Modelling%20and%20Performance%20Analysis%20of%20the%20Distributed%20Scheduler%20in%20IEEE802.16%20Mesh%20Mode - PowerPoint PPT Presentation

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Modelling%20and%20Performance%20Analysis%20of%20the%20Distributed%20Scheduler%20in%20IEEE802.16%20Mesh%20Mode

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case and for the nonidentical holdoff exponents. case. 12/22/09. OPLab, Dept. of IM, NTU ... way handshaking time for the nonidentical exponent case with N = 10 ... – PowerPoint PPT presentation

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Title: Modelling%20and%20Performance%20Analysis%20of%20the%20Distributed%20Scheduler%20in%20IEEE802.16%20Mesh%20Mode


1
Modelling and Performance Analysis of the
Distributed Scheduler in IEEE802.16 Mesh Mode
Min Cao, Dept. Electrical Computer
Engineering
University of Illinois, Urbana-Champaign
Wenchao Ma, Microsoft Research Asia Qian
Zhang, Microsoft Research Asia Xiaodong Wang,
Dept. Electrical Engineering Columbia University
Wenwu Zhu, Intel China Research
Center Proceedings of the 6th ACM international
symposium on Mobile ad hoc networking and
computing MobiHoc '05
  • Presented by Jason L.Y. Lin

2
Outline
  • Introduction
  • Background on IEEE 802.16 Mesh mode
  • Modelling and Performance Analysis
  • Simulation Results
  • Conclusions and Future Work

3
Introduction (1/3)
  • IEEE 802.16 MAC has two mode
  • - point-to-multipoint (PMP) mode
  • - multipoint-to-multipoint (mesh) mode
  • In the mesh mode
  • - nodes are organized in an ad-hoc fashion
  • - there still be certain nodes that provide the
    BS function

4
Introduction (2/3)
  • IEEE 802.16 has two mechanisms to schedule the
    data transmission in mesh mode
  • - centralized scheduling
  • - distributed scheduling
  • In centralized scheduling
  • - all the control and data packets need to go
    through the BS
  • - the scheduling procedure is simple
  • - but the connection setup delay is long

5
Introduction (3/3)
  • In distributed scheduling
  • - every node competes for channel access using a
    pseudo-random election algorithm based on the
    scheduling information of the two-hop neighbors
  • - exhibits better flexibility and scalability
  • - but distributed channel access control is more
    complex

6
Outline
  • Introduction
  • Background on IEEE 802.16 Mesh mode
  • Modelling and Performance Analysis
  • Simulation Results
  • Conclusions and Future Work

7
Background on IEEE 802.16 Mesh mode
  • the difference between 802.11 and 802.16
  • - 802.16 is a slotted system, and all
    transmissions must be synchronized
  • - 802.16 uses a three-way handshaking to set up
    connection before data transmission
  • - the control channel and data channel are
    separated in 802.16
  • - in 802.16, nodes can reserve multiple slots
    for the following packets without exchanging
    control message again

8
IEEE 802.16 Distributed Scheduling Algorithm (1/6)
  • IEEE 802.16 distributed scheduling behavior
  • - the control message and data packet are
    allocated in different time slots in a frame
  • - there is no contention in the data time slots
  • - employs a request/grant/confirm three-way
    handshaking procedure

9
IEEE 802.16 Distributed Scheduling Algorithm (2/6)
10
IEEE 802.16 Distributed Scheduling Algorithm (3/6)
  • The Scheduling message, MSH-DSCH, contains the
    schedule and data subframe allocation information
    of the neighborhood.
  • - NextXmtMx and XmtHoldoffExponent
  • The transmission time for a station is an
    aggregate of some sequential transmission
    opportunities called eligibility interval
  • The eligible interval length for a node is
  • transmission opportunities.

11
IEEE 802.16 Distributed Scheduling Algorithm (4/6)
  • After one eligibility interval, a station must
    hold off at least
  • One station sets the first transmission slot
    after the holdoff time as the temporary next
    transmission opportunity

12
IEEE 802.16 Distributed Scheduling Algorithm (5/6)


13
IEEE 802.16 Distributed Scheduling Algorithm (6/6)
  • Pseudo-random function
  • mixing value with the current node ID and
    the slot number as the inputs
  • The channel contention result is correlated with
    the total node number, exponent value and network
    topology.
  • Assumes the transmit time sequences of all the
    nodes in the control subframe form statistically
    independent renewal processes

14
Outline
  • Introduction
  • Background on IEEE 802.16 Mesh mode
  • Modelling and Performance Analysis
  • Simulation Results
  • Conclusions and Future Work

15
Modelling and Performance Analysis
  • Model and approach
  • Two scenario
  • - Collocated scenario
  • identical holdoff time
  • nonidentical holdoff exponents
  • - General topology scenario
  • Performance metrics estimation

16
Model and Approach (1/4)
  • Assumptions
  • (1) the counting process, , of each node
    eventually reaches its steady state and the
    intervals are i.i.d., that is, forms a
    stationary and ergodic renewal process
  • (2) the renewal processes of different nodes are
    mutually independent at their steady states
  • (3) when all the processes reach their steady
    states, we can assume that all the processes are
    initiated at t-8 and the time of renewal events
    of different processes are uncorrelated

17
Model and Approach (2/4)
18
Model and Approach (4/4)
the expected number of competing
nodes in slot s for the node of interest The
probability that this node wins the slot is
So the p.m.f. of S is
19
Collocated Scenario - Indentical Holdoff Exponent
(1/15)
  • In collocated scenario
  • - all nodes are one-hop neighbors of each other
  • Identical Holdoff Exponent
  • - assume equal holdoff exponents
  • - hence when the node are collocated, the
    transmission interval has the same
    distribution

20
Collocated Scenario - Indentical Holdoff Exponent
(2/15)
21
Collocated Scenario - Indentical Holdoff Exponent
(3/15)
  • LEMMA 1. (Limiting Distribution of Excess Time)
  • Let t be the renewal interval, the limiting
    distribution of the
  • excess time is
  • for fixed , where and
    is an indicator function.
  • By the stationary and ergodic assumption,

22
Collocated Scenario - Indentical Holdoff Exponent
(4/15)



23
Collocated Scenario - Indentical Holdoff Exponent
(5/15)
Figure 4T he interval t between two successive
transmissions.
24
Collocated Scenario - Indentical Holdoff Exponent
(6/15)
  • By the assumption that the renewal process is
    stationary and that the distributions of
    are identical, we can simply denote as
    .

25
Collocated Scenario - Indentical Holdoff Exponent
(7/15)

26
Collocated Scenario - Indentical Holdoff Exponent
(8/15)

27
Collocated Scenario - Indentical Holdoff Exponent
(9/15)

28
Collocated Scenario - Indentical Holdoff Exponent
(10/15)
  • denote as the number of nodes
    (among N-1 neighbors) which compete with node k
    in slot s.
  • Denote
    as
  • The expected number of nodes competing with node
    k in slot s is

29
Collocated Scenario - Indentical Holdoff Exponent
(11/15)
  • The competing nodes in slot s for node k is
  • Substituting (9) into (1) we get

30
Collocated Scenario - Indentical Holdoff Exponent
(12/15)
  • we make a further approximation that

31
Collocated Scenario - Indentical Holdoff Exponent
(13/15)
32
Collocated Scenario - Indentical Holdoff Exponent
(14/15)
33
Collocated Scenario - Indentical Holdoff Exponent
(15/15)
  • Substitute and
    into (17)

34
Collocated Scenario - Nondentical Holdoff
Exponents (1/9)
35
Collocated Scenario - Nondentical Holdoff
Exponents (2/9)
36
Collocated Scenario - Nondentical Holdoff
Exponents (3/9)


37
Collocated Scenario - Nondentical Holdoff
Exponents (4/9)
38
Collocated Scenario - Nondentical Holdoff
Exponents (5/9)
  • Assume that
    are geometrical distributed, that
  • is, assume

39
Collocated Scenario - Nondentical Holdoff
Exponents (6/9)
40
Collocated Scenario - Nondentical Holdoff
Exponents (7/9)
41
Collocated Scenario - Nondentical Holdoff
Exponents (8/9)
42
Collocated Scenario - Nondentical Holdoff
Exponents (9/9)
43
General topology scenario (1/3)
44
General topology scenario (2/3)
45
General topology scenario (3/3)
4
1
3
0
0
3
2
0
4
1
2
0
1
2
3
46
Performance metrics estimation
  • Let denote the time node A need to
    accomplish a three-way handshaking with node B.

47
Performance metrics estimation
  • Assumptions
  • - the renewal process of node A and B have run
    for a long time
  • - follows a limiting distribution as the
    excess time
  • when , we can assume that
  • when , we can assume that

48
Performance metrics estimation
  • where a is a compromising factor.
  • is a good choice for the
    identical holdoff exponent
  • case and for the
    nonidentical holdoff exponents
  • case

49
Performance metrics estimation
50
Outline
  • Introduction
  • Background on IEEE 802.16 Mesh mode
  • Modelling and Performance Analysis
  • Simulation Results
  • Conclusions and Future Work

51
Simulation Results
  • ns-2 simulator
  • - network controller
  • - scheduling controller
  • - data channel component
  • The set of possible exponent values is
    0,1,2,3,4

52
Transmission interval
Figure 9Simulation and analytical results on the
expected transmission intervals for the identical
exponent
53
Transmission interval
Figure 10Simulation and analytical results on
the expected transmission intervals for the
nonidentical exponent
54
Three-way Handshaking Time
Figure 11Simulation and analytical results on
the three-way handshaking time for the identical
exponent case
55
Three-way Handshaking Time
Figure 12Simulation and analytical results on
the three-way handshaking time for the
nonidentical exponent case with N 10
56
Three-way Handshaking Time
Figure 13Simulation and analytical results on
the three-way handshaking time for the
nonidentical exponent case with N 100
57
General Topology Scenario
Table 1Simulation and analytical results on the
expected transmission intervals for the general
topology
58
Outline
  • Introduction
  • Background on IEEE 802.16 Mesh mode
  • Modelling and Performance Analysis
  • Simulation Results
  • Conclusions and Future Work

59
Conclusions and Future Work (1/2)
  • The channel contention result is correlated with
    the total node number, exponent value and network
    topology.
  • developed methods for estimating the
    distributions of the node transmission interval
    and connection setup delay
  • also shed some light on the data subframe
    reservation scheme

60
Conclusions and Future Work (2/2)
  • Future work
  • - to propose such a reservation scheme taking
    into account the tradeoff between system resource
    utilization and the connection QoS requirements

61
Thanks for your listening
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