Minimising the context prediction error

S Sigg, S Haseloff, K David

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

Abstrakti

Context prediction mechanisms proactively provide information on future contexts. Due to this knowledge novel applications become possible that provide services with proactive knowledge to users. The most serious problem of context prediction mechanisms lies in a basic property of prediction itself. A prediction is always a guess. Since erroneous predictions may cause the application to behave insufficiently, prediction errors have to be minimised. The accuracy of prediction is seriously affected by the reliability of the context data that is utilised by the method. We study two paradigms for context prediction and compare their potential prediction accuracy. We show that the designer of context prediction architectures has to choose wisely as to which prediction paradigm to follow in order to maximise the accuracy of the whole architecture. We also introduce a simulation environment and present simulation results that support the gained insights regarding context prediction.
AlkuperäiskieliEnglanti
Otsikko2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring
KustantajaIEEE
Sivut272-276
Sivumäärä5
ISBN (painettu)1-4244-0266-2
DOI - pysyväislinkit
TilaJulkaistu - 2007
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE Vehicular Technology Conference - Dublin, Irlanti
Kesto: 22 huhtik. 200725 huhtik. 2007
Konferenssinumero: 65

Julkaisusarja

Nimi IEEE Vehicular Technology Conference
ISSN (painettu)1550-2252

Conference

ConferenceIEEE Vehicular Technology Conference
LyhennettäVTC-Spring
Maa/AlueIrlanti
KaupunkiDublin
Ajanjakso22/04/200725/04/2007

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