scholarly journals A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads

2014 ◽  
Vol 2014 ◽  
pp. 1-17
Author(s):  
Taeseok Kim ◽  
Hyokyung Bahn ◽  
Youjip Won
Keyword(s):  
Response Time ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Disk Scheduling ◽  
Best Effort ◽  
Qos Guarantees ◽  
Time Minimization ◽  
On Line ◽  
Manageable Level ◽  
Deadline Constraints

In heterogeneous I/O workload environments, disk scheduling algorithms should support different QoS (Quality-of-Service) for each I/O request. For example, the algorithm should meet the deadlines of real-time requests and at the same time provide reasonable response time for best-effort requests. This paper presents a novel disk scheduling algorithm called G-SCAN (Grouping-SCAN) for handling heterogeneous I/O workloads. To find a schedule that satisfies the deadline constraints and seek time minimization simultaneously, G-SCAN maintains a series of candidate schedules and expands the schedules whenever a new request arrives. Maintaining these candidate schedules requires excessive spatial and temporal overhead, but G-SCAN reduces the overhead to a manageable level via pruning the state space using two heuristics. One is grouping that clusters adjacent best-effort requests into a single scheduling unit and the other is the branch-and-bound strategy that cuts off inefficient or impractical schedules. Experiments with various synthetic and real-world I/O workloads show that G-SCAN outperforms existing disk scheduling algorithms significantly in terms of the average response time, throughput, and QoS-guarantees for heterogeneous I/O workloads. We also show that the overhead of G-SCAN is reasonable for on-line execution.

scholarly journals Improved fair Scheduling Algorithm for Hadoop Clustering

2017 ◽  
Vol 10 (1) ◽  
pp. 194-200 ◽  
Author(s):  
Sneha Sneha ◽  
Shoney Sebastian
Keyword(s):  
Response Time ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Map Reduce ◽  
Process Data ◽  
Strategy Analysis ◽  
Fair Scheduling ◽  
New Strategy ◽  
And Performance

Traditional way of storing such a huge amount of data is not convenient because processing those data in the later stages is very tedious job. So nowadays, Hadoop is used to store and process large amount of data. When we look at the statistics of data generated in the recent years it is very high in the last 2 years. Hadoop is a good framework to store and process data efficiently. It works like parallel processing and there is no failure or data loss as such due to fault tolerance. Job scheduling is an important process in Hadoop Map Reduce. Hadoop comes with three types of schedulers namely FIFO (First in first out), Fair and Capacity Scheduler. The schedulers are now a pluggable component in the Hadoop Map Reduce framework. This paper talks about the native job scheduling algorithms in Hadoop. Fair scheduling algorithm is analysed with its algorithm considering its response time, throughput and performance. Advantages and drawbacks of fair scheduling algorithm is discussed. Improvised fair scheduling algorithm is proposed with new strategy. Analysis is made with respect to response time, throughput and performance is calculated in naive fair scheduling and improvised fair scheduling. Improvised fair Scheduling algorithms is used in the cases where there is jobs with high and less processing time.

An Hybridized Disk Scheduling Algorithm (HDSA)

2019 ◽  
Vol 9 (3) ◽  
pp. p8789
Author(s):  
Akanmu T.A. ◽  
Aadegoke B.O. ◽  
Oladoye S.F.
Keyword(s):  
Scheduling Algorithm ◽  
Disk Scheduling

QoS aware Multi-Path Routing using Link Scheduling Algorithm

2019 ◽  
Vol 09 ◽  
Author(s):  
Satyasrikanth Palle ◽  
Shivashankar
Keyword(s):  
Cellular Networks ◽  
Scheduling Algorithm ◽  
Research Work ◽  
Scheduling Algorithms ◽  
Turnaround Time ◽  
Link Scheduling ◽  
Spatial Reuse ◽  
Mobile Cellular ◽  
Simulation Results ◽  
End To End

Objective: The demand for Cellular based multimedia services is growing day by day, in order to fulfill such demand the present day cellular networks needs to be upgraded to support excessive capacity calls along with high data accessibility. Analysis of traffic and huge network size could become very challenging issue for the network operators for scheduling the available bandwidth between different users. In the proposed work a novel QoS Aware Multi Path scheduling algorithm for smooth CAC in wireless mobile networks. The performance of the proposed algorithm is assessed and compared with existing scheduling algorithms. The simulation results show that the proposed algorithm outperforms existing CAC algorithms in terms of throughput and delay. The CAC algorithm with scheduling increases end-to-end throughput and decreases end-to-end delay. Methods: The key idea to implement the proposed research work is to adopt spatial reuse concept of wireless sensor networks to mobile cellular networks. Spatial reusability enhances channel reuse when the node pairs are far away and distant. When Src and node b are communicating with each other, the other nodes in the discovered path should be idle without utilizing the channel. Instead the other nodes are able to communicate parallelly the end-to-end throughput can be improved with acceptable delay. Incorporating link scheduling algorithms to this key concept further enhances the end-to-end throughput with in the turnaround time. So, in this research work we have applied spatial reuse concept along with link scheduling algorithm to enhance end-to-end throughput with in turnaround time. The proposed algorithm not only ensures that a connection gets the required bandwidth at each mobile node on its way by scheduling required slots to meet the QoS requirements. By considering the bandwidth requirement of the mobile connections, the CAC module at the BS not only considers the bandwidth requirement but also conforming the constrains of system dealy and jitter are met. Result: To verify the feasibility and effectiveness of our proposed work, with respect to scheduling the simulation results clearly shows the throughput improvement with Call Admission Control. The number of dropped calls is significantly less and successful calls are more with CAC. The percentage of dropped calls is reduced by 9 % and successful calls are improved by 91%. The simulation is also conducted on time constraint and ratio of dropped calls are shown. The total time taken to forward the packets and the ration of dropped calls is less when compared to non CAC. On a whole the CAC with scheduling algorithms out performs existing scheduling algorithms. Conclusion: In this research work we have proposed a novel QoS aware scheduling algorithm that provides QoS in Wireless Cellular Networks using Call Admission Control (CAC). The simulation results show that the end-to-end throughput has been increased by 91% when CAC is used. The proposed algorithm is also compared with existing link scheduling algorithms. The results reveal that CAC with scheduling algorithm can be used in Mobile Cellular Networks in order to reduce packet drop ratio. The algorithm is also used to send the packets within acceptable delay.

Parallel Scheduling Algorithms Investigation of Support Strict Resource Reservation from Grid

2014 ◽  
Vol 519-520 ◽  
pp. 108-113 ◽  
Author(s):  
Jun Chen ◽  
Bo Li ◽  
Er Fei Wang
Keyword(s):  
Parallel Computing ◽  
Resource Utilization ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Resource Reservation ◽  
Parallel Scheduling ◽  
Scheduling Model ◽  
Computing Grid ◽  
Simulation Results ◽  
Reservation Request

This paper studies resource reservation mechanisms in the strict parallel computing grid,and proposed to support the parallel strict resource reservation request scheduling model and algorithms, FCFS and EASY backfill analysis of two important parallel scheduling algorithm, given four parallel scheduling algorithms supporting resource reservation. Simulation results of four algorithms of resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. The results show that the EASY backfill + firstfit algorithm can ensure QoS of AR jobs while taking into account the performance of good non-AR jobs.

scholarly journals AN ON-LINE NON-LEPTONIC NEURAL TRIGGER APPLIED TO AN EXPERIMENT LOOKING FOR BEAUTY

1994 ◽  
Vol 05 (05) ◽  
pp. 863-870
Author(s):  
C. BALDANZA ◽  
F. BISI ◽  
A. COTTA-RAMUSINO ◽  
I. D’ANTONE ◽  
L. MALFERRARI ◽  
...  
Keyword(s):  
Neural Network ◽  
Response Time ◽  
Enrichment Factor ◽  
Data Stream ◽  
Particle Production ◽  
Event Sample ◽  
On Line

Results from a non-leptonic neural-network trigger hosted by experiment WA92, looking for beauty particle production from 350 GeV π− on a Cu target, are presented. The neural trigger has been used to send on a special data stream (the Fast Stream) events to be analyzed with high priority. The non-leptonic signature uses microvertex detector data and was devised so as to enrich the fraction of events containing C3 secondary vertices (i.e, vertices having three tracks whith sum of electric charges equal to +1 or -1). The neural trigger module consists of a VME crate hosting two ETANN analog neural chips from Intel. The neural trigger operated for two continuous weeks during the WA92 1993 run. For an acceptance of 15% for C3 events, the neural trigger yields a C3 enrichment factor of 6.6–7.1 (depending on the event sample considered), which multiplied by that already provided by the standard non-leptonic trigger leads to a global C3 enrichment factor of ≈150. In the event sample selected by the neural trigger for the Fast Stream, 1 every ≈7 events contains a C3 vertex. The response time of the neural trigger module is 5.8 μs.

scholarly journals Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1320
Author(s):  
Vijay Prakash ◽  
Seema Bawa ◽  
Lalit Garg
Keyword(s):  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Scientific Applications ◽  
Virtual Machine Migration ◽  
Simulation Based ◽  
First Come First Serve ◽  
Minimum Completion Time ◽  
Burst Time ◽  
Parent Node

Workflow scheduling is one of the significant issues for scientific applications among virtual machine migration, database management, security, performance, fault tolerance, server consolidation, etc. In this paper, existing time-based scheduling algorithms, such as first come first serve (FCFS), min–min, max–min, and minimum completion time (MCT), along with dependency-based scheduling algorithm MaxChild have been considered. These time-based scheduling algorithms only compare the burst time of tasks. Based on the burst time, these schedulers, schedule the sub-tasks of the application on suitable virtual machines according to the scheduling criteria. During this process, not much attention was given to the proper utilization of the resources. A novel dependency and time-based scheduling algorithm is proposed that considers the parent to child (P2C) node dependencies, child to parent node dependencies, and the time of different tasks in the workflows. The proposed P2C algorithm emphasizes proper utilization of the resources and overcomes the limitations of these time-based schedulers. The scientific applications, such as CyberShake, Montage, Epigenomics, Inspiral, and SIPHT, are represented in terms of the workflow. The tasks can be represented as the nodes, and relationships between the tasks can be represented as the dependencies in the workflows. All the results have been validated by using the simulation-based environment created with the help of the WorkflowSim simulator for the cloud environment. It has been observed that the proposed approach outperforms the mentioned time and dependency-based scheduling algorithms in terms of the total execution time by efficiently utilizing the resources.

N and P on-line meters: requirements, maintenance and stability

1996 ◽  
Vol 33 (1) ◽  
pp. 147-157 ◽  
Author(s):  
Henrik A. Thomsen ◽  
Kenneth Kisbye
Keyword(s):  
Sample Preparation ◽  
Response Time ◽  
Ammonium Nitrate ◽  
State Of The Art ◽  
List Price ◽  
User Friendliness ◽  
On Line ◽  
The Cost ◽  
Preparation Design

State-of-the-art on-line meters for determination of ammonium, nitrate and phosphate are presented. The on-line meters employ different measuring principles and are available in many different designs differing with respect to size, calibration and cleaning principle, user-friendliness, response time, reagent and sample consumption. A study of Danish experiences on several plants has been conducted. The list price of an on-line meter is between USD 8000 and USD 35,000. To this should be added the cost of sample preparation, design, installation and running-in. The yearly operating for one meter are in the range of USD 200-2500 and the manpower consumption is in the range of 1-5 hours/month. The accuracy obtained is only slightly smaller than the accuracy on collaborative laboratory analyses, which is sufficient for most control purposes.

scholarly journals Performance of Movable Head Disk Storage Devices with Various Disk Scheduling Algorithms

2019 ◽  
Vol 9 (2S) ◽  
pp. 486-490
Keyword(s):  
Scheduling Algorithms ◽  
Access Time ◽  
Processing Unit ◽  
Disk Scheduling ◽  
Efficient Manner ◽  
Hard Drives ◽  
Storage Devices ◽  
Disk Storage ◽  
Central Processing ◽  
The One

Hard drives are the one which needs to be accessed in an efficient manner so that it is feasible to get better recital of the central processing unit. Now a day’s magnetic disks are capable of providing more input output bandwidth yet a huge amount of this bandwidth is lost due to the access time of the hard disk. This paper discusses an analysis of performance of various disk scheduling algorithms with their merits and demerits

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