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3C Tecnología. Glosas de innovación aplicadas a la pyme.

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The unmanned aerial vehicle communication networks (UAVCN) is an emerging technology of wireless communication. By making use of this technology, the swarm of unmanned aerial vehicles (UAVs) forms a network in which the UAVs can communicate with each other and trigger the information for a particular operation of military and civilian applications. The UAV nodes frequently face design issues and power limitations , which affect the routing mechanism. It is a unique challenge for the researchers to introduce the efficient power and routing mechanism that can improve the performance of UAVs' communication networks. However, the concept of cross layer design and efficient power algorithm proposed in this paper increases the performance of UAVCN. The proposed approach integrates the layers 1,2,3 (physical, link, and network). By implementing this kind of approach, an efficient power optimized link state routing (EPOLSR) protocol introduced in this research modifies the conventional OLSR. The EPOLSR and OLSR are implemented and assessed in the first experiment scenario of UAVs communication networks by using an optimized network engineering tool. Moreover, the EPOLSR, OLSR, AODV, and DSR are implemented and assessed in the second experiment scenario. In these testbed experiments, it has been observed that EPOLSR performs better than other routing protocols for UAVs communication networks by increasing the throughput and minimizing the delay.

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The Unmanned aerial vehicle communication network (UAVCN) is a group or swarm of unmanned aerial vehicles which can be used for specific military and civilian applications without human intercession. This network faces the design problem which is based on network mobility. The frequent topology changes affect communication and collaboration among the UAVs (Unmanned aerial vehicles). To govern the movement pattern of UAVCN different mobility models needed to be studied in order to solve this communication issue. In this paper, mobility models are explored which provides the particular mobility pattern to resolve the problem of collaboration, communication and cooperation of UAVs. These models have been categorized into five groups and classified each group in detail. These mobility models provide the platform to understand and implement the unmanned aerial communication network for specific environment scenarios. The mobisim simulator tool is used to generate the mobility model s trajectories for different mobility models.

Mobility causes frequent link failures in ad-hoc networks. This results in a severe degradation of performance specially in case of high mobility of nodes. This is because the routing protocols for ad-hoc networks are not equipped to handle high mobility. In this paper, we have presented a new link management algorithm to locally manage links. This new mechanism is based on signal strength measurements. Researchers over the years have presented approaches which use signal strength measurements but their focus has been on re-active protocols while our algorithm is aimed at pro-active protocols. Pro-active protocols are used since they provide greater flexibility to take advantage of the mesh configuration. We develop the hysteresis mechanism provided by OLSR, based on hello packets, to include signal strength measurements. The mechanism in OLSR uses Hello packets received/lost to decide to establish link or not. The problem with this approach arises when there is high mobility in which case the time to break the link and use a new path becomes significant. To overcome this, we propose to use signal strength to determine if the link-quality This work is supported by the French government funded project ANR RNRT R2M (Reseaux Mesh et Mobilite-Mesh networks and mobility).

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