Parallel heuristic graph matching algorithm for task assignment problem in distributed computing systems

2012 ◽  
Author(s):  
R Mohan ◽  
N P Gopalan ◽  
S H Dinesh Prasanth ◽  
Siddhant Sanyam ◽  
Saagar R Varma
Keyword(s):  
Distributed Computing ◽  
Assignment Problem ◽  
Graph Matching ◽  
Task Assignment ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Matching Algorithm ◽  
Task Assignment Problem

An Iterated Local Search Algorithm for Task Assignment in Distributed Computing Systems

2012 ◽  
Vol 588-589 ◽  
pp. 1308-1311
Author(s):  
Qin Ma Kang ◽  
Hong He ◽  
Hai Ning Jiang
Keyword(s):  
Distributed Computing ◽  
Local Search ◽  
Search Algorithm ◽  
Task Assignment ◽  
Computation Time ◽  
Iterated Local Search ◽  
Local Search Algorithm ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Wide Range

This paper considers the problem of task assignment in heterogeneous distributed computing systems with the goal of minimizing the total execution and communication costs. An iterated local search algorithm is proposed for finding the suboptimal task assignment in a reasonable amount of computation time. We study the performance of the proposed algorithm over a wide range of parameters such as the problem scales, the ratio of average communication time to average computation time, and task interaction density of applications. The effectiveness of the algorithm is manifested by comparing it with other competing algorithms in the relevant literature.

scholarly journals An Optimal Task Assignment Strategy in Cloud-Fog Computing Environment

2021 ◽  
Vol 11 (4) ◽  
pp. 1909
Author(s):  
Jung-Fa Tsai ◽  
Chun-Hua Huang ◽  
Ming-Hua Lin
Keyword(s):  
Internet Of Things ◽  
Assignment Problem ◽  
Fog Computing ◽  
Task Assignment ◽  
The Internet ◽  
Computing Environment ◽  
Computing Systems ◽  
Assignment Strategy ◽  
The Internet Of Things ◽  
Task Assignment Problem

With the advent of the Internet of Things era, more and more emerging applications need to provide real-time interactive services. Although cloud computing has many advantages, the massive expansion of the Internet of Things devices and the explosive growth of data may induce network congestion and add network latency. Cloud-fog computing processes some data locally on edge devices to reduce the network delay. This paper investigates the optimal task assignment strategy by considering the execution time and operating costs in a cloud-fog computing environment. Linear transformation techniques are used to solve the nonlinear mathematical programming model of the task assignment problem in cloud-fog computing systems. The proposed method can determine the globally optimal solution for the task assignment problem based on the requirements of the tasks, the processing speed of nodes, and the resource usage cost of nodes in cloud-fog computing systems.

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