Autonomic Systems Design for ITS Applications Apostolos Kotsialos, Member IEEE, and Adam Poole School of Engineering and Computing Sciences Durham University Durham, South Road, DH1 3LE, United Kingdom {apostolos.kotsialos, adam.poole}@durham.ac.uk Abstract— This paper discusses a systems design approach inspired from the autonomic nervous system for ITS appli- cations. This is done not with reference to the employed computing system, but to the requirements of traffic engineering applications. It is argued that the design and development of autonomic traffic management systems must identify the control loop that needs to be endowed with autonomic properties and subsequently use this framework for defining a desired set of self-* properties. A macroscopic network modelling application is considered for showing how autonomic systems design can be used for defining and obtaining self-* properties, with particular emphasis given in self-optimisation. I. INTRODUCTION Biological systems are highly robust, fault tolerant and able to sustain successful operation through a wide range of environmental conditions. By studying the properties of biological structures it is possible to design systems with sim- ilar properties. One such idea has been the development of autonomic computational systems. In the Autonomic Com- puting Manifesto [1], the vision of autonomic computing was outlined, aiming at the development of highly complex computational systems that are hiding the complexity of managing them from the system administrator allowing for high level policy to change and modify the whole system automatically. This is achieved by embedding, by design, a number of self-* properties to the system, such as self- configuration, self-healing, self-management, self-protection, self-optimisation and so forth. Autonomic computing’s biological inspiration comes from the Autonomic Nervous System (ANS), a subsystem of the peripheral nervous system. The ANS acts below the level of consciousness controlling visceral functions, such as the heart rate, digestion, respiratory rate, salivation, perspiration and sexual arousal. This system operates within a wide range of environmental as well as own states without a conscious effort. This is the important property. The autonomic co- ordination effort and marshaling of resources allows the conscious part to focus on more important, high level issues. In this sense, autonomic technological systems that are highly complex, heterogeneous and spatially distributed are designed to hide the complexity of the low level “involun- tary” operations from their users. The users’ input comes in the form of high-level policy statements and goals, expressed in intuitive terms, which disaggregate into sets of subgoals further down the hierarchy. The building elements in this case are not cells or other biological material, but rather technological artifacts that form at some level of abstraction autonomic elements. Designing such elements requires the definition of a set of self-* properties. The meaning assigned to them is domain and application specific. The notion of autonomics for system design purposes has been used in many domains, including energy management systems [2], communication networks [3], financial markets [4] and spacecraft operations [5]. This paper takes a look towards defining autonomic sys- tems for Intelligent Transport Systems (ITS). Similar lines of research have been proposed by the organic computing ini- tiative [6]. An architecture for real-time traffic management is proposed in [7]. Optimisation of decentralised autonomic systems for traffic control is reported in [8]. The rest of this paper is structured as follows. Section II describes the autonomic control loop and section III how it is adapted for ITS applications. Section IV proposes the structure of an autonomic network traffic flow modelling application. Section V concludes this paper. II. THE AUTONOMIC CONTROL LOOP The first step when trying to design or embed systems with autonomic properties, is to identify the level at which subsystems are going to show self-* behavior. The design effort depends on the range and depth of this behavior. Bear- ing in mind it is hierarchical and highly complex systems that require such treatment, the successful development of systems with “visceral” functions requires the identification of the control loops that should possess self-* features. The criterion for describing a system as autonomic remains that of the unconscious and sustained operation over the full range of environmental and own-state conditions. Technological competencies and system integration approaches define the decoupling point between the conscious and the unconscious regimes of a functioning system. It is the feedback control loop of the uncoscious part that should possess self-* prop- erties. The general autonomic control loop can be seen in Figure 1. It depicts the basic architecture of an autonomic element consisting of a managed resource and an autonomic man- ager. For the whole system to exhibit self-* behavior, the autonomic manager goes through the Monitor-Analyse-Plan- Execute (MAPE) process with knowledge management in the background. Sensors are used to collect information about the resource and effectors for interactions. This architecture Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands, October 6-9, 2013 MoB7.1 978-1-4799-2914-613/$31.00 ©2013 IEEE 178