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In TDMA (time division multiple access), stations transmit their messages on a shared communication channel using their dedicated time slots. All the previous delay analyses of TDMA have been based on the assumption that either the interarrival times of the traffic is exponential or the message lengths are geometrically distributed. This paper presents a generalized model in which the above assumptions are relaxed. This model allows us to compute the exact performance characteristics in closed forms for the mean and the variance of the queue size and the message delay for the TDMA. The model is used to define and compare five bursty traffic distributions. These distributions are used to study their effects on the buffer size and the end-to-end delay for the Mars Regional Network.

Data centers are integral part of cloud computing that support Web services, online social networking, data analysis, computation intensive applications and scientific computing. They require high performance components for their interprocess communication, storage and sub-communication systems. The performance bottleneck that used to be the processing power has now been shifted to communication speed within data centers. The performance of a data center, in terms of throughput and delay, is directly related to the performance of the underlying internal communication network.In this paper, we introduce an analytical model that can be used to evaluate the underlying network architecture in data centers. The model can further be used to develop simulation tools that extend the scope of performance evaluation beyond what it can be achieved by the theoretical model in terms of various network topologies, different traffic distributions, scalability, and load balancing. While the model is generic, we focus on its implementation for fat-tree networks that are widely used in data centers. The theoretical results are compared and validated with the simulation results for several network configurations. The results of this analysis provide a basis for data center network design and optimization.