Redistribution for Enhanced M-Health Application Performance

Building context-aware mobile healthcare systems have become increasingly important with the emergence of new medical sensor technologies, the fast adoption of advanced mobile systems, and improved quality of care required by today's patients. A unique feature of our mobile healthcare system is a distributed processing paradigm whereby a set of bio-signal processing tasks is spread across a heterogeneous network. As well as applying the traditional adaptation methods such as protocol adaptation and data

[1]  K. Wac,et al.  Mobile patient monitoring: The MobiHealth system , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  Navendu Jain,et al.  Adaptive Control of Extreme-scale Stream Processing Systems , 2006, 26th IEEE International Conference on Distributed Computing Systems (ICDCS'06).

[3]  Ing Widya,et al.  Optimal Assignment of a Tree-Structured Context Reasoning Procedure onto a Host-Satellites System , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[4]  Bora Uçar,et al.  Task assignment in heterogeneous computing systems , 2006, J. Parallel Distributed Comput..

[5]  Ing Widya,et al.  QoC-based Optimization of End-to-End M-Health Data Delivery Services , 2006, 200614th IEEE International Workshop on Quality of Service.

[6]  Virginia Mary Lo,et al.  Heuristic Algorithms for Task Assignment in Distributed Systems , 1988, IEEE Trans. Computers.

[7]  Ying Xing,et al.  Providing resiliency to load variations in distributed stream processing , 2006, VLDB.

[8]  Yuan-Ting Zhang,et al.  Implementation of a WAP-based telemedicine system for patient monitoring , 2003, IEEE Transactions on Information Technology in Biomedicine.

[9]  Yuan-Hsiang Lin,et al.  A wireless PDA-based physiological monitoring system for patient transport , 2004, IEEE Transactions on Information Technology in Biomedicine.

[10]  Mahadev Satyanarayanan,et al.  Pervasive computing: vision and challenges , 2001, IEEE Wirel. Commun..

[11]  Kang G. Shin,et al.  Optimal Task Assignment in Homogeneous Networks , 1997, IEEE Trans. Parallel Distributed Syst..

[12]  Yang Xiao,et al.  Throughput and delay limits of IEEE 802.11 , 2002, IEEE Communications Letters.

[13]  Michael G. Norman,et al.  Models of machines and computation for mapping in multicomputers , 1993, CSUR.

[14]  Valerie M. Jones,et al.  Future Challenges and Recommendations , 2006 .

[15]  Shahid H. Bokhari,et al.  Partitioning Problems in Parallel, Pipelined, and Distributed Computing , 1988, IEEE Trans. Computers.

[16]  Klara Nahrstedt,et al.  On Composing Stream Applications in Peer-to-Peer Environments , 2006, IEEE Transactions on Parallel and Distributed Systems.

[17]  Margo I. Seltzer,et al.  Network-Aware Operator Placement for Stream-Processing Systems , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[18]  Ishfaq Ahmad,et al.  Optimal task assignment in heterogeneous distributed computing systems , 1998, IEEE Concurr..

[19]  Marten van Sinderen,et al.  A Framework for Smart Distribution of Bio-Signal Processing Units in M-Health , 2007, ICSOFT.

[20]  Mahadev Satyanarayanan,et al.  A conceptual framework for network and client adaptation , 2000, Mob. Networks Appl..

[21]  Mohd Fadlee A. Rasid,et al.  Bluetooth telemedicine Processor for multichannel biomedical signal transmission via mobile cellular networks , 2005, IEEE Transactions on Information Technology in Biomedicine.

[22]  Tien-Fu Chen,et al.  Branch-and-bound task allocation with task clustering-based pruning , 2004, J. Parallel Distributed Comput..

[23]  Carles Gomez,et al.  TCP/IP analysis and optimization over a precommercial live UMTS network , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[24]  Ahmad Rahmati,et al.  Context-for-wireless: context-sensitive energy-efficient wireless data transfer , 2007, MobiSys '07.