A promising idea for optimising the power consumption of mobile communication devices represents the usage of an additional ultra-low-power receiver unit, which is able to control the main transceiver in order to reduce the standby power consumption of the overall system. Such a Wake-Up-Receiver (WuRx) unit senses the medium and switches on the communication interfaces in case of an external request. Otherwise, all system components for the network communication are completely switched off. Especially in the domain of resource-limited and embedded devices, WuRx technologies enable novel communication paradigms. But on the application layer, not all scenarios allow the efficient usage of such WuRx technologies. Dependent on environmental parameters, technological limitations and conceptual requirements, different strategies are necessary to ensure energy-efficient system operation. In this article, we present a critical analysis of the capabilities and the conceptual limitations of WuRx approaches. Therefore, we identify critical parameters for WuRx concepts, which limit the efficiency in real world scenarios. Our goal is to classify sufficient fields of application. Furthermore we evaluate the influences of these parameters on the system behaviour. In addition, we introduce heterogeneous energy harvesting approaches as an efficient way for the system optimisation. The proposed technologies are capable to be integrated into small-sized wireless sensor platforms and prolong the system uptime significantly. The presented simulation results are focusing on actual smart metering scenarios and wireless sensor networks. Based on these measurements, we were able to apply further optimisation steps within the system configuration on the application layer. In this context, we focus on application-specific key issues, like the trade-off between measurement quality and quantity, the usage of data buffering approaches and QoS capabilities.
[1]
Matthias Vodel,et al.
SimANet - A Large Scalable, Distributed Simulation Framework for Ambient Networks
,
2008,
J. Commun..
[2]
Nathan Michael Pletcher,et al.
Ultra-low power wake -up receivers for wireless sensor networks
,
2008
.
[3]
Paramvir Bahl,et al.
Wake on wireless: an event driven energy saving strategy for battery operated devices
,
2002,
MobiCom '02.
[4]
Stefan Mahlknecht,et al.
An Ultra Low Power Wakeup Receiver for Wireless Sensor Nodes
,
2009,
2009 Third International Conference on Sensor Technologies and Applications.
[5]
Chris Nagy.
Embedded Systems Design Using the TI Msp430 Series: Embedded Technology
,
2003
.
[6]
Jan M. Rabaey,et al.
Ultra-Low Power Wireless Technologies for Sensor Networks
,
2007
.
[7]
Matthias Vodel,et al.
A capable, high-level scheduling concept for application-specific wireless sensor networks
,
2010,
2010 International Symposium on Information Technology.
[8]
John A. Stankovic,et al.
Radio-triggered wake-up capability for sensor networks
,
2004,
Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..
[9]
Matthias Vodel,et al.
The SimANet Framework
,
2008
.
[10]
S. Beeby,et al.
Energy harvesting vibration sources for microsystems applications
,
2006
.
[11]
Sébastien Roy,et al.
Low-Power 2.4 GHz Wake-Up Radio for Wireless Sensor Networks
,
2008,
2008 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications.
[12]
Jan M. Rabaey,et al.
A 2GHz 52 μW Wake-Up Receiver with -72dBm Sensitivity Using Uncertain-IF Architecture
,
2008,
2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers.