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Displaying 1-6 out of 6 total
Energy Efficient and Scalable Search in Dense Wireless Sensor Networks
Found in: IEEE Transactions on Computers
By Kiran K. Rachuri, C. Siva Ram Murthy
Issue Date:June 2009
pp. 812-826
In this paper, we consider the problem of information discovery in a densely deployed Wireless Sensor Network (WSN), where the initiator of search is unaware of the location of target information. We propose two protocols: Increasing Ray Search (IRS), an e...
 
Smartphones for Large-Scale Behavior Change Interventions
Found in: IEEE Pervasive Computing
By Neal Lathia,Veljko Pejovic,Kiran K. Rachuri,Cecilia Mascolo,Mirco Musolesi,Peter J. Rentfrow
Issue Date:July 2013
pp. 66-73
Equipped with cutting-edge sensing technology and high-end processors, smartphones can unobtrusively sense human behavior and deliver feedback and behavioral therapy. The authors discuss two applications for behavioral monitoring and change and present UBh...
 
Energy Efficient Search in Sensor Networks Using Simple Random Walks with Level Biased Steps
Found in: Distributed Computing Systems Workshops, International Conference on
By Kiran K. Rachuri, C. Siva Ram Murthy
Issue Date:June 2009
pp. 178-185
Random walk is one of the widely used techniques for information discovery in unstructured networks like Ad hoc Wireless Networks (AWNs) and Wireless Sensor Networks (WSNs). In a Random walk, instead of taking all steps uniform randomly, our idea is to mod...
 
METIS: Exploring mobile phone sensing offloading for efficiently supporting social sensing applications
Found in: 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom)
By Kiran K. Rachuri,Christos Efstratiou,Ilias Leontiadis,Cecilia Mascolo,Peter J. Rentfrow
Issue Date:March 2013
pp. 85-93
Mobile phones play a pivotal role in supporting ubiquitous and unobtrusive sensing of human activities. However, maintaining a highly accurate record of a user's behavior throughout the day imposes significant energy demands on the phone's battery. In this...
   
Contextual dissonance: design bias in sensor-based experience sampling methods
Found in: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (UbiComp '13)
By Cecilia Mascolo, Kiran K. Rachuri, Neal Lathia, Peter J. Rentfrow
Issue Date:September 2013
pp. 183-192
The Experience Sampling Method (ESM) has been widely used to collect longitudinal survey data from participants; in this domain, smartphone sensors are now used to augment the context-awareness of sampling strategies. In this paper, we study the effect of ...
     
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research
Found in: Proceedings of the 12th ACM international conference on Ubiquitous computing (Ubicomp '10)
By Andrius Aucinas, Cecilia Mascolo, Chris Longworth, Kiran K. Rachuri, Mirco Musolesi, Peter J. Rentfrow
Issue Date:September 2010
pp. 281-290
Today's mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. Phones are also part of the everyday life of billions of people, and therefore represent an exceptionally suitable tool ...
     
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