Neighbour discovery in opportunistic networks

Continuous or frequent scanning for opportunistic encounters would quickly drain the battery on existing personal mobile wireless devices. Furthermore, there is a great deal of uncertainty about when encounters between devices carried by humans will take place.This paper will discuss some of the drawbacks of using current short range neighbour discovery technology in opportunistic networks. Finally, we proposes a new neighbour discovery algorithm called PISTONSv2 which enables mobile devices to dynamically alter the rate at which they search for others, thus creating a fully decentralised and autonomous network whilst saving energy.

[1]  Cecilia Mascolo,et al.  NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems , 2011, Pervasive.

[2]  Nick Filer,et al.  The rise and fall of spatio-temporal clusters in mobile ad hoc networks , 2013, Ad Hoc Networks.

[3]  Donald F. Towsley,et al.  Performance modeling of epidemic routing , 2006, Comput. Networks.

[4]  Theus Hossmann,et al.  Twitter in disaster mode: opportunistic communication and distribution of sensor data in emergencies , 2011 .

[5]  Luciano Bononi,et al.  By train or by car? Detecting the user's motion type through smartphone sensors data , 2012, 2012 IFIP Wireless Days.

[6]  Jörg Ott,et al.  Simulating Mobility and DTNs with the ONE (Invited Paper) , 2010, J. Commun..

[7]  Jörg Ott,et al.  The ONE simulator for DTN protocol evaluation , 2009, SIMUTools 2009.

[8]  George Varghese,et al.  Experiments in Mobile Social Networking , 2008 .

[9]  Karthik Lakshmanan,et al.  U-connect: a low-latency energy-efficient asynchronous neighbor discovery protocol , 2010, IPSN '10.

[10]  Anders Lindgren,et al.  The evolution of a DTN routing protocol - PRoPHETv2 , 2011, CHANTS '11.

[11]  Jesus Alonso-Zarate,et al.  Analysis of energy efficient distributed neighbour discovery mechanisms for Machine-to-Machine Networks , 2014, Ad Hoc Networks.

[12]  Antonio Lima,et al.  Interdependence and predictability of human mobility and social interactions , 2012, Pervasive Mob. Comput..

[13]  Jörg Ott,et al.  Working day movement model , 2008, MobilityModels '08.

[14]  Nicholas R. Jennings,et al.  Breaking the habit: Measuring and predicting departures from routine in individual human mobility , 2013, Pervasive Mob. Comput..

[15]  Shivakant Mishra,et al.  CenWits: a sensor-based loosely coupled search and rescue system using witnesses , 2005, SenSys '05.

[16]  Jongmin Shin,et al.  Asynchronous probing scheme for the optimal energy-efficient neighbor discovery in opportunistic networking , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[17]  Vikram Srinivasan,et al.  PeopleNet: engineering a wireless virtual social network , 2005, MobiCom '05.

[18]  Arman Zare,et al.  Using Limited Flooding in On-Demand Distance Vector Junior for Reduction Power Consumption in ZigBee Networks , 2012, IAIT 2012.

[19]  Bhaskar Krishnamachari,et al.  Findings from an empirical study of fine-grained human social contacts , 2009, 2009 Sixth International Conference on Wireless On-Demand Network Systems and Services.

[20]  Margaret Martonosi,et al.  Implementing software on resource-constrained mobile sensors: experiences with Impala and ZebraNet , 2004, MobiSys '04.

[21]  Aravind Srinivasan,et al.  Mobile Data Offloading through Opportunistic Communications and Social Participation , 2012, IEEE Transactions on Mobile Computing.

[22]  Wei Wang,et al.  Opportunistic Energy-Efficient Contact Probing in Delay-Tolerant Applications , 2009, IEEE/ACM Transactions on Networking.

[23]  Xuemin Shen,et al.  Adaptive Asynchronous Sleep Scheduling Protocols for Delay Tolerant Networks , 2011, IEEE Transactions on Mobile Computing.

[24]  Nick Filer,et al.  Movement Speed Based Inter-probe Times for Neighbour Discovery in Mobile Ad-Hoc Networks , 2012, ADHOCNETS.

[25]  Jörg Widmer,et al.  Survey on Energy Consumption Entities on the Smartphone Platform , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[26]  Scott Burleigh,et al.  Defining Tolerance: Impacts of Delay and Disruption when Managing Challenged Networks , 2011 .

[27]  Tristan Henderson,et al.  The changing usage of a mature campus-wide wireless network , 2008, Comput. Networks.

[28]  Arnaud Troël.  Prise en compte de la mobilité dans les interactions de proximité entre terminaux à profils hétérogènes , 2004 .

[29]  H. Izumikawa,et al.  Energy-efficient adaptive interface activation for Delay/Disruption Tolerant Networks , 2010, 2010 The 12th International Conference on Advanced Communication Technology (ICACT).

[30]  Pan Hui,et al.  Pocket Switched Networks: Real-world mobility and its consequences for opportunistic forwarding , 2005 .

[31]  Ness B. Shroff,et al.  Delay and Capacity Trade-Offs in Mobile Ad Hoc Networks: A Global Perspective , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[32]  Nam P. Nguyen,et al.  Overlapping communities in dynamic networks: their detection and mobile applications , 2011, MobiCom.