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By Brian Osserman
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The results obtained from the constructed model are validated in Section 4. Section 5 uses the analytical model to carry out network performance analysis. Finally, Section 6 concludes this study. 2 Bursty and Batch Arrival Traffic This section briefly presents the Generalised Exponential (GE) distribution for modelling bursty and batch arrival network traffic. Let X denote a random variable represented by a GE distribution with mean, 1 / λ , and squared coefficient of variation (SCV), C 2 . The cumulative distribution function, F (t ) , of X can be given by , : F (t ) = P( X ≤ t ) = 1 − τ e −τ λ t , t≥0 .
263/MPEG-4 for video codec) during the multimedia transmission capability exchanges. IMN roaming between 3G and WiFi: For the 3G terminals that roam in the WiFi, AnyServer uses Info Synch and HLR/VLR Adaptor to enable the communications between WiFi and 3G. The roaming interface is to be established in AnyServer platform based on 3G and WiFi standards. IMN Registration through WiFi Networks: For WiFi-IMN, the WiFi layer authentication procedure is achieved through WiFi gateway. AnyServer enables WiFi Registered IMN to roam into 3G networks: When IMN enters 3G networks, it is able to hear the broadcast message from 3G base station (BS) and then it registers the BS through VLR.
67 34 Y. Wu, G. Min, and L. 06 Fig. 3. 67 Performance Analysis of Interconnection Networks Under Bursty and Batch Arrival Traffic 35 5 Performance Analysis In this section, we use the derived analytical model to investigate the impact of bursty and batch arrival traffic with various batch sizes on the performance of hypercubic networks. 6, respectively. e. increasing the batch size) degrades the network performance as the message latency increases. Moreover, the longer messages experience higher latency than the shorter messages as the batch size increases.
An algebra lemma by Brian Osserman