Evolving strategies for resilience

Develop specific evolving strategies for different wireless-system contexts to improve prediction and observability, fault tolerance, adaptation, survival, and recovery.

Background

The paper identifies evolvability as a supporting capability for resilience in future wireless systems. Evolvability involves learning from uncertainties and historical experience to achieve more accurate prediction and observability, more efficient fault tolerance and adaptation, and faster survival and recovery. Although artificial-intelligence- and machine-learning-driven approaches largely support evolvability in modern practice, the paper explicitly leaves the design of context-specific evolving strategies unresolved.

References

Although specific evolving strategies in different contexts remain open to be explored.

— Resilience in Trustworthy Wireless Systems  (2608.19850 - Wang et al., 20 Aug 2026) in Section 2.4, Subsection “Supporting Capabilities for Resilience”

Without an explicit owner, key lifecycle questions remain open: whether the envelope is fresh, whether a retransmission maps to an existing commitment, whether workflow execution may start, and whether a capability-change event should trigger downgrade, upgrade, recovery, release, or abort.

— A Capability Broker for Workflow-Network QoS Coordination in B5G/6G Industrial Services  (2608.24496 - Guo et al., 25 Aug 2026) in Section 2, subsection “Existing Primitives and Missing Object”