An Event-based Local Action Model for Queriable Wireless Sensor Actuator Networks

Bergelt, Rene; Hardt, Wolf‐Dietrich

doi:10.23919/softcom.2019.8903666

Cited by 3 publications

(10 citation statements)

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“…heating or climate control, and to control these active components based on events which have been detected in the area of the network. Consequently, such wireless sensor networks are often called wireless sensor actuator networks (WSAN) 1 . The common factor in all stated use cases is that the reduction of data to transmit necessary information or requested actions in a condensed way is critical in order to operate the network in an energy-efficient way [6].…”

Section: A Big Data Processing In Wireless Sensor Networkmentioning

confidence: 99%

“…The partial solutions are then combined to form a single or multiple final results (reduce step) [12]. In database-oriented WS(A)Ns these steps can be defined by users in a declarative way -like with traditional database systems -often by using some kind of query language [1].…”

Section: B Queriable Wireless Sensor Networkmentioning

confidence: 99%

“…This scenario is illustrated in Figure 2. One important parameter 1 or wireless sensor actor networks of this scenario is the distance of the event area to the sink node of the network. This distance d is defined as minimum number of hops a packet needs to travel between sink and event area, i.e.…”

Section: B Queriable Wireless Sensor Networkmentioning

confidence: 99%

“…The concept presented in this article has been first proposed in the paper An Event-based Local Action Model for Queriable Wireless Sensor Actuator Networks [1] on the 27th International Conference on Software, telecommunications and Computer Networks (SoftCOM 2019). This article extends on the classification of the concept in the scope of big data WSN and enhances the evaluation by formally quantifying the impact on energy efficiency using an energy efficiency model.…”

Section: Overview and Contributionmentioning

confidence: 99%

“…Most relevant examples for implementations of queriable WSN are TinyDB [15], Cougar [16], SINA [17], SenQ [18], MadWise [19], TikiriDB [20] and Planetary [6]. In [1] we have given a survey on the state of event support of the aforementioned query systems. In summary, TinyDB, SenQ, SINA, TikiriDB as well as Planetary all provide support for node events to some extent.…”

Section: Related Workmentioning

confidence: 99%

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An Event-based Local Action Paradigm to Improve Energy Efficiency in Queriable Wireless Sensor Actuator Networks

Bergelt

Hardt

2020

J. commun. softw. syst. (Online)

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Wireless sensor networks (WSN) are deployed in a multitude of applications both in industrial and academic fields. In recent years, due to the emerge of Internet of Things (IoT) technologies and Vehicle2X communication scenarios, novel challenges for wireless sensor network platforms - regarding hardware and software - arose. Thus, challenges known from big data processing have reached the WSN scope and consequently approaches and methods have been devised to handle these. One such approach is queriable wireless sensor networks which enable their users the specification of sensing tasks in a declarative way without the need to re-program nodes in case the application requirements change. As many current WSN applications feature active parts with which nodes can directly influence their environment, the term wireless sensor actuator networks (WSAN) has been coined, setting such networks apart from solely passively measuring networks.In this article, we will present a short introduction to big data processing in wireless sensor networks which motivates the usage of queriable networks. We will show that in order to enable a WSAN to carry out actions energy-efficiently and in a timely manner, an event-based action model is favorable. Additionally, we will demonstrate how such an event system can be used to improve sub query performance in WSNs. We conclude with an evaluation regarding the benefit of combining this approach with wake-up receiver technologies based on a qualitative energy efficiency definition for WSN.

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Section: A Big Data Processing In Wireless Sensor Networkmentioning

confidence: 99%

Section: B Queriable Wireless Sensor Networkmentioning

confidence: 99%

Section: B Queriable Wireless Sensor Networkmentioning

confidence: 99%

Section: Overview and Contributionmentioning

confidence: 99%