The wireless sensor network community approached networking abstractions as an open question, allowing answers to emerge with time and experience. The Trickle algorithm has become a basic mechanism used in numerous pr...
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The wireless sensor network community approached networking abstractions as an open question, allowing answers to emerge with time and experience. The Trickle algorithm has become a basic mechanism used in numerous protocols and systems. Trickle brings nodes to eventual consistency quickly and efficiently while remaining remarkably robust to variations in network density, topology, and dynamics. Instead of flooding a network with packets, Trickle uses a "polite gossip" policy to control send rates so each node hears just enough packets to stay consistent. This simple mechanism enables Trickle to scale to 1000-fold changes in network density, reach consistency in seconds, and require only a few bytes of state yet impose a maintenance cost of a few sends an hour. Originally designed for disseminating new code, experience has shown Trickle to have much broader applicability, including route maintenance and neighbor discovery. This paper provides an overview of the research challenges wireless sensor networks face, describes the Trickle algorithm, and outlines several ways it is used today.
A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-va...
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ISBN:
(纸本)0819464538
A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD(Biochemical Oxygen Demand) from sewage disposal system,and a good training result of soft sensing was obtained by the method.
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