Skeap & Seap: Scalable Distributed Priority Queues for Constant and Arbitrary Priorities

TL;DR

This paper introduces SKEAP and SEAP, two scalable distributed priority queue protocols that efficiently handle constant and arbitrary priorities, ensuring high throughput and consistency guarantees in distributed systems.

Contribution

The paper presents novel distributed protocols for priority queues with scalable performance, including a new $k$-selection protocol for SEAP, and guarantees for consistency and efficiency.

Findings

Both protocols achieve logarithmic runtime with high probability.

SEAP's $k$-selection runs in $O( ext{log} n)$ rounds with high probability.

SEAP uses only $O( ext{log} n)$ bit messages for operations.

Abstract

We propose two protocols for distributed priority queues (for simplicity denoted 'heap') called SKEAP and SEAP. SKEAP realizes a distributed heap for a constant amount of priorities and SEAP one for an arbitrary amount. Both protocols build on an overlay, which induces an aggregation tree on top of which heap operations are aggregated in batches, ensuring that our protocols scale even for a high rate of incoming requests. As part of SEAP we provide a novel distributed protocol for the $k$-selection problem that runs in $O(\log n)$ rounds w.h.p. SKEAP guarantees sequential consistency for its heap operations, while SEAP guarantees serializability. SKEAP and SEAP provide logarithmic runtimes w.h.p. on all their operations with SEAP having to use only $O(\log n)$ bit messages.