Hierarchical Management Architecture for Multi-Access Networks

1. Hierarchical Management Architecture for Multi-Access Networks Dzmitry Kliazovich, Tiia Sutinen, Heli Kokkoniemi-Tarkkanen, Jukka Mäkelä & Seppo Horsmanheimo IEEE Global Communications Conference 2011 Houston, TX, USA

2. OUTLINE • Background • Motivation • Hierarchical Control and Management Architecture • Experimental evaluation: a test case • Conclusions & future work

3. BACKGROUND • In future, mobile communications is characterized more and more with access technology heterogeneity and concurrent utilization of multiple networks for optimal service • Network operators and users are facing the challenge of managing and maintaining networks of multiple technologies and selecting the most appropriate one for use, dynamically • E.g. LTE, HSPA, WLAN, WiMAX • Automated, cognitive network management mechanisms may be used for: • Decreasing the burden of multi-access network management for operators • Hiding the technical complexity of access selection from the users

4. COGNITIVE NETWORK MANAGEMENT “Cognitive network management involves intelligent network elements that observe the network conditions; plan, decide, and act based on the obtained information; as well as learnfrom their earlier decisions and adapt their operation accordingly.” • Cognitive network management mechanisms may be used for improving different aspects of network performance • Resource management • Qualityof Service (QoS) • Access control • Etc. • The optimization is done in the end-to-endscope

5. MOTIVATION • Current automated network management functions do not scale well considering the vast and complex multi-access and multi-operator environments of the future • Designed for small-scale networks and assuming an accurate view of the whole network status • New solutions are required for improving the decision-making accuracy in constantly changing environments with different levels of management as well as for optimizing the signaling • We propose a distributed and hierarchical management architecture supporting cognitive decision-making techniques for localized control and management

6. HIERARCHICAL CONTROL AND MANAGEMENT ARCHITECTURE (HCAM) • Enables real-time performance optimization and adaptive self-management of network entities and mobile terminals in multi-access and multi-operator networks • A process, which: • Keeps track of current network conditions • Analyses, plans, and makes decisions based on the prevailing conditions • Controls the results of its decisions and assesses them for their quality • Learns based on the earlier decisions’ quality evolving its decision-making ability • Consists of hierarchical Network Expert Systems (NES), Mobile Expert Systems (MES), and network resource probes

7. HIERARCHICAL NETWORK EXPERT SYSTEMS IN MULTI-OPERATOR ENVIRONMENT

8. DIFFERENT LEVELS OF MANAGEMENT • Access Network NES • Serves a segment of the operator access network • Uses various setup and performance information harvested by access network probes from the access network elements • Resolves terminal performance problems within asingleaccess technology by providing e.g. a horizontal handover • Operator NES • The main decision-making entity in the operator network • Resolves access network problems (indicated through AN NES feedback) that cannot be handled within the network itself • Provides a vertical handover to another access network, if needed

9. DIFFERENT LEVELS OF MANAGEMENT • Inter-Operator NES • Stands at the highest level of the HCAM hierarchy, but has a limited influence at the operator network performance • Focuses at performance optimization of the connections roaming out of the operator network • Mobile Expert System (MES) • Resides inside a mobile terminal • Maintains an explicit knowledge about currently running user applications, their QoS requirements, and a set of current communication performance parameters • Interfaces with Access Network NES to deliver performance alerts in case the QoS demands are not satisfied and the performance drawbacks cannot be resolved at the mobile terminal locally

10. HCAM OPERATION IN DIFFERENT LEVELS OF HIERARCHY

11. DETERMINING THE OVERALL SYSTEM STATUS AND PERFORMANCE • Efficient information signaling between HCAM entities is implemented using Triggering Engine (TRG) • Each entity (NES, MES, or a probe) can register itself with TRG and send/receive a trigger towards/from another entity • A trigger can also be originated from a hardware device, a protocol layer implemented in kernel space, or from a user-space application • Stepwise trigger processing and aggregation is supported for scalability • E.g. base station > probe > AN NES > Operator NES

12. CONTROLLING THE OVERALL SYSTEM PERFORMANCE • The decision-making and learning of HCAM entities may be implemented using different technologies • E.g. Self-Organized Map (SOM), Bayesian networks, and fuzzy logic • HCAM operation is driven by a set of policies: • User policies: guide MES operation and are directed to e.g. maximize QoE or minimize the communications’ cost • Operator policies: specify operator resource allocation, user admission, and billing policies, and influence the operation of Operator NES and Access Network NESs • Inter-operator policies: reflect resource management and roaming agreements between operators, and thus guide the decisions of Inter-Operator NES

13. MESSAGE FLOW DURING INTER-OPERATOR HANDOVER

14. FIRST EXPERIMENTS ON MULTI-ACCESS NETWORK MANAGEMENT USING COGNITIVE TECHNIQUES • A special testbed has been developed to evaluate the performance of the proposed HCAM architecture concept in a multi-access WLAN environment • We tested the ability of a SOM-based NES to detect growing network congestion long before any packets start to be discarded • We also showed how the NES can be used for improving the handover performance of Mobile IPv6 by providing timely hints for the handover decision-making regarding the access networks’ status • The results obtained from the testbed experiments confirm HCAM’s ability to detect and resolve performance bottlenecks to provide an increased level of QoE for the user applications

15. CONCLUSIONS • In the paper, we present a novel control and management architecture HCAM for large multi-access and multi-operator networks • The decision-making is performed by a number of network expert systems arranged into a tree • The HCAM operation is driven by a set of policies defined by terminal users, operators, and inter-operator relations • A proper distributed control and management architecture such as HCAM is envisioned as an enabling component for building future multi-access and multi-operator networks • Future works will consider wide-scale experimentation of HCAM as well as inclusion of several media-independent handover operations

16. THANK YOU FOR YOUR ATTENTION!Questions?tiia.sutinen@vtt.fi