Performance analysis of parallel computing in a distributed overlay network

Jay W.Y. Lim, Poo Kuan Hoong, Eng Thiam Yeoh, Ian K.T. Tan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)


There are many data and computation intensive applications that generally require very high performance and a lot of computing resources which lead to the increase in the overall execution time. Parallel computing can improve overall execution time which involves breaking up large program into smaller pieces that can be executing in multi processors system. While, distributed computing offers some advantages for parallel computing, where multiple connected processors can run in parallel by contributing their computing time and memory storage. However, due to the nature of heterogeneity of processing power in distributed computing, the effect of imbalance of workload distribution between processors is an important factor to be taken into consideration. In this paper, we conducted simulations of Pi value computation for tree-based distributed system under several of types of workloads distributions. We measured the overall execution time to study and analyze the effect of different workloads distribution. From our simulation results, we found that the increment of waiting time for a processor to receive back a result significantly impact the overall execution time as well as the scalability of the distributed system.

Original languageEnglish
Title of host publicationTENCON 2011 - 2011 IEEE Region 10 Conference
Subtitle of host publicationTrends and Development in Converging Technology Towards 2020
Number of pages5
Publication statusPublished - 2011
Externally publishedYes
EventIEEE Tencon (IEEE Region 10 Conference) 2011 - Bali, Indonesia
Duration: 21 Nov 201124 Nov 2011 (Proceedings)


ConferenceIEEE Tencon (IEEE Region 10 Conference) 2011
Abbreviated titleTENCON 2011
Internet address


  • distributed system
  • OMNET++
  • parallel computing
  • tree-based

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