A calculation model of charge and discharge capacity of electric vehicle cluster based on trip chain

The rapid response characteristics and high-speed growth of electric vehicles (EVs) demonstrate its potential to provide auxiliary frequency regulation services for independent system operators through vehicle-to-grid (V2G). However, due to the spatiotemporal random dynamics of travel behavior, it is challenging to evaluate the ability of EV cluster to provide ancillary services under the premise of reaching the expected state of charge (SOC) level. To address this issue, a novel calculation model of charge and discharge capacity of EV cluster based on trip chain with excellent parallel computing performance is presented in this work. Following the introduction of the characteristic variables of the proposed trip chain model, the user’s continuous travel behavior in a time scale of several weeks is simulated. In particular, a bidirectional V2G scheduling strategy based on the five-zone map is designed to guide the charging and discharging behavior of EVs, where the expected SOC levels are guaranteed. The results of a 3-week travel simulation verify the effectiveness of the presented model in coordinating the V2G scheme and calculating the charge and discharge capacity of the EV cluster

Global EDF Schedulability Analysis for Parallel Tasks on Multi-core Platforms

With the widespread adoption of multi-core architectures, it is becoming more important to develop software in ways that takes advantage of such parallel architectures. This particularly entails a shift in programming paradigms towards fine-grained, thread-parallel computing. Many parallel programming models have been introduced for targeting such intra-task thread-level parallelism. However, most successful results on traditional multi-core real-time scheduling are focused on sequential programming models. For example, thread-level parallelism is not properly captured into the concept of interference, which is key to many schedulability analysis techniques. Thereby, most interference-based analysis techniques are not directly applicable to parallel programming models. Motivated by this, we extend the notion of interference to capture thread-level parallelism more accurately. We then leverage the proposed notion of parallelism-aware interference to derive efficient EDF schedulability tests that are directly applicable to parallel task models, including DAG models, on multi-core platforms, without knowing an optimal schedule. Our evaluation results indicate that the proposed analysis significantly advances the state-of-the-art in global EDF schedulability analysis for parallel tasks. In particular, we identify that our proposed schedulability tests are adaptive to different degrees of thread-level parallelism and scalable to the number of processors, resulting in substantial improvement of schedulability for parallel tasks on multi-core platforms.MOE (Min. of Education, S’pore)Accepted versio

Toward Efficient Scheduling for Parallel Real-Time Tasks on Multiprocessors

Modern real-time applications are becoming more demanding computationally while their temporal requirements, dictated by the physical world, often remain unchanged. This coupled with the increasing prevalence of multiprocessors in real-time systems necessitates that highly computation-demanding real-time tasks need to be parallelized to exploit the parallelism offered by the underlying hardware, in order to satisfy their temporal constraints. Scheduling parallel real-time tasks, however, introduces a new layer of complexity due to the allowance for intra-task parallelism. This dissertation addresses the problem of scheduling parallel real-time tasks in which tasks may (or may not) access shared non-processor resources, such as in-memory buffers or data structures. Specifically, for independent tasks, we propose new scheduling algorithms and schedulability analyses for parallel tasks with these characteristics, under federated and global scheduling.Experimental results show that the proposed algorithms and analyses improve the previously introduced methods. For parallel tasks that may access shared non-processor resources, we present a blocking analysis for two different types of spinlocks; through evaluations, we make a recommendation for a preferable ordering of locks. We also study practical runtime parallel scheduler designs for soft real-time applications and present a design that is more suitable for soft real-time systems