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There are many ways to model packet traffic in a network. Classically, traffic is modeled as a Poisson process, which can be studied analytically, often
There are many ways to model packet traffic in a network. Classically, traffic is modeled as a Poisson process, which can be studied analytically, often with closed form solutions. However, real world traffic arrivals don't generally follow a Poisson distribution. In this problem, we will assume a uniform distribution of packets. Assume that we have N packet sources, where each source transmits an Ethernet packet (1500 bytes-12000 bits) at an average rate of 100 packets per second, and the start time of each packet is uniformly distributed. In other words, out of a 10 millisecond time period, each source woccupy a percentage of that interval (duty cycle) beginning at a random time. Find the probability that there is no packet overlap (collision) under the following conditions R-10Mbps, for N-2:10 (assume binary signaling, so Tb-100ns) There are many ways to model packet traffic in a network. Classically, traffic is modeled as a Poisson process, which can be studied analytically, often with closed form solutions. However, real world traffic arrivals don't generally follow a Poisson distribution. In this problem, we will assume a uniform distribution of packets. Assume that we have N packet sources, where each source transmits an Ethernet packet (1500 bytes-12000 bits) at an average rate of 100 packets per second, and the start time of each packet is uniformly distributed. In other words, out of a 10 millisecond time period, each source woccupy a percentage of that interval (duty cycle) beginning at a random time. Find the probability that there is no packet overlap (collision) under the following conditions R-10Mbps, for N-2:10 (assume binary signaling, so Tb-100ns)
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