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Traffic and packet distribution across prefixes are highly skewed.
The transmission packet is modeled at each state with general packet distribution for service time.
Multicasting enables a packet to be distributed from a source to any number of destinations automatically, with the responsibility for packet distribution placed on intelligent network nodes.
To reduce such losses and further improve spectral efficiency via rate selection, we exploit either statistical or instantaneous knowledge of transmit buffer occupancy and source packet distribution in IEEE 802.11-based systems, which have highly variable frame durations.
According to the input packet distribution, we have p K ( K ≥ x | m, n ) = ∑ x ≤ k ≤ ∞ ( λ T f ( m, n ) ) k k ! exp ( - λ T f ( m, n ) ) (18).
We also explore the performance of DIAMoND across network topologies under different conditions of "normal" network traffic to determine how the interactions between underlying topology and expected variation in packet distribution and flow might alter detection capabilities.
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The probability for Alice and Bob to share the same bit, i.e., the probability for memories A1, B1 and A2, B2 to have the same state is (p=1-q/2), where (q ll1) will in our case be related to our δ parameter and the wave packet distributions.
We consider both saturated and non-saturated modes, and the packet arrival distribution of non-saturated mode is Poisson distribution.
with the packet arrival distribution.
Self-similar traffic and OC-3 packet size distribution are used for frame generation.
We first describe the benchmark packet length distribution considered in this paper, and then we report our proposed solution.
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