6,820 research outputs found
A Response-Time Analysis for Non-Preemptive Job Sets under Global Scheduling
An effective way to increase the timing predictability of multicore platforms is to use non-preemptive scheduling. It reduces preemption and job migration overheads, avoids intra-core cache interference, and improves the accuracy of worst-case execution time (WCET) estimates. However, existing schedulability tests for global non-preemptive multiprocessor scheduling are pessimistic, especially when applied to periodic workloads. This paper reduces this pessimism by introducing a new type of sufficient schedulability analysis that is based on an exploration of the space of possible schedules using concise abstractions and state-pruning techniques. Specifically, we analyze the schedulability of non-preemptive job sets (with bounded release jitter and execution time variation) scheduled by a global job-level fixed-priority (JLFP) scheduling algorithm upon an identical multicore platform. The analysis yields a lower bound on the best-case response-time (BCRT) and an upper bound on the worst-case response time (WCRT) of the jobs. In an empirical evaluation with randomly generated workloads, we show that the method scales to 30 tasks, a hundred thousand jobs (per hyperperiod), and up to 9 cores.info:eu-repo/semantics/publishedVersio
A Response-Time Analysis for Non-Preemptive Job Sets under Global Scheduling
An effective way to increase the timing predictability of multicore platforms is to use non-preemptive scheduling. It reduces preemption and job migration overheads, avoids intra-core cache interference, and improves the accuracy of worst-case execution time (WCET) estimates. However, existing schedulability tests for global non-preemptive multiprocessor scheduling are pessimistic, especially when applied to periodic workloads. This paper reduces this pessimism by introducing a new type of sufficient schedulability analysis that is based on an exploration of the space of possible schedules using concise abstractions and state-pruning techniques. Specifically, we analyze the schedulability of non-preemptive job sets (with bounded release jitter and execution time variation) scheduled by a global job-level fixed-priority (JLFP) scheduling algorithm upon an identical multicore platform. The analysis yields a lower bound on the best-case response-time (BCRT) and an upper bound on the worst-case response time (WCRT) of the jobs. In an empirical evaluation with randomly generated workloads, we show that the method scales to 30 tasks, a hundred thousand jobs (per hyperperiod), and up to 9 cores
Restart-Based Fault-Tolerance: System Design and Schedulability Analysis
Embedded systems in safety-critical environments are continuously required to
deliver more performance and functionality, while expected to provide verified
safety guarantees. Nonetheless, platform-wide software verification (required
for safety) is often expensive. Therefore, design methods that enable
utilization of components such as real-time operating systems (RTOS), without
requiring their correctness to guarantee safety, is necessary.
In this paper, we propose a design approach to deploy safe-by-design embedded
systems. To attain this goal, we rely on a small core of verified software to
handle faults in applications and RTOS and recover from them while ensuring
that timing constraints of safety-critical tasks are always satisfied. Faults
are detected by monitoring the application timing and fault-recovery is
achieved via full platform restart and software reload, enabled by the short
restart time of embedded systems. Schedulability analysis is used to ensure
that the timing constraints of critical plant control tasks are always
satisfied in spite of faults and consequent restarts. We derive schedulability
results for four restart-tolerant task models. We use a simulator to evaluate
and compare the performance of the considered scheduling models
How the structure of precedence constraints may change the complexity class of scheduling problems
This survey aims at demonstrating that the structure of precedence
constraints plays a tremendous role on the complexity of scheduling problems.
Indeed many problems can be NP-hard when considering general precedence
constraints, while they become polynomially solvable for particular precedence
constraints. We also show that there still are many very exciting challenges in
this research area
A Constraint Programming Approach for Non-Preemptive Evacuation Scheduling
Large-scale controlled evacuations require emergency services to select
evacuation routes, decide departure times, and mobilize resources to issue
orders, all under strict time constraints. Existing algorithms almost always
allow for preemptive evacuation schedules, which are less desirable in
practice. This paper proposes, for the first time, a constraint-based
scheduling model that optimizes the evacuation flow rate (number of vehicles
sent at regular time intervals) and evacuation phasing of widely populated
areas, while ensuring a nonpreemptive evacuation for each residential zone. Two
optimization objectives are considered: (1) to maximize the number of evacuees
reaching safety and (2) to minimize the overall duration of the evacuation.
Preliminary results on a set of real-world instances show that the approach can
produce, within a few seconds, a non-preemptive evacuation schedule which is
either optimal or at most 6% away of the optimal preemptive solution.Comment: Submitted to the 21st International Conference on Principles and
Practice of Constraint Programming (CP 2015). 15 pages + 1 reference pag
Dynamic Windows Scheduling with Reallocation
We consider the Windows Scheduling problem. The problem is a restricted
version of Unit-Fractions Bin Packing, and it is also called Inventory
Replenishment in the context of Supply Chain. In brief, the problem is to
schedule the use of communication channels to clients. Each client ci is
characterized by an active cycle and a window wi. During the period of time
that any given client ci is active, there must be at least one transmission
from ci scheduled in any wi consecutive time slots, but at most one
transmission can be carried out in each channel per time slot. The goal is to
minimize the number of channels used. We extend previous online models, where
decisions are permanent, assuming that clients may be reallocated at some cost.
We assume that such cost is a constant amount paid per reallocation. That is,
we aim to minimize also the number of reallocations. We present three online
reallocation algorithms for Windows Scheduling. We evaluate experimentally
these protocols showing that, in practice, all three achieve constant amortized
reallocations with close to optimal channel usage. Our simulations also expose
interesting trade-offs between reallocations and channel usage. We introduce a
new objective function for WS with reallocations, that can be also applied to
models where reallocations are not possible. We analyze this metric for one of
the algorithms which, to the best of our knowledge, is the first online WS
protocol with theoretical guarantees that applies to scenarios where clients
may leave and the analysis is against current load rather than peak load. Using
previous results, we also observe bounds on channel usage for one of the
algorithms.Comment: 6 figure
Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
Purpose: The issue resource over-allocating is a big concern for project engineers in the process
of scheduling project activities. Resource over-allocating drawback is frequently seen after
scheduling of a project in practice which causes a schedule to be useless. Modifying an
over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a
new and fast tracking method is proposed to schedule large scale projects which can help project
engineers to schedule the project rapidly and with more confidence.
Design/methodology/approach: In this article, a forward approach for maximizing net
present value (NPV) in multi-mode resource constrained project scheduling problem while
assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment
method is used and all resources are considered as pre-emptible. The proposed approach
maximizes NPV using unscheduled resources through resource calendar in forward mode. For
this purpose, a Genetic Algorithm is applied to solve.
Findings: The findings show that the proposed method is an effective way to maximize NPV in
MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast
and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The
results are then compared with branch and bound method and simulated annealing algorithm and
it is found the proposed genetic algorithm can provide results with better quality. Then algorithm
is then applied for scheduling a hospital in practice.
Originality/value: The method can be used alone or as a macro in Microsoft Office Project®
Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities
after scheduling a project. This can help project engineers to schedule project activities rapidly
with more accuracy in practice.Peer Reviewe
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