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It is well known that 802.11 suffers from both inefficiency and unfairness in the face of competition and interference.This paper provides a detailed analysis of the impact of topology and traffic type on network performance when two flows compete with each other for airspace.We consider both TCP and UDP flows and a comprehensive set of node topologies.We vary these topologies to consider all combinations of the following four node-to-node interactions:(1) nodes unable to read or sense each other,(2)nodes able to sense each other but not able to read each other’s packets and nodes able to communicate with(3)weak and with(4)strong signal.We evaluate all possible cases through simulation and show that the cases can be reduced to 9 UDP and 10 TCP 802.11g models with similar efficiency/fairness characteristics. We also validate our simulation results with extensive experiments conducted in a laboratory testbed.These more detailed models improve on previous work such as hidden-/exposed-terminal categorization and are thus better suited as a basis for adaptive techniques to improve performance in 802.11 multi-hop WLAN or Mesh Networks.
It is well known that 802.11 suffers from both inefficiency and unfairness in the face of competition and interference. This paper provides a detailed analysis of the impact of topology and traffic type on network performance when two flows compete with each other for airspace. We consider both TCP and UDP flows and a comprehensive set of node topologies. We vary these topologies to consider all combinations of the following four node-to-node interactions: (1) nodes unable to read or sense each other, (2) nodes able to sense each other but not able to read each other’s packets and nodes to communicate with (3) weak and with (4) strong signal. We evaluate all possible cases by simulation and show that the cases can be reduced to 9 UDP and 10 TCP 802.11 g also with similar efficiency / fairness characteristics. We also validate our simulation results with extensive experiments conducted in a laboratory testbed. The more detailed models improve previous work such as hidden- / exposed-term inal categorization and are thus better suited as a basis for adaptive techniques to improve performance in 802.11 multi-hop WLAN or Mesh Networks.