Ad-hoc, Mobile, and Wireless Networks: 13th International by Song Guo, Jaime Lloret Mauri, Pietro Manzoni, Stefan Ruehrup

Storage Retrieval

By Song Guo, Jaime Lloret Mauri, Pietro Manzoni, Stefan Ruehrup

This booklet constitutes the refereed court cases of the thirteenth foreign convention on Ad-hoc, cellular and instant Networks, ADHOC-NOW 2014, held in Benidorm, Spain, in June 2014. The 33 revised complete papers awarded have been rigorously reviewed and chosen from seventy eight submissions. The papers tackle such various issues as routing, mobile networks, MAC and actual layer, cellular advert hoc, sensor and robotic networks, localization and protection, vehicular ad-hoc networks.

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Extra resources for Ad-hoc, Mobile, and Wireless Networks: 13th International Conference, ADHOC-NOW 2014, Benidorm, Spain, June 22-27, 2014 Proceedings

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Mob. Comput. , pp. 519–523 (2010) 12. org/html/rfc3031 13. : Survey of multipath routing protocols for mobile ad hoc networks. J. Netw. Comput. Appl. 32, 1125–1143 (2009) 14. : On-demand multipath distance vector routing in ad hoc networks. In: Proceedings Ninth International Conference on Network Protocols, ICNP 2001, pp. 14–23. IEEE Comput. Soc. (2001) 15. org/html/rfc3561 16. : MP-DSR: a QoS-aware multi-path dynamic source routing protocol for wireless ad-hoc networks. In: Proceedings LCN 2001 26th Annual IEEE Conference on Local Computer Networks, pp.

HTR is based on the OLSR protocol and includes HELLO messages and Topology Control (TC) messages, as well as MPR for reduction of traffic flooding. However, HTR uses additional metrics such as link quality information and node device capabilities to choose MPR nodes. In addition to the features previously mentioned, HTR uses control messages to piggyback service propagation and policies that are based on human roles. The majority of routing approaches use only the hop count during routing path computation [4].

This anticipation allows the routing protocol to compensate the delay due to the computation and dissemination of the metrics. We considered ETX [5] (Expected Transmission Count) and ETT [6] (Expected Transmission Time), but we combine their computation to our prediction algorithm. Through a large set of simulations and scenarios, we have shown that our method improves significantly the PDR. When the network is a Mesh network, where the connectivity is ensured, a proper design of our algorithm leads to a PDR of 100%.

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