Intelligent fluid infrastructure for embedded networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
An efficient leader election protocol for mobile networks
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Diagnosing mobile ad-hoc networks: two distributed comparison-based self-diagnosis protocols
Proceedings of the 4th ACM international workshop on Mobility management and wireless access
Energy optimal data propagation in wireless sensor networks
Journal of Parallel and Distributed Computing
Mobile Element Scheduling with Dynamic Deadlines
IEEE Transactions on Mobile Computing
LCN '07 Proceedings of the 32nd IEEE Conference on Local Computer Networks
ANSS-41 '08 Proceedings of the 41st Annual Simulation Symposium (anss-41 2008)
Adaptive redundancy for data propagation exploiting dynamic sensory mobility
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
MobiRoute: routing towards a mobile sink for improving lifetime in sensor networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Multiple controlled mobile elements (data mules) for data collection in sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Coverage-adaptive random walks for fast sensory data collection
ADHOC-NOW'10 Proceedings of the 9th international conference on Ad-hoc, mobile and wireless networks
Modelling mobility: A discrete revolution
Ad Hoc Networks
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Collecting sensory data using a mobile data sink has been shown to drastically reduce energy consumption at the cost of increasing delivery delay. Towards improved energy-latency trade-offs, we propose a biased, adaptive sink mobility scheme, that adjusts to local network conditions, such as the surrounding density, remaining energy and the number of past visits in each network region. The sink moves probabilistically, favoring less visited areas in order to cover the network area faster, while adaptively stopping more time in network regions that tend to produce more data. We implement and evaluate our mobility scheme via simulation in diverse network settings. Compared to known blind random, non-adaptive schemes, our method achieves significantly reduced latency, especially in networks with non-uniform sensor distribution, without compromising the energy efficiency and delivery success.