pith. sign in

arxiv: 2605.26604 · v1 · pith:3AHZ3NMHnew · submitted 2026-05-26 · 💻 cs.GT · cs.DC· cs.NI· econ.TH

Credibility Trilemma in Polymatroidal Service Markets

Pith reviewed 2026-07-01 16:09 UTC · model grok-4.3

classification 💻 cs.GT cs.DCcs.NIecon.TH
keywords mechanism designpolymatroidscredibilityincentive compatibilityrevenue optimalityservice marketstrilemmawelfare loss
0
0 comments X

The pith

No static sealed-bid mechanism can be revenue-optimal, DSIC for agents, and credible for the operator on non-modular polymatroids.

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

The paper examines service markets where feasibility constraints form a polymatroid. It models the marketplace operator as potentially strategic, able to deviate from promised allocations or payments. This leads to a trilemma showing that revenue-optimal mechanisms that are dominant-strategy incentive-compatible for agents cannot also be credible to the operator when the polymatroid is non-modular. The authors define the Cost of Non-Credibility to measure the resulting welfare loss and derive exact bounds for several graph topologies, along with resolution approaches like commitment mechanisms and actor separation.

Core claim

Modelling the operator as a strategic player, we establish a credibility trilemma: for single-parameter agents on a non-modular polymatroid, no static sealed-bid mechanism is simultaneously revenue-optimal, DSIC for agents, and credible for the operator. We introduce the Cost of Non-Credibility (CoNC) as a price-of-anarchy-style welfare-loss measure and obtain tight Θ-bounds across five topology classes, plus a matching upper bound O(|S|) on general DAGs realised by an Ω(|S|) witness on the SP-augmented sub-family.

What carries the argument

The credibility trilemma for non-modular polymatroids, which prevents any static sealed-bid mechanism from satisfying revenue optimality, agent DSIC, and operator credibility at the same time.

If this is right

  • The Cost of Non-Credibility admits tight Θ-bounds across single-edge, series, parallel, tree, and series-parallel topologies.
  • A matching O(|S|) upper bound and Ω(|S|) lower bound hold on general DAGs and the SP-augmented subfamily respectively.
  • Three structurally distinct resolutions are available: public broadcast or deferred-revelation commitment, administrative domain separation under settlement separation and four side conditions, and integrator competition orthogonal to mechanism execution.
  • An instance-level grounding confirms the trilemma holds on the edge-pricing market from external prior work.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Market designers facing strategic operators may have to sacrifice revenue or incentive compatibility to maintain credibility in polymatroid settings.
  • The topology-dependent bounds imply that the cost of credibility depends on the specific structure of the feasibility constraint, suggesting structure-aware mechanism design.
  • Introducing competition among integrators could resolve the trilemma by separating the roles of execution and settlement without changing the underlying allocation rule.

Load-bearing premise

The marketplace operator acts as a strategic player who may deviate from truthful execution or reporting.

What would settle it

Discovery of a static sealed-bid mechanism on a non-modular polymatroid that is revenue-optimal, DSIC, and credible, or calculation of a Cost of Non-Credibility value outside the stated Θ-bounds for one of the five topology classes.

Figures

Figures reproduced from arXiv: 2605.26604 by Hassan Mehmood, Kalle Timperi, Lauri Lov\'en, Praveen Kumar Donta, Sasu Tarkoma, Schahram Dustdar, Sujit Gujar.

Figure 1
Figure 1. Figure 1: The credibility trilemma (Theorem 1). On a non-modular polymatroidal service market, any two of the [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Running PAA scenario and the credibility gap. Agent [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Ghost-bid surplus by mechanism on three DAG topologies (Exps. 1–2): the vermillion VCG baseline is [PITH_FULL_IMAGE:figures/full_fig_p049_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Cost of Non-Credibility by mechanism/operator (deviations only; pooled over the three DAG topologies, [PITH_FULL_IMAGE:figures/full_fig_p051_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Realised submodularity gap 𝛾𝑖𝑗 is topology-monotone: the three kernel densities (shared axis) shift right tree < sp < entangled, with per-topology means (dashed) at 0.0012 / 0.0015 / 0.0017. The distributions overlap substantially — the ordering lives in the central tendency, not in separation — as quantified by the adjacent-pair Cliff’s 𝛿 (0.38 tree→sp, 0.19 sp→entangled). The per-class CoNC lower bound o… view at source ↗
read the original abstract

Mechanism-mediated service markets with polymatroidal feasibility admit efficient, dominant-strategy incentive-compatible (DSIC) allocation, but these guarantees implicitly assume truthful execution by the marketplace operator. Modelling the operator as a strategic player, we establish a credibility trilemma: for single-parameter agents on a non-modular polymatroid, no static sealed-bid mechanism is simultaneously revenue-optimal, DSIC for agents, and credible for the operator. We introduce the Cost of Non-Credibility (CoNC) as a price-of-anarchy-style welfare-loss measure and obtain tight $\Theta$-bounds across five topology classes (single-edge, series, parallel, tree, series-parallel), plus a matching upper bound $O(|\mathcal{S}|)$ on general DAGs realised by an $\Omega(|\mathcal{S}|)$ witness on the SP-augmented sub-family, turning the trilemma into a structural quantity. Three structurally distinct resolutions follow: public broadcast or deferred-revelation commitment, administrative domain separation under settlement separation and four side conditions, and integrator competition orthogonal to mechanism execution under disjoint actors. An instance-level grounding over the edge-pricing market of Amin et al. confirms the trilemma's robustness on a refereed external setting. The result establishes marketplace neutrality as a first-order design constraint on polymatroidal service markets rather than an implementation detail: where the operator is a strategic player, credibility trades off against revenue optimality and agent incentive compatibility along structurally characterised lines.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 1 minor

Summary. The manuscript claims that in mechanism-mediated service markets with polymatroidal feasibility, modeling the operator as a strategic player yields a credibility trilemma: for single-parameter agents on a non-modular polymatroid, no static sealed-bid mechanism is simultaneously revenue-optimal, DSIC for agents, and credible for the operator. It introduces the Cost of Non-Credibility (CoNC) as a price-of-anarchy-style welfare-loss measure, derives tight Θ-bounds across five topology classes (single-edge, series, parallel, tree, series-parallel) plus an O(|S|) upper bound on general DAGs with a matching Ω(|S|) witness on the SP-augmented subfamily, and proposes three resolutions (public broadcast/deferred-revelation commitment, administrative domain separation under four side conditions, and integrator competition). The trilemma is further grounded via an instance-level analysis on the edge-pricing market of Amin et al.

Significance. If the central negative result and the accompanying structural bounds hold, the work is significant in reframing marketplace neutrality as a first-order design constraint rather than an implementation detail for polymatroidal service markets. The explicit topology-class bounds, the matching DAG bounds, the introduction of CoNC, and the grounding on an external refereed setting (Amin et al.) are concrete strengths that could influence subsequent mechanism-design research in service markets.

minor comments (1)
  1. The abstract is information-dense; consider splitting the description of the trilemma, the CoNC bounds, and the resolutions into separate sentences or short paragraphs for improved readability.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript and the recommendation to accept. We are pleased that the credibility trilemma, the introduction of the Cost of Non-Credibility, the tight topology-class bounds, the matching DAG bounds, and the grounding on the Amin et al. setting are viewed as concrete strengths.

Circularity Check

0 steps flagged

No significant circularity; derivation is self-contained theoretical impossibility result

full rationale

The paper establishes a negative result (impossibility of a static sealed-bid mechanism satisfying revenue optimality, DSIC, and operator credibility on non-modular polymatroids) under the explicit modeling choice that the operator may act strategically. This premise is definitional to the trilemma rather than derived from or reducing to prior fitted parameters, self-citations, or ansatzes within the paper. No equations or steps in the provided abstract reduce a claimed prediction to an input by construction, nor does the result rely on load-bearing self-citation chains or uniqueness theorems imported from the authors' prior work. The CoNC bounds and resolution mechanisms are presented as derived structural quantities, with the overall claim remaining independent of its own outputs. The paper is self-contained as a proof against external benchmarks in mechanism design.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review prevents extraction of specific free parameters, axioms, or invented entities; the central modeling choice of a strategic operator is stated but not audited for independence.

pith-pipeline@v0.9.1-grok · 5829 in / 1009 out tokens · 27086 ms · 2026-07-01T16:09:33.641422+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

84 extracted references · 65 canonical work pages

  1. [1]

    Ibrahim Afolabi, Tarik Taleb, Konstantinos Samdanis, et al. 2018. Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions.IEEE Communications Surveys & Tutorials20, 3 (2018), 2429–2453. doi:10.1109/COMST.2018.2815638

  2. [2]

    Aiyer, Lorenzo Alvisi, Allen Clement, Mike Dahlin, Jean-Philippe Martin, and Carl Porth

    Amitanand S. Aiyer, Lorenzo Alvisi, Allen Clement, Mike Dahlin, Jean-Philippe Martin, and Carl Porth. 2005. BAR Fault Tolerance for Cooperative Services. InProc. 20th ACM Symposium on Operating Systems Principles (SOSP). 45–58. doi:10.1145/1095810.1095816

  3. [3]

    Mohammad Akbarpour and Shengwu Li. 2020. Credible Auctions: A Trilemma.Econometrica88, 2 (2020), 425–467. doi:10.3982/ECTA15925

  4. [4]

    AMD. 2024. AMD Secure Encrypted Virtualization-Secure Nested Paging (SEV-SNP). White paper

  5. [5]

    Saurabh Amin, Patrick Jaillet, Haripriya Pulyassary, and Manxi Wu. 2026. Market Design for Capacity Sharing in Networks.ACM Transactions on Economics and Computation14, 1, Article 2 (Feb. 2026), 47 pages. doi:10.1145/3777901

  6. [6]

    Anderson, André de Palma, and Jacques-François Thisse

    Simon P. Anderson, André de Palma, and Jacques-François Thisse. 1992.Discrete Choice Theory of Product Differentiation. MIT Press, Cambridge, MA

  7. [7]

    Aaron Archer and Éva Tardos. 2001. Truthful Mechanisms for One-Parameter Agents. InProc. 42nd IEEE Symp. Foundations of Computer Science (FOCS). 482–491. doi:10.1109/SFCS.2001.959924

  8. [8]

    Mark Armstrong. 2006. Competition in Two-Sided Markets.RAND Journal of Economics37, 3 (2006), 668–691. doi:10.1111/j.1756-2171.2006.tb00037.x

  9. [9]

    Lawrence M. Ausubel. 2004. An Efficient Ascending-Bid Auction for Multiple Objects.American Economic Review94, 5 (December 2004), 1452–1475. doi:10.1257/0002828043052330

  10. [10]

    Ausubel and Paul Milgrom

    Lawrence M. Ausubel and Paul Milgrom. 2006. The Lovely but Lonely Vickrey Auction. InCombinatorial Auctions, Peter Cramton, Yoav Shoham, and Richard Steinberg (Eds.). MIT Press, 17–40. https://doi.org/10.7551/mitpress/ 9780262033428.003.0002

  11. [11]

    2015.Industrial Organization: Markets and Strategies(2nd ed.)

    Paul Belleflamme and Martin Peitz. 2015.Industrial Organization: Markets and Strategies(2nd ed.). Cambridge University Press

  12. [12]

    Dirk Bergemann and Stephen Morris. 2005. Robust Mechanism Design.Econometrica73, 6 (2005), 1771–1813. doi:10.1111/j.1468-0262.2005.00638.x

  13. [13]

    Sushil Bikhchandani, Shurojit Chatterji, Ron Lavi, Ahuva Mu’alem, Noam Nisan, and Arunava Sen. 2006. Weak Monotonicity Characterizes Deterministic Dominant-Strategy Implementation.Econometrica74, 4 (2006), 1109–1132. doi:10.1111/j.1468-0262.2006.00697.x

  14. [14]

    Shyam Bikhchandani and John W. Mamer. 1997. Competitive Equilibrium in an Exchange Economy with Indivisibilities. Journal of Economic Theory74, 2 (1997), 385–413. doi:10.1006/jeth.1996.2269

  15. [15]

    Eric Budish, Peter Cramton, and John Shim. 2015. The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response.Quarterly Journal of Economics130, 4 (2015), 1547–1621. doi:10.1093/qje/qjv027

  16. [16]

    Matthew Weinberg

    Yang Cai, Constantinos Daskalakis, and S. Matthew Weinberg. 2017. A Duality-Based Unified Approach to Bayesian Mechanism Design.J. ACM64, 6 (2017), Article 39. doi:10.1145/3140772

  17. [17]

    Bernard Caillaud and Philippe Jehiel. 1998. Collusion in Auctions with Externalities.RAND Journal of Economics29, 4 (1998), 680–702. doi:10.2307/2556095

  18. [18]

    Bernard Caillaud and Bruno Jullien. 2003. Chicken and Egg: Competition Among Intermediation Service Providers. RAND Journal of Economics34, 2 (2003), 309–328. doi:10.2307/1593720

  19. [19]

    Jorge Cardoso, Amit Sheth, John Miller, Jonathan Arnold, and Krys Kochut. 2004. Quality of Service for Workflows and Web Service Processes.Web Semantics1, 3 (2004), 281–308. doi:10.1016/j.websem.2004.03.001

  20. [20]

    Fabio Casati and Ming-Chien Shan. 2001. Models and Languages for Describing and Discovering E-Services.SIGMOD Record30, 1 (2001), 83–92. doi:10.1145/373626.373738

  21. [21]

    Raymond Cheng, Fan Zhang, Jernej Kos, Warren He, Nicholas Hynes, Noah Johnson, Ari Juels, Andrew Miller, and Dawn Song. 2019. Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts. InProc. IEEE European Symposium on Security and Privacy (EuroS&P). 185–200. doi:10.1109/EuroSP.2019.00023

  22. [22]

    Tarun Chitra, Matheus V. X. Ferreira, and Kshitij Kulkarni. 2024. Credible, Optimal Auctions via Public Broadcast. In 6th Conf. Advances in Financial Technologies (AFT) (LIPIcs, Vol. 316). 19:1–19:16. doi:10.4230/LIPIcs.AFT.2024.19

  23. [23]

    Edward H. Clarke. 1971. Multipart Pricing of Public Goods.Public Choice11 (1971), 17–33. doi:10.1007/BF01726210

  24. [24]

    Victor Costan and Srinivas Devadas. 2016. Intel SGX Explained. InIACR Cryptology ePrint Archive. Report 2016/086. 0:60 Lovén et al

  25. [25]

    Francisco Curbera, Rania Khalaf, Nirmal Mukhi, Stefan Tai, and Sanjiva Weerawarana. 2003. The Next Step in Web Services. InCommunications of the ACM, Vol. 46. 29–34. doi:10.1145/944217.944234

  26. [26]

    Shuiguang Deng, Hailiang Zhao, Ziqi Wang, et al . 2025. Agentic Services Computing. arXiv:2509.24380 [cs.SE] https://arxiv.org/abs/2509.24380

  27. [27]

    Hana Derouiche, Zaki Brahmi, and Haithem Mazeni. 2025. Agentic AI Frameworks: Architectures, Protocols, and Design Challenges. arXiv:2508.10146 [cs.AI] https://arxiv.org/abs/2508.10146

  28. [28]

    R. J. Duffin. 1965. Topology of Series-Parallel Networks.J. Math. Anal. Appl.10, 2 (1965), 303–318. doi:10.1016/0022- 247X(65)90125-3

  29. [29]

    Jack Edmonds. 2003. Submodular Functions, Matroids, and Certain Polyhedra. InCombinatorial Optimization - Eureka, You Shrink!Springer-Verlag, Berlin, Heidelberg, 11–26. doi:10.1007/3-540-36478-1_2

  30. [30]

    Matheus V. X. Ferreira and S. Matthew Weinberg. 2020. Credible, Truthful, and Two-Round (Optimal) Auctions via Cryptographic Commitments. InProc. 21st ACM Conf. Economics and Computation (EC). 683–712. doi:10.1145/3391403. 3399495

  31. [31]

    Friedman and Paul Resnick

    Eric J. Friedman and Paul Resnick. 2001. The Social Cost of Cheap Pseudonyms.Journal of Economics & Management Strategy10, 2 (2001), 173–199. doi:10.1111/j.1430-9134.2001.00173.x

  32. [32]

    2005.Submodular Functions and Optimization(2nd ed.)

    Satoru Fujishige. 2005.Submodular Functions and Optimization(2nd ed.). Vol. 58. Elsevier

  33. [33]

    Williamson, and Oana Ciobotaru

    Ariel Gabizon, Zachary J. Williamson, and Oana Ciobotaru. 2019. PLONK: Permutations over Lagrange-bases for Oecumenical Noninteractive arguments of Knowledge. Cryptology ePrint Archive, Report 2019/953. https: //eprint.iacr.org/2019/953

  34. [34]

    Keke Gai, Jinnan Guo, Liehuang Zhu, and Shui Yu. 2020. Blockchain Meets Cloud Computing: A Survey.IEEE Communications Surveys & Tutorials22, 3 (2020), 2009–2030. doi:10.1109/COMST.2020.2989392

  35. [35]

    Aadityan Ganesh and Qianfan Zhang. 2025. Truthful, Credible, and Optimal Auctions for Matroids via Blockchains and Commitments. InProc. 26th ACM Conf. Economics and Computation (EC). doi:10.1145/3736252.3742652

  36. [36]

    Gagan Goel, Vahab Mirrokni, and Renato Paes Leme. 2015. Polyhedral Clinching Auctions and the AdWords Polytope. J. ACM62, 3, Article 18 (2015). doi:10.1145/2738038

  37. [37]

    Google Cloud. 2025. Announcing the Agent2Agent Protocol (A2A). Google Developers Blog. https://developers. googleblog.com/en/a2a-a-new-era-of-agent-interoperability/ Accessed: 2026-02-23

  38. [38]

    Jens Groth. 2016. On the Size of Pairing-Based Non-Interactive Arguments. InAdvances in Cryptology – EUROCRYPT 2016 (LNCS, Vol. 9666). Springer, 305–326. doi:10.1007/978-3-662-49896-5_11

  39. [39]

    Theodore Groves. 1973. Incentives in Teams.Econometrica41, 4 (1973), 617–631. doi:10.2307/1914085

  40. [40]

    Faruk Gul and Ennio Stacchetti. 1999. Walrasian Equilibrium with Gross Substitutes.Journal of Economic Theory87, 1 (1999), 95–124. doi:10.1006/jeth.1999.2531

  41. [41]

    Andrei Hagiu, Tat-How Teh, and Julian Wright. 2022. Should Platforms Be Allowed to Sell on Their Own Marketplaces? RAND Journal of Economics53, 2 (2022), 297–327. doi:10.1111/1756-2171.12408

  42. [42]

    John William Hatfield and Paul R. Milgrom. 2005. Matching with Contracts.American Economic Review95, 4 (2005), 913–935. doi:10.1257/0002828054825466

  43. [43]

    Thomas W. Hazlett. 2017. The Political Spectrum: The Tumultuous Liberation of Wireless Technology, from Herbert Hoover to the Smartphone.Yale University Press(2017)

  44. [44]

    Independent Assignment

    Masao Iri and Nobuaki Tomizawa. 1968. An Algorithm for Finding an Optimal “Independent Assignment”.Journal of the Operations Research Society of Japan11, 4 (1968), 201–217

  45. [45]

    Philippe Jehiel and Benny Moldovanu. 2001. Efficient Design with Interdependent Valuations.Econometrica69, 5 (2001), 1237–1259. doi:10.1111/1468-0262.00240

  46. [46]

    Xiaolin Jiang, Hossein Shokri-Ghadikolaei, Gabor Fodor, et al. 2019. Low-Latency Networking: Where Latency Lurks and How to Tame It.Proc. IEEE107, 2 (2019), 280–306. doi:10.1109/JPROC.2018.2863960

  47. [47]

    Bruno Jullien, Alessandro Pavan, and Marc Rysman. 2021. Two-Sided Markets, Pricing, and Network Effects. In Handbook of Industrial Organization. Vol. 4. Elsevier, 485–592. doi:10.1016/bs.hesind.2021.11.007

  48. [48]

    Kelso and Vincent P

    Alexander S. Kelso and Vincent P. Crawford. 1982. Job Matching, Coalition Formation, and Gross Substitutes. Econometrica50, 6 (1982), 1483–1504. doi:10.2307/1913392

  49. [49]

    Lina M. Khan. 2017. Amazon’s Antitrust Paradox.Yale Law Journal126, 3 (2017), 710–805

  50. [50]

    Elias Koutsoupias and Christos Papadimitriou. 2009. Worst-case equilibria.Computer Science Review3, 2 (2009), 65–69. doi:10.1016/j.cosrev.2009.04.003

  51. [51]

    1993.A Theory of Incentives in Procurement and Regulation

    Jean-Jacques Laffont and Jean Tirole. 1993.A Theory of Incentives in Procurement and Regulation. MIT Press, Cambridge, MA

  52. [52]

    Huaizhi Li and Mukesh Singhal. 2007. Trust Management in Distributed Systems .Computer40, 02 (Feb. 2007), 45–53. doi:10.1109/MC.2007.76

  53. [53]

    Lauri Lovén, Reza Farahani, Ilir Murturi, et al. 2026. Agentic Edge Intelligence: A Research Agenda. InProceedings of the 18th IEEE/ACM International Conference on Utility and Cloud Computing (UCC ’25). Association for Computing Credibility Trilemma in Polymatroidal Service Markets 0:61 Machinery, New York, NY, USA, Article 66, 5 pages. doi:10.1145/377327...

  54. [54]

    Lauri Lovén, Mohammad Mehdi Saleh, Bahar Farahani, Ilir Murturi, Miguel Bordallo López, Praveen Kumar Donta, and Schahram Dustdar. 2026. Real-Time AI Service Economy: A Framework for Agentic Computing Across the Continuum. arXiv preprint arXiv:2603.05614(2026)

  55. [55]

    Preston McAfee

    R. Preston McAfee. 1992. A Dominant Strategy Double Auction.Journal of Economic Theory56, 2 (1992), 434–450. doi:10.1016/0022-0531(92)90091-U

  56. [56]

    Paul Milgrom and Chris Shannon. 1994. Monotone Comparative Statics.Econometrica62, 1 (1994), 157–180. doi:10. 2307/2951479

  57. [57]

    2003.Discrete Convex Analysis

    Kazuo Murota. 2003.Discrete Convex Analysis. SIAM. doi:10.1137/1.9780898718508

  58. [58]

    Roger B. Myerson. 1981. Optimal Auction Design.Mathematics of Operations Research6, 1 (1981), 58–73. doi:10.1287/ moor.6.1.58

  59. [59]

    Myerson and Mark A

    Roger B. Myerson and Mark A. Satterthwaite. 1983. Efficient Mechanisms for Bilateral Trading.Journal of Economic Theory29, 2 (1983), 265–281. doi:10.1016/0022-0531(83)90048-0

  60. [60]

    OASIS WSBPEL TC. 2007. Web Services Business Process Execution Language Version 2.0. OASIS Standard. http: //docs.oasis-open.org/wsbpel/2.0/OS/wsbpel-v2.0-OS.html

  61. [61]

    James B. Orlin. 2013. Max Flows in O(nm) Time, or Better. InProc. 45th Annual ACM Symposium on Theory of Computing (STOC). 765–774. doi:10.1145/2488608.2488705

  62. [62]

    James G. Oxley. 2011.Matroid Theory(2nd ed.). Oxford Graduate Texts in Mathematics, Vol. 21. Oxford University Press

  63. [63]

    Papazoglou, Paolo Traverso, Schahram Dustdar, and Frank Leymann

    Mike P. Papazoglou, Paolo Traverso, Schahram Dustdar, and Frank Leymann. 2007. Service-Oriented Computing: State of the Art and Research Challenges.Computer40, 11 (2007), 38–45. doi:10.1109/MC.2007.400

  64. [64]

    Alessandro Pavan, Ilya Segal, and Juuso Toikka. 2014. Dynamic Mechanism Design: A Myersonian Approach. Econometrica82, 2 (2014), 601–653. doi:10.3982/ECTA10269

  65. [65]

    Jean-Charles Rochet and Jean Tirole. 2003. Platform Competition in Two-Sided Markets.Journal of the European Economic Association1, 4 (2003), 990–1029. doi:10.1162/154247603322493212

  66. [66]

    Roth and Marilda A

    Alvin E. Roth and Marilda A. O. Sotomayor. 1990.Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis. Cambridge University Press

  67. [67]

    Tim Roughgarden. 2015. Intrinsic Robustness of the Price of Anarchy.J. ACM62, 5 (2015), Article 32, 42 pages. doi:10.1145/2806883

  68. [68]

    Tim Roughgarden and Éva Tardos. 2002. How Bad is Selfish Routing?J. ACM49, 2, 236–259. doi:10.1145/506147.506153

  69. [69]

    Alaa Saleh et al. 2025. Follow-Me AI: Energy-Efficient User Interaction With Smart Environments.IEEE Pervasive Computing24, 1 (2025), 32–42. doi:10.1109/MPRV.2025.3539421

  70. [70]

    Steven C. Salop. 1979. Monopolistic Competition with Outside Goods.Bell Journal of Economics10, 1 (1979), 141–156. doi:10.2307/3003323

  71. [71]

    Mahadev Satyanarayanan. 2017. The Emergence of Edge Computing.Computer50, 1 (2017), 30–39. doi:10.1109/MC. 2017.9

  72. [72]

    2003.Combinatorial Optimization: Polyhedra and Efficiency

    Alexander Schrijver. 2003.Combinatorial Optimization: Polyhedra and Efficiency. Algorithms and Combinatorics, Vol. 24. Springer. Three volumes (A, B, C)

  73. [73]

    Vincenzo Sciancalepore, Xavier Costa-Perez, and Albert Banchs. 2019. RL-NSB: Reinforcement Learning-Based 5G Network Slice Broker.IEEE/ACM Transactions on Networking27, 4 (2019), 1543–1557. doi:10.1109/TNET.2019.2924471

  74. [74]

    George J. Stigler. 1971. The Theory of Economic Regulation.Bell Journal of Economics and Management Science2, 1 (1971), 3–21. doi:10.2307/3003160

  75. [75]

    Steven Tadelis. 2016. Reputation and Feedback Systems in Online Platform Markets.Annual Review of Economics8 (2016), 321–340. doi:10.1146/annurev-economics-080315-015325

  76. [76]

    Hongru Tan and Julian Wright. 2018. A Price Theory of Multi-Sided Platforms: Comment.American Economic Review 108, 9 (2018), 2758–2760. doi:10.1257/aer.20171048

  77. [77]

    Donald M. Topkis. 1998.Supermodularity and Complementarity. Princeton University Press, Princeton, NJ

  78. [78]

    Tarjan, and Eugene L

    Jacobo Valdes, Robert E. Tarjan, and Eugene L. Lawler. 1982. The Recognition of Series Parallel Digraphs.SIAM J. Comput.11, 2 (1982), 298–313. doi:10.1137/0211023

  79. [79]

    William Vickrey. 1961. Counterspeculation, Auctions, and Competitive Sealed Tenders.Journal of Finance16, 1 (1961), 8–37. doi:10.1111/j.1540-6261.1961.tb02789.x

  80. [80]

    Christof Weinhardt, Arun Anandasivam, Benjamin Blau, et al. 2009. Cloud Computing – A Classification, Business Models, and Research Directions.Business & Information Systems Engineering1, 5 (2009), 391–399. doi:10.1007/s12599- 009-0071-2

Showing first 80 references.