Reactive Programming Optimizations in Pervasive Computing

Chen, Chao; Xu, Yi; Li, Kun; Helal, Sumi

doi:10.1109/saint.2010.92

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…The work in [8] presents a rule-based ServiceOriented Device Architecture (SODA) reactive system in which ECA rules are defined by programmers. This event-driven programming mechanism includes a time frequency modifier operator which allows the optimization of pull/push operations to retrieve data from sensors, thus, achieving important energy savings.…”

Section: Related Workmentioning

confidence: 99%

Customizing smart environments: A tabletop approach

Pons

Catalá

Jaén

2015

AIS

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Abstract. Smart environments are becoming a reality in our society and the number of intelligent devices integrated in these spaces is increasing very rapidly. As the combination of intelligent elements will open a wide range of new opportunities to make our lives easier, final users should be provided with a simplified method of handling complex intelligent features. Specifying behavior in these environments can be difficult for non-experts, so that more efforts should be directed towards easing the customization tasks. This work presents an entirely visual rule editor based on dataflow expressions for interactive tabletops which allows behavior to be specified in smart environments. An experiment was carried out aimed at evaluating the usability of the editor in terms of non-programmers' understanding of the abstractions and concepts involved in the rule model, ease of use of the proposed visual interface and the suitability of the interaction mechanisms implemented in the editing tool. The study revealed that users with no previous programming experience were able to master the proposed rule model and editing tool for specifying behavior in the context of a smart home, even though some minor usability issues were detected.

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Section: Related Workmentioning

confidence: 99%

Customizing smart environments: A tabletop approach

Pons

Catalá

Jaén

2015

AIS

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“…actuating a device or invoking a service) are executed, to respond to the event. Details about the design and implementation of ECA are found in our early work [15].…”

Section: Event-driven Programming Modelmentioning

confidence: 99%

“…We have extended the event formulation structure to support composite events [15]. For example, an event associated with a single sensor only is called a basic event, while an event defined in terms of one or more basic events is called a composite event.…”

Section: Event-driven Programming Modelmentioning

confidence: 99%

“…Optimization techniques to balance push and pull have been extensively discussed in [10][13] [14], which focus on network topology and routing algorithms. Furthermore, a new model discussed in [15] utilizes the mixed push/pull strategy and takes advantage of the optimization opportunity provided by the event structure and its time-frequency relaxations. However, none of the above approaches fit perfectly into a cloud-based sensor computing paradigm.…”

Section: Related Workmentioning

confidence: 99%

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Optimizing push/pull envelopes for energy-efficient cloud-sensor systems

Helal

Thai

et al. 2011

Proceedings of the 14th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

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Unlike traditional distributed systems, where the resources/needs of computation and communication dominate the performance equation, sensor-based systems (SBS) raise new metrics and requirements for sensors as well as for computing and communication. This includes sensing latency and energy consumption. In this paper, we present a performance model for SBS based on a three-tier architecture that uses edge devices to connect massive-scale networks of sensors to the cloud. In this architecture, which we call Cloud, Edge, and Beneath (CEB), initial processing of sensor data occurs in-and near-network, in order to achieve system sentience and energy efficiency. To optimize CEB performance, we propose the concept of optimal push/pull envelope (PPE). PPE dynamically and minimally adjusts the base push and pull rates for each sensor, according to the relative characteristics of sensor requests (demand side from the Cloud) and sensor data change (supply side from Beneath). We demonstrate the CEB architecture and its push/pull envelope optimization algorithm in an experimental evaluation that measures energy savings and sentience efficiency over a wide range of practical constraints. In addition, from the experiments we demonstrate that by combining PPE optimization algorithm with lazy sampling algorithm, we can achieve further energy saving.

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System-wide support for safety in pervasive spaces

Chen

Helal

2011

J Ambient Intell Human Comput

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Reactive Programming Optimizations in Pervasive Computing

Cited by 8 publications

References 19 publications

Customizing smart environments: A tabletop approach

Customizing smart environments: A tabletop approach

Optimizing push/pull envelopes for energy-efficient cloud-sensor systems

System-wide support for safety in pervasive spaces

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