Task-Complexity-Driven Stability Phase Transitions in Crowdsensing Systems
Bibliographic Data
| ID | 22107995 |
|---|---|
| Authors | Jiajun Zhang (0000-0002-8859-9542, Southeast University), Jun Tao (0000-0003-0610-4305, Southeast University), Haotian Wang (0000-0001-9783-6389, Southeast University), Yifan Xu (0000-0002-1573-9217, Southeast University), Zuyan Wang (0000-0002-7338-5912, Southeast University) |
| Year | 2026 |
| Volume | 13 |
| Issue | 3 |
| Pages | 2955-2968 |
| Publication date | 2026-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2026.3663288 |
| OpenAlex | W7140556308 |
| Language | EN |
| References cited | 42 |
Task complexity is widely regarded as a major barrier to cooperation in mobile crowdsensing (MCS), often leading to trust collapse and market failure. However, this view overlooks the constructive role of task complexity in shaping cooperative evolution. In this article, we propose a three-party evolutionary game framework involving workers, platforms, and task requesters, in which task complexity is explicitly modeled as an endogenous driver of trust dynamics and strategic interactions. We derive a set of anti-collapse conditions under which the marginal benefits of cooperative behavior overcompensate for the marginal costs induced by task complexity. Task complexity thereby propels an evolutionary phase transition from a low-trust trap to a stable cooperative equilibrium by reshaping the payoff structure of cooperative strategies. We further characterize the critical complexity thresholds that govern this phase transition through theoretical stability analysis. Extensive numerical simulations validate the theoretical predictions and demonstrate the robustness and effectiveness of the proposed mechanism in sustaining cooperative behavior across a wide range of task complexities
Crowdsensing · Phase transition · Diffusion and Search Dynamics · Distributed Control Multi-Agent Systems · Mobile Crowdsensing and Crowdsourcing
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| Citation velocity | historical |
|---|---|
| Highly cited | No |