Control reconfiguration

About: Control reconfiguration is a research topic. Over the lifetime, 22423 publications have been published within this topic receiving 334217 citations.

Software-Defined Networking for RSU Clouds in Support of the Internet of Vehicles

Abstract: We propose a novel roadside unit (RSU) cloud, a vehicular cloud, as the operational backbone of the vehicle grid in the Internet of Vehicles (IoV). The architecture of the proposed RSU cloud consists of traditional and specialized RSUs employing software-defined networking (SDN) to dynamically instantiate, replicate, and/or migrate services. We leverage the deep programmability of SDN to dynamically reconfigure the services hosted in the network and their data forwarding information to efficiently serve the underlying demand from the vehicle grid. We then present a detailed reconfiguration overhead analysis to reduce reconfigurations, which are costly for service providers. We use the reconfiguration cost analysis to design and formulate an integer linear programming (ILP) problem to model our novel RSU cloud resource management (CRM). We begin by solving for the Pareto optimal frontier (POF) of nondominated solutions, such that each solution is a configuration that minimizes either the number of service instances or the RSU cloud infrastructure delay, for a given average demand. Then, we design an efficient heuristic to minimize the reconfiguration costs. A fundamental contribution of our heuristic approach is the use of reinforcement learning to select configurations that minimize reconfiguration costs in the network over the long term. We perform reconfiguration cost analysis and compare the results of our CRM formulation and heuristic. We also show the reduction in reconfiguration costs when using reinforcement learning in comparison to a myopic approach. We show significant improvement in the reconfigurations costs and infrastructure delay when compared to purist service installations.

Multi-agent plan reconfiguration under local LTL specifications

Abstract: We propose a cooperative motion and task planning scheme for multi-agent systems where the agents have independently assigned local tasks, specified as linear temporal logic formulas. These tasks contain hard and soft sub-specifications. A least-violating initial plan is synthesized first for the potentially infeasible task and the partially-known workspace. This discrete plan is then implemented by the potential-field-based navigation controllers. While the system runs, each agent updates its knowledge about the workspace via its sensing capability and shares this knowledge with its neighbouring agents. Based on the knowledge update, each agent verifies and revises its motion plan in real time. It is ensured that the hard specification is always fulfilled for safety and the satisfaction for the soft specification is improved gradually. The design is distributed as only local interactions are assumed. The overall framework is demonstrated by a case study and an experiment.

On-line disk array reconfiguration

Abstract: A system for performing on-line reconfiguration of a disk array in which a source logical volume is reconfigured to a destination logical volume. Disk array configuration is invoked if a new physical drive is inserted, or a drive is removed. Reconfiguration can also be performed if the user desires to change the configuration of a particular logical volume, such as its stripe size. The disk array reconfiguration is run as a background task by firmware on a disk controller board. The reconfigure task first moves data from the source logical volume to a posting memory such as RAM memory. The reconfigure task operates one stripe at a time, with the stripe size being that of the destination logical volume. Once a stripe of data is moved into the posting memory, it is written back to corresponding locations in the destination logical volume. The reconfigure task continues until all data in the source logical volume have been moved into the destination logical volume. While the reconfigure task is working on a particular logical volume, data remains accessible to host write and read requests.

Overload management in real-time control applications using (m, k)-firm guarantee

Abstract: Tasks in a real-time control application are usually periodic and they have deadline constraints by which each instance of a task is expected to complete its computation, even in the adverse circumstances caused by component failures. Techniques to recover from processor failures often involve a reconfiguration in which all tasks are assigned to fault-free processors. This reconfiguration may result in processor overload where it is no longer possible to meet the deadlines of all tasks. In this paper, we discuss an overload management technique which discards selected task instances in such a way that the performance of the control loops in the system remain satisfactory even after a failure. The technique is based on the rationale that real-time control applications can tolerate occasional misses of the control law updates, especially if the control law is modified to account for these missed updates. The paper devises a scheduling policy which deterministically guarantees when and where the misses will occur. The paper also proposes a methodology for modifying the control law to minimize the deterioration in the control system behavior as a result of these missed control law updates.