TCEP: Transitions in Operator Placement to Adapt to Dynamic Network Environments

TL;DR

This paper introduces TCEP, a method for adaptive operator placement in distributed event processing systems that optimizes transition costs and analyzes behavior to improve performance in dynamic IoT environments.

Contribution

It extends previous transition methodologies by optimizing transition costs and analyzing multi-mechanism behavior for better adaptivity in DCEP systems.

Findings

Transition costs can be significant and are analyzed in detail.

Optimized transition strategies reduce overhead during operator migrations.

Behavioral analysis informs better adaptive placement decisions.

Abstract

Distributed Complex Event Processing (DCEP) is a commonly used paradigm to detect and act on situational changes of many applications, including the Internet of Things (IoT). DCEP achieves this using a simple specification of analytical tasks on data streams called operators and their distributed execution on a set of infrastructure. The adaptivity of DCEP to the dynamics of IoT applications is essential and very challenging in the face of changing demands concerning Quality of Service. In our previous work, we addressed this issue by enabling transitions, which allow for the adaptive use of multiple operator placement mechanisms. In this article, we extend the transition methodology by optimizing the costs of transition and analyzing the behaviour using multiple operator placement mechanisms. Furthermore, we provide an extensive evaluation on the costs of transition imposed by operator migrations and learning, as it can inflict overhead on the performance if operated uncoordinatedly.