HASA: Half The Average Scheduling Algorithm

2017 ◽  
Vol 2 (9) ◽  
pp. 35-39
Author(s):  
Afaf Abd Elkader Abd Elhafiz
Keyword(s):  
Scheduling Algorithm ◽  
Experimental Results ◽  
Objective Functions ◽  
Completion Times ◽  
Independent Tasks

The process of assigning independent tasks to resources with the aim of optimizing some objective functions is known as scheduling. The efficient scheduling of independent tasks to improve the performance of a system is an important problem. Several algorithms are developed to schedule tasks on their resources to minimize the makespan. One of these algorithms is ACTA (Average of Completion Times Algorithm). This paper proposes an algorithm HASA (Half the Average Scheduling Algorithm) that ameliorates the makespan produced by ACTA. Experimental results show that the proposed algorithm gives makespan smaller than ACTA.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

scholarly journals Online Makespan Scheduling with Job Migration on Uniform Machines

Algorithmica ◽  
2021 ◽  
Author(s):  
Matthias Englert ◽  
David Mezlaf ◽  
Matthias Westermann
Keyword(s):  
Competitive Ratio ◽  
Online Algorithm ◽  
Parallel Machines ◽  
Scheduling Algorithm ◽  
Input Sequence ◽  
Job Migration ◽  
Average Completion Time ◽  
Uniform Machine ◽  
Uniform Machines ◽  
Completion Times

AbstractIn the classic minimum makespan scheduling problem, we are given an input sequence of n jobs with sizes. A scheduling algorithm has to assign the jobs to m parallel machines. The objective is to minimize the makespan, which is the time it takes until all jobs are processed. In this paper, we consider online scheduling algorithms without preemption. However, we allow the online algorithm to change the assignment of up to k jobs at the end for some limited number k. For m identical machines, Albers and Hellwig (Algorithmica 79(2):598–623, 2017) give tight bounds on the competitive ratio in this model. The precise ratio depends on, and increases with, m. It lies between 4/3 and $$\approx 1.4659$$ ≈ 1.4659 . They show that $$k = O(m)$$ k = O ( m ) is sufficient to achieve this bound and no $$k = o(n)$$ k = o ( n ) can result in a better bound. We study m uniform machines, i.e., machines with different speeds, and show that this setting is strictly harder. For sufficiently large m, there is a $$\delta = \varTheta (1)$$ δ = Θ ( 1 ) such that, for m machines with only two different machine speeds, no online algorithm can achieve a competitive ratio of less than $$1.4659 + \delta $$ 1.4659 + δ with $$k = o(n)$$ k = o ( n ) . We present a new algorithm for the uniform machine setting. Depending on the speeds of the machines, our scheduling algorithm achieves a competitive ratio that lies between 4/3 and $$\approx 1.7992$$ ≈ 1.7992 with $$k = O(m)$$ k = O ( m ) . We also show that $$k = \varOmega (m)$$ k = Ω ( m ) is necessary to achieve a competitive ratio below 2. Our algorithm is based on maintaining a specific imbalance with respect to the completion times of the machines, complemented by a bicriteria approximation algorithm that minimizes the makespan and maximizes the average completion time for certain sets of machines.

Batch Scheduling Algorithm with Approximation of Job Completion Times and Case Studies

2020 ◽  
Vol 43 (4) ◽  
pp. 23-32
Author(s):  
Song-Eun Kim ◽  
◽  
Seong-Hyeon Park ◽  
Su-Min Kim ◽  
Kyungsu Park ◽  
...  
Keyword(s):  
Case Studies ◽  
Scheduling Algorithm ◽  
Batch Scheduling ◽  
Completion Times

scholarly journals An Efficient Fault-Tolerant Multi-Bus Data Scheduling Algorithm Based on Replication and Deallocation

2016 ◽  
Vol 16 (2) ◽  
pp. 69-84
Author(s):  
Chafik Arar ◽  
Mohamed Salah Khireddine
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Experimental Results ◽  
Data Scheduling ◽  
Heterogeneous Architectures ◽  
Hardware Faults

Abstract The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed scheduling algorithm takes into consideration only one bus fault in multi-bus heterogeneous architectures, caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies, to minimize the scheduling length of data on buses. In the experiments, this paper evaluates the proposed methods in terms of data scheduling length for a set of DAG benchmarks. The experimental results show the effectiveness of our technique.

scholarly journals IMPROVING THE AUTOMATIC PROCUREMENT OF WEB SERVICES USING CONSTRAINT PROGRAMMING

2005 ◽  
Vol 14 (04) ◽  
pp. 439-467 ◽  
Author(s):  
ANTONIO RUIZ–CORTÉS ◽  
OCTAVIO MARTÍN–DÍAZ ◽  
AMADOR DURÁN ◽  
M. TORO
Keyword(s):  
Web Services ◽  
Internal Consistency ◽  
Constraint Programming ◽  
Experimental Results ◽  
Objective Functions ◽  
Run Time ◽  
Linear Objective Functions ◽  
Best Offer

Software solutions to automate the procurement of web services are gaining importance when technology evolves, the number of providers increases and the needs of the clients become more complex. There are several proposals in this field, but they all have important drawbacks, namely: many of them are not able to check offers and demands for internal consistency; selecting the best offer usually relies on evaluating linear objective functions, which is quite a naive solution; the language to express offers is usually less expressive than the language to express demands; and, last but not least, providers cannot impose constraints on their clients. In this article, we present a solution to overcome these problems that relies on constraint programming; furthermore, we present a run-time framework, some experimental results, and a comparison with other proposals.

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2010 ◽  
Vol 2 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
Grid Environment ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

Taxi Intelligent Dispatch System Based on GPS

2013 ◽  
Vol 742 ◽  
pp. 463-468
Author(s):  
Zhong Min Yao ◽  
Zhao Peng Long ◽  
Qiang Li
Keyword(s):  
Mobile Phones ◽  
Time Complexity ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Positioning System ◽  
Traffic Jam ◽  
Gps Positioning ◽  
Dispatch System ◽  
Intelligent Scheduling

GPS positioning system is installed in taxis and most mobile phones support GPS positioning function at present. GPS phones are used in the taxi to achieving intelligent scheduling based on this basis. The taxi intelligent dispatch system based on GPS is proposed, improve the traditional Dijkstra scheduling algorithms by setting taxi maximum reasonable scheduling range, experimental results show that improved algorithms reduce the time complexity and improve scheduling efficiency. Meanwhile the traffic jam information can be sent to the dispatch center and make scheduling algorithm more reasonable by combined with above information.

Based on Improved Genetic Algorithm for Task Scheduling of Heterogeneous Multi-Core Processor

2014 ◽  
Vol 1030-1032 ◽  
pp. 1671-1675
Author(s):  
Yue Qiu ◽  
Jing Feng Zang
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Execution Time ◽  
Scheduling Algorithm ◽  
Experimental Results ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
High Quality ◽  
Multi Core Processor ◽  
Better Than

This paper puts forward an improved genetic scheduling algorithm in order to improve the execution efficiency of task scheduling of the heterogeneous multi-core processor system and give full play to its performance. The attribute values and the high value of tasks were introduced to structure the initial population, randomly selected a method with the 50% probability to sort for task of individuals of the population, thus to get high quality initial population and ensured the diversity of the population. The experimental results have shown that the performance of the improved algorithm was better than that of the traditional genetic algorithm and the HEFT algorithm. The execution time of tasks was reduced.

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