Towards autonomic management of communications networks

TLDR

Communications networks are increasingly dynamic, heterogeneous, and large, making traditional human‑based management ineffective and prompting a shift toward autonomic network management that enables self‑governance within business constraints. This article introduces the FOCALE autonomic network management architecture as a solution to the identified challenges. FOCALE is designed to enable business rule‑driven resource allocation, contextual sensing and interpretation, adaptive control loops, and dynamic data verification and learning.

Abstract

As communications networks become increasingly dynamic, heterogeneous, less reliable, and larger in scale, it becomes difficult, if not impossible, to effectively manage these networks using traditional approaches that rely on human monitoring and intervention to ensure they operate within desired bounds. Researchers and practitioners are pursuing the vision of autonomic network management, which we view as the capability of network entities to self-govern their behavior within the constraints of business goals that the network as a whole seeks to achieve. However, applying autonomic principles to network management is challenging for a number of reasons, including: (1) A means is required to enable business rules to determine the set of resources and/or services to be provided. (2) Contextual changes in the network must be sensed and interpreted, because new management policies may be required when context changes. (3) As context changes, it may be necessary to adapt the management control loops that are used to ensure that system functionality adapts to meet changing user requirements, business goals, and environmental conditions. (4) A means is required to verify modeled data and to add new data dynamically so that the system can learn and reason about itself and its environment. This article provides an introduction to the FOCALE autonomic network management architecture, which is designed to address these challenges.