Stochastic Estimation of Wireless Traffic Parameters

Different services based on different switching
techniques in wireless networks leads to drastic changes in the
properties of network traffic. Because of these diversities in services,
network traffic is expected to undergo qualitative and quantitative
variations. Hence, assumption of traffic characteristics and the
prediction of network events become more complex for the wireless
networks. In this paper, the traffic characteristics have been studied
by collecting traces from the mobile switching centre (MSC). The
traces include initiation and termination time, originating node, home
station id, foreign station id. Traffic parameters namely, call interarrival
and holding times were estimated statistically. The results
show that call inter-arrival and distribution time in this wireless
network is heavy-tailed and follow gamma distributions. They are
asymptotically long-range dependent. It is also found that the call
holding times are best fitted with lognormal distribution. Based on
these observations, an analytical model for performance estimation is
also proposed.

• Somenath Mukherjee
• Raj Kumar Samanta
• Gautam Sanyal

• Wireless networks
• traffic analysis
• long-range dependence
• heavy-tailed distribution.

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