Next century challenges: mobile networking for “Smart Dust”
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
SPINS: security protocols for sensor networks
Wireless Networks
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Energy-efficient routing for connection-oriented traffic in wireless ad-hoc networks
Mobile Networks and Applications
Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Monte Carlo localization for mobile wireless sensor networks
Ad Hoc Networks
A Swarm-Intelligence-Based Protocol for Data Acquisition in Networks with Mobile Sinks
IEEE Transactions on Mobile Computing
Asynchronous Corona Training Protocols in Wireless Sensor and Actor Networks
IEEE Transactions on Parallel and Distributed Systems
ACM Transactions on Sensor Networks (TOSN)
VIBE: An energy efficient routing protocol for dense and mobile sensor networks
Journal of Network and Computer Applications
Applicability of Hop Distance in Random Sensor Networks
Wireless Personal Communications: An International Journal
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Studies of wireless networks often work with a relatively high communication range so that each node typically communicates with a high number of neighbors. This is necessary, with a random placement, to avoid loss of coverage or connectivity. However, communicating through remote neighbors requires more energy, which can be a severe disadvantage since energy is often critical in this type of network. By comparing two-ranges, one to ensure coverage and one to save energy, we identify link-nodes which play an essential role to keep the network connected. Characterizing these nodes and their occurrence in communication routes will help to save energy and increase lifetime of the overall network. Without precautions, these link-nodes receive a high traffic load. Using simulations we find that slightly longer routes can avoid link-nodes and thus reduce average energy consumption. Network lifetime can be extended by identifying these nodes at startup and reducing their energy consumption wherever possible.