Behzad Saemi

Behzad Saemi
Kavosh Institute of Higher Education · Computer Department

Master of Engineering

About

8
Publications
6,112
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
328
Citations
Introduction
Parallel meta-heuristic algorithm
Skills and Expertise
Cloud Computing
Computer Networking
Classification
Machine Learning
Data Clustering
Pattern Recognition
Data Mining and Knowledge Discovery
Neural Networks and Artificial Intelligence
Data Science
Routing
Additional affiliations
January 2016 - June 2020
Www.Varanegar.com
  • software production
  • Iran
Position
  • Programmer
Description
  • Providing intelligent systems for optimizing the path of vehicles, providing intelligent reporting systems for software production of broadcasting companies
Education
January 2017 - January 2019
Kavosh University
Field of study
  • Computer

Publications

Publications (8)
View
View
RSU
Communication in VANET [3]
Type of communication in VANETs [3]
An example of VANETs [8]
+13 Greedy routing from node x\documentclass[12pt]{minimal}...
Improving the quality of real-time data transmission service in VANETS by balancing the load on road side units
Article
Full-text available
  • Mar 2024
Vehicular Ad Hoc Networks (VANETs) play a critical role in ensuring safety and welfare applications for drivers and passengers amidst the escalating vehicular population in urban environments. The efficient functioning of VANETs hinges on addressing the challenge of load balancing among Road Side Units (RSUs). This paper introduces a groundbreaking...
View
FIGURE 6. A sample of the Crossover operator in the proposed algorithm.
FIGURE 7. Scheduling algorithms are compared in terms of their...
FIGURE 9. Scheduling algorithms tested against the time it takes to...
FIGURE 10. Scheduling algorithm evaluations in terms of the number of...
+1 Unique numbering to process each task by each available processor.
Solving Task Scheduling Problem in Mobile Cloud Computing Using the Hybrid Multi-Objective Harris Hawks Optimization Algorithm
Article
Full-text available
  • Jan 2023
Nowadays, mobile devices can run a wide range of programs, and they all require more and more processing power. Due to their limited resources, mobile devices often make use of cloud computing’s offloading features to do more complex tasks. The offloading problem in Mobile Cloud Computing (MCC) is the task scheduling problem, which entails deciding...
View
Fig. 1: Hybrid MCC Architecture for Task Scheduling and Offloading
Fig. 2: Comparison of scheduling algorithms based on run-time
Fig. 4: Comparison of scheduling algorithms based on average task...
Fig. 6: Comparison of scheduling algorithms based on makespan
A New Optimization Approach for Task Scheduling Problem Using Water Cycle Algorithm in Mobile Cloud Computing
Conference Paper
Full-text available
  • Jun 2021
Mobile devices are used by numerous applications that continuously need computing power to grow. Due to limited resources for complex computing, offloading, a service offered for mobile devices, is commonly used in cloud computing. In Mobile Cloud Computing (MCC), offloading decides where to execute the tasks to efficiently maximize the benefits. H...
View
Fig. 2 A sample of scheduling graph
Fig. 3 Pseudo-code of ICA
Fig. 4 Pseudo-code of FA
Fig. 7 Scheduling Gantt chart for a sample of the country in Fig. 3
+14 Fig. 10 Application of absorption operator by the single-point method
An enhancement of task scheduling in cloud computing based on imperialist competitive algorithm and firefly algorithm
Article
Full-text available
  • Aug 2020
Cloud computing is an Internet-based approach in which all applications and files are hosted in a cloud consisting of thousands of computers that are linked in complex ways. The major challenge of cloud data centers is to show how the millions of requests of final users are correctly and effectively being investigated and serviced. Load-balancing t...
View
Optimal schedule for Taillard Benchmark instance with the makespan of 193
Fitness diagram of the EGA_OS for the Test_7_7 dataset, based on...
Dispersion diagram of the various crossover operations for the Test_8_8...
Dispersion diagram of the various crossover operations for the Test_5_5...
+17 Fitness diagram of various crossover and mutation operations for the...
Extended Genetic Algorithm for solving open-shop scheduling problem
Article
Full-text available
  • Jul 2019
Open-shop scheduling problem (OSSP) is a well-known topic with vast industrial applications which belongs to one of the most important issues in the field of engineering. OSSP is a kind of NP problems and has a wider solution space than other basic scheduling problems, i.e., Job-shop and flow-shop scheduling. Due to this fact, this problem has attr...
View
Table 1 . Features of each data sets for data clustering algorithms
Fig. 2. Cluster center based display 
Table 2 . Results of each algorithm based on internal distance within...
Fig. 3. Cluster center based display based on data numbering 
+13 Fig. 4. Display based on two statuses 0, 1 
Nature Inspired Partitioning Clustering Algorithms: A Review and Analysis
Conference Paper
Full-text available
  • Aug 2018
Clustering algorithms are developed as a powerful tool to analyze the massive amount of data which are produced by modern applications. The main goal of these algorithms is to classify the data in clusters of objects, so that data in each cluster is similar based on specific criteria and data from two different clusters be different as much as poss...
View

Network

Cited
View All
Cited By
View All