Abstract: Estimated quantiles and/or percentiles for streaming data are computed over a sliding window. An exemplary method comprises obtaining a stream of data values; obtaining a summary of a distribution of previously processed data values; adding streamed data values to a buffer; and when the buffer reaches a predefined fullness threshold, performing the following steps: processing tuples in the summary to apply a decay function to each tuple using the number of items in the stream in the stream at the time the tuple is created and a minimal rank bound; for each item in the buffer, creating a tuple; adding the tuple to the summary, and removing the item from the buffer; and building a search tree that is used to process one or more of percentile queries and quantile queries. The summary is optionally compressed by merging consecutive tuples that satisfy a predefined invariant constraint.

Abstract: There are provided a system and method of computerized optimizing neighbor relation tables (NRTs) of access points in a cellular network comprising a plurality of access points (APs). The method comprises: a) obtaining initial handover-related estimations for AP pairs each constituted by a given source AP and its neighbouring APs located in a predefined range and thereby considerable as candidates for an NRT of the given AP; b) generating a handover (HO) prediction model; c) using the generated HO prediction model to assess HO-related counts for each AP pair of the AP pairs; d) using the assessed HO-related counts to generate, by the computer, data usable for NRT optimization; and e) enabling modifying at least one NRT in accordance with the generated data.

Abstract: There are provided a system and method of computerized optimizing neighbor relation tables (NRTs) of access points in a cellular network comprising a plurality of access points (APs). The method comprises: a) obtaining initial handover-related estimations for AP pairs each constituted by a given source AP and its neighbouring APs located in a predefined range and thereby considerable as candidates for an NRT of the given AP; b) generating a handover (HO) prediction model; c) using the generated HO prediction model to assess HO-related counts for each AP pair of the AP pairs; d) using the assessed HO-related counts to generate, by the computer, data usable for NRT optimization; and e) enabling modifying at least one NRT in accordance with the generated data.