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REVIEW 3 major objections 6 minor 103 references

A Survey on Open-Source Edge Computing Simulators and Emulators: The Computing and Networking Convergence Perspective

T0 review · 3 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read The paper maps more than 40 open-source edge simulators and emulators and compares them on five dimensions so researchers can pick the right tool for validating computing and networking convergence ideas.

desk verdict Useful but uneven survey of edge simulators; the 'comprehensive' claim needs an inclusion audit before the guide can be trusted. read the letter →

arxiv 2505.09995 v1 pith:ODPE7F3A submitted 2025-05-15 cs.NI cs.DL

Jianpeng Qi , Chao Liu , Xiao Zhang , Lei Wang , Rui Wang , Junyu Dong , Yanwei Yu This is my paper · ORCID
classification cs.NIcs.DL
keywords edgecomputingsimulatoremulatoropen-sourcesoftwareandnetworkingconvergenceparadigmsperformancemetricsresourcemanagement
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper aims to establish a practical tool-selection guide for researchers working on the convergence of computing and networking. It surveys more than 40 open-source edge simulators and emulators, sorts them into packet-level simulators, application-level simulators, and emulators, and compares them along five dimensions: computing paradigms, resource simulation, performance metrics, resource management and utilization, and usability. A reader who trusts the survey gains a quick way to screen tools before reading code or documentation, which matters because edge-computing research often relies on self-written scripts and a mismatched tool can skew results or waste effort. The comparison also exposes weak spots in the ecosystem, such as sparse support for edge-environment conditions, custom metrics, and packet-level processing inside application-level simulators, and it uses those gaps to propose future directions for tool builders.

What carries the argument

The survey's load-bearing instrument is a five-dimension comparison grid — computing paradigms, resource simulation, performance metrics, resource management and utilization, and usability — applied to tools grouped into three implementation levels: packet-level simulation, application-level simulation, and emulation. The grid is what lets the paper hold tools as different as NS-3 and CloudSim side by side, by mapping each tool's core engine, its inheritance from a base engine such as CloudSim or OMNeT++, and the features it exposes in each dimension. The five tables produced by this grid are the mechanism that turns more than 40 separate tools into a comparable landscape, and they are also what makes the survey actionable for a reader choosing a tool.

What would settle it

Take one row of Tables I–V, for instance the claim that EdgeCloudSim models WLAN/WAN links and device mobility, and run a minimal edge-cloud scenario in that tool. If the advertised paradigm, metric, or scheduling policy is missing or unusable in practice, that row's guidance is false; enough such mismatches across the tables would refute the survey's usefulness as a selection guide.

Watch

Extended reading notes

Core claim

The authors claim that the open-source edge-computing ecosystem can be usefully organized by implementation level and by a common set of evaluation axes. They classify tools into packet-level simulators such as NS-3 and OMNeT++ and their extensions, application-level simulators such as CloudSim and its many descendants plus flow-level and serverless simulators, and emulators such as the Mininet family, CORE, Fogify, and StarryNet. For each tool they document which computing paradigms it supports, which hardware and communication resources it represents, which performance metrics it reports, how it allocates resources and schedules tasks, and how usable it is in terms of modular components, scripting, logging, and visualization. The payoff claim is that the five resulting tables let a researcher match a tool's strengths to the fidelity and scale their experiment needs, and they tell simulator builders where the ecosystem is still weak.

Load-bearing premise

The survey's usefulness rests on the accuracy of its five hand-compiled tables: if a table misstates what a tool actually supports, a researcher who follows the guide can pick the wrong tool.

Editorial extensions

If this is right

  • A researcher facing an edge-computing experiment can use the three-level classification to decide upfront whether they need packet-level fidelity, application-level scalability, or real-code emulation.
  • The five tables provide a quick shortlisting pass: check which tools support the needed computing paradigm, resource granularity, metric, and scheduling policy before reading any code.
  • The survey identifies concrete weak spots in the ecosystem — edge-environment factors such as weather, user-defined metric interfaces, and scenario-script and visualization support are rare — giving tool builders a targeted agenda.
  • Future edge simulators should move toward integrating multiple computing paradigms and toward bringing packet-level processing into application-level tools, since those are the gaps the comparison exposes.
  • The accompanying repository extends the comparison beyond the 40 surveyed tools to an actively curated list of more than 80 open-source projects, keeping the guide live as new tools appear.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • An implication the authors leave implicit is that their exclusion of specialized tools such as Emu5GNet, EmuEdge, and RaSim means the survey is best read as a general-purpose shortlist; a reader working on satellite, V2X, or constrained-device scenarios may still need a separate dedicated-tool pass.
  • Because the five tables record a snapshot of actively maintained repositories, the specific entries will decay quickly; the durable contribution is the five-dimension framework itself, which could stay useful as a living checklist that is re-run as repositories evolve.
  • The paper's observation that application-level simulators lack packet-level processing suggests an unexplored design: a hybrid that combines CloudSim-scale resource scheduling with NS-3-style packet event tracing could serve computing-while-transmitting scenarios better than either tool class alone.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper surveys open-source edge-computing simulators and emulators, with a companion GitHub repository, classifying more than 40 tools into packet-level simulators, application-level simulators, and emulators. It compares the tools across five dimensions (computing paradigms, resource simulation, performance metrics, resource management and utilization, and usability), presents the results in five tables, draws lessons about paradigm support and resource representation, and proposes five future research directions. The intended contribution is a practical tool-selection guide for researchers working on the convergence of computing and networking (CNC).

Significance. If the tool inventory is complete and the table entries are accurate, the survey would be a useful and timely reference for researchers selecting simulation and emulation platforms for CNC experiments. The companion GitHub repository, the explicit tracing of core-engine inheritance (e.g., CloudSim-derived tools), and the inclusion of community metrics such as stars and forks are concrete strengths that go beyond a purely narrative survey. The paper does not offer formal proofs or quantitative benchmarks, but the central value is as a structured, multidimensional comparison; its correctness hinges on the completeness and accuracy of the manually compiled Tables I–V.

major comments (3)
  1. [Section I.B and Tables I–V] The paper's central claim of comprehensiveness is not auditable as written. The selection criteria in Section I.B exclude tools without code updates in more than six years and tools that are specialized rather than general-purpose, but the terms 'specialized' and 'general-purpose' are never defined, and the manuscript does not provide a tool-by-tool reconciliation of the 80+ tools in the companion repository with the 42 tools in Tables I–V. At least one actively maintained, open-source, general-purpose edge-computing simulator, EdgeSimPy, appears to satisfy the stated criteria yet is absent from all five tables. If EdgeSimPy or comparable qualifying tools are omitted, the abstract's unqualified 'comprehensive' claim is false by the paper's own standard, and the selection guide would miss valid options. Please add an explicit inclusion/exclusion audit, define the 'general-purpose' criterion operationally, and either add qualifying tools or restrict the claimed scope.
  2. [Section I.B and Section II.A] The relationship between the literature-review process and the final tool list is unclear. Section I.B reports a Web of Science / Ei Compendex search yielding 192 results, refined to 41 unique papers, but the text never maps those 41 papers to the 42 tools in Tables I–V, nor does it explain how tools such as NS-3 and OMNeT++, which predate the five-year window, were selected. Without this mapping, the reader cannot distinguish tools that were deliberately excluded because they failed a criterion from tools that were simply not considered. This is load-bearing for the survey's completeness claim.
  3. [Section II.A and Table V] The three-way classification into packet-level simulators, application-level simulators, and emulators is central to the paper, but the operational rule for resolving overlap is not fully specified. The Remark in Section II.A states that classification is guided by the 'core purpose and most prominent use case,' yet Table V then assigns each tool a single 'Type' value (DES, Emu, or Hybrid) without showing how the rule was applied. For example, Simu5G is labeled Hybrid and PureEdgeSim is labeled DSE (almost certainly a typo for DES), but the criteria for 'Hybrid' are not defined in the text. The paper should make the classification rule precise enough that an independent reader could reproduce the column.
minor comments (6)
  1. [Section I.C] The organization paragraph contains an unresolved cross-reference: 'explores the core engines and supported computing paradigms (Section ??)' should be replaced with the actual section number.
  2. [Section VI (paragraph before Section VII)] The paragraph beginning 'We believe these adjustments, along with the detailed metrics in Section V, will provide a clearer and more accurate representation...' is leftover reviewer-response text and should be removed from the published version.
  3. [Section III.C and Tables I, II, IV, V] The simulator YAFS is consistently rendered as 'Y AFS' in the text and in all four tables; this should be corrected to YAFS, matching reference [38].
  4. [Section IV.A] The sentence 'For emulators, basic metrics can be directly obtained using well-developed tools such astopandiPerfonLinux' has missing spacing and should read 'such as top and iPerf on Linux.'
  5. [Section III.A and Section V.C] Several grammatical and typographical errors should be fixed, including 'faas-sim and SimGrid belongs to this category, as it simulates basic components' (subject-verb agreement and pronoun agreement), 'having a uniformed optimizing target' (should be 'a uniform optimizing target'), and the double comma in 'due to diverse user requirements,,'.
  6. [Table V] The 'Statistics' column is labeled inconsistently: the table footnote says 'citations/licenses/project information (Stars, Forks, Watchers, Contributors)', but the values in the column are GitHub stars, forks, watchers, and contributors, not citations. The column header and footnote should be aligned, and the retrieval date for these metrics should be stated.

Circularity Check

0 steps flagged · score 1.0 of 10

No material circularity: the survey's comparisons rest on external tool documentation and literature; self-citations appear as inputs but do not drive the conclusions.

full rationale

This is a survey and classification paper, not a derivation. The central claims are that more than 40 open-source edge computing simulators/emulators exist, that they can be grouped into packet-level simulators, application-level simulators, and emulators, and that their features can be compared along five dimensions. These claims are grounded in the cited primary tool papers, public repositories, and the authors' own inspection of code and documentation. There is no equation chain in which one result is derived from another, no fitted parameter that is later renamed as a prediction, and no uniqueness theorem invoked to force a choice. The self-references, notably the authors' GitHub repository [62] and their EasiEI simulator [92], function as survey inputs and as one source of tool discovery, not as the justification for the survey's classification or evaluation. Section I.B describes an independent literature search and explicit inclusion/exclusion criteria, so the selection is checkable against external sources. Whether the tool set is fully complete (e.g., possible omission of a qualifying tool such as EdgeSimPy) is an empirical scope/correctness concern, not circularity: the paper's own criteria could be applied to test that claim. The leftover editorial sentence in Section VI ('We believe these adjustments...') is a manuscript artifact with no argumentative role. Overall, no step reduces by construction or by self-citation to its own inputs.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

No free parameters or invented entities appear because the paper is a survey. The central claims rely on three domain assumptions about the comparison framework, selection criteria, and popularity metrics.

assumptions (3)
  • domain assumption The five comparison dimensions (computing paradigms, resource simulation, performance metrics, resource management, usability) are sufficient to characterize CNC simulators.
    The survey's entire comparative value depends on this framework; no justification is given beyond the authors' choice. Appears throughout Sections I through VI.
  • domain assumption The selection criteria (open-source, updated within six years, general-purpose) yield a representative set of tools for the CNC field.
    Section I.B states excluded tools not updated for over six years and specialized platforms (Emu5GNet, EmuEdge, RaSim); the impact of these exclusions on the 'comprehensive' claim is not assessed.
  • domain assumption GitHub popularity metrics (stars, forks, contributors) and citation counts are meaningful indicators of a tool's usability and impact.
    Table V reports these as 'Statistics' and implies they help researchers choose tools; no evidence is given for this proxy.

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Cite this review

Pith. "Pith review of A Survey on Open-Source Edge Computing Simulators and Emulators: The Computing and Networking Convergence Perspective." pith.science (2026). https://pith.science/paper/ODPE7F3A

@misc{pith2026250509995,
  author       = {Pith},
  title        = {Pith review of: A Survey on Open-Source Edge Computing Simulators and Emulators: The Computing and Networking Convergence Perspective},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ODPE7F3A}},
  note         = {Machine review of arXiv:2505.09995}
}
read the original abstract

Edge computing, with its low latency, dynamic scalability, and location awareness, along with the convergence of computing and communication paradigms, has been successfully applied in critical domains such as industrial IoT, smart healthcare, smart homes, and public safety. This paper provides a comprehensive survey of open-source edge computing simulators and emulators, presented in our GitHub repository (https://github.com/qijianpeng/awesome-edge-computing), emphasizing the convergence of computing and networking paradigms. By examining more than 40 tools, including CloudSim, NS-3, and others, we identify the strengths and limitations in simulating and emulating edge environments. This survey classifies these tools into three categories: packet-level, application-level, and emulators. Furthermore, we evaluate them across five dimensions, ranging from resource representation to resource utilization. The survey highlights the integration of different computing paradigms, packet processing capabilities, support for edge environments, user-defined metric interfaces, and scenario visualization. The findings aim to guide researchers in selecting appropriate tools for developing and validating advanced computing and networking technologies.

Figures

Figures reproduced from arXiv: 2505.09995 by the authors.

Figure 1
Figure 1. Categories Classified in This Survey Therefore, in the context of resource simulation, the ques￾tion remains: What level of detail or granularity is suitable for representing resources? What types of resources does the simulator support? These questions are not merely technical but also touch on the broader aspects of standardization, collaboration, and future-proofing in the rapidly evolving field of computing tech… view at source ↗
Figure 2
Figure 2. Categories and Inheritance of Simulators and Emulators [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗

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Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.