Sliding Block Hashing (Slick) -- Basic Algorithmic Ideas

We present {\bf Sli}ding Blo{\bf ck} Hashing (Slick), a simple hash table data structure that combines high performance with very good space efficiency. This preliminary report outlines avenues for analysis and implementation that we intend to pursue

Answering Spatial Multiple-Set Intersection Queries Using 2-3 Cuckoo Hash-Filters

We show how to answer spatial multiple-set intersection queries in O(n(log w)/w + kt) expected time, where n is the total size of the t sets involved in the query, w is the number of bits in a memory word, k is the output size, and c is any fixed constant. This improves the asymptotic performance over previous solutions and is based on an interesting data structure, known as 2-3 cuckoo hash-filters. Our results apply in the word-RAM model (or practical RAM model), which allows for constant-time bit-parallel operations, such as bitwise AND, OR, NOT, and MSB (most-significant 1-bit), as exist in modern CPUs and GPUs. Our solutions apply to any multiple-set intersection queries in spatial data sets that can be reduced to one-dimensional range queries, such as spatial join queries for one-dimensional points or sets of points stored along space-filling curves, which are used in GIS applications.Comment: Full version of paper from 2017 ACM SIGSPATIAL International Conference on Advances in Geographic Information System

Switch based high cardinality node detection

The detection of supernodes with high cardinality is of interest for network monitoring and security. Existing schemes for supernode detection rely on data structures that are independent of the switching functions. This means that for each packet that traverses the switch, both the switching table and the supernode detection structure have to be checked which requires significant memory bandwidth. This can create a bottleneck and reduce the speed of the switch, especially for software implementations. In this letter, a scheme that performs supernode detection as part of Ethernet switching and does not require additional memory accesses nor separated data structures is presented. The scheme has been implemented and compared with the existing methods. The results show that the proposed scheme can reliably identify supernodes while providing a speed up of more than 15% when compared with the existing solutions.This work was supported in part by the Higher Education Commission (HEC) Pakistan and the Ministry of Planning, Development and Special Initiatives under National Centre for Cyber Security; in part by the ACHILLES Project PID2019-104207RB-I00 and the Go2Edge network RED2018-102585-T funded by the Spanish Ministry of Science and Innovation; and in part by the Madrid Community Research Project TAPIR-CM under Grant P2018/TCS4496