Effective collaborative monitoring in smart cities: Converging MANET and WSN for fast data collection

Ubiquitous smart environments, equipped with low-cost and easy-deployable Wireless Sensor Networks (WSNs) and with widespread Mobile Ad-hoc NETworks (MANETs), are opening brand new opportunities in urban monitoring. Urban data collection, i.e., the harvesting of monitoring data sensed by a large number of collaborating sensors in a wide-scale city, is still a challenging task due to typical WSN limitations (limited bandwidth and energy, long delivery time, …). In particular, effective data collection is crucial for classes of services that require a timely delivery of urgent data, such as environmental monitoring, homeland security, and city surveillance. This paper proposes an original solution to integrate and to opportunistically exploit MANET overlays that are impromptu and collaboratively formed over WSNs in order to boost data collection: overlays are used to dynamically differentiate and fasten the delivery of urgent sensed data over low-latency MANET paths. The reported experimental results show the feasibility and effectiveness (e.g., limited coordination overhead) of our solution for MANET overlays over WSNs. In addition, our proposal can easily integrate with the latest emergent WSN data collection standards/specifications, thus allowing immediate deployability over existing smart city environments.

[1]  Siarhei Kuryla,et al.  RPL: IPv6 Routing Protocol for Low power and Lossy Networks , 2010 .

[2]  P. Kumar,et al.  Capacity of Ad Hoc Wireless Networks , 2002 .

[3]  Deborah Estrin,et al.  Hyper: A Routing Protocol To Support Mobile Users of Sensor Networks , 2006 .

[4]  Martin T. Pietrucha,et al.  FIELD STUDIES OF PEDESTRIAN WALKING SPEED AND START-UP TIME , 1996 .

[5]  Prasun Sinha,et al.  CMAC: An Energy Efficient MAC Layer Protocol Using Convergent Packet Forwarding for Wireless Sensor Networks , 2007, 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[6]  Daiyuan Peng,et al.  The Study of Mutual Authentication and Key Exchange Protocols for Low Power Wireless Communications , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).

[7]  Chen Zhang,et al.  ExScal: elements of an extreme scale wireless sensor network , 2005, 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'05).

[8]  Tsvetko Tsvetkov RPL: IPv6 Routing Protocol for LOW Power and Lossy Networks , 2011 .

[9]  Paolo Bellavista,et al.  A survey of context data distribution for mobile ubiquitous systems , 2012, CSUR.

[10]  Antonio Corradi,et al.  Cross-Network Opportunistic Collection of Urgent Data in Wireless Sensor Networks , 2011, Comput. J..

[11]  Myung J. Lee,et al.  A Comprehensive Performance Study of IEEE 802 . 15 . 4 , 2004 .

[12]  Gregory S. Yovanof,et al.  An Architectural Framework and Enabling Wireless Technologies for Digital Cities & Intelligent Urban Environments , 2009, Wirel. Pers. Commun..

[13]  David E. Culler,et al.  Procrastination Might Lead to a Longer and More Useful Life , 2007, HotNets.

[14]  Ashutosh Sabharwal,et al.  Using Predictable Observer Mobility for Power Efficient Design of Sensor Networks , 2003, IPSN.

[15]  J. Redi,et al.  A brief overview of ad hoc networks: challenges and directions , 2002, IEEE Communications Magazine.

[16]  Pern Hui Chia Analyzing the incentives in Community-based Security Systems , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[17]  Edgar H. Callaway,et al.  Home networking with IEEE 802.15.4: a developing standard for low-rate wireless personal area networks , 2002, IEEE Commun. Mag..

[18]  Qin Wang,et al.  A Realistic Power Consumption Model for Wireless Sensor Network Devices , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[19]  Wei Wang,et al.  Using mobile relays to prolong the lifetime of wireless sensor networks , 2005, MobiCom '05.

[20]  Suresh Singh,et al.  Exploiting heterogeneity in sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[21]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[22]  Jian Ma,et al.  Mobile Wireless Sensor Network: Architecture and Enabling Technologies for Ubiquitous Computing , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[23]  Paolo Bellavista,et al.  The Future Internet convergence of IMS and ubiquitous smart environments: An IMS-based solution for energy efficiency , 2012, J. Netw. Comput. Appl..

[24]  Jian Ma,et al.  mWSN for Large Scale Mobile Sensing , 2008, J. Signal Process. Syst..

[25]  Philip Levis,et al.  Collection tree protocol , 2009, SenSys '09.

[26]  Sang Ho Lee,et al.  Towards ubiquitous city: concept, planning, and experiences in the Republic of Korea , 2008 .

[27]  Jon Crowcroft,et al.  Siphon: overload traffic management using multi-radio virtual sinks in sensor networks , 2005, SenSys '05.

[28]  Pei Zhang,et al.  The PSI Board: Realizing a Phone-Centric Body Sensor Network , 2007, BSN.