Ubiquitous analysis thus becomes increasingly important, especially for

         Ubiquitous Computing poses the challenge of increased communication,context-awareness and functionality. In a highly dynamic and weekly connectedubiquitous environment, continuous access to the network (synchronouscommunication) is very difficult. So it’s necessary to go for tuple space whichprovides asynchronous communication without any loss in data.

Tuple spaceoffers a coordination infrastructure for communication between autonomousentities by providing a logically shared memory along with data persistence,transactional security as well as temporal and spatial decoupling propertiesthat make it desirable for distributed systems 2 such as Ubiquitous Computing(Sudha,R., et al ,2007). With the advancement of laptops, palmtops, cellphones, and wearable computers is making ubiquitous access to large quantity ofdata possible. The emerging benefits of “ubiquitous computing” havethe potential of fundamentally altering the way we live and work. Most companiesare in business to win, and outperform their competitors.

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They adopt newtechnologies to fend off new competitors, reinforce an exciting competitiveadvantage, leapfrog competitors, or just to make money in new markets.Performance is critical (Lee,H.J., Leem,C.S.,2005) Accessing and analyzing data from a ubiquitouscomputing device offer many challenges.

For example, UDM introduces additionalcost due to communication, computation, security, and other factors. Manyapplications such as security informatics and social computing require aubiquitous data analysis platform so that decisions can be made rapidly underdistributed and dynamic system environments. Although data mining has now beenpopularly used to achieve such goals, building a data mining system is,however, a nontrivial task, which may require a complete understanding onnumerous data mining techniques as well as solid programming skills. Employingagent techniques for data analysis thus becomes increasingly important,especially for users not familiar with engineering and computational sciences,to implement an effective ubiquitous mining platform.

Such data mining agentsshould, in practice, be intelligent, complete, and compact(Wu,X.-D., Zhu,X.-Q., Chen,Q.-J., Wang,F.-Y.,2009).


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