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Event Query Processing Based on Data-Centric Storage in Wireless Sensor Networks Longjiang Guo, Yingshu Li and Jianzhong Li Globalcom IEEE 2007 Outline Introduction Event formulation and storage Event query processing Choosing optimal storage strategy Simulation Conclusion INTRODUCTION interested in the events, instead of the sensors A event is a fusion of multiple sensed data satisfying some conditions. event fire: temperature>90 AND smoke>100L/mol, find all the locations where ET satisfied the pre-defined observation attributes. EVENT FORMULATION AND STORAGE preprocessing of the observed data : includes a check on whether the data satisfies the event conditions If it does, the event information will be stored in the sensor network. EVENT FORMULATION AND STORAGE A. Event Formulation Definition 1: Observation attribute Ai (i=1…n) Definition 2: Observation value Definition 3: Round Definition 4: Event type ETi (A1, A2, …, Aiki ) a group of pre-defined observation attributes ET(Tmpt, Wnd, Hudit) = Tmpt>t1 and Wnd>w2 and Hudit>h3 Definition 5: Observation zone divided into m×n grids ,each grid is an observation zone. Definition 6: Event e(ET, g, t) Definition 7: Event query Q{[t1, t2],ETi} EVENT FORMULATION AND STORAGE A. Event Formulation The observation nodes of ETi : Si1, Si2, …, Siki , where node Sij observes attribute Aij. W: types of events ET1 , ET2 ,…, ETw EVENT FORMULATION AND STORAGE A. Event Formulation Every node Sij broadcasts a message within its observation zone. ETi , Sij’s ID , Sij’s position When a node Sij receives a message, it firstly checks whether the event type is the same as its own forwards the message to its neighbors EVENT FORMULATION AND STORAGE A. Event Formulation For each observation zone, in the kth round, Sij is selected as the event fusion node j=(k mod ki )+1 the event fusion node routes the event to storage node Si2 ,…, Si6 route IDs and values to Si1 Broadcast Si1 ‘s position Si2 Si1 k=1, Si1 as event fusion node Si6 Si5 Si3 Si4 EVENT FORMULATION AND STORAGE B. Event Storage External storage: the sink is the event storage node an event fusion node will route the events directly to the sink Local storage: the event storage node is the same as the event fusion node. Data centric storage: hash to an in-network position (x, y) according to the event type. nearest to that position, called Home Node EVENT FORMULATION AND STORAGE B. Event Storage More energy can be saved to put Home Node at the center of a network. Center Mapping Data Centric Storage (CM-DCS) Events of the same type will be hashed to an observation zone lying at the center of the network. A node in the observation zone nearest to the center of the network serves as an event storage node EVENT FORMULATION AND STORAGE B. Event Storage Lemma 1: the total energy consumption for routing events is proportional to the distance between the event fusion node and the event storage node. Proof: This is obvious. EVENT FORMULATION AND STORAGE B. Event Storage Lemma 2: If observation nodes are distributed uniformly in an observation zone, event fusion node is the center of the observation zone. Proof: event fusion node’s (c, d) (E(Xf), E(Yf)) (a, b) position (Xf, Yf) : node (X, Y) an observation is a two dimensional E(Xf)=0.5(a+c) random variable. E(Yf)=0.5(b+d) EVENT FORMULATION AND STORAGE B. Event Storage Theorem 1: If event storage nodes are located near the center of the sensor network, energy consumption for routing events from an event fusion node to an event storage node is minimized. Proof: (X1, Y1), (X2, Y2), …, (Xmxn, Ymxn) :centers of the observation zones (fusion nodes). (X, Y) : event storage node EVENT FORMULATION AND STORAGE B. Event Storage Mapping: {ET1→Z6; ET2→Z10; ET3→Z11;ET4→Z7} : storage node EVENT FORMULATION AND STORAGE C. Storage at an Individual Event Storage Node each event storage node is responsible for event type ETi time-stamped vector-based storage strategy: If (j1, j2, …, jk of I) = 1 , observation zones event of type ETi. detected the EVENT QUERY PROCESSING extract information from the sensor network for query Q{[t1, t2], ETi}. Event query processing based on CMDCS Event query processing based on Local Storage EVENT QUERY PROCESSING A. Event query processing based on CM-DCS Phase 1: Deciding the routing destination. Phase 2: Routing query Q{[t1, t2], ETi}. from the sink to the event storage node p Phase 3: Answering query Q{[t1, t2], ETi}. Phase 4:Routing Ip back to the sink from node p. A={(I,t)} | t [t1 , t2 ], then Ip ( I ,t ),t[ t1 ,t 2 ] sink I Ip (x , y ) i i p ETi Q{[t1 , t2], ETi}. EVENT QUERY PROCESSING B. Event query processing based on Local Storage Phase 1:Query dissemination. sink broadcasts the query, add its ID to query packet. p replaces the ID in the query packet with its own ID Phase 2:Collection of children’s IDs. p broadcasts <p,fp> , where fp is p’s parents p receives {<q1, fq1>, < q2, fq2 >, …, < qm, fqm >}, Children(p)={qi| <qi, fqi>, where fqi =p}. Phase 3:Combination of query results. event storage node p receives an event query A={(I,t)} | t [t1 , t2 ], then p computes I p I ( I ,t ),t[ t ,t ] Phase 4:Routing Ip back to the sink from node p. 1 2 CHOOSING OPTIMAL STORAGE STRATEGY provide a guideline of choosing a correct storage strategy for different applications. CHOOSING OPTIMAL STORAGE STRATEGY CHOOSING OPTIMAL STORAGE STRATEGY A. Estimation of Energy Consumption For Initialization broadcast a message and forward a message to its neighbors Receive from neighbors/broadcast to neighbors CHOOSING OPTIMAL STORAGE STRATEGY B. Estimation of Energy Consumption For Event Formulation The expected number of hops (nodefusion node) =sqrt(N/(8mn)) (A random node fusion node) CHOOSING OPTIMAL STORAGE STRATEGY C. Estimation of Energy Consumption For External Storage The expected number of hops (nodesink) =(2N)/2 #events (node fusion node) (fusion node sink) CHOOSING OPTIMAL STORAGE STRATEGY D. Estimation of Energy Consumption For CM-DCS The expected number of hops (node storage node) =(2N)/4 (node fusion node) (fusion node storage ) Query: (sink storage node) Answer: (storage node sink) CHOOSING OPTIMAL STORAGE STRATEGY E. Estimation of Energy Consumption For Local Storage Query Answer CHOOSING OPTIMAL STORAGE STRATEGY F. Comparing the Energy Consumptions Assume: Eb =Eu , Er =1.5Eb , Sevent =Squery =0.25Sresult Observation 1: if Nq >N·prob, external storage Observation 2: ifρ and Nq increase,CM-DCS if ρ is a constant and N increases, local storage SIMULATION RESULTS SIMULATION RESULTS SIMULATION RESULTS SIMULATION RESULTS SIMULATION RESULTS SIMULATION RESULTS CONCLUSION propose a data centric storage strategy CM-DCS event query processing algorithms: EP-CM-DCS and EP-LS. compare the energy consumptions users can have a guideline of choosing a correct storage strategy for different applications.