GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
GHT: a geographic hash table for data-centric storage
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Data-centric storage in sensornets
ACM SIGCOMM Computer Communication Review
Data-centric storage in sensornets with GHT, a geographic hash table
Mobile Networks and Applications
Fundamental scaling laws for energy-efficient storage and querying in wireless sensor networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
On the lifetime of wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Scaling laws for data-centric storage and querying in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
A grid-based dynamic load balancing approach for data-centric storage in wireless sensor networks
Computers and Electrical Engineering
Spatial Model for Energy Burden Balancing and Data Fusion in Sensor Networks Detecting Bursty Events
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Improving security in data-centric storage for wireless sensor networks
Proceedings of the 10th ACM symposium on Performance evaluation of wireless ad hoc, sensor, & ubiquitous networks
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This paper presents a novel framework for Data Centric Storage in a wireless sensor and actor network that enables the use of a randomly-selected set of data replication nodes which also change over the time. This allows reducing the average network traffic and energy consumption by adapting the number of replicas to applications' traffic, while balancing energy burdens by varying their location. To that end we propose and validate a simple model to determine the optimal number of replicas, in terms of minimizing average traffic/energy consumption, from the measured applications' production/consumption traffic. Simple protocols/mechanisms are proposed to decide when the current set of replication nodes should be changed, to enable new applications and sensor nodes to efficiently bootstrap into a working sensor network, to recover from failing nodes, and to adapt to changing conditions. Extensive simulations demonstrate that our approach can extend a sensor network's lifetime by at least a 60%, and up to a factor of 10x depending on the lifetime criterion being considered.