Multiple Mobile Sinks in Event-based Wireless Sensor Networks Exploiting Traffic Conditions in Smart City Applications

Modern cities are subject to a lot of periodic or unexpected critical events, which may have different monitoring and control requirements according to the expected impacts on people safety and urban mobility. When multiple monitoring and automation systems are deployed, adaptive wireless sensor networks may adjust sensing and transmission configurations according to the detected events, optimizing the network overall operation. In this context, mobile sinks come as an effective way to enhance monitoring performance in smart city environments. However, practical issues related to the available roads and traffic load should be considered, allowing the computation of the best final positions and movement paths for each sink. Therefore, this paper proposes algorithms to compute dynamic sinks movement in reactive wireless sensor networks, supporting efficient adaptation to event-based monitoring in smart cities.

[1]  Nadeem Javaid,et al.  Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks , 2017, Sensors.

[2]  Wen-Tsuen Chen,et al.  Design and Implementation of a Real Time Video Surveillance System with Wireless Sensor Networks , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[3]  João B. Rocha-Junior,et al.  TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications , 2018, Sensors.

[4]  Luiz Affonso Guedes,et al.  Selecting redundant nodes when addressing availability in wireless visual sensor networks , 2014, 2014 12th IEEE International Conference on Industrial Informatics (INDIN).

[5]  Luiz Affonso Guedes,et al.  Adaptive Monitoring Relevance in Camera Networks for Critical Surveillance Applications , 2013, Int. J. Distributed Sens. Networks.

[6]  Luiz Affonso Guedes,et al.  Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization , 2015, Sensors.

[7]  C. P. Kruger,et al.  Wireless sensor network for building evacuation , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[8]  Daniel G. Costa,et al.  Wireless visual sensor networks for smart city applications: A relevance-based approach for multiple sinks mobility , 2017, Future Gener. Comput. Syst..

[9]  Moumena Chaqfeh,et al.  An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities , 2016, Sensors.

[10]  Metin Koç,et al.  Controlled Sink Mobility Algorithms for Wireless Sensor Networks , 2014, Int. J. Distributed Sens. Networks.

[11]  Giovanni Pau,et al.  A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications , 2017, Sensors.

[12]  M. Angelidou Smart cities: A conjuncture of four forces , 2015 .

[13]  Luiz Affonso Guedes,et al.  A routing mechanism based on the sensing relevancies of source nodes for time-critical applications in visual sensor networks , 2012, 2012 IFIP Wireless Days.

[14]  Mohsen Guizani,et al.  Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges , 2016, IEEE Wireless Communications.

[15]  Luiz Affonso Guedes,et al.  Exploiting the sensing relevancies of source nodes for optimizations in visual sensor networks , 2011, Multimedia Tools and Applications.

[16]  Daniel G. Costa,et al.  QoE-aware multiple sinks mobility in wireless sensor networks , 2015, 2015 7th International Conference on New Technologies, Mobility and Security (NTMS).

[17]  Wilfried N. Gansterer,et al.  Static vs. mobile sink: The influence of basic parameters on energy efficiency in wireless sensor networks , 2013, Comput. Commun..

[18]  Tai-Hoon Kim,et al.  Smart City and IoT , 2017, Future Gener. Comput. Syst..

[19]  Jean-Marie Bonnin,et al.  Wireless sensor networks: a survey on recent developments and potential synergies , 2013, The Journal of Supercomputing.