Topic
Geographic routing
About: Geographic routing is a research topic. Over the lifetime, 11687 publications have been published within this topic receiving 302224 citations.
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01 Jan 2007
TL;DR: This work explores grid-based coordinated routing in wireless sensor networks and compares the energy available in the network over time for different grid sizes.
Abstract: Wireless sensor networks are battery-powered ad-hoc networks in which sensor nodes that are scattered over a region connect to each other and form multi-hop networks. These nodes are equipped with sensors such as temperature sensors, pressure sensors, and light sensors and can be queried to get the corresponding values for analysis. However, since they are battery operated, care has to be taken so that these nodes use energy efficiently. One of the areas in sensor networks where an energy analysis can be done is routing. This work explores grid-based coordinated routing in wireless sensor networks and compares the energy available in the network over time for different grid sizes.
66 citations
19 May 2008
TL;DR: The design goal is achieved by effectively integrating the above two strategies such that decision on each packet forwarding is made with the awareness of potential coding opportunities.
Abstract: Opportunistic routing and network coding have been considered as effective strategies for improving the throughput of wireless mesh networks (WMN) However, most existing work studied opportunistic routing and network coding separately This has largely limited the ability of the above strategies from effectively improving the network performance To achieve improved network throughput, in this paper, we propose a coding-aware opportunistic routing mechanism for WMNs The design goal is achieved by effectively integrating the above two strategies such that decision on each packet forwarding is made with the awareness of potential coding opportunities Simulation results show that our proposed mechanism can remarkably improve the network throughput
66 citations
TL;DR: A novel protocol that uses Q-learning-based geographic routing (QGeo) to improve the network performance of unmanned robotic networks and finds that QGeo has a higher packet delivery ratio and a lower network overhead than existing methods.
Abstract: This letter proposes a novel protocol that uses Q-learning-based geographic routing (QGeo) to improve the network performance of unmanned robotic networks. A rapid and reliable network is essential for the remote control and monitoring of mobile robotic devices. However, controlling the network overhead required for route selection and repair is still a notable challenge, owing to high mobility of the devices. To alleviate this problem, we propose a machine-learning-based geographic routing scheme to reduce network overhead in high-mobility scenarios. We evaluate the performance of QGeo in comparison with other methods using the NS-3 simulator. We find that QGeo has a higher packet delivery ratio and a lower network overhead than existing methods.
66 citations
TL;DR: The proposed routing algorithm, MaxEW, adopts the social welfare function from social sciences to compute energy welfare as a goodness measure for energy populations and supports preparedness and hence robustness to diverse event generation patterns.
66 citations
TL;DR: The proposed scheme associates the backward difference traffic moments with the Sleep-time duration to tune the activity durations of a node for achieving optimal energy conservation and alleviating the uncontrolled energy consumption of wireless devices.
65 citations