Constraint-guided dynamic reconfiguration in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Medium access control with coordinated adaptive sleeping for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Autonomous and distributed node recovery in wireless sensor networks
Proceedings of the fourth ACM workshop on Security of ad hoc and sensor networks
Adaptive design optimization of wireless sensor networks using genetic algorithms
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysing qos trade-offs in wireless sensor networks
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
System-scenario-based design of dynamic embedded systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Proceedings of the 6th ACM conference on Embedded network sensor systems
A modeling approach on the TelosB WSN platform power consumption
Journal of Systems and Software
Adaptive control of sensor networks
ATC'10 Proceedings of the 7th international conference on Autonomic and trusted computing
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Network dynamics, such as mobility and increase in network load, can influence the performance of a Wireless Sensor Network (WSN). In this paper, we introduce a method which exploits design-time knowledge of the application scenario dynamics to construct a proactive run-time reconfiguration approach. The approach anticipates for the impact that predefined dynamic events can have on the performance of the WSN by switching between various modes of operation defined at design-time. A mode defines the values for the controllable parameters of the network protocol stack. Our approach explicitly differentiates between parameters that can be adapted locally, per node, and those that should be considered globally for the whole WSN. Design-time definition of modes results in a very low run-time overhead as we only require detection of the mode to use and a low overhead synchronization to change global parameters. The approach is made robust by using a recovery approach for nodes unaware of their global mode after, for example, (re-)joining the network. Experiments with an office monitoring deployment and extensive simulations of a cow-health monitoring scenario show that our approach can easily be adopted by practical WSN deployments and results in a significant reduction in resource usage, e.g., power consumption in our examples, at a very low run-time overhead cost.