The partitioned EDF scheduling of implicit-deadline sporadic task systems upon identical multiprocessor platforms is considered. The problem is known to be intractable, but many different polynomial-time algorithms have been proposed for solving it approximately. These different approximation algorithms have previously been compared using utilization bounds; they are compared here using a different metric--the speedup factor. It is shown that from the perspective of their speedup factors, the best partitioning algorithms are those that (i) assign the tasks in decreasing order of utilization; and (ii) are "reasonable" in the sense that they will assign a task if there is capacity available on some processor--such algorithms include the widely-used First-Fit Decreasing, Best-Fit Decreasing, and Worst-Fit Decreasing partitioning heuristics.

Hard real-time systems require absolute guarantees in their execution times. Worst case execution time (WCET) of a program has therefore become an important problem to address. However, performance enhancing features of a processor (e.g. cache) make WCET analysis a difficult problem. In this paper, we propose a novel analysis framework by combining abstract interpretation and program verification for different varieties of cache analysis ranging from single to multi-core platforms. Our framework can be instantiated with different program verification techniques, such as model checking and symbolic execution. Our modeling is used to develop a precise yet scalable timing analysis method on top of the Chronos WCET analysis tool. Experimental results demonstrate that we can obtain significant improvement in precision with reasonable analysis time overhead.

Today's embedded systems are exposed to variations in load demand due to complex software applications, dynamic hardware platforms, and the impact of the run-time environment. When these variations are large, and efficiency is required, adaptive on-line resource managers may be deployed on the system to control its resource usage. An often neglected problem is whether these resource managers are stable, meaning that the resource usage is controlled under all possible scenarios. In this paper we develop mathematical models for real-time embedded systems and we derive conditions which, if satisfied, lead to stable systems. For the developed system models, we also determine bounds on the worst case response times of tasks. We also give an intuition of what stability means in a real-time context and we show how it can be applied for several resource managers. We also discuss how our results can be extended in various ways.

Real-time multiprocessor systems have an increasing importance in current technology and are the source of innovations to build new applications that require high levels of computations (in for example, industrial processes, transportation, telecommunications, multimedia and medical equipment). In the context of real-time systems, it is not sufficient to prove the correctness of applications in term of results but also that those results are delivered in time. The following papers are extended, peer-reviewed, journal-versions of papers focusing on multiprocessor systems that have been selected by the conference program committee of the 19th Real-Time and Network Systems Conference (RTNS’2011) for their high quality. RTNS’2011 was held in Nantes, France in September 2011. The annual RTNS conference is mainly focused on the following topics: realtime system design and analysis; infrastructure and hardware for real-time systems; and real-time applications in the automotive, avionics, telecommunications, process control and the multimedia industries. Each paper was extended to add significant extra material and the resulting papers were re-reviewed and subject to the usual editorial process. The result is a special issue that we hope will be of interest to the real-time community. In recent years, multiprocessor architectures have become a firm favorite with the real-time community, and multicore processors are found in products ranging from small portable cell phones to large computer servers. New scheduling approaches

In this paper we study the scheduling of parallel and real-time recurrent tasks on multiprocessor platforms. Firstly, we propose a new parallel task model which allows recurrent tasks to be composed of several phases, each one composed of several threads. Each thread requires a single processor for execution and can be scheduled simultaneously. We then propose an algorithm to transpose popular Fork-Join task model to our MPMT task model. Secondly, we define several kinds of real-time schedulers that can be applied to our parallel task model. We distinguish between two scheduling classes: Hierarchical schedulers and Global Thread schedulers. We present and prove correct an exact schedulability test for each class. Lastly, we also evaluate the performance of our scheduling paradigm in comparison with Gang scheduling by means of simulations. In this work we extend the work of Lupu and Goossens in Scheduling of hard real-time multi-thread periodic tasks (Real-Time and Network Systems, 2011) which considers mono-phase multi-thread task model. We extend their previous results to a Multi-Phase Multi-Thread task model.

Memory resources are a serious bottleneck in many real-time multicore systems. Previous work has shown that, in the worst case, execution time of memory intensive tasks can grow linearly with the n...

Without the use of caches the increasing gap between processor and memory speeds in modern embedded microprocessors would have resulted in memory access times becoming an unacceptable bottleneck. In such systems, cache related pre-emption delays can be a significant proportion of task execution times. To obtain tight bounds on the response times of tasks in pre-emptively scheduled systems, it is necessary to integrate worst-case execution time analysis and schedulability analysis via the use of an appropriate model of pre-emption costs. In this paper, we introduce a new method of bounding pre-emption costs, called the ECB-Union approach. The ECB-Union approach complements an existing UCB-Union approach. We improve upon both of these approaches via the introduction of Multiset variants which reduce the amount of pessimism in the analysis. Further, we combine these Multiset approaches into a simple composite approach that dominates both. These approaches to bounding pre-emption costs are integrated into response time analysis for fixed priority pre-emptively scheduled systems. Further, we extend this analysis to systems where tasks can access resources in mutual exclusion, in the process resolving omissions in existing models of pre-emption delays. A case study and empirical evaluation demonstrate the effectiveness of the ECB-Union, Multiset and combined approaches for a wide range of different cache configurations including cache utilization, cache set size, reuse, and block reload times.

Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with fixed period and variable budget. When the feedback law demands an increase of the reservation budget, the system must run a schedulability test to check if there is enough spare bandwidth to accommodate such increase. The schedulability test must be very fast, as it may be performed at each budget update, i.e. potentially at each instance of a task; yet, it must be as efficient as possible, to maximize resource usage. In this paper, we tackle the problem of performing an efficient on-line schedulability test for adaptive resource reservations in fixed priority schedulers. In the literature, a number of algorithms have been proposed for on-line admission control in fixed priority systems. We describe four of these tests, with increasing complexity and performance. In addition, we propose a novel on-line test, called Spare-Pot algorithm, which has been specifically designed for the problem at hand, and which shows a good cost/performance ratio compared to the other tests.

This paper presents PRIDE, a novel data abstraction layer for collaborative 2-tier sensor network applications. PRIDE, more specifically, targets distributed real-time applications, in which multiple collaborative mobile devices have to analyze a global situation by collecting and managing data streams from massive underlying sensors. PRIDE at these devices hides the details of underlying sensors and provides transparent, timely, and robust access to global sensor data under highly dynamic and unpredictable environments of emerging sensor network applications. For transparent and efficient sharing of global sensor data, a model-based predictive replication mechanism is proposed and integrated into a conventional data management system that supports diverse types of spatial and temporal queries. In addition, for robust and timely query processing, the predictive replication scheme is extended to the problem of guaranteeing Quality-of-Service (QoS) by introducing feedback control of the accuracy bounds of models. We show the viability of the proposed solution by implementing and evaluating it on a 2-tier sensor network testbed, emulating collaborative search-and-rescue tasks with realistic workloads. Our evaluation results demonstrate that PRIDE can achieve timely sensor data sharing among a large number of devices in a highly robust and controlled manner.

This issue of the journal Real-Time Systems contains extended versions of a selection of four papers from among those that were presented at the 18th International Conference on Real-Time and Network Systems (RTNS-2010), which was held in Toulouse on November 4 and 5, 2010. The scope of the conference covered all aspects of real-time systems and networks. A selection of the papers presented at the conference were invited to submit extended versions for this journal special issue. These papers had all been rated very favorably during the conference review process, and were selected based on their quality, relevance and significance. The extended versions were subject to an additional rigorous review process in accordance with the standards and expectations of this journal, with the authors required to satisfactorily address all concerns expressed by the reviewers before the papers were accepted for publication in this issue. The paper entitled “Partitioned EDF Scheduling for Multiprocessors using a C = D Task Splitting Scheme” is written by Alan Burns, Robert Davis, Pengyu Wang and Fengxiang Zhang. It introduces an EDF-based task-splitting scheme for scheduling multiprocessor systems. One of the advantages of this scheme is that no special run-time mechanisms are required; furthermore, run-time overheads are kept to a minimum. Evaluation is provided via a comparison with a fully partitioned scheme and by determining the theoretical maximum processor utilisation.