Fuzzy Logic Based Algorithm for Disk Scheduling Policy

Disk scheduling changes the sequence order to serve the requests that are waiting in the queue. While data placement reduces the access time of a disk request, scheduling reduces the waiting time of a request. Thus, the response time is found as: Response time = Waiting time + Access time The longer the waiting queue, the more useful is the scheduling method. When there is no waiting queue, any scheduling methods perform the same. Expected waiting time and queue length can be found using queueing theory. The queueing theory is out of the scope of this book. In general, a disk scheduling policy changes the service order of waiting requests. A disk scheduling policy accepts the waiting requests and serves them in the new service sequence. Notice that the service sequence may or may not be the same as the incoming order of the waiting requests. In this chapter, we shall describe two common disk scheduling methods. First, we shall describe the simple first-in-first-out method. After that, we shall describe the efficient SCAN algorithm in the following sections.

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Hysteresis in Categorization: Fuzzy Logic Makes Fuzzy Boundaries

PsycEXTRA Dataset ◽

10.1037/e502412013-438 ◽

2012 ◽

Author(s):

Thomas M. Crawford ◽

Justin Fine ◽

Donald Homa

Keyword(s):

Fuzzy Logic

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Quotation of upper limb risk musculoskeletal disorders by fuzzy logic: Particular case of manual wheelchair propulsion and curb ascent

Movement & Sport Sciences - Science & Motricité ◽

10.1051/sm/2015037 ◽

2016 ◽

pp. 33-40

Author(s):

Claire Marchiori ◽

Didier Pradon ◽

Dany Gagnon ◽

Djamel Bensmail

Keyword(s):

Fuzzy Logic ◽

Musculoskeletal Disorders ◽

Upper Limb ◽

Wheelchair Propulsion ◽

Manual Wheelchair

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Continuous Estimation of CO2 Production during Exercise

Methods of Information in Medicine ◽

10.1055/s-0038-1636856 ◽

1997 ◽

Vol 36 (04/05) ◽

pp. 368-371

Author(s):

R. Soma ◽

Y. Yamamoto

Keyword(s):

Fuzzy Logic ◽

Steady State ◽

Infusion Rate ◽

Feedback System ◽

Whole Body ◽

Co2 Production ◽

Cycle Exercise ◽

Continuous Estimation ◽

Breath Measurement ◽

13Co2 Enrichment

Abstract.A new method was developed for continuous isotopic estimation of human whole body CO2 rate of appearance (Ra) during non-steady state exercise. The technique consisted of a breath-by-breath measurement of 13CO2 enrichment (E) and a real-time fuzzy logic feedback system which controlled NaH13CO3 infusion rate to achieve an isotopic steady state. Ra was estimated from the isotope infusion rate and body 13CO2 enrichment which was equal to E at the isotopic steady state. During a non-steady state incremental cycle exercise (5 w/min or 10 w/min), NaH13CO3 infusion rate was successfully increased by the action of feedback controller so as to keep E constant.

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Modified fuzzy-based greedy routing protocol for VANETs

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189154 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8357-8364

Author(s):

Thompson Stephan ◽

Ananthnarayan Rajappa ◽

K.S. Sendhil Kumar ◽

Shivang Gupta ◽

Achyut Shankar ◽

...

Keyword(s):

Fuzzy Logic ◽

Routing Protocol ◽

Intelligent Transportation Systems ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Research Area ◽

Transportation Systems ◽

Delivery Ratio ◽

Greedy Routing ◽

Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

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Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v2i1.138 ◽

2018 ◽

Vol 2 (1) ◽

Author(s):

Raid Daoud ◽

Yaareb Al-Khashab

Keyword(s):

Fuzzy Logic ◽

Control System ◽

Input Parameter ◽

Traffic Density ◽

The Internet ◽

Linguistic Variables ◽

Internet Service ◽

Traffic Distribution ◽

Smart Control ◽

High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

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Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan ◽

10.32492/jintake.v9i1.720 ◽

2018 ◽

Vol 9 (1) ◽

pp. 1-5

Author(s):

Fachrudin Hunaini ◽

Imam Robandi ◽

Nyoman Sutantra

Keyword(s):

Fuzzy Logic ◽

Particle Swarm Optimization ◽

Control System ◽

Membership Function ◽

Fuzzy Logic Control ◽

Particle Swarm ◽

Optimization Method ◽

Swarm Optimization ◽

Motion Error ◽

Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

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