Multi-hop communication is order-optimal for homogeneous sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Purposeful Mobility for Relaying and Surveillance in Mobile Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks
IEEE Transactions on Knowledge and Data Engineering
Using predictable observer mobility for power efficient design of sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Sensor networks with mobile agents
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
The capacity of wireless networks
IEEE Transactions on Information Theory
On the scaling laws of dense wireless sensor networks: the data gathering channel
IEEE Transactions on Information Theory
Engineering of Software-Intensive Systems: State of the Art and Research Challenges
Software-Intensive Systems and New Computing Paradigms
Sink mobility in wireless sensor networks: when theory meets reality
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
MSN'07 Proceedings of the 3rd international conference on Mobile ad-hoc and sensor networks
A mobility management framework for optimizing the trajectory of a mobile base-station
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
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We present a procedure for communication power optimization in a network of randomly distributed sensors with an observer (data collector) moving on a fixed path. The key challenge in using a mobile observer is that it remains within communication range of any sensor for a brief duration, and inability to transfer data in this duration leads to data loss. We establish that the process of data collection can be modeled by a queue with deadlines, where arrivals correspond to the observer entering the range of a sensor and a missed deadline means data loss. The queuing model is then used to identify the combination of system parameters that ensures adequate data collection with minimum power. The results obtained from the queuing analogy take a simple form in the asymptotic regime of dense sensor networks. Additionally, for sensor networks that cannot tolerate data loss, we derive a tight bound on minimum sensor separation that ensures that no data will be lost on account of mobility. We present two examples to illustrate our results, from which it is seen that power reduction by two orders of magnitude or more is typical relative to a static sensor network. The scenarios chosen for power comparisons also provide guidelines on the choice of path, if such a choice is available.