Mikko Laurikkala

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This paper exploits a newish self-organizing clustering method to analyze network data. The method is hascd on cooperative behaviour of ants. Collective intelligence of an ant colony rests on interactions of individual ants and the environment. IIence no central control i s nceded and the whole process is pcrformed unsupervised by simplc agents. The data(More)
Keywords: Quality management Fuzzy case-based reasoning Classification GPRS a b s t r a c t Mobile networks pose challenges to quality management because of the limited capacity of the air interface and the mobility of the users. GPRS is the prevailing system for mobile connectivity at the moment. This paper approaches quality management in GPRS networks(More)
This paper presents a system theoretic approach to, and performance analysis of improved congestion control methods i.e. the RED (Random Early Detection)-like AQM (Active Queue Management) algorithms. We revisit the principles of Fuzzy-RED and its linear counterparts and examine their advantages and possible shortcomings from a control theoretical point of(More)
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Analysis of large data volumes calls for reliable and robust methods. Statistical features specific to telecommunication network traffic - such as self-similarity and heavy-tailed distributions - ruin some of the traditional analysis tools. We emphasize the role of statistics in data analysis and present how Monte Carlo simulation can help when analytical(More)
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