MARWIS: A Management Architecture for Heterogeneous Wireless Sensor Networks

Wagenknecht, Gerald; Anwander, Markus; Braun, Torsten; Staub, Thomas; Matheka, James K.; Morgenthaler, Simon

doi:10.1007/978-3-540-68807-5_15

Cited by 34 publications

(13 citation statements)

References 16 publications

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“…The tethered nature of these newly introduced cluster heads, however, enables them to communicate with each other directly, effectively turning the WSN into a network with multiple sink nodes. Wireless backhaul links between cluster heads have been proposed [4], [5], [6]. These solutions commonly rely on the use of a secondary communication channel, e.g., IEEE 802.11, to transfer data between the cluster heads.…”

Section: Related Workmentioning

confidence: 99%

Exploiting platform heterogeneity in wireless sensor networks by shifting resource-intensive tasks to dedicated processing nodes

Reinhardt

Burgstahler

2013

2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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Platform heterogeneity in wireless sensor networks is often seen as a major challenge for application development. Once embedded systems with different processor architectures, computational power, and memory are part of the same network, algorithms and applications must be adapted to this additional degree of complexity. As a result, current sensor network deployments are (with exception of the sink node) commonly comprised of devices of identical make and model. In this paper, we show how device heterogeneity may be exploited to improve the energy efficiency of the sensor network by shifting resource-intensive processing tasks to other nodes within the network. To this end, we analyze the energy demand for representative processing operations and wireless communications on six heterogeneous state-of-the-art sensor platform types. Based on the created models, we assess the achievable energy savings when tasks are shifted to more powerful processing nodes. Our results show that platform heterogeneity, although often being perceived as a hindrance to the easy deployment of applications, also serves as an enabler for increased energy efficiency of the network.

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Section: Related Workmentioning

confidence: 99%

Exploiting platform heterogeneity in wireless sensor networks by shifting resource-intensive tasks to dedicated processing nodes

Reinhardt

Burgstahler

2013

2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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“…Sensor network diagnostics and visualization is discussed in [10]. Different sensor network visualization applications include SpyGlass [11] and MARWIS [12]. These applications do not use realtime "on the map" visualization of the network, instead they use relative locations to visualize the network topology.…”

Section: Related Workmentioning

confidence: 99%

CiNetView - Graphic Interface for Wireless Sensor Network Deployment and Monitoring

Hakala

Hongell

Luomala

2010

2010 Fourth International Conference on Sensor Technologies and Applications

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Reliable communication is crucial for successful deployment of a wireless sensor network. Many environmental factors can affect the performance of radio links, and the deployment of a network without real-time information about link qualities can be a demanding task. This paper describes the CiNetView application that is intended to support the deployment and monitoring of wireless sensor network. CiNetView is based on diagnostic information collected by sensor nodes, and it allows the user to see a graphical presentation of the network topology and to monitor the network diagnostic information in real time.

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“…The wiring description file defines dependencies between components through the channel interface connecting components. Marwis (Wagenknecht, 2008) is a middleware based on Contiki (Dunkels et Al., 2004) (executed on the sensors) and Linux (executed on computers managing the WSN), that aims at managing WSNs composed by different kinds of sensors. Sensors are divided into smaller sensor subnetworks (SSNs), each containing only sensors of one type, then a wireless mesh network (WMN) operates as a backbone for the SSNs and as a gateway to the WSNs.…”

Section: Event-based Programmingmentioning

confidence: 99%

Programming a Sensor Network in a layered middleware architecture

Albano¹,

Chessa²

2010

Sustainable Wireless Sensor Networks

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Wireless Sensor Networks (WSNs) have become a mature technology aimed at performing environmental monitoring and data collection. Nonetheless, harnessing the power of a WSN presents a number of research challenges. WSN application developers have to deal both with the business logic of the application and with WSN's issues, such as those related to networking (routing), storage, and transport. A middleware can cope with this emerging complexity, and can provide the necessary abstractions for the definition, creation and maintenance of applications. This work discusses the problems related to the development of such a middleware and surveys the state of the art on the field.

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MARWIS: A Management Architecture for Heterogeneous Wireless Sensor Networks

Cited by 34 publications

References 16 publications

Exploiting platform heterogeneity in wireless sensor networks by shifting resource-intensive tasks to dedicated processing nodes

Exploiting platform heterogeneity in wireless sensor networks by shifting resource-intensive tasks to dedicated processing nodes

CiNetView - Graphic Interface for Wireless Sensor Network Deployment and Monitoring

Programming a Sensor Network in a layered middleware architecture

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