Inferring Temporal Behaviours Through Kernel Tracing

In order to provide reliable system support for real-time applications, it is often important to be able to collect statistics about the tasks temporal behaviours (in terms of execution times and inter-arrival times). Such statistics can, for example, be used to provide a-priori schedulability guarantees, or to perform some kind of on-line adaptation of the scheduling parameters (adaptive scheduling, or feedback scheduling). This work shows how the Linux kernel allows to collect such statistics by using an internal function tracer called Ftrace. Based on this feature, tools can be developed to evaluate the real-time performance of a system or an application, to debug real-time applications, and/or to infer the temporal properties (for example, periodicity) of tasks running in the system

How to rapidly prototype a real-time scheduler

Journal ArticleImplementing a new scheduling algorithm in an OS kernel is often an important step in scheduling research because it permits evaluation of the algorithm's performance on real workloads. However, developing a new scheduler is not a trivial task because it requires sophisticated programming skills and a deep knowledge of kernel internals. In this paper we show how to use the HLS scheduling framework to develop new schedulers in a user-level simulator, where advanced debugging tools can be used to achieve a high level of robustness before the scheduler is converted to a loadable kernel module simply by recompiling it. Besides facilitating debugging and porting, the HLS abstraction has the benefit of bringing the programming model very close to what, in our experience, scheduler developers want

EDF scheduling of real-time tasks on multiple cores: Adaptive Partitioning vs. Global Scheduling

This paper presents a novel migration algorithm for real-time tasks on multicore systems, based on the idea of migrating tasks only when strictly needed to respect their temporal constraints and a combination of this new algorithm with EDF scheduling. This new “adaptive migration” algorithm is evaluated through an extensive set of simulations showing good performance when compared with global or partitioned EDF: our results highlight that it provides a worst-case utilisation bound similar to partitioned EDF for hard real-time tasks and an empirical tardiness bound (like global EDF) for soft real-time tasks. Therefore, the proposed scheduler is effective for dealing with both hard and soft real-time workloads

An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems

We show a methodology for the computation of the probability of deadline miss for a periodic real-time task scheduled by a resource reservation algorithm. We propose a modelling technique for the system that reduces the computation of such a probability to that of the steady state probability of an infinite state Discrete Time Markov Chain with a periodic structure. This structure is exploited to develop an efficient numeric solution where different accuracy/computation time trade-offs can be obtained by operating on the granularity of the model. More importantly we offer a closed form conservative bound for the probability of a deadline miss. Our experiments reveal that the bound remains reasonably close to the experimental probability in one real-time application of practical interest. When this bound is used for the optimisation of the overall Quality of Service for a set of tasks sharing the CPU, it produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27, Issue: 3, March 201

Experimental Evaluation of the Real-Time Performance of Publish-Subscribe Middlewares

REACTION 2013. 2nd International Workshop on Real-time and distributed computing in emerging applications. December 3rd, 2013, Vancouver, Canada.The integration of the complex network of modules composing a modern distributed embedded systems calls for a middleware solution striking a good tradeoff between conflicting needs such as: modularity, architecture independence, re-use, easy access to the limited hardware resources and ability to respect real–time constraints. Several middleware architectures proposed in the last years offer reliable and easy to use abstractions and intuitive publish-subscribe mechanism that can simplify system development to a good degree. However, a complete compliance with the different requirements of assistive robotics application (first and foremost real–time constraints) remains to be investigated. This paper evaluates the performance of these solutions in terms of latency and scalability

Randomized Packet Filtering through Specialized Partitioning of Rulesets

A key issue in high speed traffic processing is to immediately detect potentially interesting packets. At very high speed, this operation is particularly crucial as filtering packets close to the wire relieves real applications from handling large volumes of (uninteresting) data. This paper proposes a fast and randomized approach to packet filtering based on partitioning rule databases for their storage in fast and compact Bloom filters that can be placed in fast cache memory. Database partitioning is obtained by a specially tailored clustering algorithm and the results show that even large rulesets can be divided into a limited number of partitions and accommodated in reasonably small Bloom filters

Performance Modeling in Predictable Cloud Computing

This paper deals with the problem of performance stability of software running in shared virtualized infrastructures. The focus is on the ability to build an abstract performance model of containerized application components, where real-time scheduling at the CPU level, along with traffic shaping at the networking level, are used to limit the temporal interferences among co-located workloads, so as to obtain a predictable distributed computing platform. A model for a simple client-server application running in containers is used as a case-study, where an extensive experimental validation of the model is conducted over a testbed running a modified OpenStack on top of a custom real-time CPU scheduler in the Linux kernel

The Wizard of OS: a Heartbeat for Legacy Multimedia Applications

Multimedia applications are often characterised by implicit temporal constraints but, in many cases, they are not programmed using any specialised real-time API. These "Legacy applications" have no way to communicate their temporal constraints to the OS kernel, and their quality of service (QoS), being necessarily linked to the temporal behaviour, fails to satisfy acceptable standards. In this paper we propose an innovative way for dealing with these applications, based on the combination of an on-line identification mechanism (which extracts from high-level observations such important parameters as the execution rate) and an adaptive scheduler (specialised for legacy applications) that identifies the correct amount of CPU needed by each application. Preliminary experimental results are reported, proving the effectiveness of the proposed idea in providing a widely used multimedia player on Linux with appropriate QoS guarantees, through an appropriate choice of the scheduling parameters. Finally, a detailed road-map is presented with the possible extensions to the approach

A robust mechanism for adaptive scheduling of multimedia applications

We propose an adaptive scheduling technique to schedule highly dynamic multimedia tasks on a CPU. We use a combination of two techniques: the first one is a feedback mechanism to track the resource requirements of the tasks based on local observations. The second one is a mechanism that operates with a global visibility, reclaiming unused bandwidth. The combination proves very effective: resource reclaiming increases the robustness of the feedback, while the identification of the correct bandwidth made by the feedback increases the effectiveness of the reclamation. We offer both theoretical results and an extensive experimental validation of the approach