Steven Davy

Design and evaluation of algorithms for mapping and scheduling of virtual network functions

Network function virtualization has received attention from both academia and industry as an important shift in the deployment of telecommunication networks and services. It is being proposed as a path towards cost efficiency, reduced time-to-markets, and enhanced innovativeness in telecommunication service provisioning. However, efficiently running virtualized services is not trivial as, among other initialization steps, it requires first mapping virtual networks onto physical networks, and thereafter mapping and scheduling virtual functions onto the virtual networks. This paper formulates the online virtual function mapping and scheduling problem and proposes a set of algorithms for solving it. Our main objective is to propose simple algorithms that may be used as a basis for future work in this area. To this end, we propose three greedy algorithms and a tabu search-based heuristic. We carry out evaluations of these algorithms considering parameters such as successful service mappings, total service processing times, revenue, cost etc, under varying network conditions. Simulations show that the tabu search-based algorithm performs only slightly better than the best greedy algorithm.

The policy continuum-Policy authoring and conflict analysis

The policy continuum is a fundamental component of any policy-based management implementation for autonomic networking, but as of yet has no formal operational semantics. We propose a policy continuum model and accompanying policy authoring process that demonstrates the key properties that set a continuum apart from a non-hierarchical policy model. As part of the policy authoring process we present a policy conflict analysis algorithm that leverages the information model, making it applicable to arbitrary applications and continuum levels. The approach for policy conflict analysis entails analysing a candidate policy (either newly created or modified) on a pair-wise basis with already deployed policies and potential conflicts between the policies are fed back to the policy author. Central to the approach is a two-phase algorithm which firstly determines the relationships between the pair of policies and secondly applies an application specific conflict pattern to determine if the policies should be flagged as potentially conflicting. In this paper we present the formal policy continuum and two-phase conflict analysis algorithm as part of the policy authoring process, we describe an implementation where we demonstrate the detection of potential conflicts within a policy continuum.

Policy-based architecture to enable autonomic communications - a position paper

The increase in complexity of network management systems and a consequent lack of association to business requirements has driven the need for autonomic communications. By integrating context information, autonomic computing can provide more efficient means to counter technical problems found in complex network systems and at the same time address associated business requirements. In this paper, we propose an autonomic communications architecture that manages complexity through policy-based management where we incorporate a shared information model integrated with knowledge-based reasoning mechanisms to provide self- governaning behavior.

Challenges to support edge-as-a-service

A new era in telecommunications is emerging. Virtualized networking functions and resources will offer network operators a way to shift the balance of expenditure from capital to operational, opening up networks to new and innovative services. This article introduces the concept of edge as a service (EaaS), a means of harnessing the flexibility of virtualized network functions and resources to enable network operators to break the tightly coupled relationship they have with their infrastructure and enable more effective ways of generating revenue. To achieve this vision, we envisage a virtualized service access interface that can be used to programmatically alter access network functions and resources available to service providers in an elastic fashion. EaaS has many technically and economically difficult challenges that must be addressed before it can become a reality; the main challenges are summarized in this article.

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.

A Model Based Approach for Policy Tool Generation and Policy Analysis

We outline an approach to policy specification and analysis in which an information model is used as the starting point for semi-automated generation of an integrated suite of languages, tools and an ontology. The suite includes separate domain-specific languages for the specification of systems structure and policies respectively, editors and checkers for these languages, and a baseline ontology that can be augmented with semantic information to support policy analyses processes. We describe a prototypical realisation of the approach, showing how the languages, tools and ontology are used to support policy transformation and conflict detection processes.

The design of a novel context-aware policy model to support machine-based learning and reasoning

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 are all different, and hence require different data in different formats. This complicates the construction of context from diverse information sources. This paper describes a new version of the DEN-ng context-aware policy model, which is part of the FOCALE autonomic network architecture. This model has been built using three guiding principles: (1) both the context model and the policy model are rooted in information models, so that they can govern managed entities, (2) each 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 that supports machine-based reasoning and learning can be developed from it.

Application domain independent policy conflict analysis using information models

A key part of the policy authoring process is analysis of the potential for newly created or modified policies to conflict with already deployed policies. We propose an approach for policy conflict analysis in which candidate policies (either newly created or modified) are analyzed on a pair-wise basis with already deployed policies, with potential conflicts between the policies being notified to the policy author. Central to the approach is a two-phase algorithm which, querying an information model, firstly determines the relationships between the pair of policies and, secondly, applies an application-specific conflict pattern to determine if the policies should be flagged as potentially conflicting. The algorithm is generic in the sense that all application specific information is encoded in the information model; as long as a minimal set of assumptions regarding the policy model are adhered to it can be applied in arbitrary application domains. In the paper we present the two phase algorithm and describe an implementation in which it is used to detect potential conflicts for both access control and filtering (firewall) policies.

Self-organising Management Overlays for Future Internet Services

Networks are becoming service-aware implying that all relevant business goals pertaining to a service are fulfilled, and also the network resources are used optimally. Future Internet Networks (FIN) have time varying topology (e.g. such networks are envisaged in Autonomic Internet [1], FIND program [2], GENI program [3], FIRE program [4], Ambient Networks [5], Ad-hoc networks [6]) and service availability and service context change as nodes join and leave the networks. In this paper we propose and evaluate a new self-organising service management system that manages such changes known as the Overlay Management Backbones (OMBs). The OMB is a self-organising solution to the problem space in which each OMB node is dynamically assigned a different service context task. The selection of OMB nodes is conducted automatically, without the need of relatively heavy-weighted dynamic negotiations. Our solution relies on the scalability and dynamicity advantages of Distributed Hash Tables (DHTs). This system is needed to select continuously, automatically, and dynamically a set of network nodes, to become responsible for collecting the availability information of service context in the changing network. This solution advances the state of the art avoiding dynamic negotiations between all network nodes reducing management complexity and cost for bandwidth-limited environments.

On harnessing information models and ontologies for policy conflict analysis

We present a policy conflict analysis process that makes use of pre-defined semantic models of an application to perform effective and efficient conflict analysis. The process is effective as it can be used to analyse for policy conflicts that may occur in different applications due to the separation of application specific information and constraints from the algorithms to semantic models, such as information model and ontologies. The process is efficient as it incorporates a pre-analysis policy selection step that reduces the number of policies that need to be analysed more extensively. Experimental results show that this process results in a significant reduction in the number of policies that needed to be analysed for potential conflict and that it is flexible enough to detect for policy conflict both for many popular applications and between different applications.