Performance Analysis of ZigBee Wireless Networks for AAL through Hybrid Ray Launching and Collaborative Filtering

This paper presents a novel hybrid simulation method based on the combination of an in-house developed 3D ray launching algorithm and a collaborative filtering (CF) technique, which will be used to analyze the performance of ZigBee-based wireless sensor networks (WSNs) to enable ambient assisted living (AAL). The combination of Low Definition results obtained by means of a deterministic ray launching method and the application of a CF technique leads to a drastic reduction of the time and computational cost required to obtain accurate simulation results. The paper also reports that this kind of AAL indoor complex scenario with multiple wireless devices needs a thorough and personalized radioplanning analysis as radiopropagation has a strong dependence on the network topology and the specific morphology of the scenario. The wireless channel analysis performed by our hybrid method provides valuable insight into network design phases of complex wireless systems, typical in AAL-oriented environments. Thus, it results in optimizing network deployment, reducing overall interference levels, and increasing the overall system performance in terms of cost reduction, transmission rates, and energy efficiency.

[1]  R. Luebbers.  A heuristic UTD slope diffraction coefficient for rough lossy wedges , 1989 .

[2]  Francisco Falcone,et al.  Convergence Analysis in Deterministic 3D Ray Launching Radio Channel Estimation in Complex Environments , 2014 .

[3]  Josep Domingo-Ferrer,et al.  Privacy Preserving Collaborative Filtering with k-Anonymity through Microaggregation , 2013, 2013 IEEE 10th International Conference on e-Business Engineering.

[4]  Francisco Falcone,et al.  Implementing context aware scenarios to enable smart health in complex urban environments , 2014, 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[5]  José Javier Astrain,et al.  Measurement and modeling of a UHF‐RFID system in a metallic closed vehicle , 2012 .

[6]  Francisco Falcone,et al.  Ubiquitous Connected Train Based on Train-to-Ground and Intra-Wagon Communications Capable of Providing on Trip Customized Digital Services for Passengers , 2014, Sensors.

[7]  Josep Domingo-Ferrer,et al.  A k-anonymous approach to privacy preserving collaborative filtering , 2015, J. Comput. Syst. Sci..

[8]  Erik Aguirre,et al.  Analysis and Description of HOLTIN Service Provision for AECG monitoring in Complex Indoor Environments , 2013, Sensors.

[9]  Francisco Falcone,et al.  A Ray Launching-Neural Network Approach for Radio Wave Propagation Analysis in Complex Indoor Environments , 2014, IEEE Transactions on Antennas and Propagation.

[10]  Francisco Falcone,et al.  Analysis of Topological Impact on Wireless Channel Performance on Intelligent Street Lighting System , 2014 .

[11]  Taghi M. Khoshgoftaar,et al.  A Survey of Collaborative Filtering Techniques , 2009, Adv. Artif. Intell..

[12]  Awais Ahmad,et al.  Data Transmission Scheme Using Mobile Sink in Static Wireless Sensor Network , 2015, J. Sensors.

[13]  Athanasios V. Vasilakos,et al.  Internet of Vehicles for E-Health Applications in View of EMI on Medical Sensors , 2015, J. Sensors.

[14]  Fran Casino,et al.  On Privacy Preserving Collaborative Filtering: Current Trends, Open Problems, and New Issues , 2013, 2013 IEEE 10th International Conference on e-Business Engineering.

[15]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[16]  Roberto Di Pietro,et al.  Smart health: A context-aware health paradigm within smart cities , 2014, IEEE Communications Magazine.

[17]  Rama Chellappa,et al.  An electronic infrastructure for a virtual university , 1997, CACM.

[18]  Francisco Falcone,et al.  IVAN: Intelligent Van for the Distribution of Pharmaceutical Drugs , 2012, Sensors.

[19]  Martha Larson,et al.  Collaborative Filtering beyond the User-Item Matrix , 2014, ACM Comput. Surv..

[20]  Francisco Falcone,et al.  Characterization and consideration of topological impact of wireless propagation in a commercial aircraft environment [wireless corner] , 2013, IEEE Antennas and Propagation Magazine.

[21]  Pietro Siciliano,et al.  Context-Aware AAL Services through a 3D Sensor-Based Platform , 2013, J. Sensors.

[22]  Erik Aguirre,et al.  Analysis of estimation of electromagnetic dosimetric values from non-ionizing radiofrequency fields in conventional road vehicle environments , 2015, Electromagnetic biology and medicine.

[23]  Raymond J. Luebbers.  Comparison of lossy wedge diffraction coefficients with application to mixed path propagation loss prediction , 1988 .

[24]  Francisco Falcone,et al.  Towards a Traceability System Based on RFID Technology to Check the Content of Pallets within Electronic Devices Supply Chain , 2013 .

[25]  Paolo Barsocchi,et al.  Middleware Infrastructure for Monitoring Bed Activity , 2013 .

[26]  Alberto Córdoba,et al.  Ontology Based Road Traffic Management , 2012, IDC.

[27]  F. Fuschini,et al.  Speed-Up Techniques for Ray Tracing Field Prediction Models , 2009, IEEE Transactions on Antennas and Propagation.

[28]  Davinder S. Saini,et al.  Lifetime Optimization of a Multiple Sink Wireless Sensor Network through Energy Balancing , 2015, J. Sensors.

[29]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[30]  Augusto Neto,et al.  Autonomic Context-Aware Wireless Sensor Networks , 2015, J. Sensors.