Control reconfiguration

Abstract: We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme to reduce duty cycle and minimize idle listening. B-MAC supports on-the-fly reconfiguration and provides bidirectional interfaces for system services to optimize performance, whether it be for throughput, latency, or power conservation. We build an analytical model of a class of sensor network applications. We use the model to show the effect of changing B-MAC's parameters and predict the behavior of sensor network applications. By comparing B-MAC to conventional 802.11-inspired protocols, specifically SMAC, we develop an experimental characterization of B-MAC over a wide range of network conditions. We show that B-MAC's flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC. By deploying a real world monitoring application with multihop networking, we validate our protocol design and model. Our results illustrate the need for flexible protocols to effectively realize energy efficient sensor network applications.

Abstract: A general formulation of the feeder reconfiguration problem for loss reduction and load balancing is given, and a novel solution method is presented. The solution uses a search over different radial configurations created by considering switchings of the branch exchange type. To guide the search, two different power flow approximation methods with varying degrees of accuracy have been developed and tested. The methods are used to calculate the new power flow in the system after a branch exchange and they make use of the power flow equations developed for radial distribution systems. Both accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations. For load balancing, a load balance index is defined and it is shown that the search and power flow estimation methods developed for power loss reduction can also be used for load balancing since the two problems are similar. >

Abstract: The state machine approach is a general method for implementing fault-tolerant services in distributed systems. This paper reviews the approach and describes protocols for two different failure models—Byzantine and fail stop. Systems reconfiguration techniques for removing faulty components and integrating repaired components are also discussed.

Abstract: Future manufacturing systems need to cope with frequent changes and disturbances. As such, their control requires constant adaptation and high flexibility. Holonic manufacturing is a highly distributed control paradigm that promises to handle these problems successfully. It is based on the concept of autonomous co-operating agents, called `holons'. This paper gives an overview of the holonic reference architecture for manufacturing systems as developed at PMA-KULeuven. This architecture, called PROSA, consists of three types of basic holons: order holons, product holons, and resource holons. They are structured using the object-oriented concepts of aggregation and specialisation. Staff holons can be added to assist the basic holons with expert knowledge. The resulting architecture has a high degree of self-similarity, which reduces the complexity to integrate new components and enables easy reconfiguration of the system. PROSA shows to cover aspects of both hierarchical as well as heterarchical control approaches. As such, it can be regarded as a generalisation of the two former approaches. More importantly, PROSA introduces significant innovations: the system structure is decoupled from the control algorithm, logistical aspects can be decoupled from technical ones, and PROSA opens opportunities to achieve more advanced hybrid control algorithms.