Networking smartphones for disaster recovery

In this paper, we investigate how to network smart-phones for providing communications in disaster recovery. By bridging the gaps among different kinds of wireless networks, we have designed and implemented a system called TeamPhone, which provides smartphones the capabilities of communications in disaster recovery. Specifically, TeamPhone consists of two components: a messaging system and a self-rescue system. The messaging system integrates cellular networking, ad-hoc networking and opportunistic networking seamlessly, and enables communications among rescue workers. The self-rescue system energy-efficiently groups the smartphones of trapped survivor and sends out emergency messages so as to assist rescue operations. We have implemented TeamPhone as a prototype application on the Android platform and deployed it on off-the-shelf smartphones. Experiment results show that TeamPhone can properly fulfill communication requirements and greatly facilitate rescue operations in disaster recovery.

[1]  Matthias Frank,et al.  Human mobility in MANET disaster area simulation - a realistic approach , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[2]  Ramesh Govindan,et al.  Medusa: a programming framework for crowd-sensing applications , 2012, MobiSys '12.

[3]  Jon Crowcroft,et al.  Evaluating opportunistic networks in disaster scenarios , 2013, J. Netw. Comput. Appl..

[4]  Suguru Yamaguchi,et al.  SOSCast: Location Estimation of Immobilized Persons through SOS Message Propagation , 2012, 2012 Fourth International Conference on Intelligent Networking and Collaborative Systems.

[5]  Alexandre M. Bayen,et al.  iShake: mobile phones as seismic sensors -- user study findings , 2011, MUM.

[6]  Akihiro Fujihara,et al.  Disaster Evacuation Guidance Using Opportunistic Communication: The Potential for Opportunity-Based Service , 2014, Big Data and Internet of Things.

[7]  Yonggang Wen,et al.  Skeleton construction in mobile social networks: Algorithms and applications , 2014, 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).

[8]  Yonggang Wen,et al.  Algorithms and Applications for Community Detection in Weighted Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[9]  Yi Wang,et al.  SmartPhoto: A Resource-Aware Crowdsourcing Approach for Image Sensing with Smartphones , 2014, IEEE Transactions on Mobile Computing.

[10]  Nei Kato,et al.  Relay-by-smartphone: realizing multihop device-to-device communications , 2014, IEEE Communications Magazine.

[11]  Daniel Gutiérrez-Reina,et al.  A Survey on Ad Hoc Networks for Disaster Scenarios , 2014, 2014 International Conference on Intelligent Networking and Collaborative Systems.

[12]  Simin Nadjm-Tehrani,et al.  A Partition-Tolerant Manycast Algorithm for Disaster Area Networks , 2009, 2009 28th IEEE International Symposium on Reliable Distributed Systems.

[13]  Gil Zussman,et al.  Energy efficient routing in ad hoc disaster recovery networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[14]  Daniel Gutiérrez-Reina,et al.  Evaluation of Ad Hoc Networks in Disaster Scenarios , 2011, 2011 Third International Conference on Intelligent Networking and Collaborative Systems.

[15]  Xiaolin Li,et al.  Guoguo: enabling fine-grained indoor localization via smartphone , 2013, MobiSys '13.

[16]  Jie Yang,et al.  E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures , 2014, MobiCom.

[17]  Ellen W. Zegura,et al.  Serendipity: enabling remote computing among intermittently connected mobile devices , 2012, MobiHoc '12.

[18]  Alexander Boden,et al.  Help beacons: design and evaluation of an ad-hoc lightweight s.o.s. system for smartphones , 2014, CHI.