Subscribe Now Subscribe Today
Science Alert
 
FOLLOW US:     Facebook     Twitter
Blue
   
Curve Top
Australasian Journal of Computer Science
  Year: 2017 | Volume: 4 | Issue: 1 | Page No.: 17-31
DOI: 10.3923/aujcs.2017.17.31
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
Modeling Delay and Energy Consumption for Wireless Sensor Networks with High Coefficient of Variability
Michael Okopa , Ruth Nambasa, Barbara K. Asingwire, Samuel Kakuba and Davis Matovu

Abstract:
Background and Objective: Previous attempts to estimate the delay and energy consumption in wireless sensor networks employed an M/M/1 queue model. In the M/M/1 queue model, the packet length is assumed to have low variability in packet sizes and therefore, service time is best modeled by the exponential distribution. The objective of this study was to estimate the delay and energy consumption for wireless sensor networks with high coefficient of variability. Methodology: To overcome the weaknesses of M/M/1 queue model, this study proposed to model delay and energy consumption under heavy-tail distribution where packet sizes was highly variable as depicted in the Internet using M/G/1 queue model. The service time of packets in the M/G/1 queue was modeled using Bounded Pareto, Lognormal and Weibull distributions. Bounded Pareto, Lognormal and Weibull distributions that depict the heavy-tailed distributions. The coefficient of variation represents the ratio of the standard deviation to the mean and it is a useful statistic for comparing the degree of variation. Results: The numerical results obtained from the derived models show that the average waiting time and energy consumption is higher under the M/G/1 (where G represents Bounded Pareto and Weibull distributions) than under M/M/1 queue model. However, the average waiting time and energy consumption was lower under M/Lognormal/1 than under M/M/1 queue model. It was also observed that increase in the coefficient of variability leads to increase in average waiting time and energy consumption. Conclusion: The M/M/1 queue model under estimates delay and energy consumption for wireless sensor networks with high coefficient of variability.
PDF Fulltext XML References Citation Report Citation
How to cite this article:

Michael Okopa, Ruth Nambasa, Barbara K. Asingwire, Samuel Kakuba and Davis Matovu, 2017. Modeling Delay and Energy Consumption for Wireless Sensor Networks with High Coefficient of Variability. Australasian Journal of Computer Science, 4: 17-31.

DOI: 10.3923/aujcs.2017.17.31

URL: https://scialert.net/abstract/?doi=aujcs.2017.17.31

 
COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 

       

       

Curve Bottom