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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.
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