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Information Flow in Opportunistic Wireless Networks

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New study on high-performance opportunistic networks

Mobile devices are gradually becoming the first go-to device for information and content consumption, and this huge number of interactions amongst people could be the key to establishment of opportunistic networks. High throughput and capacity as well as low energy consumption will render such networks one of the most promising technologies for next-generation mobile applications.

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The widespread availability of mobile devices with ubiquitous connectivity is revolutionising the computing landscape, creating a new world of pervasive services. But, the increasing growth of mobile traffic puts a burden on the network capacity as the available spectrum resources are limited. To overcome this challenge, further research is needed on the fundamental properties of complex wireless systems. Owing to high mobility and changing topology, opportunistic networks exploit all available networking resources, allowing mobile devices to exchange a small amount of information during brief contact opportunities. The EU-funded project INFLOW (Information flow in opportunistic wireless networks) was devoted to studying opportunistic mobile networks for offloading mobile data and relevant network coding schemes for maximising total network channel capacity. Based on a stochastic geometric model, scientists explored the fundamental limitations on the maximum throughput and derived cut-set bounds on the theoretical capacity of wireless networks. The time variations in wireless channels are a fundamental property of wireless networks. Scientists thoroughly investigated the information propagation speed in multi-lane vehicle-to-vehicle networks such as roads or highways, focusing on the impact of time-varying range of radio waves, which had not been hitherto studied in this context. Further, the team identified the threshold on vehicle density under which information propagates at the speed of the fastest vehicle and above which information propagates dramatically faster. Drawing from statistical physics methods, scientists derived new message passing algorithms for optimal utilisation of cognitive radio networks as well as for scheduling multicast traffic in input-queued switches. Detailed understanding of the power consumption of wireless devices enables the development of energy-efficient protocols and algorithms. The team used the innovative NITOS energy consumption monitoring framework to assess energy performance of realistic systems, focusing on the trade-off between throughput and energy. As technology of mobile devices such as smartphones is continuously advancing, many applications of opportunistic networks will arise. Advanced protocols and algorithms for increasing the data flow and reducing energy consumption will boost the performance of such networks.


Opportunistic networks, mobile devices, network capacity, INFLOW, wireless networks

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