Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1278
Title: Optimized Service Function Path Selection for IoT Devices Using Virtual Network Function Performance Data
Authors: Shanaka, W. A
Abeysiriwardhana, P
Wijekoon, J
Nishi, H
Keywords: Optimized Service
Function Path Selection
IoT Devices
Virtual Network
Function Performance Data
Issue Date: 9-Jan-2019
Publisher: IEEE
Citation: W. A. S. P. Abeysiriwardhana, J. Wijekoon and H. Nishi, "Optimized Service Function Path Selection for IoT Devices Using Virtual Network Function Performance Data," 2019 International Conference on Information Networking (ICOIN), 2019, pp. 165-170, doi: 10.1109/ICOIN.2019.8718150.
Series/Report no.: 2019 International Conference on Information Networking (ICOIN);Pages 165-170
Abstract: Software defined networking (SDN) and network function virtualization (NFV) are proposed as software based applications to cater to smart services requirements of smart communities. The services are linked together to support different sets of clients using service function chaining (SFC). Service functions (SFs) in an SFC must be distributed among available computing resources by creating a service function path (SFP) allowing resource management and optimal SF execution. This paper proposes a novel SFP allocation algorithm considering the computation capabilities of hardware resources while minimizing the completion time of SFCs. The proposed algorithm shows 10% performance increment compared to recently developed algorithms such as nearly optimal service function path and optimal service function selection algorithms.
URI: http://rda.sliit.lk/handle/123456789/1278
ISSN: 1976-7684
Appears in Collections:Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

Files in This Item:
File Description SizeFormat 
Optimized_Service_Function_Path_Selection_for_IoT_Devices_Using_Virtual_Network_Function_Performance_Data.pdf
  Until 2050-12-31
747.5 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.