Dynamic DAG Scheduling on Multiprocessor Systems: Reliability, Energy, and Makespan

Abstract

Multiprocessor systems are increasingly deployed in real-time applications, where reliability, energy consumption, and makespan are often the main scheduling objectives. In this work, we investigate dynamic scheduling of tasks modelled by directed acyclic graphs (DAGs), which is an NP-hard problem with all existing methods being heuristics. Our contributions have two steps: (i) Assuming that the allocation of DAG nodes to processors is given, we propose OEA (Optimal Energy Allocation) and SOEA (Search-based OEA)-the first optimal methods that minimise the energy consumption whilst satisfying the reliability requirement-for homogeneous and heterogeneous systems, respectively; (ii) We present a novel scheduling algorithm ODS (Out-Degree Scheduling) that allocates the DAG nodes according to their out-degrees, and considering energy consumption, reliability, as well as dynamic finish time. ODS dominates the widely applied HEFT (Heterogeneous Earliest Finish Time) in makespan. Combining SOEA with ODS makes a complete solution to the problem of dynamic DAG scheduling on multiprocessor systems, and achieves generally better results compared to the existing approaches. Specifically, in most cases, we are better on all the three objectives, i.e., reliability, energy as well as makespan, and in other cases we are better on some of the objectives.

Reliability-Constrained Task Scheduling for DAG Applications in Mobile Edge Computing

“…Tang [14] proposed a fault-tolerant cost-efficient workflow scheduling algorithm that minimizes the cost and time of application execution, while also ensuring reliability. Huang et al [17] presented an out-degree scheduling algorithm that allocates the DAG nodes based on their outdegrees, considering energy consumption, reliability, and dynamic finish time. Hu et al [19] built a safety-guaranteed and development cost-minimized schedule for functionality modeled as a DAG running on an automotive system.…”

“…As a result, re-executing the task consumes more time and energy [7]. Therefore, in addition to the indicators mentioned above, there is an increasing focus on execution reliability [7,[14][15][16][17][18][19]. Based on the above analysis, we consider execution reliability as a constraint in DAG task scheduling in this paper.…”

Multiobjective Approach to Schedule DAG Tasks on Voltage Frequency Islands

“…Huang et al [15] have experimented the dynamic scheduling of activities described by directed acyclic graphs (DAGs), an NP-hard issue with only heuristic solutions, was the subject of this study. There were two steps to our contributions: 1) Assuming that the allocation of DAG nodes to processors was known, this paper suggests optimal energy allocation (OEA) and search-based OEA (SOEA), the first optimal approaches that minimize energy usage while rewarding the reliability demand homogeneous and heterogeneous systems, respectively.…”

Reliability‐based offloading strategy for deadline‐constrained taskflows in vehicular edge computing environments

“…For a task flow, $$$ N $$$ and $$$ E $$$ determine the complexity of the task flow. In this article, we investigate the number of nodes, which represents the total number of tasks, and the maximum out‐degree that represents the maximum number of directed edges starting with a single task 34 . For a task flow, a task may have multiple predecessor and successor tasks.…”

“…In this article, we investigate the number of nodes, which represents the total number of tasks, and the maximum out-degree that represents the maximum number of directed edges starting with a single task. 34 For a task flow, a task may have multiple predecessor and successor tasks. We create the set of predecessor tasks as pre(n i ) and the set of successor tasks as sub(n i ).…”