An Evolutionary Fuzzy based Scheduling Algorithm for Soft Real-Time Multiprocessor Systems

Hassan, Heba E.; Nagib, Gihan; Ibrahiem, Khaled Hosny

doi:10.1109/jac-ecc48896.2019.9051189

Cited by 2 publications

(4 citation statements)

References 12 publications

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“…Several test cases were simulated and the behaviours of both the algorithms were compared to determine the strength of the proposed algorithm. The proposed AFS outperformed the EFA [32] as demonstrated graphically in Figures 5-8 with respect to average response time. The graphical analysis demonstrates that, when the system's load is normal, that is, when the value of load factor is below 1, both proposed AFS and EFA algorithms gives similar performance for number of processors 10 and 20.…”

Section: Resultsmentioning

confidence: 85%

“…Discussions, the results of the proposed approach are analyzed and compared with the existing fuzzy algorithms such as evaluationary fuzzy based algorithms [32], new fuzzy scheduling algorithms [33], earliest deadline first [34] and least laxity first [35] scheduling algorithms, and proved that the proposed approach placed better compartively. The graphical analysis given above demonstrates the results gained for missed deadlines, mean response time and mean turnaround time for different load factors, by making use of different number of processors scu as 10, 20, 50, and 100, in four cases.…”

Section: Resultsmentioning

confidence: 95%

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Algorithm fuzzy scheduling (AFS) for realtime jobs on multiprocessor systems

Holagundi¹,

Ashwathsetty²,

Basthikodi

2022

IJEECS

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The computing in Real-time is rapidly focusing much developments in technologies so that the real-time jobs are to be scheduled and executed on computing systems in particular time frame. The scheduling and load balancing techniques in distributed systems face numerous challenges because of lack of centralized strategy to dispatch the jobs in multiprocessors systems. In this work, we propose an Algorithm Fuzzy Scheduling (AFS) for real-time jobs that includes of Arrival time, Deadline and Computation time as the scheduling parameters of input. The approach AFS is analyzed and compared with Existing Fuzzy Algorithm (EFA) model for evaluation of performances from the outcome of the simulation. The jobs are scheduled on multiprocessor at higher system load by making use of fuzzy mechanisms in the algorithms. The experimental results prove that the proposed AFS achieves a better performance comparatively to EFA at various system load factors with respect to mean turnaroundtime, mean response time and count of missed deadlines. This is the initial phase of the algorithm, that will be enhanced to consider a greater number of parameters to be associated with jobs for better decision making and to investigate the scope for algorithm level parallelism.

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Section: Resultsmentioning

confidence: 85%

Section: Resultsmentioning

confidence: 95%

Algorithm fuzzy scheduling (AFS) for realtime jobs on multiprocessor systems

Holagundi¹,

Ashwathsetty²,

Basthikodi

2022

IJEECS

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“…a request [21,22]. There are numerous scheduling algorithms that use fuzzy logic in scheduling such as [23] but some of them are often performed on uniprocessor systems such as [24], as shown in Table 1.…”

Section: Priority-fuzzy-b-level Algorithm (Pfb) [Proposed]mentioning

confidence: 99%

“…Nevertheless, in many situations, the values of those parameters are vague. This vagueness proposes that we can benefit from fuzzy logic to determine the order in which the requests have to be executed for proper utilization of the system and to diminish the chance of missing a request [21,22]. There are numerous scheduling algorithms that use fuzzy logic in scheduling such as [23] but some of them are often performed on uniprocessor systems such as [24], as shown in Table 1.…”

Section: Introductionmentioning

confidence: 99%

A novel task scheduling approach for dependent non‐preemptive tasks using fuzzy logic

Hassan

Nagib

Ibrahiem

2021

IET Computers & Digital Tech

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Multiprocessor task scheduling problem is a pressing problem that affects systems' performance and is still being investigated by the researchers. Finding the optimal schedules is considered to be a computationally hard problem. Recently, researchers have used fuzzy logic in the field of task scheduling to achieve optimal performance, but this area of research is still not well investigated. In addition, there are various scheduling algorithms that used fuzzy logic but most of them are often performed on uniprocessor systems. This article presents a new proposed algorithm in which the priorities of the tasks are derived from the fuzzy logic and bottom level parameter. This approach is designed to find task schedules with optimal or sub-optimal lengths in order to achieve high performance for a multiprocessor environment. With respect to the proposed algorithm, the precedence constraints between the non-preemptive tasks and their execution times are known and described by a directed acyclic graph. The number of processors is fixed, the communication costs are negligible and the processors are homogeneous. The suggested technique is tested and compared with the Prototype Standard Task Graph Set. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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An Evolutionary Fuzzy based Scheduling Algorithm for Soft Real-Time Multiprocessor Systems

Cited by 2 publications

References 12 publications

Algorithm fuzzy scheduling (AFS) for realtime jobs on multiprocessor systems

Algorithm fuzzy scheduling (AFS) for realtime jobs on multiprocessor systems

A novel task scheduling approach for dependent non‐preemptive tasks using fuzzy logic

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