Moving range queries in distributed complex event processing

Abstract

Up to now, correlations in complex event processing (CEP) systems are detected by a well defined set of operators, whose configuration is determined ahead of deployment time. Although CEP operators involve location specific attributes, state of the art systems are heavily constrained in detecting situations where the interest in a situation changes depending on the consumer's location, e.g., with the movement of mobile devices.This paper adopts the concept of range queries to CEP systems. We propose a mobility-aware event delivery semantics and present a corresponding execution model, which accounts for mobility driven selection of primary event streams to the CEP system. By utilizing the properties of this execution model, we derive an algorithm that establishes low cost and coordinated reconfiguration of CEP operators in a distributed system. The algorithm minimizes the amount of information that needs to be streamed between operators and avoids additional delays as a result of a reconfiguration of CEP operators. We present an analysis of the algorithm's properties and evaluate the efficiency of the proposed reconfiguration algorithm.

Predictable Low-Latency Event Detection With Parallel Complex Event Processing

“…To optimize processes, for example, in logistics, the smart grid [4], [5], or traffic management [17]- [20], it is necessary to support such applications to react to the occurrence of critical situations with low latency. Such situations can, for instance, be accidents, load variations in power consumption, or changing weather conditions.…”

Opportunistic spatio-temporal event processing for mobile situation awareness

“…In contrast, our system supports CEP for mobile devices, such as smart vehicles, which requires migrating an operator graph to a new region when a user moves. Koldehofe et al [19] propose a system that supports CEP on moving ranges. However, they do not address the latency of processing historical events when an operator graph moves to another region.…”

“…Following the results of [19], it is beneficial to create and initialize an operator graph on demand based on user mobility, instead of deploying a vast amount of operator graphs for all possible regions. Consider again the example that a consumer is interested in accidents that happened in the last hour in a 5 km perimeter.…”

“…Computing events outside that area results in wasted computation. The reduction in needed computation when only processing events in a range around the mobile user, vs. processing all events, is substantial [19]. A naive solution would be to start the operator graph anew in different locations as the mobile user moves to those locations.…”

Access Policy Consolidation for Event Processing Systems

“…While, traditionally event processing systems have applied powerful operators in a central way, the emerging increase of event sources and event consumers have raised the need to reduce the communication load by distributed in-network processing of stream operations [3], [4], [5], [6]. In addition, the collaborative nature of today's economy results in largescale networks, where different users, companies, or groups exchange events.…”