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Routing metrics for cache-based reliable transport in wireless sensor networks

: Grilo, Antonio; Heidrich, Mike

Fulltext urn:nbn:de:0011-n-2688544 (996 KByte PDF)
MD5 Fingerprint: fc7a549a19a231a9eaaa8fa57b932907
Created on: 4.12.2013

EURASIP journal on wireless communications and networking (2013), Art. 139, 16 pp.
ISSN: 1687-1472
ISSN: 1687-1499
Journal Article, Electronic Publication
Fraunhofer ESK ()
wireless sensor network; WSN; Internet of Things; IoT; routing metric; Cache; cross-layer architecture

The Internet of Things (IoT) will bring the pervasive networking of objects, integrating different technologies that will interconnect nodes with heterogeneous capabilities and resources. Although radio-frequency identification will likely play a major role in the IoT, it is not the only one. Wireless sensor networks (WSN) will likely become the paradigm for communication of more powerful nodes in the IoT. The energy and bandwidth constraints of WSNs have motivated the development of new reliable transport protocols in which intermediate nodes are able to cache packets and to retransmit them to the destination in the course of the end-to-end packet recovery process (e.g., pump slowly fetch quickly, reliable multi-segment transport, distributed TCP caching, distributed transport for sensor networks (DTSN)). These protocols use memory resources at the intermediate nodes to achieve lower energy consumption, higher goodput, and lower delay. In a heterogeneous IoT environment, nodes are likely to differ greatly in terms of memory capacity, ranging from almost memoryless tags to more powerful sensors/actuators. Consequently, network nodes will present different eligibilities to support the reliable transport functions, which must be taken into account when setting up routes. The ability to select paths formed by cache-rich nodes becomes essential to maximize network performance and increase energy efficiency. This paper proposes new routing metrics related with the availability of the transport-layer cache at intermediate nodes. A cross-layer protocol architecture is also proposed to support those metrics as well as to integrate legacy metrics such as hop distance and link quality. Simulation results based on the DTSN transport protocol demonstrate that the proposed metrics and cross-layer architecture are essential to leverage the transport layer error recovery mechanism, resulting in increased energy efficiency.