Adaptive decision-making in buildingEXODUS

Given the importance of occupant behaviour on evacuation efficiency, a new behavioural feature has been implemented into buildingEXODUS. This feature concerns the response of occupants to exit selection and re-direction. This behaviour is not simply pre-determined by the user as part of the initialisation process, but involves the occupant taking decisions based on their previous experiences and the information available to them. This information concerns the occupants prior knowledge of the enclosure and line-of-sight information concerning queues at neighbouring exits. This new feature is demonstrated and reviewed through several examples.

Adaptive decision-making in response to crowd formations in building EXODUS

Given the importance of occupant behavior on evacuation efficiency, a new behavioral feature has been developed and implemented into buildingEXODUS. This feature concerns the response of occupants to exit selection and re-direction. This behavior is not simply pre-determined by the user as part of the initialization process, but involves the occupant taking decisions based on their previous experiences and the information available to them. This information concerns the occupants prior knowledge of the enclosure and line-of-sight information concerning queues at neighboring exits. This new feature is demonstrated and reviewed through several examples.

Adaptive decision-making in buildingEXODUS in response to exit congestion

Given the importance of occupant behavior on evacuation efficiency, a new behavioral feature has been implemented into building EXODUS. This feature concerns the response of occupants to exit selection and re-direction, given that the occupant is queuing at an external exit. This behavior is not simply pre-determined by the user as part of the initialization process, but involves the occupant taking decisions based on their previous experiences with the enclosure and the information available to them. This information concerns the occupant's prior knowledge of the enclosure and line-of-sight information concerning queues at neighboring exits. This new feature is demonstrated and reviewed through several examples.

Shape-optimized mesh partitioning and load balancing for parallel adaptive FEM

We present a dynamic distributed load balancing algorithm for parallel, adaptive Finite Element simulations in which we use preconditioned Conjugate Gradient solvers based on domain-decomposition. The load balancing is designed to maintain good partition aspect ratio and we show that cut size is not always the appropriate measure in load balancing. Furthermore, we attempt to answer the question why the aspect ratio of partitions plays an important role for certain solvers. We define and rate different kinds of aspect ratio and present a new center-based partitioning method of calculating the initial distribution which implicitly optimizes this measure. During the adaptive simulation, the load balancer calculates a balancing flow using different versions of the diffusion algorithm and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. Experimental results for Bramble's preconditioner and comparisons to state-of-the-art load balancers show the benefits of the construction.

Natural inspiration for self-adaptive systems

The emergent behaviour of autonomic systems, together with the scale of their deployment, impedes prediction of the full range of configuration and failure scenarios; thus it is not possible to devise management and recovery strategies to cover all possible outcomes. One solution to this problem is to embed self-managing and self-healing abilities into such applications. Traditional design approaches favour determinism, even when unnecessary. This can lead to conflicts between the non-functional requirements. Natural systems such as ant colonies have evolved cooperative, finely tuned emergent behaviours which allow the colonies to function at very large scale and to be very robust, although non-deterministic. Simple pheromone-exchange communication systems are highly efficient and are a major contribution to their success. This paper proposes that we look to natural systems for inspiration when designing architecture and communications strategies, and presents an election algorithm which encapsulates non-deterministic behaviour to achieve high scalability, robustness and stability.

On the persistence of computer dreams: an application framework for robust adaptive deployment

The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems – without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.

Spatial variability of air pollution in the vicinity of a permanent monitoring station in central Paris

The strong spatial and temporal variability of traffic-related air pollution detected at roadside locations in a number of European cities has raised the question of how representative the site and time period of air quality measurements actually can be. To address this question, a 7-month sampling campaign was carried out on a major road axis (Avenue Leclerc) leading to a very busy intersection (Place Basch) in central Paris, covering the surroundings of a permanent air quality monitoring station. This station has recorded the highest CO and NOx concentrations during recent years in the region of Paris. Diffusive BTX samplers as well as a mobile monitoring unit equipped with real-time CO, NOx and O3 analysers and meteorological instruments were used to reveal the small-scale pollution gradients and their temporal trends near the permanent monitoring station. The diffusive measurements provided 7-day averages of benzene, toluene, xylene and other hydrocarbons at different heights above the ground and distances from the kerb covering summer and winter periods. Relevant traffic and meteorological data were also obtained on an hourly basis. Furthermore, three semiempirical dispersion models (STREET-SRI, OSPM and AEOLIUS) were tested for an asymmetric canyon location in Av. Leclerc. The analysis of this comprehensive data set has helped to assess the representativeness of air quality monitoring information.

Flexible self-adjustment of task deployment in dynamic environments

This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies. Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication. This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker. A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy

Generic support for policy-based self-adaptive systems

This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.

Policy-based techniques for self-managing parallel applications

This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined.

Adaptive partition and hybrid method in fractal video compression

Fractal image compression is a relatively recent image compression method, which is simple to use and often leads to a high compression ratio. These advantages make it suitable for the situation of a single encoding and many decoding, as required in video on demand, archive compression, etc. There are two fundamental fractal compression methods, namely, the cube-based and the frame-based methods, being commonly studied. However, there are advantages and disadvantages in both methods. This paper gives an extension of the fundamental compression methods based on the concept of adaptive partition. Experimental results show that the algorithms based on adaptive partition may obtain a much higher compression ratio compared to algorithms based on fixed partition while maintaining the quality of decompressed images.

Adaptive ordering for imperfect successive decision feedback multiuser detection

A method for selecting the order in which the users are detected in communication systems employing adaptive successive decision feedback multiuser detection is proposed. Systems employing channel coding without the assumption of perfect decision feedback are analyzed. The method is based on the mean squared error (MSE) measurements during a training period for each user. The analysis' shows that the method delivers BER performance improvement relative to other previously proposed ordering methods