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
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
Data-centric storage in sensornets with GHT, a geographic hash table
Mobile Networks and Applications
Data Dissemination with Ring-Based Index for Wireless Sensor Networks
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards
Computer Communications
An energy efficient framework for mobile target tracking in sensor networks
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks
IEEE Transactions on Wireless Communications
Making data-centric storage adaptive and cost-optimal
Computer Networks: The International Journal of Computer and Telecommunications Networking
On Analysis of the Contention Access Period of IEEE 802.15.4 MAC and its Improvement
Wireless Personal Communications: An International Journal
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In wireless sensor networks, storage policies can be categorized into external storage, local storage and data centric storage. Each storage police has its suitable network environments. If a correct storage policy is chosen for a given network condition, unnecessary control messages can be significantly reduced. Then the network lifetime can be increased. In this paper, adaptive data storage (ADS) policy which can dynamically choose suitable storage policy for wireless sensor network according to the frequencies of user queries and events happening is proposed. Through collection and computation of user query and event rates, the proposed algorithm switches between local storage and data centric storage policies adaptively. Simulations are given to justify that the proposed adaptive storage policy indeed reduces the traffic in network and increases network lifetime.