Sentence examples for modeling packet from inspiring English sources

Li and Shen [49] focused on hybrid networks (MANET nodes plus a wireless infrastructure), by exploiting anycast communication and by modeling packet routing issues as resource scheduling problems.

In this paper, however, a key goal is to formulate modeling mechanisms that can capture multi-scale topological localities in human postural movements and use such locality information for modeling packet routing delay.

Modeling packet loss probability is very critical in per-flow throughput prediction, and it depends on MAC behavior which is strongly tied with geometry of contending links.

Afghah et al. [10] suggested a unique game theoretical method to model packet forwarding in relay networks.

(ii) We accurately model packet loss probability for each station in multi-hop WMN, and this modeling can clearly differentiate between interference from transmission range and carrier sense range.

The correlated loss model is generally used for modeling the packet loss model of IEEE 802.11 wireless LAN [15].

But [5] was not able to capture the comprehensive access mechanism behavior specifically did not model packet loss due to MAC behavior and also lacked binary exponential backoff mechanism.

In this work, we model packet loss probability of individual station based on our prior geometric analysis of a two-flow classification in [12], and unlike [1], our proposed model can clearly differentiate between interference from transmission and carrier sense range.

It has been subsequently extended to model bursty packet loss processes [21].

In the simulations, we use the Gilbert two-state Markov chain to model the packet loss process over WLAN [15].

We accurately model conditional packet loss probability for each station based on geometrical locations of all the interfering stations around it.