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Energy-Efficient Wake-Up Scheduling for Data Collection and Aggregation Yanwei Wu, Member, IEEE, Xiang-Yang Li, Senior Member, IEEE, YunHao Liu, Senior Member, IEEE, and Wei Lou IEEE TPDS, vol. 21, no. 2, 2010, pp. 275-287.
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Outline 2 Introduction System model and assumption Homogeneous wireless sensor networks Heterogeneous wireless sensor networks Formation of data gathering tree Performance evaluation Conclusion
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Introduction Wireless sensors are often powered by batteries and have limited computing and memory resources. Schedule the nodes’ activities to reduce energy consumption. Previous studies did not consider all possible energy consumption by wireless sensors, Wasted listening, and the state transitions. 3
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Introduction 4 Traditionally, the scheduling algorithms often schedule the individual activities for each sensor one by one. Find the best time slots for sending and receiving data. Communication and interference range. Homogeneous wireless sensor networks Heterogeneous wireless sensor networks
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Introduction 5 A scheduling should reduce the state transitions to increase the lifetime of a sensor. To minimize the sensor’s wake-up times in a scheduling period. Any sensor node needs only to wake up at most twice in our protocol. Once for continuously receiving all packets from its children nodes and once for sending its own data to its parent node.
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System model and assumption 6 Network System Models Problem Description
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Network System Models 7 Tree-based All data will be collected and sent to the sink. Each wireless node will use a fixed power to communicate with its neighboring sensors. The fixed power transmission by a node v i will define an interference range. R I (v i ) such that the transmission of node v i will interfere the reception of any node v k when The physical link is reliable if v i can communicate with v j. vkvk vivi vjvj
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Problem Description 8 Energy-Efficient Scheduling Data Collection Tree Construction
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Problem Description- Energy-Efficient Scheduling 9 The amount of slots assigned to a node v i for transmitting should be enough. A node v i with children nodes u 1, u 2,..., u j should be active for receiving at the time slots when these children nodes send data to v i. The observed link reliability Packets received from its children nodes {0,1}
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Problem Description- Energy-Efficient Scheduling 10 Any node can only be in one of the states. All transmissions should be interference-free. {0,1}
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Problem Description- Energy-Efficient Scheduling 11 Notice that the energy cost by a node v i in all states is The energy cost for state transitions is The objective of a schedule S is to minimize the summation of these two energy costs. Slot size Energy consumption of # {0,1}
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Problem Description- Data Collection Tree Construction 12 Tree T is given for the data collection or aggregation. The total energy cost of the optimum activities scheduling based on this tree is the lowest. The objective is to find a data collection tree T that should satisfy the data requirements of all nodes. NP-hard problem.
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Goals 13 This paper use a TDMA for scheduling node activities to reduce the energy consumption. Focused on the energy cost by the radio. Transmitting, receiving, listening, and sleeping.
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Outline Introduction System model and assumption Homogeneous wireless sensor networks Heterogeneous wireless sensor networks Formation of data gathering tree Performance evaluation Conclusion 14
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Homogeneous wireless sensor networks- Centralized Activity Scheduling 15 The total number of time slots that node v i should wake up to receive the data from its children is: Parent node Child node
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Homogeneous wireless sensor networks- Centralized Activity Scheduling 16 Conflicting Cluster
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Homogeneous wireless sensor networks- Centralized Activity Scheduling 17 4 1-hop 4-hop 3-hop 2-hop 1/2 The node z is within the distance at most 3R I from node p. The sensors from conflicting clusters C j,l can only be distributed inside the circle with the radius 3R I z q v p RI(p)RI(p) RT(p)RT(p) u
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Homogeneous wireless sensor networks- Centralized Activity Scheduling 18 Schedule the clusters in the decreasing order of their weight W i. Then each child v j will be assigned a consecutive w j time slots from this chunk. Time slot W j,i :The clusters which conflict with cluster C i and are scheduled before cluster C i. g j,i : Gaps,non-conflicting clusters, which could be assigned to cluster C i. WiWi {w 1,w 2,w 3 … }
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Homogeneous wireless sensor networks- Centralized Activity Scheduling 19 SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN Time slot g j,1 g j,2 g j,3 g j,4 w j,1 w j,2 w j,3 w j,4 C4C4 C5C5 C2C2
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Homogeneous wireless sensor networks- Centralized Activity Scheduling (More discussions) 20 Besides reducing the energy consumption and increasing network throughput Another important issue in WSNs is to reduce the delay. Instead of scheduling using the available earliest time slots, this paper use the latest available time slots. SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN Time slot g j,1 g j,2 g j,3 g j,4 w j,1 w j,2 w j,3 w j,4 didi uiui d i,w i =3 u i,w i =4 didi uiui
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Homogeneous wireless sensor networks- Distributed Activity Scheduling (TTL) 21 SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN Time slot g j,1 g j,2 g j,3 g j,4 w j,1 w j,2 w j,3 w j,4 C4C4 C7C7 IamScheduled
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Outline Introduction System model and assumption Homogeneous wireless sensor networks Heterogeneous wireless sensor networks Formation of data gathering tree Performance evaluation Conclusion 22
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Heterogeneous wireless sensor networks - Centralized Activity Scheduling 23 SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN Time slot g j,1 g j,2 g j,3 g j,4 w j,1 w j,2 w j,3 w j,4 C2C2 C3C3 First divide the sensors into buckets according to their interference radii. Interference Range : B 1 <B 2 <B 3 C4C4
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Heterogeneous wireless sensor networks - Distributed Activity Scheduling (TTL) 24 SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN SWSW SYNSYN Time slot g j,1 g j,2 g j,3 g j,4 w j,1 w j,2 w j,3 w j,4 C6C6 C7C7 First divide the sensors into buckets according to their interference radii. C1C1
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Formation of data gathering tree -Connected dominating set 25 Energy efficiency is a critical issue in WSNs since the sensor nodes are with limited energy.
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Performance evaluation 26 Randomly placing 32 sensors in a square 5*5 square meters. Transmission radius as 1m. Interference radius as 2m.
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Performance evaluation 27 Impact of Data Rate
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Performance evaluation 28 Impact of Number of Nodes
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Performance evaluation 29 Impact of Heterogeneous Nodes
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Conclusion 30 In this paper proposed an efficient centralized and distributed scheduling algorithms. Remove the unnecessary listening cost Reduce the energy cost for state switching and clock synchronization. Every node needs only to wake up at most twice in one scheduling period One for receiving data from its children and one for sending data to its parent.
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