Optimization based pattern discovery has emerged as an important field in knowledge
discovery and data mining (KDD), and has been used to enhance the efficiency and …

In a dynamic stream there is an assumption that the underlying process generating the
stream is non-stationary and that concepts within the stream will drift and change as the …

Clustering data streams has drawn lots of attention in the last few years due to their ever-
growing presence. Data streams put additional challenges on clustering such as limited time …

A data stream is a continuously arriving sequence of data and clustering data streams
requires additional considerations to traditional clustering. A stream is potentially …

Recently, the concept of the internet of things and its services has emerged with cloud
computing. Cloud computing is a modern technology for dealing with big data to perform …

Analyzing data streams has received considerable attention over the past decades due to
the widespread usage of sensors, social media and other streaming data sources. A core …

Owing to the scattered nature of Denial-of-Service attacks, it is tremendously challenging to
detect such malicious behavior using traditional intrusion detection systems in Wireless …

In recent years, a significant boost in data availability for persistent data streams has been
observed. These data streams are continually evolving, with the clusters frequently forming …

Data growth in today's world is exponential, many applications generate huge amount of
data streams at very high speed such as smart grids, sensor networks, video surveillance …

Meta-heuristic search algorithms are developed to solve optimization problems. Such
algorithms are appropriate for global searches because of their global exploration and local …