Glossary

Words used in this document or in hots domain may have a special meaning that differs from their usual one. This section explains those terms in details.

cluster

In the context of hots application, cluster is used for its machine-learning meaning (it could be confused with the meaning related to infrastructure). In this context, a cluster is a group of similar individuals, resulting from clustering.

clustering

Clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).

heuristic

A heuristic is a method, used for solving a given problem, that is not guaranteed to be optimal, perfect or rational, but which is nevertheless sufficient for reaching an immediate, short-term goal. It is often used for solving very hard problems, by quickly finding a feasible solution.

hots

hots is the name given to this application. hots comes from Resource Allocation via Clustering. It then denotes a methodology that solves a resource allocation problem, using clustering (in addition to a heuristic).