Handling Overload Conditions in Real-Time Systems

This chapter deals with the problem of handling overload conditions, that is, those critical situations in which the computational demand requested by the application exceeds the processor capacity. If not properly handled, an overload can cause an abrupt performance degradation, or even a system crash. Therefore, a real-time system should be designed to anticipate and tolerate unexpected overload situations through specific kernel mechanisms

Response-Time Analysis of Conditional DAG Tasks in Multiprocessor Systems

Different task models have been proposed to represent the parallel structure of real-time tasks executing on manycore platforms: fork/join, synchronous parallel, DAG-based, etc. Despite different schedulability tests and resource augmentation bounds are available for these task systems, we experience difficulties in applying such results to real application scenarios, where the execution flow of parallel tasks is characterized by multiple (and nested) conditional structures. When a conditional branch drives the number and size of sub-jobs to spawn, it is hard to decide which execution path to select for modeling the worst-case scenario. To circumvent this problem, we integrate control flow information in the task model, considering conditional parallel tasks (cp-tasks) represented by DAGs composed of both precedence and conditional edges. For this task model, we identify meaningful parameters that characterize the schedulability of the system, and derive efficient algorithms to compute them. A response time analysis based on these parameters is then presented for different scheduling policies. A set of simulations shows that the proposed approach allows efficiently checking the schedulability of the addressed systems, and that it significantly tightens the schedulability analysis of non-conditional (e.g., Classic DAG) tasks over existing approaches

Resource Reservation for Mixed Criticality Systems

Abstract. This paper presents a reservation-based approach to schedule mixed criticality systems in a way that guarantees the schedulability of high-criticality tasks independently of the behaviour of low-criticality tasks. Two key ideas are presented: first, to reduce the system uncertainty and advance the time at which a high-criticality task reveals its actual execution time, the initial portion of its code is handled by a dedicated server with a bandwidth reserved for the worst-case, but with a shorter deadline; second, toavoidthepessimism relatedtooff-linebudget allocation, an efficient reclaiming mechanism, namely the GRUB algorithm [6], is used to exploit the budget left by high-criticality tasks in favor of those low-criticality tasks that can still complete within their deadline.

A Hyperbolic Bound for the Rate Monotonic Algorithm

In this paper we propose a novel schedulability analysis for verifying the feasibility of large periodic task sets under the rate monotonic algorithm, when the exact test cannot be applied on line due to prohibitively long execution times. The proposed test has the same complexity as the original Liu and Layland bound but it is less pessimistic, so allowing to accept task sets that would be rejected using the original approach. The performance of the proposed approach is evaluated with respect to the classical Liu and Layland method, and theoretical bounds are derived as a function of n (the number of tasks) and for the limit case of n tending to in nity. The analysis is also extended to include aperiodic servers and blocking times due to concurrency control protocols. Extensive simulations on synthetic tasks sets are presented to compare the eectiveness of the proposed test with respect to the Liu and Layland method and the exact response time analysis

Efficient Aperiodic Service under Earliest Deadline Scheduling

In this paper we present four new on-line algo-rithms for servicing soft aperiodic requests in real-time systems, where a set of hard periodic lash is scheduled using the Earliest Deadline First (EDF) algorithm. All the proposed solutions can achieve full processor ulilization and enhance aperiodic responsiveness, still guaranteeing the ezecution of the periodic tads. Op-eration of dhe algorithms, performance, schedulability analysis, and implemenlation compleaity are discussed and compared with classical alternative solutions, such as background and polling service. Ezlensive simula-tions show that algorithms with contained run-time overhead present nearly optimal responsiveness. A valuable contribdion of this work is to provide the real-dime system designer with a wide range of practi-cal solu2ions which allow to balance eficiency against implementation complezity

The Space of Rate Monotonic Schedulability

Feasibility analysis of fixed priority systems has been widely studied in the real-time literature and several acceptance tests have been proposed to guarantee a set of periodic tasks. They can be divided in two main classes: polynomial time tests and exact tests. Polynomial time tests are used for on-line guarantee of dynamic systems, where tasks can be activated at runtime. These tests introduce a negligible overhead, when executed upon a new task arrival, however provide only a sufficient schedulability condition, which may cause a poor processor utilization. On the other hand, exact tests, which are based on response time analysis, provide a necessary and sufficient schedulability condition, but are too complex to be executed on line for large task sets. As a consequence, for large task sets, they are often executed off line. This pape

Supporting Component-Based Development in Partitioned Multiprocessor Real-Time Systems

The fast evolution of multicore systems, combined with the need of sharing the same platform for independently developed software, demands for new methodologies and algorithms that allow resource partitioning, while guaranteeing the isolation of concurrent applications. Unfortunately, a major problem that can break the isolation property of concurrent partitions is resource sharing. Although a number of resource access protocols exist for hierarchical uniprocessor systems, no protocols are available today for managing hierarchical partitions implemented on top a multiporcessor platform under partitioned scheduling. This paper presents a framework to support component based design on a multiprocessor platform and proposes a novel reservation server mechanism, called M-BROE, to handle shared resources in multiprocessor systems in the presence of resource reservation scheduling mechanisms