Abstract: In this paper, the problem of estimating the link quality in mesh networks has been considered. Such a problem is a major task to develop an efficient network layer, since an accurate knowledge of the link qualities allows routing protocols to efficiently use neighbors as relays for multi-hop communications. In the last years, a number of link-quality aware routing metrics based on the packet delivery ratio have been proposed and analyzed. However, very few works have addressed the problem of correctly estimating the delivery ratio of a wireless link. Therefore, in this paper we resort to a 802.11b mesh network to carry on a performance comparison between two widely adopted delivery ratio estimators, namely the Simple Moving Average and the Exponentially Weighted Moving Average, and a recently proposed one based on the neural network paradigm.
Link quality estimators for multi-hop mesh network / Cacciapuoti, ANGELA SARA; Caleffi, Marcello; Paura, Luigi; Rahman, MD ARAFATUR. - (2014), pp. 1-6. (Intervento presentato al convegno 2014 Euro Med Telco Conference - From Network Infrastructures to Network Fabric: Revolution at the Edges, EMTC 2014 tenutosi a University of Naples "Federico II" Congress Center, ita nel 2014) [10.1109/EMTC.2014.6996637].
Link quality estimators for multi-hop mesh network
CACCIAPUOTI, ANGELA SARA;CALEFFI, MARCELLO;PAURA, LUIGI;RAHMAN, MD ARAFATUR
2014
Abstract
Abstract: In this paper, the problem of estimating the link quality in mesh networks has been considered. Such a problem is a major task to develop an efficient network layer, since an accurate knowledge of the link qualities allows routing protocols to efficiently use neighbors as relays for multi-hop communications. In the last years, a number of link-quality aware routing metrics based on the packet delivery ratio have been proposed and analyzed. However, very few works have addressed the problem of correctly estimating the delivery ratio of a wireless link. Therefore, in this paper we resort to a 802.11b mesh network to carry on a performance comparison between two widely adopted delivery ratio estimators, namely the Simple Moving Average and the Exponentially Weighted Moving Average, and a recently proposed one based on the neural network paradigm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
