Algorithms for Hierarchical and Semi-Partitioned Parallel Scheduling

We propose a model for scheduling jobs in a parallel machine setting that takes into account the cost of migrations by assuming that the processing time of a job may depend on the specific set of machines among which the job is migrated. For the makespan minimization objective, the model generalizes classical scheduling problems such as unrelated parallel machine scheduling, as well as novel ones such as semi-partitioned and clustered scheduling. In the case of a hierarchical family of machines, we derive a compact integer linear programming formulation of the problem and leverage its fractional relaxation to obtain a polynomial-time 2-approximation algorithm. Extensions that incorporate memory capacity constraints are also discussed

Hierarchical Scheduling for Real-Time Periodic Tasks in Symmetric Multiprocessing

In this paper, we present a new hierarchical scheduling framework for periodic tasks in symmetric multiprocessor (SMP) platforms. Partitioned and global scheduling are the two main approaches used by SMP based systems where global scheduling is recommended for overall performance and partitioned scheduling is recommended for hard real-time performance. Our approach combines both the global and partitioned approaches of traditional SMP-based schedulers to provide hard real-time performance guarantees for critical tasks and improved response times for soft real-time tasks. Implemented as part of VxWorks, the results are confirmed using a real-time benchmark application, where response times were improved for soft real-time tasks while still providing hard real-time performance

On real-time partitioned multicore systems

Partitioning is a common approach to developing mixed-criticality systems, where partitions are isolated from each other both in the temporal and the spatial domain in order to prevent low-criticality subsystems from compromising other subsystems with high level of criticality in case of misbehaviour. The advent of many-core processors, on the other hand, opens the way to highly parallel systems in which all partitions can be allocated to dedicated processor cores. This trend will simplify processor scheduling, although other issues such as mutual interference in the temporal domain may arise as a consequence of memory and device sharing. The paper describes an architecture for multi-core partitioned systems including critical subsystems built with the Ada Ravenscar profile. Some implementation issues are discussed, and experience on implementing the ORK kernel on the XtratuM partitioning hypervisor is presented

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.The challenge of mixed-criticality scheduling is to keep tasks of higher criticality running in case of resource shortages caused by faults. Traditionally, mixedcriticality scheduling has focused on methods to handle faults where tasks overrun their optimistic worst-case execution time (WCET) estimate. In this paper we present the Adaptive Tolerance based Mixed-criticality Protocol (ATMP), which generalises the concept of mixed-criticality scheduling to handle also faults of other nature, like failure of cores in a multi-core system. ATMP is an adaptation method triggered by resource shortage at runtime. The first step of ATMP is to re-partition the task to the available cores and the second step is to optimise the utility at each core using the tolerance-based real-time computing model (TRTCM). The evaluation shows that the utility optimisation of ATMP can achieve a smoother degradation of service compared to just abandoning tasks

Response Time Analysis of Hierarchical Scheduling: the Synchronized Deferrable Servers Approach

Hierarchical scheduling allows reservation of processor bandwidth and the use of different schedulers for different applications on a single platform. We propose a hierarchical scheduling interface called synchronized deferrable servers that can reserve different processor bandwidth on each core, and can combine global and partitioned scheduling on a multicore platform. Significant challenges will arise in the response time analysis of a task set if the tasks are globally scheduled on a multiprocessor platform and the processor bandwidth reserved for the tasks on each processor is different; as a result, existing works on response time analysis for dedicated scheduling on identical multiprocessor platforms are no longer applicable. A new response time analysis that overcomes these challenges is presented and evaluated by simulations. Based on this new analysis, we show that evenly allocating bandwidth across cores is “better” than other allocation schemes in terms of schedulability, and that the threshold between lightweight and heavyweight tasks under hierarchical scheduling may be different from the threshold under dedicated scheduling

Survivable algorithms and redundancy management in NASA's distributed computing systems

The design of survivable algorithms requires a solid foundation for executing them. While hardware techniques for fault-tolerant computing are relatively well understood, fault-tolerant operating systems, as well as fault-tolerant applications (survivable algorithms), are, by contrast, little understood, and much more work in this field is required. We outline some of our work that contributes to the foundation of ultrareliable operating systems and fault-tolerant algorithm design. We introduce our consensus-based framework for fault-tolerant system design. This is followed by a description of a hierarchical partitioning method for efficient consensus. A scheduler for redundancy management is introduced, and application-specific fault tolerance is described. We give an overview of our hybrid algorithm technique, which is an alternative to the formal approach given

Grasp : visualizing the behavior of hierarchical multiprocessor real-time systems

Trace visualization is a viable approach for gaining insight into the behavior of complex distributed real-time systems. Grasp is a versatile trace visualization toolset. This paper presents its unique visualization capabilities for hierarchical multiprocessor systems, including partitioned and global multiprocessor scheduling with migrating tasks and jobs, communication between jobs via shared memory and message passing, and hierarchical scheduling in combination with multiprocessor scheduling. Its flexible plugin infrastructure allows for easy extension with custom visualization and analysis techniques for automatic trace verification. Grasp is freely available on the web