A high-throughput path metric for multi-hop wireless routing
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In this paper, we propose a lexical routing metric to enable path-wise link quality-aware routing in Wireless Sensor Networks (WSNs). The realization of this routing metric is achieved by applying the indexing techniques of formal language processing in multi-metric route classification and cost evaluation for WSNs. In particular, the metric is motivated from the fact that IEEE 802.15.4 networks are formed on links with highly variable quality, and selection of poor quality links degrades the data delivery considerably. Although IEEE 802.15.4 supports link-level awareness through LQI, (a) it remains unbeknownst at the path level, and therefore, (b) its processing is link-local in scope. We propose LABILE, a composite routing metric, that is implemented through modifying RREQ and RREP structures of AODV to capture and convey two-state link information to destination which in turn is processed through an easy to compute routing lexicon and a corresponding lexical algorithm for path selection in case of availability of multiple paths. Multiple paths are represented in a path space through a proposed cost model that encompasses hop-count, weak links and a quantity weakness factor of each link, depending upon a thresholding mechanism which in turn declares a link to be either healthy (aka usable) or weak (aka unusable). Using the weakness factor, the success probability of data delivery over weak link turns out to be a fraction of success probability at healthy link. The mathematical model along with the experiments done for LABILE show that proposed composite metric and its parsing scheme together achieve link robustness consistently by evading the link failures, as the number of weak links is fairly reduced in lexical path as compared to the hop-count-based metric. Increased data delivery is obtained through preventing retransmissions as on failure-prone links.