Journal Article Presented at ECRTS 2019

Today, Ali presented our Real-time Systems article “Uneven Memory Regulation for Scheduling IMA Applications on Multi-core Platforms” in the Journal-to-conference (J2C) session at ECRTS.

This article addresses the problem of resource sharing in mixed-criticality systems through temporal isolation by extending the state-of-the-art Single-Core Equivalence (SCE) framework in three ways: 1) we extend the theoretical toolkit for the SCE framework by considering EDF and server-based scheduling, instead of partitioned fixed-priority scheduling, 2) we support uneven memory access budgets on a per-server basis, rather than just on a per-core basis, and 3) we formulate an Integer-Linear Programming Model (ILP) guaranteed to find a feasible mapping of a given set of servers to processors, including their execution time and memory access budgets, if such a mapping exists. Our experiments with synthetic task sets confirm that considerable improvement in schedulability can result from the use of per-server memory access budgets under the SCE framework.

Overall, I greatly appreciate that key conferences in the real-time community are starting to allow journal articles to be presented. This increases the exposure of these works that are often longer and better edited. It is also helpful for researchers at the institutes where conference publications are not considered a relevant KPI. You can argue the validity of this reasoning in areas of computer science where conferences are highly competitive with 20-30% acceptance rates, but it is reality for some researchers. An interesting thing with the MODELS conference is that they collaborate with the SOSYM journal such that some accepted articles in the journal gets a full slot at the conference. This is a nice way to highlight good articles and to appreciate the work done by both authors and reviewers.

Paper Accepted at RTCSA 2019

A paper “Memory Bandwidth Regulation for Multiframe Task Sets” has been accepted at RTCSA 2018. This paper aims to reduce cost of real-time systems where the worst-case execution times of tasks vary from job to job, according to known patterns. This kind of execution behavior can be captured by the multi-frame task model. However, this model is optimistic and unsafe for multi-cores with shared memory controllers, since it ignores memory contention, and existing approaches to stall analysis based on memory regulation are very pessimistic if straight-forwardly applied.

This paper remedies this by adapting existing stall analyses for memory-regulated systems to the multi-frame model. Experimental evaluations with synthetic task sets show up to 85% higher scheduling success ratio for our analysis, compared to the frame-agnostic analysis, enabling higher platform utilization without compromising safety. We also explore implementation aspects, such as how to speed up the analysis and how to trade off accuracy with tractability.

Paper Accepted at RTCSA 2018

We celebrate the acceptance of our paper “Mixed-criticality Scheduling with Dynamic Memory Bandwidth Regulation” at RTCSA. This paper is the next step in my research collaboration with CISTER on mixed-criticality systems.

The paper aims to safely reduce the cost of mixed-criticality multi-core systems by addressing inefficient usage of memory bandwidth. This is achieved by combining per-core memory access regulation with the well-established Vestal model, which improves on the state-of-the-art in two respects: 1) We allow the memory access budgets of the cores to be dynamically adjusted, when the system undergoes a mode change, reflecting the different needs in each mode, for better schedulability. 2) We devise memory regulation-aware and stall-aware schedulability analysis for such systems, based on AMC-max. By comparison, the state-of-the-art offered no option of dynamic adjustment of core budgets, and only offered regulation-aware schedulability analysis based on AMC-rtb, which is inherently more pessimistic. Finally, 3) we consider different task assignment and bandwidth allocation heuristics, to assess the improvement from the dynamic memory budgets and new analysis. Our results show improvements in schedulability ratio of up to 9.1% over the state-of-the-art.

Paper Accepted at ECRTS 2018

We are pleased to announce that our paper “Worst-case Stall Analysis for Multicore Architectures with Two Memory Controllers” has been accepted at ECRTS 2018. This paper represents another successful collaboration with my former colleagues from CISTER.

The paper addresses the problem that increasing bandwidth requirements have resulted in platform architectures with multiple memory controllers, for which existing analyses to compute worst-case memory stall time are not safe. This work presents a new worst-case memory stall analysis for a memory-regulated multi-core architecture with two memory controllers. This stall analysis can be integrated into the schedulability analysis of systems under fixed-priority partitioned scheduling. Five heuristics for assigning tasks and memory budgets to cores in a stall-cognisant manner are also proposed. We experimentally quantify the cost in terms of extra stall for letting all cores benefit from the memory space offered by both controllers, and also evaluate the five heuristics for different system characteristics.

Paper Accepted at DATE 2018

Another paper written with my former colleagues at CISTER has been accepted. The paper is entitled “Mixed-criticality Scheduling with Memory Bandwith Regulation” and appear at DATE 2018. The paper considers the problem that existing schedulability analyses for mixed-criticality multi-core systems do not consider task interference in shared platform resources, such as memories, potentially making them optimistic and unsafe. We address this issue by formulating a schedulability analysis for mixed-criticality fixed-priority-scheduled multi-core systems using per-core memory access regulation. We also propose multiple heuristics for memory bandwidth allocation and task-to-core assignment. The analysis and heuristics are implemented in a tool and evaluated through extensive experiments.