Cross-Layer Application-Specific WSN Design over SS-Trees

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Cross-Layer Application-Specific WSN Design over
SS-Trees

• -Prepared by Amy

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Outline

• Background Introduction
• Sleep Scheduling Issues the SS-Tree Concept
• SS-Tree Operational Stages
• SS-Tree Computation
• SS-Tree Operational Specifics Sleep Scheduling
• Conclusions and Future Work

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Background Introduction

• Wide-area surveillance WSN applications
• expected lifetime
• limited battery supply
• Energy Efficiency is paramount
• Adaptive sleep schedules to minimize energy lost

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Background Introduction

• Sleep scheduling
• shorten the time radio transceiver engaged in
  idle listening
• Good impact
• reduced overhearing
• Ensuing problem
• link table entries expire prematurely
• control and data packet compete for resources
• real-time data reporting function reduced

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Background Introduction

• Ultimate Design Goal
• Balance
• sensing requirements
• end-to-end data communication overhead
• network control effectiveness
• With energy efficiency
• Through a cross-layer sleep scheduling scheme

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Sleep Scheduling Issues

• Not recommended
• Random sleep scheduling
• detrimental effect on network connectivity and
  topology control efficiency
• Global sleep scheduling
• network-wide communication blackout
• Groups of leaf nodes sleep scheduling
• non-leaf nodes depleting battery reserves sooner

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Sleep Scheduling Issues

• Using coordinated sleep scheduling
• Realize the benefits
• reduced overhearing
• reduced packet collision
• simplified topology
• Without sacrifice
• network connectivity
• sensing capabilities

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SS-Tree Concept
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SS-Tree Concept

• Advantages
• Avoid overburdening any set of nodes from being
  the sole virtual backbone
• Increase monitoring sensitivity (greater event
  reporting windows) without altering communication
  duty cycle(reporting frequencies)

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SS-Tree Concept--issues to be considered
Gaps appearing in between the active period of
adjacent SS-Tree
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SS-Tree Concept--issues to be considered
-- Blackout duration -- Sleep period --
number of mutually adjacent SS-Trees -- Active
period
Number of distinct live path To guarantee 100
real-time event reporting capability
Not feasible due to limited nodal density And
high SS-Tree computation complexity Not necessary
to approach real-time Intuition suggests the
number of SS-Tree Should less than the average
nodal degree
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SS-Tree Concept--issues to be considered
Drawback timer-driven Data cannot be
simultaneously Gathered from all SS-Trees
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SS-Tree Operational Stages
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SS-Tree Operational Stages

• Network Initialization
• gather network connectivity information,
• compute the SS-Trees
• disseminate the sleep schedules
• Sleep
• shut down the radio transceiver
• processor and sensing unit remain active
• Hibernation
• Shutting down all hardware components
• except for a tiny low-power wakeup timer

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SS-Tree Operational Stages

• Active
• all data reporting
• network maintenance tasks are performed
• Failure Recovery
• data sink repair or reconstruct SS-Trees
• Neighborhood Update
• neighboring nodes exchange local information
• for each others sleep schedule

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SS-Tree Computation
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SS-Tree Computation

• A greedy depth-first approach
• From the bottom-up on a branch-by-branch basis
• Proceeds in a number of iterations
• In each iteration an end-to-end minimum cost path
  is appended to one of the SS-Trees.

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SS-Tree Computation
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SS-Tree Computation
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SS-Tree Computation
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SS-Tree Computation
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SS-Tree Operational Specifics Sleep Scheduling

• Major task determine an optimal sleep schedule
  that maximizes energy efficiency
• Short active period -gt high transmission latency
• Longer active period -gt increase sleep time
  between two consecutive active periods
• Determine an upper bound of active period
• balance low communication duty cycle
• monitoring sensitivity
• end-to-end packet transmissions

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SS-Tree Operational Specifics Sleep Scheduling
Network Layer Routing
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SS-Tree Operational Specifics Sleep Scheduling

• Some flexible strategies in manipulating
  application requirements
• Compact query formats
• shrink packet size by formatting data types
• reduce hop-by-hop transmission time
• Aggressive data aggregation
• duplicate suppression
• reduce unnecessary packet exchange
• Hop-by-hop ACK in MAC layer
• instead of end-to end ACK in transport layer
• reduce energy expenditure

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SS-Tree Operational Specifics Sleep Scheduling
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SS-Tree Operational Specifics Sleep Scheduling

• Medium Access Control
• Prefer single-channel unslotted CSMA
• simplicity
• greater scalability
• looser time synchronization requirements
• Bypass the RTS/CTS handshake
• long end-to-end propagation delay

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SS-Tree Operational Specifics Sleep Scheduling
Timing components constituting a single active
period
Round-trip time recorded for node I on its
respective SS-Tree
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SS-Tree Operational Specifics Sleep Scheduling
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SS-Tree Operational Specifics Sleep Scheduling
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SS-Tree Operational Specifics Sleep Scheduling
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SS-Tree Operational Specifics Sleep Scheduling
IACK works better in reducing the time when the
size of C/D packet is comparable to that of EACK
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Conclusion and Future Work

• Following issues will be explored
• For a given random topology, what is the maximum
  number of SS-Trees that can be constructed to
  minimize the number of shared nodes?
• For a given number of nodes, what is the optimal
  method of deployment that ensures 100 coverage
  of the subject area while maximizing the number
  of available SS-Trees with minimum shared nodes?
• What are the suitable neighborhood discovery and
  failure recovery strategies for the SS-Tree
  design?

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The End