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Cross-Layer, Energy-Efficient Design for Supporting Continuous Queries in Wireless Sensor Networks A Quorum-Based Approach. Chia-Hung Tsai, Tsu-Wen Hsu, Meng-Shiuan Pan, and Yu-Chee Tseng. Springer Netherlands Wireless Personal Communications 2009. Outline. Introduction

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slide1

Cross-Layer, Energy-Efficient Design for Supporting Continuous Queries in Wireless Sensor Networks A Quorum-Based Approach

Chia-Hung Tsai, Tsu-Wen Hsu,

Meng-Shiuan Pan, and Yu-Chee Tseng

Springer Netherlands

Wireless Personal Communications 2009

outline
Outline
  • Introduction
  • System architecture
  • Quorum layer
  • Query-processing layer
  • Simulation results
  • Conclusions
introduction
Introduction
  • Power saving and query processing are two main issues in WSNs
  • Applying the quorum-based power-saving protocols to the continuous query-processing problem
  • This paper contributes in proposing a cross-layer approach to integrating the grid-quorum system with continuous queries
query session information
Query session information
  • Each node will maintain a QSI table to keep track of the query paths that currently pass it and the quorums to support these paths
query format
Query format
  • Query is denoted by a 5-tuple (sn, sr, t, p, len)
    • sn is the sink node
    • sr is the source node
    • t is the lifetime of the query
    • p is the period that sr will generate reports
    • len is the expected packet length per report
quorum layer
Quorum layer
  • Grid quorum system
  • Quorum set for continuous queries
quorum set for continuous queries
Quorum set for continuous queries
  • The wake-up/sleep schedule of a node will be determined by one or multiple grid quorums, which we call quorum set
  • Each grid quorum is denoted by a 4-tupleg = (n1, n2, R, C)
  • We define the duty cycle of a grid quorum g
example
Example

dty(g) = (4+3-1) / 12 = 1/2

query processing layer
Query-processing layer
  • As more and more continuous queries pass the node, its quorum set will contain more grid quorums
  • A DSR-like routing protocol will be applied
  • An energy cost function will be defined to evaluate the quality of a query path
query processing
Query-processing
  • Query-Requesting Process
  • Query-Replying Process
  • Query-Removing Process
  • Local Slot Synchronization
query requesting process
Query-Requesting Process
  • Quorum preparing
  • QREQ initiating and processing
  • QREQ rebroadcasting
quorum preparing
Quorum preparing

y = (sn, sr, t, p, len)

  • When a sink node sn has a query y to a source node sr, it will compute a grid quorum gini to support the query y
example1
Example

len/r * 1/p

100/10 * 1/50 = 0.2

y = (sn, sr, t, p, len)

y= (0, 8, 500, 50, 100)

n1=3

n2=3

dty(g) = (3+3-1)/9 = 0.56

qreq initiating and processing
QREQ initiating and processing
  • There are two cases involving in producing a QREQ packet:
    • a node initiates a new query
    • a node receives a QREQ and rebroadcasts it
slide17
QREQ
  • We suppose that node xi receives from node xi−1 a QREQ(gini, y, c, PATH) for possibly supporting a query y initiated by node x0
    • gini is the grid quorum computed by x0
    • c is the cost calculated by xi−1
    • PATH is a list of 2-tuples, where each 2-tuple is of the form (node_id, quorum)
duty cycle
Duty cycle
  • xi will find a quorum to serve query y, which we call gser(y)
  • Given G(xi), we can estimate xi’s duty cycle as follows:
example2
Example

1-0.5=0.5

1-0.625=0.375

0.5*0.375=0.1875

Dty=1-0.1875=0.8125

traffic load
Traffic load
  • From xi’s QSI, we can measure xi’s current traffic load as follows
    • len(z) is the length of each sensing report
    • p(z) is the period per report for query z
  • xi’s current traffic load is
capacity 1 2
Capacity(1/2)
  • xi can measure whether its current quorum set can accommodate y or not by checking LD(xi) + ld(y) ≤ DTY (G(xi))
  • The capacity of gcan is defined as follows
    • QS(gcan) means the set of quorum slots of gcan
    • s-deg(sj) is the share degree of the quorum slot sj in gcan
capacity 2 2
Capacity(2/2)
  • If there exists one gcan such that then gcan will be assigned to support y and we will set gser(y) = gcan
costs
Costs
  • The average extra energy cost Cact for xi to remain active per slot
  • The average extra energy cost Ctx for xi to transmit data for y per slot
the average extra energy cost to remain active per slot
The average extra energy cost to remain active per slot
  • Eact is the energy to remain active for one full slot
the average extra energy cost to transmit data for y per slot
The average extra energy cost to transmit data for y per slot
  • Etx is the energy to transmit one full slot of data
qreq rebroadcasting
QREQ rebroadcasting
  • Node xi will also maintain the minimum cost cmin for all paths from x0 to xi that xi has learned so far
query replaying process
Query-replaying process
  • Node xi will collect QREQs for a while and choose the QREQ(gini,y, c, PATH) with the lowest cost c
  • Then xi will unicast QREP(y, PATH) back to x0
quorum set
Quorum set
  • If G(xj) = {gdef}, xj will directly set G(xj) = {gser(y)}
  • Otherwise, xj will set G(xj) = G(xj) ∪ {gser(y)}
  • After a node adjusts its quorum set, it can wake up and sleep according to the quorums in its set
query removing process
Query-removing process
  • Eachintermediate node when receiving the QREM(y) will remove the corresponding entry from its QSI table
local slot synchronization
Local slot synchronization
  • At the clock level, two neighboring nodes will try to synchronize their clocks by aligning their slots
  • At the quorum level, they will try to synchronize this quorum by aligning the first slot of this quorum at each side
assign priority
Assign priority
  • Along a query path, a node that is closer to the source node has a higher priority
  • Between two query paths, the path which was established earlier has a higher priority
simulation results
Simulation results
  • Set up a 400 × 400 m2 sensing field, on which hundreds of sensor nodes are randomly deployed
  • Transmission range and carrier sensing range of each sensor node are set to 50 and 100 m
  • The whole simulation time is 7200 seconds
quorum setting
Quorum setting
  • The default quorum gdef is set to (40, 40, {1}, {1}) with each quorum slot fixed to 0.1 second
  • Initially operate under 5% duty cycle and each quorum group is 160 seconds
impact of our cross layer design
Impact of our cross-layer design
  • The first one lets each query path adjust its quorum on this own [referred to as SP-NC (shortest-path, no-coordination)]
  • The second one enforces all quorum paths to share the same quorum [referred to SP-GQ (shortest path,global-quorum)]
comparison with the sp nc scheme
Comparison with the SP-NC Scheme
  • Each query reporting period is set to 60 seconds
comparison with sp gq scheme
Comparison with SP-GQ scheme
  • The SP-GQ scheme will pick the quorum with the lowest duty cycle that can meet all nodes’ requirement as the global quorum
impact of traffic loads
Impact of traffic loads
  • Impact of Transmission Rate
  • Impact of Packet Length
  • Impact of Query Period
impact of transmission rate
Impact of Transmission Rate
  • A smaller transmission rate r will result in slower transmission (and thus a higher traffic load)
  • Evaluate the energy consumption of our system by varying the transmission rate at 250 kbps, 100 kbps, 50 kbps, and 10kbps
impact of packet length
Impact of Packet Length
  • Vary the length len per report to evaluate the energy performance
  • The transmission rate r is fixed to 250 kbps and len varies from 100, 1000, to 5000 bytes
impact of query period
Impact of Query Period
  • We set r = 250 kbps and len = 100 bytes and vary the reporting period p from 30 to 70 seconds
  • A higher reporting period will incur less energy consumption
conclusions
Conclusions
  • Increasing the overlapping of query paths for energy efficiency
  • We modify the original DSR routing scheme by adding a cost metric to choose quorums along a query path
  • Simulation results also verify the correctness and performance of the proposed scheme