Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
A digital fountain approach to reliable distribution of bulk data
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Reed-Solomon Codes and Their Applications
Reed-Solomon Codes and Their Applications
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
XORs in the air: practical wireless network coding
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Growth codes: maximizing sensor network data persistence
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Proceedings of the 6th international conference on Information processing in sensor networks
Differentiated Data Persistence with Priority Random Linear Codes
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
On the sphere-decoding algorithm I. Expected complexity
IEEE Transactions on Signal Processing - Part I
Design challenges for energy-constrained ad hoc wireless networks
IEEE Wireless Communications
Space-time diversity systems based on linear constellation precoding
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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Maintaining data persistence in a scalable fashion for large-scale distributed systems has become critical and essential. It becomes more challenging when nodes have finite energy. In this work, we propose a novel approach called network modulation (NeMo) to significantly improve the data persistence. Built on algebraic number theory, NeMo operates at the level of modulated symbols. Its core notion is to mix data at intermediate network nodes and meanwhile guarantee the symbol recovery at the sink(s) without pre-storing or waiting for other symbols. The persistence performance of NeMo has been evaluated by simulations to show that the proposed approach is efficient to enhance the data persistence for energy-constrained networks.