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  "paper_id": "efficient-cloud-tracing-levels",
  "page_url": "https://naser.github.io/research-publications/papers/efficient-cloud-tracing-levels/",
  "title": "Efficient Cloud Tracing: From Very High Level to Very Low Level",
  "title_variants": [],
  "authors": [
    "Yves J. Bationo",
    "Naser Ezzati-Jivan",
    "Michel R. Dagenais"
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  "publication": {
    "year": 2018,
    "venue": "IEEE International Conference on Consumer Electronics (ICCE)",
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    "issue": null,
    "pages": "1-6",
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  "description": "The paper correlates OpenStack Nova, QEMU/KVM, and host/guest kernel evidence to diagnose live-migration behavior across cloud-system layers.",
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    "problem": "A single cloud-management layer cannot explain migration downtime, resource contention, or the host/guest causes of a slow or failed VM migration.",
    "method": "Build a multi-layer trace from Nova state/log events, QEMU/KVM migration stages, and host/guest LTTng kernel events; synchronize controller, source, and destination traces and inspect the result in Trace Compass.",
    "findings": "The layered view connects Nova lifecycle states to QEMU migration stages and kernel scheduling, CPU, memory, I/O, and wait evidence. A colocated stress workload exposes slower migration and resource contention that high-level Nova events cannot explain.",
    "limitations": "The evaluation is a small live-migration use-case study with missing hardware/software/run-count metadata. Table III conflicts with the surrounding prose for the middle experiment; integration should preserve the table values and flag the conflict rather than normalize it.",
    "future_work": "Add richer Neutron and OpenDaylight/NFV request-flow evidence to cover the network-service path that is insufficiently represented in the current trace."
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  "tags": [
    "kernel-tracing",
    "system-tracing",
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    "cloud tracing",
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    "Trace Compass",
    "live migration"
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