Beyond Centrality
Conditional Connectivity and Boundary Control in Interdependent Networks
- Wu, Shaoyuan
Global AI Governance and Policy Research Center, EPINOVA LLC
https://orcid.org/0009-0008-0660-8232
Description
This working paper develops a Node-Boundary-Network-System framework for analyzing conditional connectivity and boundary control in interdependent networks. It argues that power cannot be inferred from centrality, brokerage, dependence, jurisdiction, or cross-network position alone when the usability of a relation varies by actor, function, direction, and time. The paper defines boundaries as indexed admissibility states, distinguishes rules from implementation interfaces, decomposes control into rights bundles, and separates structural exposure, available leverage, boundary action, admissible capacity, target response, network adaptation, and system transformation. A semiconductor-export-control walkthrough using NVIDIA A100/H100 product-time evidence illustrates the coding logic without claiming a causal estimate of policy effectiveness.
Abstract
Network analysis has transformed the study of power by showing how centrality, brokerage, dependence, exit options, and network topology shape influence. Contemporary network science also provides mature tools for multilayer, temporal, and interdependent networks, while weaponized-interdependence research demonstrates that jurisdiction and domestic institutions can convert structural position into coercive leverage. This article develops a Node-Boundary-Network-System framework centered on conditional usability. A boundary is defined as an actor-, function-, direction-, and time-indexed admissibility state. Rules define admissibility criteria; interfaces implement crossing; and control-rights bundles identify who may set, interpret, authorize, veto, enforce, or override those conditions. The framework separates structural position, available leverage, boundary action, admissible capacity, target response, network adaptation, and system transformation, and distinguishes systemic effects from systemic power. Capacity equations are restricted to explicitly ratio-scaled admissible capacity and separate authorized flow, unauthorized flow, and probabilistic approval. A semiconductor-export-control walkthrough uses a concrete NVIDIA A100/H100 product-time trace to illustrate the coding logic without claiming a causal estimate of policy effectiveness. Four discriminating hypotheses and a three-layer comparison strategy specify how NBNS can be tested against topology-only baselines and near-neighbor theories that already incorporate jurisdiction, institutions, dependence, and cross-network position.
Files
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Keywords
- network power
- conditional connectivity
- boundary control
- interdependence
- access
- decentralization
- systemic power
- strategic distance
- AI governance
- Node-Boundary-Network-System
- NBNS
- conditional usability
- boundary power
- admissible capacity
- control-rights bundle
- implementation interface
- cross-network conversion
- weaponized interdependence
- cross-network weaponization
- multilayer networks
- temporal networks
- systems theory
- semiconductor export controls
- NVIDIA A100
- NVIDIA H100
- EPINOVA
Subjects
- Network theory
- International political economy
- Strategic studies
- Systems theory
- AI governance
- Technology governance
- Semiconductor export controls
- Interdependence
- Power theory
- Complex systems
- Security studies
- Public policy
Recommended citation
Wu, S. (2026). Beyond Centrality: Conditional Connectivity and Boundary Control in Interdependent Networks (EPINOVA Working Paper No. EPINOVA–WP–T–2026–01). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.67037/epinova.wp.t.2026.01
APA citation
Wu, S. (2026). Beyond centrality: Conditional connectivity and boundary control in interdependent networks. EPINOVA Working Paper Series, EPINOVA-WP-T-2026-001. Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.67037/epinova.wp.t.2026.01.
Alternate identifiers
| Scheme | Identifier | Description |
|---|---|---|
| URL | https://epinova.org/working-papers | Official EPINOVA working papers page |
| EPINOVA working paper number | EPINOVA–WP–T–2026–01 | Working paper number printed in the PDF |
| File name | Beyond Centrality Conditional Connectivity, Boundary Control, and Systemic Power in Interdependent Networks.pdf | Source PDF file name |
| Framework acronym | NBNS | Node-Boundary-Network-System framework |
| Analytical concept | Conditional usability | Actor-, function-, direction-, and time-specific usability of a relation or transition |
| Analytical concept | Boundary power | Capacity to alter indexed admissibility conditions for relations, resources, information, authority, or functions across domains |
| Analytical concept | Systemic power | Attributable capacity to deliberately produce durable changes in rules, interoperability, architecture, or functional reproduction across networks |
Related works
| Relation | Identifier | Type | Description |
|---|---|---|---|
| IsPartOf | https://epinova.org/working-papers | Publication series | EPINOVA Working Paper Series |
| IsSupplementedBy | https://github.com/EPINOVALLC/EPINOVA-Research | Repository | Supplementary repository and structural archive |
| References | Farrell, H., & Newman, A. L. (2019). Weaponized interdependence | Journal article | Near-neighbor theory used as a strong baseline for jurisdictional and institutional conversion of centrality into leverage |
| References | Beaumier, G., & Cartwright, M. (2024). Cross-network weaponization in the semiconductor supply chain | Journal article | Near-neighbor theory used as a baseline for cross-network leverage in semiconductor supply chains |
| References | Hu et al. (2019). Guide to attribute based access control | Technical report | Referenced for fine-grained subject/object/operation/environment authorization logic |
| References | Schlager, E., & Ostrom, E. (1992). Property-rights regimes and natural resources | Journal article | Referenced for the bundle-of-rights logic adapted to boundary control |
| References | NVIDIA Corporation. (2022a, 2022b, 2024) | Corporate filings | Used for the A100/H100 semiconductor-control coding walkthrough |
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