C2EM: cloud-assisted complex event monitoring in wireless multimedia sensor networks

This paper addresses the problem of how to provide a more flexible service for complex event monitoring in wireless multimedia sensor networks (WMSNs). In particular, we propose C2EM, a cloud-assisted complex event monitoring architecture that involves scalar sensors, camera sensors, cloudlets, and clouds to leverage computation offloading reliability, service response time, coverage efficiency, and energy efficiency. On clouds, we design an opportunistic service access point selection scheme that provides quality of service (QoS) supports for scalar sensor computation offloading. Meanwhile, clouds are responsible for optimizing camera sensor utilization of the whole network. On cloudlets, we design a real-time camera actuation scheme with the objective of minimizing the possible coverage overlaps while providing probabilistic guarantee in residual energy. Through computation division, most complex computations and network environment profilers are executed on cloudlets or clouds. Sensors only need to carry out very simple operations. We evaluate the performance of C2EM through simulations under a complex event scenario. The results demonstrate that C2EM can enhance complex event monitoring performance with optimized energy efficiency, desirable event coverage quality, and potential adaptability to the dynamics of complex events.

[1]  Khaled A. Harras,et al.  Making the case for computational offloading in mobile device clouds , 2013, MobiCom.

[2]  Lu Zhao,et al.  QMOR: QoS-Aware Multi-sink Opportunistic Routing for Wireless Multimedia Sensor Networks , 2014, Wirel. Pers. Commun..

[3]  Xin Chen,et al.  Energy-Efficient Link Selection and Transmission Scheduling in Mobile Cloud Computing , 2014, IEEE Wireless Communications Letters.

[4]  Wenjing Lou,et al.  WSN09-3: Fault-tolerant Event Boundary Detection in Wireless Sensor Networks , 2006, IEEE Globecom 2006.

[5]  Mahadev Satyanarayanan,et al.  Scalable crowd-sourcing of video from mobile devices , 2013, MobiSys '13.

[6]  Deepa Kundur,et al.  Reliable Event-Detection in Wireless Visual Sensor Networks Through Scalar Collaboration and Game-Theoretic Consideration , 2008, IEEE Transactions on Multimedia.

[7]  Shiwen Mao,et al.  A survey of mobile cloud computing for rich media applications , 2013, IEEE Wireless Communications.

[8]  Nael B. Abu-Ghazaleh,et al.  Coverage algorithms for visual sensor networks , 2013, TOSN.

[9]  J. Wenny Rahayu,et al.  Mobile cloud computing: A survey , 2013, Future Gener. Comput. Syst..

[10]  M. Shamim Hossain,et al.  A Survey on Sensor-Cloud: Architecture, Applications, and Approaches , 2013, Int. J. Distributed Sens. Networks.

[11]  Chang Wen Chen,et al.  Joint Coding/Routing Optimization for Distributed Video Sources in Wireless Visual Sensor Networks , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[12]  Dongman Lee,et al.  A virtual cloud computing provider for mobile devices , 2010, MCS '10.

[13]  Andrea Vitaletti,et al.  Smart City: An Event Driven Architecture for Monitoring Public Spaces with Heterogeneous Sensors , 2010, 2010 Fourth International Conference on Sensor Technologies and Applications.

[14]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[15]  Alec Wolman,et al.  MAUI: making smartphones last longer with code offload , 2010, MobiSys '10.

[16]  Mac Schwager,et al.  Eyes in the Sky: Decentralized Control for the Deployment of Robotic Camera Networks , 2011, Proceedings of the IEEE.

[17]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[18]  Kemal Akkaya,et al.  Distributed collaborative camera actuation for redundant data elimination in wireless multimedia sensor networks , 2011, Ad Hoc Networks.

[19]  Byung-Gon Chun,et al.  CloneCloud: elastic execution between mobile device and cloud , 2011, EuroSys '11.

[20]  Valentina Casola,et al.  An SLA-Based Approach to Manage Sensor Networks as-a-Service , 2013, 2013 IEEE 5th International Conference on Cloud Computing Technology and Science.

[21]  Rajeev Piyare,et al.  Integrating Wireless Sensor Network into Cloud services for real-time data collection , 2013, 2013 International Conference on ICT Convergence (ICTC).

[22]  Kishor S. Trivedi,et al.  Combining Cloud and sensors in a smart city environment , 2012, EURASIP J. Wirel. Commun. Netw..

[23]  Rajkumar Buyya,et al.  A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing , 2013, IEEE Communications Surveys & Tutorials.

[24]  Bang Wang,et al.  Coverage problems in sensor networks: A survey , 2011, CSUR.

[25]  Nalini Venkatasubramanian,et al.  Privacy-preserving event detection in pervasive spaces , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[26]  Kai Bu,et al.  ENDA: embracing network inconsistency for dynamic application offloading in mobile cloud computing , 2013, MCC '13.

[27]  Xiuzhen Cheng,et al.  Localized fault-tolerant event boundary detection in sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[28]  Karim Habak,et al.  COSMOS: computation offloading as a service for mobile devices , 2014, MobiHoc '14.

[29]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[30]  Mohan S. Kankanhalli,et al.  Design of multimedia surveillance systems , 2009, TOMCCAP.

[31]  Bo Li,et al.  The Intrusion Detection in Mobile Sensor Network , 2012, IEEE/ACM Transactions on Networking.

[32]  Jukka K. Nurminen,et al.  CloudTorrent - Energy-Efficient BitTorrent Content Sharing for Mobile Devices via Cloud Services , 2010, 2010 7th IEEE Consumer Communications and Networking Conference.

[33]  Tao Li,et al.  A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[34]  Ling Guan,et al.  Distributed Algorithms for Network Lifetime Maximization in Wireless Visual Sensor Networks , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[35]  Xiaofei Wang,et al.  AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds , 2013, IEEE Transactions on Multimedia.

[36]  Martin Reisslein,et al.  Network performance evaluation using frame size and quality traces of single-layer and two-layer video: A tutorial , 2004, IEEE Communications Surveys & Tutorials.