Bayesian Network Based Behavior Prediction Model for Intelligent Location Based Services

Chen, Wenzhi; Liubai,; Fu, Zhenzhu

doi:10.1109/mesa.2006.296936

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…"Subscription" refers to an interest in receiving messages on a particular topic. In a Pub/Sub system, producers of the event-driven data are usually decoupled from the consumers of the data [14,15]: meaning publishers and subscribers are independent components that share information by publishing event-driven messages and by subscribing to event-driven messages of choice [14]. The central component of this system is called an event broker.…”

Section: Basics Of a Publish/subscribe Messaging Servicementioning

confidence: 99%

Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements

Mishra

Mishra²,

Kertész

2021

Energies

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Presently, Internet of Things (IoT) protocols are at the heart of Machine-to-Machine (M2M) communication. Irrespective of the radio technologies used for deploying an IoT/M2M network, all independent data generated by IoT devices (sensors and actuators) rely heavily on the special messaging protocols used for M2M communication in IoT applications. As the demand for IoT services is growing, the need for reduced power consumption of IoT devices and services is also growing to ensure a sustainable environment for future generations. The Message-Queuing Telemetry Transport or in short MQTT is a widely used IoT protocol. It is a low-resource-consuming messaging solution based on the publish–subscribe type communication model. This paper aims to assess the performance of several MQTT broker implementations (also known as MQTT servers) using stress testing, and to analyze their relationship with system design. The evaluation of the brokers is performed by a realistic test scenario, and the analysis of the test results is done with three different metrics: CPU usage, latency, and message rate. As the main contribution of this work, we analyzed six MQTT brokers (Mosquitto, Active-MQ, Hivemq, Bevywise, VerneMQ, and EMQ X) in detail, and classified them using their main properties. Our results showed that Mosquitto outperforms the other considered solutions in most metrics; however, ActiveMQ is the best performing one in terms of scalability due to its multi-threaded implementation, while Bevywise has promising results for resource-constrained scenarios.

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Section: Basics Of a Publish/subscribe Messaging Servicementioning

confidence: 99%

Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements

Mishra

Mishra²,

Kertész

2021

Energies

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“…For example, Wenzhi et al [9] use Bayesian networks for predicting the future behavior of a mobile user in an intelligent Location-Based Services (LBS) publish/subscribe system. Laskey et al [10] present an approach based on Bayesian networks to detect threatening user behavior in an information system.…”

Section: Related Workmentioning

confidence: 99%

Modeling User Behavior in P2P Live Video Streaming Systems through a Bayesian Network

Ullah

Bonnet

Doyen

et al. 2010

Mechanisms for Autonomous Management of Networks and Services

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Abstract. Live video streaming over a Peer-to-Peer (P2P) architecture is promising due to its scalability and ease of deployment. Nevertheless, P2P-based video streaming systems still face some challenges regarding their performance. These systems are in fact overlays of users who control peers. As peers depend upon each other for receiving the video stream, the user behavior has an impact over the performance of the system. We collect the user behavior studies over live video streaming systems and identify the impact of different user activities on the performance. Based on this information, we propose a Bayesian network that models a generic user behavior initially and then adapts itself to individuals through learning from observations. We validate our model through simulations.

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“…Wenzhi et al presented a method that predicted user's behavior based on a UBPM (User Behavior Prediction Model) model [3]. User's future behavior was predicted through the model which was built by using date, time, user's location, and user's past behavior information.…”

Section: Related Workmentioning

confidence: 99%

A Recommendation Agent for Mobile Phone Users Using Bayesian Behavior Prediction

Kim

Cho

2009

2009 Third International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies

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This paper presents a novel agent system which provides a user with useful recommendations of behavior and information based on behavior prediction. The agent understands user's context from a GPS sensor and a mobile phone, and predicts user's future behavior based on user's context. And the prediction of user's future behavior can be used to provide the user with the suggestion of performing behavior and/or the recommendation of information which are relevant to the predicted user's behavior. Here, behavior prediction is performed by Dynamic Bayesian Network, which can handle time-series data. The experimental results showed that the proposed agent system was enough to provide convenient recommendation services to users.

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Bayesian Network Based Behavior Prediction Model for Intelligent Location Based Services

Cited by 4 publications

References 21 publications

Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements

Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements

Modeling User Behavior in P2P Live Video Streaming Systems through a Bayesian Network

A Recommendation Agent for Mobile Phone Users Using Bayesian Behavior Prediction

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