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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.

Angiosperms, http://name.umdl.umich.edu/IC-HERB00IC-X-1660808%5DMICH-V-1660808, https://quod.lib.umich.edu/cgi/i/image/api/thumb/herb00ic/1660808/MICH-V-1660808/!250,250, The University of Michigan Library provides access to these materials for educational and research purposes. Some materials may be protected by copyright. If you decide to use any of these materials, you are responsible for making your own legal assessment and securing any necessary permission. If you have questions about the collection, please contact the Herbarium professional staff: herb-dlps-help@umich.edu. If you have concerns about the inclusion of an item in this collection, please contact Library Information Technology: libraryit-info@umich.edu., https://www.lib.umich.edu/about-us/policies/copyright-policy

© Springer International Publishing Switzerland 2014. Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.

Angiosperms, http://name.umdl.umich.edu/IC-HERB00IC-X-1532045%5DMICH-V-1532045, https://quod.lib.umich.edu/cgi/i/image/api/thumb/herb00ic/1532045/MICH-V-1532045/!250,250, The University of Michigan Library provides access to these materials for educational and research purposes. Some materials may be protected by copyright. If you decide to use any of these materials, you are responsible for making your own legal assessment and securing any necessary permission. If you have questions about the collection, please contact the Herbarium professional staff: herb-dlps-help@umich.edu. If you have concerns about the inclusion of an item in this collection, please contact Library Information Technology: libraryit-info@umich.edu., https://www.lib.umich.edu/about-us/policies/copyright-policy

Angiosperms, http://name.umdl.umich.edu/IC-HERB00IC-X-1533688%5DMICH-V-1533688, https://quod.lib.umich.edu/cgi/i/image/api/thumb/herb00ic/1533688/MICH-V-1533688/!250,250, The University of Michigan Library provides access to these materials for educational and research purposes. Some materials may be protected by copyright. If you decide to use any of these materials, you are responsible for making your own legal assessment and securing any necessary permission. If you have questions about the collection, please contact the Herbarium professional staff: herb-dlps-help@umich.edu. If you have concerns about the inclusion of an item in this collection, please contact Library Information Technology: libraryit-info@umich.edu., https://www.lib.umich.edu/about-us/policies/copyright-policy

Angiosperms, http://name.umdl.umich.edu/IC-HERB00IC-X-1531867%5DMICH-V-1531867, https://quod.lib.umich.edu/cgi/i/image/api/thumb/herb00ic/1531867/MICH-V-1531867/!250,250, The University of Michigan Library provides access to these materials for educational and research purposes. Some materials may be protected by copyright. If you decide to use any of these materials, you are responsible for making your own legal assessment and securing any necessary permission. If you have questions about the collection, please contact the Herbarium professional staff: herb-dlps-help@umich.edu. If you have concerns about the inclusion of an item in this collection, please contact Library Information Technology: libraryit-info@umich.edu., https://www.lib.umich.edu/about-us/policies/copyright-policy

Angiosperms, http://name.umdl.umich.edu/IC-HERB00IC-X-1547542%5DMICH-V-1547542, https://quod.lib.umich.edu/cgi/i/image/api/thumb/herb00ic/1547542/MICH-V-1547542/!250,250, The University of Michigan Library provides access to these materials for educational and research purposes. Some materials may be protected by copyright. If you decide to use any of these materials, you are responsible for making your own legal assessment and securing any necessary permission. If you have questions about the collection, please contact the Herbarium professional staff: herb-dlps-help@umich.edu. If you have concerns about the inclusion of an item in this collection, please contact Library Information Technology: libraryit-info@umich.edu., https://www.lib.umich.edu/about-us/policies/copyright-policy