Sven van der Meer

Towards autonomic management of communications networks

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.

Large Scale Management of Distributed Systems

Proceedings of the 17th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management, DSOM 2006, Dublin, Ireland, October 23-25, 2006

The Design of a New Policy Model to Support Ontology-Driven Reasoning for Autonomic Networking

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data, which include information and data models, ontologies, machine learning algorithms, and policy languages, are all different, and hence require different data in different formats. This paper describes a new version of the Directory Enabled Networks next generation (DEN-ng) policy model, which is part of the FOCALE autonomic network architecture. This new policy model has been built using three guiding principles: (1) the policy model is rooted in information models, so that it can govern managed entities, (2) the model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language can be developed from it.

Challenges for federated, autonomic network management in the Future Internet

Regardless of which networking protocols or technologies form the core of the Future Internet it is clear that the environment as a whole will need to support a very broad range of business and user interaction modes. In todays Internet we observe the growing trend for services to be both provided and consumed by loosely coupled value networks of consumers, providers and combined consumer/providers. In this paper we argue that this trend has major implications for network management in the Future Internet. In particular, we discuss six research challenges that we believe need to be addressed by the network management community if the potential for the Future Internet to flexibly support value networks is to be realized.

The Design of a New Context-Aware Policy Model for Autonomic Networking

This paper describes a new version of the DEN-ng context model, and how this model in conjunction with the DEN-ng policy model can be used for more effective and flexible context management. Both are part of the FOCALE autonomic network architecture. Context selects policies, which select roles that can be used, which in turn define allowed functionality for that particular context.

The Use of Context-Aware Policies and Ontologies to Facilitate Business-Aware Network Management

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, existing network management data has no link to business concepts. This makes it very difficult to ensure that services offered by the network are meeting business objectives. This paper describes a novel context-aware policy model that uses a combination of modeled and ontological data to determine the current context, which policies are applicable to that context, and what services and resources should be offered to which users and applications.

Modelling Context for Autonomic Networking

This paper describes a new version of the DEN-ng context model, and how this model in conjunction with the DEN-ng policy model can be used for more effective and flexible context management for autonomic networking. Both are part of the FOCALE autonomic network architecture. Context selects policies, which select roles that can be used, which in turn define allowed functionality for that particular context. A brief description of applications of this model for the FP7 Autonomic Internet project are described.

A recommender system architecture for predictive telecom network management

Current telecom networks generate massive amounts of monitoring data consisting of observations on network faults, configuration, accounting, performance, and security. Due to the ever increasing degree of complexity of networks, coupled with specific constraints (legal, regulatory, increasing scale of management in heterogeneous networks), the traditional reactive management approaches are increasingly stretched beyond their capabilities. A new network management paradigm is required that takes a preemptive rather than reactive approach to network management. This work presents the design and specification of E-Stream, a predictive recommendationbased solution to automated network management. The architecture of E-Stream illustrates the challenges of leveraging vast volumes of management data to identify preemptive corrective actions. Such design challenges are mitigated by the components of E-Stream, which together form a single functional system. The EStream approach starts by abstracting trace information to extract sequences of events relevant to interesting incidents in the network. After observing event sequences in incoming event streams, specific appropriate actions are selected, ranked, and recommended to preempt the predicted incidents.

Towards real-time management of virtualized telecommunication networks

The idea of virtualizing network functions is driven by recent advances in network-focused hardware. In 2012, several large telecommunication operators issued a call to action for Network Function Virtualization (NFV)1. The underlying idea is that every network service currently delivered on proprietary, application specific hardware should be deliverable using virtual machines. This means that routers, firewalls, load balancers and other network devices run virtualized on commodity hardware. Consequently, ETSI is extending this idea to mobile networks. Here, parts of the core and the radio access network will be virtualized. The immediate advantage is that any Virtual Network Function (VNF) can now be deployed, re-deployed and undeployed in the same way as any traditional virtual machine. Thus, NFV will result in more dynamic and agile networks than seen heretofore. However, this will raise a number of serious issues in managing these future networks. In this paper, we examine issues and challenges in orchestrating these virtualized functions and their interconnections to provide a more agile mobile telecommunication network.

Ontological generation of filter rules for context exchange in autonomic multimedia networks

Network management has suffered from increases in business, system, and operational complexity. This has been exacerbated by the heterogeneity in management data as well as the high quality requirements of multimedia services. Autonomic networking manages this growing complexity by adding intelligence inside network nodes and network management applications. While most autonomic applications simply use a control loop to monitor and configure entities, our work is aimed at building a self-governing network that is able to fulfill the requirements of current and future services. This means that management applications need a detailed and dynamic view of the contextual status of the network nodes as a whole in order to adapt their behaviour to changing context. In this paper, we propose an algorithm to semi-automatically generate filter rules based on existing information in a network management information model. These filter rules are used to determine the set of contextual data that needs to be exchanged with other nodes. The algorithm exploits the reasoning capabilities of ontologies and relies on the introduction of additional semantic relationships to achieve a fine-grained context exchange model. Large scale evaluations were conducted to characterise the performance of this ontological approach.