Minji Wu, Jianliang Xu, Xueyan Tang, Wang-Chien Lee Professor : 陳朝鈞 教授 Speaker : 邱志銘 Minji Wu, Jianliang Xu, Xueyan Tang, Wang-Chien Lee, “Top-k Monitoring in Wireless Sensor Networks”, Knowledge and Data Engineering, IEEE Transactions on Volume 19, Issue 7, July 2007

 Introduction  Top-k Monitoring ◦ FILA Overview ◦ Filter Setting (Uniform & Skewed) ◦ Filter Update (Eager & Lazy)  Performance Evaluation ◦ Simulation ◦ Eager versus Lazy Filter Update ◦ Performance Comparison with TAG and Cache  Conclusions /12/3

 Top-K Query ◦ Environmental Monitoring  A top-k query is issued find out the nodes and their corresponding areas with the highest pollution indexes for the purpose of pollution control or research study. ◦ Network Management  A top-k query may be issued to continuously monitor the sensor nodes with the least residual energy /12/3

 This paper focuses on continuously monitoring top-k queries in sensor networks. ◦ Utilize previous top-k result to obtain a new top-k result /12/3

 Monitoring a Top-1 query ◦ TAG Base Station A BC t1t1 t2t2 t3t t1t1 t2t2 t3t t1t1 t2t2 t3t 總共需要 9 次傳送 /12/3

 Monitoring a Top-1 query ◦ FILA Base Station A BC t1t1 t2t2 t3t t1t1 t2t2 t3t t1t1 t2t2 t3t probe node C [39, 47][47, 80] [20, 39] 總共需要 6 次傳送 /12/3

 Base station has a continuous power supply.  Sensor nodes powered by battery.  Each sensor node measures the local physical phenomenon at a fixed sampling rate /12/3

1. Filter Setting ◦ the base station computes a filter [ li, ui ] for each sensor node i and sends it to the node for installation. 2. Query Reevaluation 3. Filter update /12/3

 T internal ： the set of internal updates  T join ： the set of join updates  T leave ： the set of leave updates  T ： the old top-k set ◦ If |T’|=|T|-|T leave |+|T join |≧k  The new top-k set must be a subset of T’ ◦ Otherwise, if |T’|<k  The nodes that are not in T have to be probed /12/3

 Uniform filter setting ◦ It is simple and favorable when the readings of sensor nodes follow a similar changing pattern /12/3

 Skewed filter setting ◦ Taking into account the changing patterns of sensor readings. ◦ Suppose the average time for the reading of node I to change beyond is f i (δ)  1 /fi (δ): the rate of sensor-initiated updates by node i /12/3

 Eager filter update ◦ If a new filtering windows [ l i ’, u i ’ ] is different from the old one [ l i, u i ] then the new filter [ l i ’,u i ’ ] is immediately sent to node i  Lazy filter update ◦ If a new filtering windows [ l i ’, u i ’ ] fully contains the old one [ l i, u i ], then the base station delays the filter update until node i’s reading violates the old filter [ l i, u i ] /12/3

 Simulation Setup ◦ Energy cost in transmitting a message  s: message size  α: distance-independent term  β: coefficient  q: distance-dependent term  d: distance ◦ Energy cost in receiving a message  γ is set at 50 nJ/b /12/3

 A Sensor initiated update message: ◦ Sensor ID: 4 bytes ◦ Sensor Reading: 4 Bytes  A filtering windows is characterized by 8 bytes /12/3

15 10 Sensor120 Sensor

 Simulated using the real traces provided by the Live from Earth and Mars (LEM) project at the University of Washington.  Two kinds of sensor readings are used ◦ Temperature (TEMP) ◦ Dew point (DEW) ◦ Logged by the station at the University of Washington from August 2004 to August 2005  Total sensor readings ◦ Extract many subtraces stating at different dates ◦ Each subtrace contains readings ◦ The subtraces were used to simulate the physical phenomena in the immediate surroundings of different sensor nodes /12/3

/12/3

 Network Lifetime ◦ The network lifetimes is defined as the time duration before the first sensor node runs out of power.  Average Energy Consumption ◦ It is defined as the average amount of energy consumed by a sensor node per time unit.  Monitoring Accuracy ◦ This is defined as the mean accuracy of monitored results against the real results /12/3

/12/3

/12/3

/12/3

 This paper exploited the semantics of top-k query and proposed a novel energy-efficient monitoring approach called FILA.  Two filter setting algorithms (that is, uniform and skewed) and two filter update strategies (that is, eager and lazy) have been proposed /12/3