Place: A Distributed Spatio-Temporal Data Stream Management System for Moving Objects

Xiong, Xiaopeng; Elmongui, Hicham G.; Chai, Xiaoyong; Aref, Walid G.

doi:10.1109/mdm.2007.16

Cited by 21 publications

(11 citation statements)

References 24 publications

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“…The PLACE [11] solution extends data streaming management systems to support location-aware environments. These environments are characterized by the wide variety of continuous spatiotemporal queries and the unbounded spatiotemporal streams.…”

Section: Related Workmentioning

confidence: 99%

Online detection of patterns in semantic trajectory data streams

Roganović

Stojanović

2013

2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)

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In this paper a system for online detection of patterns in symbolic trajectory data streams is presented. Indoor positioning and analysis of obtained location data using Data Stream Management System are combined into a very powerful system. It contains two separate components: a mobile application and a central server. These components are loosely coupled with an idea to demonstrate knowledge that could be extracted from mobile users from their everyday activities. The system has increased performance in comparison to other similar systems that use raw data from mobile application (GPS feeds) and analysis is done on central server. System process raw data within mobile application and enrich them with semantic meaning, and central server process that semantic data using the Data Stream Management System NEsper detecting patterns in semantic trajectory data streams.

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Section: Related Workmentioning

confidence: 99%

Online detection of patterns in semantic trajectory data streams

Roganović

Stojanović

2013

2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)

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“…These streams are organized in distributed, historic event buffers, that allow historic access to data streams for a certain time Δs. The organization and analysis of such a buffer is not focus of the paper, however, many approaches of the literature provide efficient mechanisms [27,32]. In particular, for the organization of the primary event streams we use a grid-like structure to organize the event storage, where [32].…”

Section: Provisioning Of Historic Eventsmentioning

confidence: 99%

“…Typical examples of such queries are "retrieve all restaurants close to my current location" or "retrieve all objects that were inside a Region R between 11:00 and 12:00". In addition, moving range queries [32,7] continuously retrieve all data of interest in a range depending on the location of a moving focal object, e.g., a car querying for nearby traffic-lights.…”

Section: Introductionmentioning

confidence: 99%

Moving range queries in distributed complex event processing

Koldehofe

Ottenwälder

Rothermel

et al. 2012

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems

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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.

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“…[19]); movement in planar space, unconstrained by transportation networks (e.g. [20][21][22]) or centralized storage and processing of movement data (e.g. most work in the area of moving object databases [23]).…”

Section: Trajectories and Checkpointsmentioning

confidence: 99%

Decentralized Monitoring of Moving Objects in a Transportation Network Augmented with Checkpoints

Both

Duckham

Laube

et al. 2012

The Computer Journal

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This paper examines efficient and decentralized monitoring of objects moving in a transportation network. Previous work in moving object monitoring has focused primarily on centralized information systems, like moving object databases and geographic information systems. In contrast, in this paper monitoring is in-network, requiring no centralized control and allowing for substantial spatial constraints to the movement of information. The transportation network is assumed to be augmented with fixed checkpoints that can detect passing mobile objects. This assumption is motivated by many practical applications, from traffic management in vehicle ad hoc networks to habitat monitoring by tracking animal movements. In this context, this paper proposes and evaluates a family of efficient decentralized algorithms for capturing, storing and querying the movements of objects. The algorithms differ in the restrictions they make on the communication and sensing constraints to the mobile nodes and the fixed checkpoints. The performance of the algorithms is evaluated and compared with respect to their scalability (in terms of communication and space complexity), and their latency (the time between when a movement event occurs, and when all interested nodes are updated with records about that event). The conclusions identify three key principles for efficient decentralized monitoring of objects moving past checkpoints: structuring computation around neighboring checkpoints; taking advantage of mobility diffusion and separating the generation and querying of movement information.

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Place: A Distributed Spatio-Temporal Data Stream Management System for Moving Objects

Abstract: Abstract

Cited by 21 publications

References 24 publications

Online detection of patterns in semantic trajectory data streams

Online detection of patterns in semantic trajectory data streams

Moving range queries in distributed complex event processing

Decentralized Monitoring of Moving Objects in a Transportation Network Augmented with Checkpoints

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