Titlebook: Distributed Computing in Sensor Systems; 5th IEEE Internation Bhaskar Krishnamachari,Subhash Suri,Urbashi Mitra Conference proceedings 2009

易碎

https://doi.org/10.1007/978-3-642-02085-8Online; Scheduling; System; Transceiver; bandwith constrainted; cognition; communication; compressed stream

Feigned

Oligarchy

Distributed Computing in Sensor Systems978-3-642-02085-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

背帶

共和國(guó)

Distributed Continuous Action Recognition Using a Hidden Markov Model in Body Sensor Networks, a technique inspired by continuous speech recognition that combines segmentation and classification using Hidden Markov Models. This technique is distributed and only involves limited data sharing between sensor nodes. We show the results of this technique and the bandwidth savings over full data transmission.

Fibroid

wall-stress

刺激

The Foundations of Computability Theoryved by dynamic programming and one-step-look-ahead methods. Simulation results are presented to evaluate the performance of both methods. The dynamic programming method produced better results with higher computational cost than the one-step-look-ahead method.

neutralize

An East—West Negotiating Proposaled to broadcasting based schemes, MCP greatly reduces signal collision and saves both the dissemination time and reduces the number of dissemination messages. Our experiments results show that MCP can reduce dissemination time by 25% and message overhead by 20% under various network settings.

enmesh

Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multi-hop Wirempeting applications is modeled as a form of distributed utility maximization. We also show how our model can be adapted to more realistic cases, where in-network compression may be varied only discretely, and where a fusion operation cannot be fractionally distributed across multiple nodes.