GloMoSim: a library for parallel simulation of large-scale wireless networks
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Routing with guaranteed delivery in ad hoc wireless networks
Wireless Networks
SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
A line in the sand: a wireless sensor network for target detection, classification, and tracking
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Military communications systems and technologies
Approximately uniform random sampling in sensor networks
DMSN '04 Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004
Topological hole detection in wireless sensor networks and its applications
DIALM-POMC '05 Proceedings of the 2005 joint workshop on Foundations of mobile computing
Proceedings of the 3rd international conference on Embedded networked sensor systems
Efficient broadcasting protocols for regular wireless sensor networks: Research Articles
Wireless Communications & Mobile Computing
Geographic gossip: efficient aggregation for sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Contour map matching for event detection in sensor networks
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Peer counting and sampling in overlay networks: random walk methods
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Boundary recognition in sensor networks by topological methods
Proceedings of the 12th annual international conference on Mobile computing and networking
Exact distributed Voronoi cell computation in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Approximate isocontours and spatial summaries for sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Catching elephants with mice: sparse sampling for monitoring sensor networks
Proceedings of the 5th international conference on Embedded networked sensor systems
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Efficient estimation of population size is a common requirement for many wireless sensor network applications. Examples include counting the number of nodes alive in the network and measuring the scale and shape of physically correlated events. These tasks must be accomplished at extremely low overhead due to the severe resource limitation of sensor nodes, which poses a challenge for large-scale sensor networks. In this article we design a novel measurement technique, FLAKE based on sparse sampling that is generic, in that it is applicable to arbitrary wireless sensor networks (WSN). It can be used to efficiently evaluate system size, scale of event, and other global aggregating or summation information of individual nodes over the whole network in low communication cost. This functionality is useful in many applications, but hard to achieve when each node has only a limited, local knowledge of the network. Therefore, FLAKE is composed of two main components to solve this problem. One is the Injected Random Data Dissemination (Sampling) method, the other is sparse sampling algorithm based on Inverse Sampling, upon which it improves by achieving a target variance with small error and low communication cost. FLAKE uses approximately uniform random data dissemination and sparse sampling in sensor networks, which is an unstructured and localized method. At last we provide experimental results demonstrating the efftectiveness of our algorithm on both small-scale and large-scale WSNs. Our measurement technique appears to be the practiclal and appropriate choice.