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UI ECE 5995 - Lecture Note

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Introduction to Wireless Sensor NetworksDirected Diffusion : A Scalable and Robust Paradigm for Sensor NetworksIntroduction and terminology …..Simplified view….Example of events ……Objective……Two ways of packet forwarding during routing….Assumptions ……Directed Diffusion basics…..Possible naming (structure) of an Interest…Interest propagation……..Establishing Gradients…..Slide 13The Algorithm…….Algorithm(cont……)Directed Diffusion….Slide 17Slide 18Slide 19Data Caching…….Data propagation…..Reinforcement …..Reinforcement…..Example of reinforcement….Slide 25Slide 26Slide 27Slide 28Slide 29Slide 30Slide 31Slide 32Negative reinforcement…..Slide 34Directed Diffusion robustness….Slide 36Slide 37Slide 38Design considerations……Multiple sources……Multiple sinks……Evaluation metrics……….Compared with ……DD performance graphs….Impact of node failures….Observations……..Rumor Routing…..Slide 48Algorithm….Slide 50Slide 51Features…Slide 53The University of Iowa. Copyright© 2005A. KrugerIntroduction to Wireless Sensor Networks Directed Diffusion28 March 2005The University of Iowa. Copyright© 2005A. KrugerDirected Diffusion : A Scalable and Robust Paradigm for Sensor NetworksC. Intanogonwiwat R. GovindanD. EstrinThe University of Iowa. Copyright© 2005A. KrugerIntroduction and terminology …..•Availing cheap nodes for sensing, communication and computation •Deploying them in a region of interest to form a network and sensing environment phenomena ( events )• Events are transmitted ( directed ) from the sensing nodes( source ) to a destination ( sink ) for processing.The University of Iowa. Copyright© 2005A. KrugerSimplified view….The University of Iowa. Copyright© 2005A. KrugerExample of events ……•Detecting variations in temperature •Seismic vibrations•Detecting any object like a four-legged animal in an area under inspectionThe University of Iowa. Copyright© 2005A. KrugerObjective……•Making the routing algorithm1)energy efficient : Optimizing radio communications, efficient routing and performing local computations 2)Scalable : Scale with an increase in the number of source and sinks3)Robust : Handling node failuresThe University of Iowa. Copyright© 2005A. Kruger Two ways of packet forwarding during routing….•Address Centric: The nodes route data independently without looking at the data content.•Data Centric: The nodes while routing data use aggregation functions to eliminate redundancy. •Our focus is data centric.The University of Iowa. Copyright© 2005A. KrugerAssumptions ……•Data centric routing•Achieving a desired global behavior through local interactions •Application aware – the task types are known at the time the sensor network is deployedThe University of Iowa. Copyright© 2005A. KrugerDirected Diffusion basics…..•A sink node expresses interest in a particular data and inserts it as a query in the network •Sensor nodes reply to this interest •An interest may look like “At every I ms for the next T seconds send me a location estimate of any four legged animal in sub region R of the sensor field “The University of Iowa. Copyright© 2005A. KrugerPossible naming (structure) of an Interest… type = four-legged animalInterval = 10msRect = [-100,200,300,400]Timestamp = 01:22:35expiresAt = 01:30:40Consists of attribute value pairs – its like querying the network for a particular dataThe University of Iowa. Copyright© 2005A. KrugerInterest propagation……..•Flooding•Geographic routing ( filtering out the interests on basis of the coordinate specification )•Using cached data to find out which neighbor had previously responded to similar interest•Any other intelligent way, depending on the applicationThe University of Iowa. Copyright© 2005A. KrugerEstablishing Gradients…..•Done between every pair of nodes •Consists of a <rate, direction > pairE.g. the gradient from A to neighbor Brate : the inverse of the value of the Interval in the interest sent by B direction : The link to B ( A might have many neighbors – a local naming is required )•They are used for sending back data to the sink – the path with the highest gradient is generally preferredThe University of Iowa. Copyright© 2005A. KrugerSimplified view….The University of Iowa. Copyright© 2005A. KrugerThe Algorithm…….•Initially the sink sends an exploratory interest ( with a low data rate i.e. high interval )•The sensors store it in an Interest cache and forwards it. Subsequent interests having same type,interval,rect values are suppressed – thus selective forwarding•Gradients set up between neighborsThe University of Iowa. Copyright© 2005A. KrugerAlgorithm(cont……)•A sensor whose sensed value matches with the type in an interest samples the readings based on the stored interval and sends it to all the neighbors with which it has a gradient•The intermediate sensors route the data based on the gradient in that direction•Eventually the sink receives the sampled information through some neighboring nodeThe University of Iowa. Copyright© 2005A. KrugerDirected Diffusion….InterestSinkSourceGradientDirectional FloodingThe University of Iowa. Copyright© 2005A. KrugerDirected Diffusion….InterestSinkSourceGradientThe University of Iowa. Copyright© 2005A. KrugerDirected Diffusion….InterestSinkSourceGradientThe University of Iowa. Copyright© 2005A. KrugerDirected Diffusion….SinkSourceGradientThe University of Iowa. Copyright© 2005A. KrugerData Caching…….•Helps in suppressing similar interests from different sinks•Helps in suppressing similar event information from different sources and helps in data aggregationThe University of Iowa. Copyright© 2005A. KrugerData propagation…..•The sources send back the data along the paths which were set upInterestReplyThe University of Iowa. Copyright© 2005A. KrugerReinforcement …..•The sink chooses a high quality( optimal path ) by choosing the appropriate neighbor (using greedy strategy) and reinforces it by 1) sending an interest packet with a lower interval to that link 2) negatively reinforce non-optimal linksThe University of Iowa. Copyright© 2005A. KrugerReinforcement…..•The reinforced interest is forwarded by each sensor node till it reaches the source•The exploratory gradients exist which helps the network to be robust in case of node


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