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Real-time Wireless Sensor Networks (WSNs): Theory

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Georgia Tech Broadband Institute Real-time Wireless Sensor Networks (WSNs): Theory & Applications Prof. Raghupathy Sivakumar, ECE – PowerPoint PPT presentation

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Title: Real-time Wireless Sensor Networks (WSNs): Theory


1
Georgia Tech Broadband Institute
Real-time Wireless Sensor Networks (WSNs) Theory
Applications
Prof. Raghupathy Sivakumar, ECE
2
Objectives
  • Design and develop algorithms, protocols, and
    systems for real-time and mission-critical
    communication in WSNs
  • Three main challenges addressed timeliness,
    robustness, correctness
  • Four complimentary goals
  • Higher capacity
  • Lower energy consumption
  • Information Prioritization
  • Reliable communication
  • Demonstrate research through test-bed and
    real-life applications

3
Team Funds
  • 11 Members
  • Raghupathy Sivakumar (Fac)
  • Umakishore Ramachandran (Fac)
  • Faramarz Fekri (Fac)
  • Mary Ann Ingram (Fac)
  • Sandeep Kakamanu
  • Sriram Lakshmanan
  • Rajnish Kumar
  • Junsuk Shin
  • Badri Narayanan
  • Nazanin Rahnavard
  • Lakshmi Thanayankizil
  • Other Sources of Funds
  • Heterogeneous WSNs
  • NSF ITR, NSF REU
  • Securing WSNs
  • Navy
  • Multi-channel WSNs
  • NSF NOSS
  • WSNs with smart antennas
  • NSF CCR, NSF NOSS
  • Multi-scale unreliable sensor networks
  • NSF NOSS

(650K total funding in 2006-2007)
4
Solutions
  • Information Prioritization Real-time
    Prioritization algorithms Multi-sensor
    peer-to-peer fusion Increased timeliness
  • Opportunistic Large Arrays Cooperative
    transmissions Simple amplify and forward
    Increased range, and battery power
  • Reliable Broadcast using Fractional
    Transmissions Hybrid coding and routing
    Lightweight rate-less coding Increased
    reliability
  • Component based Multi-channel allocation Single
    channel component level operation Optimal
    performance with key practical benefits
    Increased capacity

5
Applications
Medical (patient monitoring)
Security (digital surveillance)
Video (video over IP)
Wireless (channel management)
6
Real Time Sensor Networks challenges and
solutions
  • Objective
  • Reduces transmissions without sacrificing
    reliability
  • Motivation
  • An opportunistic large array (OLA) is a form of
    cooperative diversity where simple,
    single-antenna nodes transmit together in
    response to a source or another OLA
  • OLA state of the art uses flooding. While MAC
    and routing overhead is eliminated for single
    messages, more energy can still be saved
  • Proposed schemes
  • OLA-T (OLA-Threshold) a threshold will be
    applied to the received power to determine if the
    node should repeat. Saves about 50 of the energy
    when compared to whole network flood
  • OLACRA (OLA Concentric Routing Algorithm) -
    Upstream routing suitable for SNs. Saves about
    60 of the energy in comparison with whole
    network flood, while maintaining connectivity
  • Objective
  • Efficient data gathering from sensors in
    wireless sensor networks
  • Efficient data broadcasting in multi-hop
    wireless sensor networks
  • Motivation
  • Gathering data from image sensors with
    correlated data
  • Updating software in already deployed
    sensor/actuator networks
  • Proposed schemes
  • Date gathering Scheme Distributed Source Coding
    (DSC)
  • Broadcasting Schemes
  • No information about the network topology is
    available Collaborative Rateless Broadcast
    (CRBcast) a two-phase data dissemination
    algorithm employing rateless coding and
    probabilistic broadcasting in the first phase and
    a local recovery in the second phase
  • Local information about the network topology is
    available Fractional Transmission Scheme (FTS)
    employs rateless coding to make it possible for
    the nodes to send just a fraction of data
  • Three main challenges of real-time sensor
    networks
  • Timeliness
  • Reliability (Packet level)
  • Correctness (Application level)
  • Objective
  • Using multiple channels for throughput
    enhancement of wireless sensor networks with low
    complexity
  • Motivation
  • Channel assignment in multi-channel wireless
    networks can increase achievable throughput by
    overcoming the problems of interference, varying
    channel characteristics, poor end-to-end
    characteristics
  • At any given time a node with a single radio can
    operate on only one channel
  • No hardware/MAC changes, no switching delay, no
    synchronization requirement, and no scheduling
    overheads
  • Proposed schemes
  • We introduce a new model for channel assignment
    known as Component-Based where all links in a
    connected component induced by the underlying
    flow graph operate in a single channel
  • Although the component based model looks simple,
    we show that this model can have equal if not
    better performance over link and flow based
    approaches
  • Objective
  • Right information at the right time
  • Motivation
  • Moving from a centralized to a distributed
    solution
  • Increase Information-Awareness
    (Cognitive-Awareness)
  • Information Prioritization and Fidelity
    Adjustment
  • Proposed Scheme
  • ASAP Architecture
  • Separate data and
  • control network
  • Priority-aware
  • transport
  • Using multi-modal
  • sensing to do prioritization
  • Application 1
  • IPTV enhancement using WSN.
  • Application 2
  • Video surveillance application with
    information prioritization
  • Application 3
  • Wireless mesh network management

7
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