Connectivity-optimal Shortest Paths Using Crowdsourced Data

Hultman, TimLinköpings universitet,Programvara och system,Tekniska fakulteten (författare)

With the increasing dependency of ubiquitous connectivity for applications ranging from multimedia entertainment to intelligent transportation systems, having good signal coverage becomes vital. Therefore, route planners and navigation systems should take into account not only the physical distance, but also the characteristics and availability of the cellular network on the potential routes. In this paper we present a route planning tool that finds the connectivity-aware shortest paths based on crowdsourced data from OpenStreetMap and OpenSignal. The tool calculates optimal paths and allows physical distance tobe traded against signal quality. The evaluation shows that a 15% increase of the physical path length can achieve an 8.7dBm improvement of worst-case signal strength.

Boudjadar, AbdeldjalilLinköpings universitet,Programvara och system,Tekniska fakulteten,Real-time Systems Laboratory(Swepub:liu)abdbo42 (författare)
Asplund, Mikael,1981-Linköpings universitet,Programvara och system,Tekniska fakulteten,Real-time Systems Laboratory(Swepub:liu)mikas34 (författare)
Linköpings universitetProgramvara och system (creator_code:org_t)

Ingår i:2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops): IEEE Computer Society, s. 1-69781509019410

Av författaren/redakt...: Hultman, Tim; Boudjadar, Abdel ...; Asplund, Mikael, ...

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