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Design and Analysis of an MST-Based Topology Control Algorithm

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Maintain connectivity using the minimum transmission power. ... algorithms rely on the cache to inexplicitly build an underlying topology. ... – PowerPoint PPT presentation

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Title: Design and Analysis of an MST-Based Topology Control Algorithm


1
Design and Analysis of an MST-Based
TopologyControl Algorithm
  • Ning Li, Jennifer Hou and Lui Sha
  • Department of Computer Science
  • University of Illinois at Urbana-Champaign
  • Presented By Reed Newman

2
Outline
  • Motivation
  • Topology Control
  • LMST Local Minimum Spanning Tree
  • Simulation Study
  • Future Work

3
Motivations
(2) With Topology Control
(1) No Topology Control
4
RD Roadmap and Opportunities
  • Maximize information throughput but not data
    throughput

Data Aggregation/Computation
Application Layer
  • Maintain connectivity using the minimum
    transmission power.
  • Maintain connectivity by moving some router
    nodes to fill in thehole.
  • Enable nodes to self-organize themselves into
    clusters.
  • Load balance with power consideration

Transport Layer
QoS Mapping (e.g. bounded delay)
Admission Control
Error Control
  • Realize Service Differentiation
  • Provide bounded transmission delay

Network Layer
Routing
Integrated real time scheduling and power control
Topology Control
MAC Layer
Scheduling
Contention Resolution
Physical Layer
GPS Positioning Synchronizing
Power Adjustment
Channels Selection (frequency/code)
Directional Beam-Forming
5
Topology Control
  • Observations
  • Almost all ad-hoc routing algorithms rely on the
    cache to inexplicitly build an underlying
    topology.
  • Many broadcast/multicast algorithms for ad-hoc
    wireless networks maintain some kind of
    underlying topology, upon which the multicast
    tree/mesh can be built.
  • Topology control can achieve
  • Global connectivity
  • Low energy consumption
  • Low interference
  • High throughput

6
Design Guidelines
  • Network connectivity should be preserved.
  • Bi-directional links are preferred.
  • Algorithms should be distributed.
  • To be immune to the impact of mobility, the
    algorithm should depend on local information.

7
LMSTLocal Minimum Spanning Tree
  • Static wireless multihop networks.
  • Transmission power can be adjusted.
  • Each node knows its own position.
  • Each node will build its own minimum spanning
    tree in its neighborhood and only retain those
    one-hop neighbors on the tree as its neighbors in
    the final topology.

8
LMST
  • Visible neighborhood the set of nodes that node
    u can reach by using the maximum transmission
    power.
  • Information collection Each node broadcast
    periodically a Hello message using its maximal
    transmission power.
  • Topology construction
  • Each node applies Prims algorithm independently
    to obtain its local minimum spanning tree.
  • Each node takes all the one-hop, on-tree nodes as
    its neighbors.
  • The network topology under LMST is all the nodes
    in V and their individually perceived neighbor
    relations.
  • Determination of transmission power a node
    transmits using the power that can reach its
    farthest neighbor.

9
LMST Properties
  • The resulting topology preserves the
    connectivity.
  • After removal of asymmetric links, all links are
    bi-directional and the connectivity is still
    preserved.
  • The degree of any node is bounded by 6.

10
LMST Example
w3
w2
w4
w1
w5
u
w6
w7
11
Uni-directional Links
w3
w2
w4
w1
d
u
v
dmax
dmax
12
Connectivity
  • G0 is connected with some uni-directional links.
  • We can either add extra links into G0 so that all
    uni-directional links become bi-directional or
    delete all uni-directional links in G0.
  • Both approaches give us connected graph with
    bi-directional links.

13
Simulations
14
Simulations (Cont.)
15
Dealing with Mobility
16
Future Work
  • Extend LMST to mobile networks.
  • Build the multicast/broadcast protocol upon LMST.
  • Implement LMST on a Motes testbed at UIUC.
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