Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Abstract: We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) parallelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. … Read more

Analyzing Big Security Logs in Cluster with Apache Spark

Abstract. Cyber security is the major concern in today’s highly net- worked environment and logging is the primary way of tracking compli- ance with the security policies. However analyzing the massive amount of logs has become a “Big Data” problem. Apache Spark is one of the latest and most notable incarnation of Data Flow Models … Read more