A Design Science Research Architecture for Specialized Data Centers Supporting Real-Time C5I Operations in Contested, Hyper-Connected Environments: An EWNOC-Integrated Design with Simulation-Based Evaluation
More details
Hide details
1
Emiri Signal Corps, Qatar Armed Forces, Qatar
Submission date: 2026-09-26
Final revision date: 2026-10-12
Acceptance date: 2026-10-13
Online publication date: 2026-10-24
Publication date: 2026-10-24
Przegląd Nauk o Obronności 2026;(23):49-70
KEYWORDS
ABSTRACT
Objectives:
This study proposes, specifies, and evaluates a five-layer data-centre architecture integrated with an Electronic Warfare Network Operations Center (EWNOC) for real-time C5I operations in contested, Denied, Disconnected, Intermittent, and Limited (D-DIL) environments. The contribution is a design artefact accompanied by a reproducible model-based evaluation.
Methods:
Following Design Science Research (DSR), the study outlines three research questions, six design objectives, and six testable propositions. It specifies system boundaries, data flows, interfaces, and Zero Trust enforcement points. Evaluation against a centralized baseline and edge configuration employs: (i) a parameterized decision-cycle latency model with Monte Carlo and Sobol’ sensitivity analysis; (ii) an alternating-renewal availability model across four stress scenarios (EMS denial, thermal, physical attrition); and (iii) a model-based fault-injection campaign across eleven fault classes.
Results:
The architecture achieves a modelled machine-side decision-cycle latency of 0.96 ms at idle and 4.60 ms at peak load, outperforming the edge configuration (8.21 ms) and centralized baseline (64.8 ms). Under mid-range planning assumptions, mission availability reaches 99.907% with a 14.2-min MTTR (baseline: 99.40%, 89 min). Target goals (99.985% availability, 12-min MTTR) are achieved (99.993%, 2.2 min) only within an explicit envelope of failover coverage, common-cause separation, and logistics. Sensitivity is dominated by repair time, failover coverage, and common-cause fractions.
Conclusions:
The artefact offers transparent, falsifiable performance claims. High availability and fast recovery are conditional design requirements rather than intrinsic properties, requiring physical prototyping and expert evaluation prior to operational deployment.
REFERENCES (19)
1.
Avizienis, A., Laprie, J. C., Randell, B., & Landwehr, C. (2004). Basic concepts and taxonomy of dependable and secure computing. IEEE Transactions on Dependable and Secure Computing, 1(1), 11–33.
2.
Barroso, L. A., & Hölzle, U. (2007). The case for energy-proportional computing. Computer, 40(12), 33–37.
3.
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital twin: Enabling technologies, challenges and open research. IEEE Access, 8, 108952–108971.
4.
Gregor, S., & Hevner, A. R. (2013). Positioning and presenting design science research for maximum impact. MIS Quarterly, 37(2), 337–355.
5.
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105.
6.
Hsueh, M. C., Tsai, T. K., & Iyer, R. K. (1997). Fault injection techniques and tools. Computer, 30(4), 75–82.
7.
Kott, A., & Linkov, I. (2019). Fundamental concepts of cyber resilience: Introduction and overview. In A. Kott & I. Linkov (Eds.), Cyber resilience of systems and networks. Springer.
8.
Kott, A., Swami, A., & West, B. J. (2016). The Internet of Battle Things. Computer, 49(12), 70–75.
9.
Larsen, K. R., Lukyanenko, R., Mueller, R. M., Storey, V. C., Parsons, J., VanderMeer, D., & Hovorka, D. S. (2025). Validity in design science. MIS Quarterly, 49(4), 1267–1294.
https://doi.org/10.25300/MISQ/....
10.
Lewis, G., Echeverría, S., Simanta, S., Bradshaw, B., & Root, J. (2014). Tactical cloudlets: Moving cloud computing to the edge. In Proceedings of the IEEE Military Communications Conference (MILCOM 2014) (pp. 1440–1446). IEEE.
https://doi.org/10.1109/MILCOM....
11.
Marsili, M. (2021). The Russian influence strategy in its contested neighbourhood. In H. Mölder, V. Sazonov, A. Chochia, & T. Kerikmäe (Eds.), The Russian Federation in global knowledge warfare: Influence operations in Europe and its neighbourhood. Springer.
https://doi.org/10.1007/978-3-....
12.
Marsili, M. (2023). Guerre à la carte: Cyber, information, cognitive warfare and the metaverse. Applied Cybersecurity & Internet Governance, 2(1), 105–120.
https://doi.org/10.60097/ACIG/....
13.
McKay, M. D., Beckman, R. J., & Conover, W. J. (1979). A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics, 21(2), 239–245.
14.
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77.
15.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global sensitivity analysis: The primer. Wiley.
16.
Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1), 30–39.
17.
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637–646.
18.
Sobol’, I. M. (2001). Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280.
19.
Venable, J., Pries-Heje, J., & Baskerville, R. (2016). FEDS: A framework for evaluation in design science research. European Journal of Information Systems, 25(1), 77–89.