Optimization of makespan and resource utilization in the fog computing environment through task scheduling algorithm

The Fog computing is rising as a dominant and modern computing model to deliver Internet of Things (IoT) computations, which is an addition to the cloud computing standard to get it probable to perform the IoT requests in the network of edge. In those above independent and dispersed environment, resource allocation is vital. Therefore, scheduling will be a test to enhance potency and allot resources properly to the tasks. This paper offers a distinct task scheduling algorithm in the fog computing environment that tries to depreciate the makespan and maximize resource utilization. This algorithm catalogues the task based on the mean Suffrage value. The suggested algorithm gives much resource utilization and diminishes makespan. Our offered algorithm is compared with different alive scheduling for performance investigation, and test results confirm that our algorithm has a more significant resource utilization rate and low makespan than other familiar algorithms.

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An effective task scheduling algorithm based on dynamic energy management and efficient resource utilization in green cloud computing environment

Cluster Computing ◽

10.1007/s10586-017-1272-y ◽

2017 ◽

Vol 22 (S1) ◽

pp. 513-520 ◽

Cited By ~ 9

Author(s):

Yong Lu ◽

Na Sun

Keyword(s):

Cloud Computing ◽

Energy Management ◽

Resource Utilization ◽

Task Scheduling ◽

Scheduling Algorithm ◽

Computing Environment ◽

Cloud Computing Environment ◽

Task Scheduling Algorithm ◽

Efficient Resource ◽

Dynamic Energy Management

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An improved list-based task scheduling algorithm for fog computing environment

Computing ◽

10.1007/s00607-021-00935-9 ◽

2021 ◽

Author(s):

R. Madhura ◽

B. Lydia Elizabeth ◽

V. Rhymend Uthariaraj

Keyword(s):

Task Scheduling ◽

Scheduling Algorithm ◽

Fog Computing ◽

Computing Environment ◽

Task Scheduling Algorithm

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HTSCC A Hybrid Task Scheduling Algorithm in Cloud Computing Environment

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY ◽

10.24297/ijct.v17i2.7584 ◽

2018 ◽

Vol 17 (2) ◽

pp. 7236-7246 ◽

Cited By ~ 1

Author(s):

Rasha Ali Al-Arasi ◽

Anwar Saif

Keyword(s):

Cloud Computing ◽

Resource Utilization ◽

Task Scheduling ◽

Scheduling Algorithm ◽

Application Software ◽

Computing Environment ◽

Cloud Computing Environment ◽

Task Scheduling Algorithm ◽

Np Hard Problem ◽

Software And Hardware

Nowadays, cloud computing makes it possible for users to use the computing resources like application, software, and hardware, etc., on pay as use model via the internet. One of the core and challenging issue in cloud computing is the task scheduling. Task scheduling problem is an NP-hard problem and is responsible for mapping the tasks to resources in a way to spread the load evenly. The appropriate mapping between resources and tasks reduces makespan and maximizes resource utilization. In this paper, we present and implement an independent task scheduling algorithm that assigns the users' tasks to multiple computing resources. The proposed algorithm is a hybrid algorithm for task scheduling in cloud computing based on a genetic algorithm (GA) and particle swarm optimization (PSO). The algorithm is implemented and simulated using CloudSim simulator. The simulation results show that our proposed algorithm outperforms the GA and PSO algorithms by decreasing the makespan and increasing the resource utilization.

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Limit Value Task Scheduling (LVTS): an Efficient Task Scheduling Algorithm for Distributed Computing Environment

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d9228.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 10457-10462

Keyword(s):

Resource Utilization ◽

Task Scheduling ◽

Scheduling Algorithm ◽

Computing Environment ◽

Complete Problem ◽

Limit Value ◽

Computational Environment ◽

Task Scheduling Algorithm ◽

Np Complete ◽

Diverse Groups

The grid computational environment suits to meet the computational demands of large, diverse groups of tasks. Assigning tasks to heterogeneous wide spread resources seems complex and is termed as an NP-Complete problem. A new task scheduling algorithm, called Limit Value Task Scheduling Algorithm (LVTS) is presented to efficiently identify the appropriate resources, which is responsible for the scheduling process. The proposed algorithm (LVTS) schedules the tasks to the appropriate resources by calculating the limit value of the tasks and the ceil value of the tasks which represents the completion time of the last tasks scheduled in the resource with highest processing capacity. The efficiency of the (LVTS) measured based on makespan and resource utilization. Experimental results indicates LVTS algorithm sounds good than the Min-min on both makespan and resource utilization.

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