In this paper we present a generalised framework for expressing batching strategies of a mix. First, we note that existing mixes can be represented as functions from the number of messages in the mix to the fraction of messages to be flushed. We then show how to express existing mixes in the framework, and then suggest other mixes which arise out of that framework. We note that these cannot be expressed as pool mixes. In particular, we call binomial mix a timed pool mix that tosses coins and uses a probability function that depends on the number of messages inside the mix at the time of flushing. We discuss the properties of this mix. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Díaz, C., & Serjantov, A. (2003). Generalising mixes. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2760, 18–31. https://doi.org/10.1007/978-3-540-40956-4_2
Mendeley helps you to discover research relevant for your work.