uCast Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks - PowerPoint PPT Presentation

View by Category
About This Presentation
Title:

uCast Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks

Description:

Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks Qing Tao, Tian He, Tarek Abdelzaher Presented By Andrew Connors – PowerPoint PPT presentation

Number of Views:99
Avg rating:3.0/5.0
Slides: 48
Provided by: Andrew1223
Learn more at: http://people.cs.vt.edu
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: uCast Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks


1
uCast Unified Connectionless Multicast for
Energy Efficient Content Distribution in Sensor
Networks
  • Qing Tao, Tian He, Tarek Abdelzaher
  • Presented By
  • Andrew Connors

2
Introduction
  • This paper introduces uCast
  • Connection-less protocol
  • Does not keep state in any intermediate node
  • Keeps list of destination addresses in message
    headers
  • Forwarding decisions made at each node
  • Uses underlying unicast protocols
  • Defines simple interface to use distance
    embedded in unicast protocol
  • And demonstrates performance improvements

3
Sensor Challenges
  • Extremely Energy Constrained
  • Short battery life
  • Use conservation protocols
  • Limited Memory
  • 4K bytes on Mica2/MicaZ
  • Dynamic
  • For this paper this means topology changes due to
    nodes entering sleep states
  • Not changes due to sensor movement

4
Unicast
  • Used to send packets to single destination

5
Unicast
  • Multiple addressing schemes
  • Identifier
  • Geographical location
  • Network Encoding

6
Unicast
  • Identifier
  • No topology information
  • Requires routing tables
  • Uses flooding to establish routes
  • Examples for ad-hoc networks include
  • Dynamic Source Routing (DSR)
  • Ad-Hoc, On Demand Distance Vector Routing (AODV)

7
Unicast
  • Geographical location
  • Each node is location aware using GPS or
    localization
  • Location approximate relative topology
  • Do not need flooding as only local information is
    used for routing
  • Examples include
  • Greedy Perimeter Stateless Routing (GPSR)
  • GEographical DIstance Routing (GEDIR)
  • GEDIR FACE-2 GEDIR (GFG)
  • Location Aided Routing (LAR)

8
Unicast
  • Network Encoding
  • Topology information encoded in identifier
  • Identifiers directly used for routing
  • No flooding needed
  • Examples include
  • Virtual location-based geographical routing
  • Logical coordinate-based routing (LCR)
  • Graph embedded-based routing (GEM)

9
Multicast
  • Used to send packets to multiple destinations

10
Multicast
  • Three types of multicast
  • Sensor Networks
  • Ad-Hoc Networks
  • Internet

11
Multicast
  • Sensor Network Multicast Protocols
  • Geocast
  • Destinations located within geographical region
  • Mobicast
  • Spatiotemporal multicast where destinations are
    in a moving zone and the goal is to deliver
    packets just in time to zone for tracking
    purposes
  • Data Caching Placement
  • Uses multicast for asynchronous data updates
  • Two-Tier Data Dissemination (TTDD)
  • Optimized for mobile sinks and uses a grid
    structure combined with localized flooding to
    track sinks (users that collects these data
    reports from the sensor network)

12
Multicast
  • Ad-Hoc Network Multicast Protocols
  • Tree-Based
  • For example Ad-hoc On-Demand Distance Vector
    Routing (AODV), that builds multicast trees
    on-demand to connect members
  • Mesh-Based
  • For example, core-assisted mesh protocol (CAMP)
    forms multicast meshes (higher connectivity
    graphs than trees) for each multicast group
  • Group-Based
  • For example, On-Demand Multicast Routing Protocol
    (ODMRP) also mesh based but also uses forwarding
    groups

13
Multicast
  • Internet Multicast Protocols
  • Internet Group Management Protocol (IGMP)
  • Used to maintain groups of multicast members by
    IP and routes through existing routers to
    optimize delivery through network
  • Distance Vector Multicast Routing Protocol
    (DVMRP)
  • Used to share information between routers to
    transport multicast packets, and each router
    generates a router table for multicast group
  • Explicit Multi-Unicast (Xcast)
  • Does not use multicast addresses but places IP
    addresses of destinations into headers, but still
    relies on routing tables and a single unicast
    protocol

14
Related Work
  • Existing protocols for sensor, ad-hoc or IP
    networks are not suitable for dynamic sensor
    networks
  • Either do not use unicast or only one specific
    unicast protocol and difficult to maintain
    multiple protocols in small memory footprint
  • Construction of overlays expensive uses
    flooding to maintain topology uses too much
    energy
  • Designed more for laptops not sensors
  • Rely on routing tables and/or connection state
    again difficult to implement in small memory

15
Connection-Less Threshold
  • When to use a connection-less protocol versus
    connection based

Cost per Member
Cost Threshold (Conceptual)
Application Domain of uCast
Connection-based Multicast
Fewer Members/Light Traffic per Session
More Members/Heavy Traffic per Session
16
uCast Design
  • Uses underlying unicast protocol through single
    interface to facilitate a pair-wise comparison to
    obtain closest to destination
  • Implements a scoreboard algorithm executed at
    intermediate nodes using destination list and
    current node neighbors and generates a multicast
    task allocation of a list of next hop nodes that
    should receive multicast packet

17
Unicast Interface
  • Defines only one method
  • compare (Node N1, Node N2, Node Dest)
  • Which returns the selected nearest Node to the
    Destination node

18
Scoreboard Algorithm
  • INPUT Destination Set (DS), Neighbor Set NS, and
    Current Node (S)
  • FOR EACH node in NS that are in DS, set selected
    in NS and move from DS into Covered Set (CS)
  • FOR EACH node in DS, if only one neighbor in NS
    closer than S, set that node in NS to selected,
    and move from DS into CS
  • FOR EACH node is DS, if no neighbor in NS closer
    than S move from DS to Local Maximum Set (LS)
  • FOR EACH node in SN, find all destinations for
    which it closer compared to S, move those from DS
    to CS

19
Scoreboard Algorithm
  • WHILE DS is NOT EMPTY
  • FOR EACH node in DS, find all unselected nodes in
    NS, set each node with a score of 0, assign one
    more score to node closer to S to node in DS
  • FIND unselected node K in NS with highest score,
    break ties randomly or using node ID, set K to
    selected
  • FOR EACH node is DS, find nodes for which K is
    closer than current node S and move them from DS
    to CS
  • FOR EACH node in SN, find all destinations for
    which it closer compared to S, move those from DS
    to CS

20
Scoreboard Algorithm
  • FINALLY PERFORM OPTIMIZATION
  • FOR EACH node in NS that are selected insert into
    SN
  • FOR EACH destination in CS choose the best node,
    snode, among nodes in SN (i.e. closest to that
    CS node) add destination to SD set of snode
  • FOR EACH node is NS, remove nodes with empty SD,
    for other nodes form individual delivery tasks
    based on SD
  • IF LS is not empty, switch to underlying unicast
    protocol and corresponding local maximum handling
    approach to deliver packets to destination in LS

21
Detailed Example
S N53 DS N51,N55 NS
N52,N54,N43 Score 1 1 0 CS
N51 DS N55 NS N52,N54,N43 Score
_ 1 0 CS N51,,N55 SN
N52,N54 N51 gt N52 N55 gt N54
S N53 DS N51,N55 NS
N52,N54,N43
S N22 DS N51,N15,N55 NS
N21,N31,N32,N33,N23,N13,N12 Score 1 1 2
3 2 1 1 CS N51,N15,N55
SN N33 N51,N15,N55 gt N33
S N22 DS N51,N15,N55 NS
N21,N31,N32,N33,N23,N13,N12
S N33 DS N51,N15,N55
NSN32,N42,N43,N44,N34,N24,N23,N22 Score 1 1
2 1 2 1 1 0 CS
N51,N55 DS N15 NSN32,N42,N43,N44,
N34,N24,N23,N22 Score 0 0 _ 0 0
1 0 0 CS N51,N55,N15 SN
N43,N24 N51,N55 gt N43 N15 gt N24
S N33 DS N51,N15,N55 NS
N32,N42,N43,N44,N34,N24,N23,N22
S N11 DS NS N21,N22,N12
Score 2 3 2 CS N51,N15,N55
SN N22 N51,N15,N55 gt N22
S N11 DS N51,N15,N55 NS
N21,N22,N12
22
Handling Local Minima
42
44
34
32
23
Other Examples
24
Design Tradeoffs
  • Uses greedy algorithm may not be globally
    optimal
  • Limit to maximum number of destinations due to
    packet header size limitations
  • However, is at least as good as the NP-Complete
    Set Cover problem
  • To be globally optimal would need another
    NP-Complete problem - Steiner tree generation
    but cannot be generated in reasonable time due to
    large number of nodes

25
Optimality Analysis
  • Use simulation
  • With nodes having range of 50m
  • In 500m x 500m region
  • Source node placed an (250, 250)
  • 6 destination nodes in 60 degree region
  • At least six hops in each route
  • Each scenario tested for 100 rounds
  • Same topology used for minimum cover selection,
    scoreboard, and plain unicast

26
Optimality Analysis
27
Destination Encodings
  • Imposes limit to size of multicast destinations
  • Three possible trade-offs to mitigate
  • With longer packets such as used in video
    streams size not an issue
  • Compress destination header trading space for
    computational time
  • In network aggregation use train of packets
    that share destination list but need
    synchronization and retransmission mechanisms
  • In any case uCast is designed for small-group
    multicast

28
Performance Evaluation
  • Compare with connection-based protocols
  • Shortest Path Tree (SPT)
  • Source node sends packets along shortest paths to
    destinations and aggregates common paths to form
    tree structure
  • Greedy Incremental Tree (GIT)
  • Centralized construction and requires full
    knowledge of topology and is computationally
    intensive
  • Plain unicast
  • Uses geographical forwarding with the GPSR
    traversing technique to handle local minimum set

29
Destination Placement
  • Uses four parameters
  • Polar angle of dispersion (AOD)
  • Radius which is furthest destination node
  • Density number of nodes within communication
    range
  • Number of destination nodes

30
Default Parameters
  • Communication range 50m
  • Area 500m x 500m
  • Density 20 nodes per communication range
  • AOD 900
  • Number of destinations 10
  • Radius 250m
  • Total nodes 636
  • Data rate 6 packets / minute
  • Use PicaZ nodes with CC2420 radio

31
Energy Efficiency
GIT is best but impractical uCast performs better
than SPT Unicast
  • Impact of AOD

32
Energy Efficiency
GIT is best but impractical uCast performs better
than SPT Unicast
  • Impact of Destinations

33
Energy Efficiency
GIT is best but impractical uCast performs better
than SPT Unicast
  • Impact of Range

34
Energy Efficiency
GIT is best but impractical uCast has longer path
length then SPT due to GPSR but in reality
voids are not common
  • Impact of Density

35
Average Path Length
uCast GIT have longer path lengths due to path
aggregation leading to higher end-to-end
delay SPT Unicast find near optimal paths But
trading energy consumption for longer path lengths
  • Impact of AOD

36
Average Path Length
uCast GIT have longer path lengths due to path
aggregation leading to higher end-to-end
delay SPT Unicast find near optimal paths But
trading energy consumption for longer path lengths
  • Impact of Density

37
Topological Changes
  • Introduce topological changes by using energy
    saving protocols
  • Using parameters
  • Toggle cycle time interval between sleep state
    transitions
  • Scale size of multicast area larger the area
    then cost of reconstruction greater
  • Packet Delivery Rate use 6 and 12 packets per
    minute

38
Topological Changes
Shows stateless multicast is superior with node
state transitions As toggle periods shorten SPT
degrades considerably, but uCast achieves 96
delivery ratio
  • Impact of Toggle Period (Rate 10ppm)

39
Topological Changes
Connection based multicast is less scalable than
uCast as range increased there is higher
probability of state loss
  • Impact of Scale

40
Topological Changes
Shows 1000s of control packets are needed to
rebuild tree
  • Impact of Toggle Cycle Range 250m
  • On SPT

41
Topological Changes
Shows 1000s of control packets are needed to
rebuild tree
  • Impact of Toggle Cycle Range 500m
  • On SPT

42
Topological Changes
Shows effect of increased data rate which
decreases delivery ratio
  • Increasing Data Rate to 12 ppm

43
Unicast Protocols
Geo forwarding and logical coordinates-based
routing similar in their performances. However,
uCast based on GEM shows quite different
performance characteristics due to convoluted
delivery paths and polar coordinates
44
Running System
  • Used actual sensor platform with
  • 25 MICA2 motes
  • Code Size of 992 bytes
  • 3V supplies
  • 19.2 kbps
  • 12 byte payload

45
System Evaluation
uCast significantly reduces energy consumption
46
uCast unicast
uCast significantly reduces data load
Recorded data load at each node
47
Conclusions
  • uCast is generally as efficient as
    connection-based protocols even with static
    networks
  • uCast is more robust in a dynamic network due to
    its connectionless nature
  • uCast can be implemented on different unicast
    routing protocols
  • A real implementation supports these conclusions
About PowerShow.com