• Home
  • About Rimag
  • Contact Us
  • Register
  • Log in
  • Order
Advanced
  • Home
  •  
  • Current Issue

    41
    Issue 41   Vol 11 Winter 2023
    Submit Your Paper List of Journal Reviewers

    Published Issues

    • Vol. 11
      • ✓ Issue 41 - Winter 2023
    • Vol. 10
      • ✓ Issue 40 - Autumn 2022
      • ✓ Issue 39 - Summer 2022
      • ✓ Issue 38 - Spring 2022
      • ✓ Issue 37 - Winter 2022
    • Vol. 9
      • ✓ Issue 36 - Autumn 2021
      • ✓ Special Issue
      • ✓ Issue 35 - Summer 2021
      • ✓ Issue 34 - Spring 2021
      • ✓ Issue 33 - Winter 2021
    • Vol. 8
      • ✓ Issue 32 - Autumn 2020
      • ✓ Issue 31 - Summer 2020
      • ✓ Issue 30 - Spring 2020
      • ✓ Issue 29 - Winter 2020
    • Vol. 7
      • ✓ Issue 28 - Autumn 2019
      • ✓ Issue 27 - Summer 2019
      • ✓ Issue 26 - Spring 2019
      • ✓ Issue 25 - Winter 2019
    • Vol. 6
      • ✓ Issue 24 - Autumn 2018
      • ✓ Issue 23 - Summer 2018
      • ✓ Issue 22 - Spring 2018
      • ✓ Issue 21 - Winter 2018
    • Vol. 5
      • ✓ Issue 20 - Autumn 2017
      • ✓ Issue 19 - Summer 2017
      • ✓ Issue 18 - Spring 2017
      • ✓ Issue 17 - Winter 2017
    • Vol. 4
      • ✓ Issue 16 - Autumn 2016
      • ✓ Issue 15 - Summer 2016
      • ✓ Issue 14 - Spring 2016
      • ✓ Issue 13 - Winter 2016
    • Vol. 3
      • ✓ Issue 12 - Autumn 2015
      • ✓ Issue 11 - Summer 2015
      • ✓ Issue 10 - Spring 2015
      • ✓ Issue 9 - Winter 2015
    • Vol. 2
      • ✓ Issue 8 - Autumn 2014
      • ✓ Issue 7 - Summer 2014
      • ✓ Issue 6 - Spring 2014
      • ✓ Issue 5 - Winter 2014
    • Vol. 1
      • ✓ Issue 4 - Autumn 2013
      • ✓ Issue 3 - Summer 2013
      • ✓ Issue 2 - Spring 2013
      • ✓ Issue 1 - Winter 2013

    Browse

    • •  Current Issue
    • •  By Issue
    • • Author Index
    • •  By Subject
    • •  By Author

    Menu

    • •  Editorial Board
    • •  Journal Policy
    • •  About Journal
    • •  Special Issues
    • •  Author Guide
    • •  Article Processing Charges (APC)
    • •  Evaluation Process
    • Contact Journal
    OpenAccess
    • List of Articles  

      • Open Access Article
        • Abstract Page
        • Full-Text

        1 - Ant Colony Scheduling for Network On Chip
        Neda  Dousttalab Mohammad Ali Jabraeil Jamali Ali Ghaffari
        10.7508/jist.2015.02.004
        The operation scheduling problem in network on chip is NP-hard; therefore effective heuristic methods are needful to provide modal solutions. This paper introduces ant colony scheduling, a simple and effective method to increase allocator matching efficiency and hence n More
        The operation scheduling problem in network on chip is NP-hard; therefore effective heuristic methods are needful to provide modal solutions. This paper introduces ant colony scheduling, a simple and effective method to increase allocator matching efficiency and hence network performance, particularly suited to networks with complex topology and asymmetric traffic patterns. Proposed algorithm has been studied in torus and flattened-butterfly topologies with multiple types of traffic pattern. Evaluation results show that this algorithm in many causes has showed positive effects on reducing network delays and increased chip performance in comparison with other algorithms. Manuscript profile
      • Open Access Article
        • Abstract Page
        • Full-Text

        2 - Data Aggregation Tree Structure in Wireless Sensor Networks Using Cuckoo Optimization Algorithm
        Elham Mohsenifard Behnam Talebi
        10.7508/jist.2016.03.006
        Wireless sensor networks (WSNs) consist of numerous tiny sensors which can be regarded as a robust tool for collecting and aggregating data in different data environments. The energy of these small sensors is supplied by a battery with limited power which cannot be rech More
        Wireless sensor networks (WSNs) consist of numerous tiny sensors which can be regarded as a robust tool for collecting and aggregating data in different data environments. The energy of these small sensors is supplied by a battery with limited power which cannot be recharged. Certain approaches are needed so that the power of the sensors can be efficiently and optimally utilized. One of the notable approaches for reducing energy consumption in WSNs is to decrease the number of packets to be transmitted in the network. Using data aggregation method, the mass of data which should be transmitted can be remarkably reduced. One of the related methods in this approach is the data aggregation tree. However, it should be noted that finding the optimization tree for data aggregation in networks with one working-station is an NP-Hard problem. In this paper, using cuckoo optimization algorithm (COA), a data aggregation tree was proposed which can optimize energy consumption in the network. The proposed method in this study was compared with genetic algorithm (GA), Power Efficient Data gathering and Aggregation Protocol- Power Aware (PEDAPPA) and energy efficient spanning tree (EESR). The results of simulations which were conducted in matlab indicated that the proposed method had better performance than GA, PEDAPPA and EESR algorithm in terms of energy consumption. Consequently, the proposed method was able to enhance network lifetime. Manuscript profile
  • Home Page
  • Site Map
  • Contact Us
  • Home
  • Site Map
  • Regional Science and Technology Information Center
  • Contact Us

The rights to this website are owned by the Raimag Press Management System.
Copyright © 2017-2023

Home| Login| About Rimag| Contact Us|
[فارسی] [العربية] [fa] [ar]
  • Ricest
  • Login
  • email