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Improving Wireless Link Simulation Using Multilevel Markov Models
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DOI：10.1145/2529991.png)
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Modeling the behavior of 802.15.4 links is a nontrivial problem, because 802.15.4 links experience different level of dynamics at short and long time scales. This makes the design of a suitable model that combines the different dynamics at different time scales a nontrivial problem. We propose a novel multilevel approach, the M&M model, involving hidden Markov models (HMMs) and mixtures of multivariate Bernoullis (MMBs) for modeling the long and short time-scale behavior of wireless links from 802.15.4 test beds. We characterize the synthetic traces generated from our model of the wireless link in terms of the mean and variance of the packet reception rates from the data traces, comparison of distributions of run lengths, and conditional packet delivery functions of successive packet receptions (1's) and losses (0's). Our results show that when compared to the closest-fit pattern matching model in TOSSIM, the proposed modeling approach is able to mimic the behavior of the data traces quite closely, with differences in packet reception rates of the empirical and simulated traces of less than 1.9% on average and 6.6% in the worst case. Moreover, the simulated links from our proposed approach were able to account for long runs of 1's and 0's as observed in empirical data traces.
Keyword:
Algorithms
Measurement
Performance
Design
Experimentation
Simulation
802.15.4 low-power wireless networks
wireless channel model
hidden Markov models
mixture of multivariate Bernoulli
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