view that exposes how VM threads, virtual CPUs, hypervisor transitions, and physical CPUs interact.
Keywords: virtualized systems · kernel tracing · multilayer analysis · virtualization overhead · LTTng
2015 · Concurrency and Computation: Practice and Experience
The paper proposes a multilevel data-cube model for computing statistics over live execution traces across several time scales.
Keywords: data cube · stream cube · live trace statistics · LTTng · State History Tree
2013 · ACM SIGOPS Operating Systems Review
The framework computes system-parameter statistics for arbitrary intervals and resource hierarchies from very large traces using a disk-resident history structure and controlled granularity.
Keywords: trace statistics · LTTng · Linux kernel 2.6.38.6 · disk-resident interval tree · history tree
2013 · IEEE International Conference on Social Computing
The paper presents a disk-oriented State History Tree that stores very large, time-ordered trace intervals without repeated node rebalancing.
Keywords: State History Tree · disk-based interval data · streaming interval data · time-ordered intervals · LTTng
2011 · Sixth International Conference on Internet Monitoring and Protection (ICIMP 2011)
The paper moves part of an application proxy into the kernel to reduce context switches and unnecessary data copies during connection filtering.
Keywords: in-kernel proxy · connection filtering · Fire Bench · SPECWeb2009 · context switches
2010 · Wireless Sensor Network
The paper proposes L-SYNCng, a time-synchronization protocol for heterogeneous wireless sensor networks that combines topology-aware clustering with convex-hull clock estimation.
Keywords: wireless sensor networks · time synchronization · L-SYNCng · convex hull · clock drift