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Mobility-Aware Real-Time Scheduling for
Low-Power Wireless Networks
• Behnam Dezfouli
• Marjan Radi
• Octav Chipara
Contact:
http://behnam.dezfouli.com
dezfouli [at] ieee [dot] org
IEEE 35th International Conference on Computer Communications (INFOCOM’16)
10-15 April 2016 San Francisco, CA, USA
Department of Computer Science
The University of Iowa
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
Non Real-Time vs Real-Time Wireless Networks
2
Nodes contend for transmission
whenever they have data
Non Real-Time Networks
• Provide a best-effort service
• No guarantee of timeliness or
reliability
• Network dynamics affect the
service provided
• For example: Connecting
devices using WiFi
Real-Time Networks
• Packets should be delivered in a
timely and reliable manner
• Network dynamics do not affect
the service provided
• For example: Connecting
devices using WirelessHART
Nodes’ transmission schedules
are predetermined
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
• Wireless devices in industrial
applications: annual growth
rate of 27.2%
• 43.5 million devices by 2020
Industrial Real-Time Wireless Networks
3
Make wireless technology an attractive solution for
process monitoring and control applications
• Reducing the cost
• Simplifying the deployment
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
WirelessHART
4
4-20 mA
Access
Point
Access
Point
HART All-Digital Multidrop Mode
Security Manager
Network Manager
Host Application
(e.g. Asset Management)
Process Automation
Controller
AcAcAAccececesssssss
AcAcAcAccecececesssssss
WirelessHART
Devices
WirelessHART
Adapter
WirelessHART
Adapter
WirelessHART
Devices
WirelessHART
Gateway
WirelessHART
Gateway
Connections
HART-IP
Modbus
Ethernet
more
WIRELESSHART MESH NETWORK
HART Device +
WirelessHART Adapter
Non-HART Device +
WirelessHART Adapter
Time Slot
Channel
The schedules assigned
to the red and blue links
Courtesy of: Field Comm Group
Gateway is responsible
for managing medium
access schedules
Through time slot and
channel assignment
(FTDMA: Frequency-Time
Division Multiple Access)
Central Network Management
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
1. Shortcomings of contention-based medium access:
• Does not guarantee end-to-end delay
• Significant packet collision and loss
2. Shortcomings of distributed schedule-based medium access:
• Does not guarantee end-to-end delay
• Moderate packet loss due to intra-network interference
Why Centralized Medium Access Scheduling?
5
3. Benefits of centralized schedule-based medium access:
• Guaranteed end-to-end delay
• Avoids packet loss due to intra-network interference
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
Research Gap
6
Existing real-time wireless networks assume:
Nodes are stationary, and
The set of traffic flows are fixed
Limits the applicability of these solutions to dynamic
applications with mobile entities such as
patients, robots, firefighters, etc.
How to support real-time communication with mobile nodes?
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Objective
7
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Objective
Sample Application
8
— Timely and reliable delivery of patients’ vital signs to the Gateway
Gateway
Patient
(Mobile)
Ready Ready
Deadline Deadline
Time
Ready
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Basic Assumptions and Requirements
9
• Each mobile node can generate one or more data flows
• Each flow i is characterized by its period (Pi) and deadline (Di)
• The mobility pattern of the mobile nodes is unknown
• Packets of each data flow should be delivered to the Gateway
before their deadline
• For example:
• A mobile node samples heart rate every 1 sec
• The sample should be delivered to the Gateway no later than
0.9 sec after its generation
Ready Ready Ready
Deadline Deadline
Time
Objective 9
packet
generation
packet
delivery
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
10
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Architecture
11
A Low-Power Wireless Infrastructure Node
• Communicates in a real-time manner with the Gateway Gateway
• Communicates with the nodes
• Computes and distributes
nodes’ schedules
A Low-Power Wireless Mobile Node
• Communicates in a real-time manner
with the Gateway
Communication Between
Infrastructure Nodes
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Architecture
12
• Base stations are connected
through wire links
• Similar to cellular (3G, 4G) and most
WiFi networks
• Hard network deployment
• Bandwidth reservation only between
mobile-infrastructure
• A multi-hop wireless infrastructure
• Easy network deployment
• Bandwidth reservation between
infrastructure-infrastructure as well as
mobile-infrastructure
Wireless Link Wire LinkWire Link
Wireless
Link
Wireless
Link
Wireless
Link
Wired infrastructure
Wireless infrastructure (our choice)
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Implication of Assumptions on Scheduling
13
Unpredictable mobility paths
Low energy consumption:
Short communication ranges
The need to deliver data in a timely
and reliable manner
How these assumptions affect
our network design?
Network Design
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Mobility and Data Forwarding Paths
14
Low
Power Consumption
Short
Communication Range
Frequent
Association with
Infrastructure Nodes
Frequent
Changes in Data
Forwarding Paths
Bandwidth Reservation
Upon Node Admission
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Two Bandwidth Reservation Strategies
15
• Whenever a mobile node needs to communicate over a path, it sends a
request to the Gateway
• Shortcoming #1: Huge bandwidth should be reserved for
exchanging control data
• Gateway performs bandwidth reservation over the new communication
path after receiving a request
• Shortcoming #2: The Gateway may not be able to reserve bandwidth
over the new communication path: CONNECTION LOSS!
1: On-Demand Bandwidth Reservation
Mobile
Node
Gateway
Request for bandwidth
reservation over Path i
New transmission schedules
Mobile
Node
Gateway
Request for bandwidth
reservation over Path i
Failed scheduling
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Two Bandwidth Reservation Strategies
16
• Bandwidth is reserved over all the potential communication paths
upon node join
• Gateway admits a mobile node if bandwidth reservation over all the
potential communications paths was successful
• Shortcoming: If performed naively, the number of admitted mobile
nodes would be very small
• We propose techniques to address this shortcoming
2: On-Join Bandwidth Reservation (our choice)
Mobile
Node
Gateway
Request for admission
Successful scheduling:
New transmission schedules
Unsuccessful scheduling:
Rejection
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Mobile Node Admission
17
Admitting a mobile node:
1. Beaconing:
• Infrastructure nodes periodically broadcast beacon packets
• Mobile node can discover nearby infrastructure nodes
2. Request for Join:
• Mobile node sends a request for join
• Infrastructure nodes forward the request towards the Gateway
3. Schedule Computation and Dissemination
• The Gateway computes a new schedule to accommodate for the new
node
• Infrastructure nodes distribute the computed schedule
• The mobile node receives the schedule
Network Design 17
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: First Step
18
1. Beaconing
• Infrastructure nodes regularly broadcast beacon packets
• Mobile nodes discover nearby nodes
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: Second Step
19
2. Join Request
• The mobile node sends a join request
• Infrastructure nodes forward the request to the Gateway
• Gateway decides about the admission of the mobile node
Gateway implements a scheduling algorithm that
reserves bandwidth for the new mobile node
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: Third Step
20
3. Schedule Computation and Dissemination
If:
The mobile node can be admitted
Then:
Distribute transmission schedules
How much data
should be
distributed?
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Schedule Computation and Dissemination
21
How much data should be distributed when a mobile node is admitted?
Existing scheduling strategies:
Scheduling a new flow may modify
the schedules of existing flows
Every admission requires distributing the transmissions of:
new mobile node + existing mobile nodes
A huge amount of control data should be distributed after each join
Long node admission delay
Increasing #Admitted Nodes Increasing Admission Delay
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Observations
22
We should employ on-join scheduling instead of on-demand scheduling
Observation 1
We propose mechanisms that increase real-time capacity
We should minimize the amount of
control data required for schedule dissemination
We propose additive scheduling
Contribution:
Observation 2
Contribution:
Network Design 22
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
23
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Mobility, Association, and Routing Paths
24
• To forward a flow i:
• M associates with infrastructures nodes, depending on its location
— On-join bandwidth reservation:
• Reserve bandwidth for M over all the potential communication paths
• How a scheduling algorithm designed for stationary real-time networks
would perform the scheduling?
• We refer to this algorithm as Static Real-time Scheduling (SRS)
Potential Communication Paths
A
B
C
E
D
MPath 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
25
The scheduling matrix produced by SRS
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA CA
c2 EC DC BA
c3
…
This schedule is inefficient !
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
A
B
C
E
D
M
Scheduling Constraints:
• A node cannot send and receive simultaneously
• On a path, a transmission BC can be scheduled
after transmission AB has been scheduled
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
26
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME
c2
c3
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
highest depth:
higher priority
lowest depth:
lower priority
D = 1
D = 2
D = 2
D = 3
D = 3
Potential Communication Paths
A
B
C
E
D
M
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
27
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD
c2 EC
c3
…
ready transmissions =
{(MD), (EC), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
28
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB
c2 EC DC
c3
…
ready transmissions =
{(MB), (MC), (DC), (MA), (CA)}
D = 1
D = 2
D = 2
D = 2
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 DC CA
Path 5 CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
29
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC
c2 EC DC BA
c3
…
ready transmissions =
{(MC), (BA), (MA), (CA), (CA)}
D = 1
D = 1
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 BA
Path 3 MC CA
Path 4 CA
Path 5 CA
D = 1
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
30
ready transmissions =
{(MA), (CA), (CA), (CA)}
D = 1
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1 MA
Path 2
Path 3 CA
Path 4 CA
Path 5 CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Static Real-time Scheduling
31
ready transmissions =
{(CA), (CA), (CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA
c2 EC DC BA
c3
…
SRS: Static Real-time Scheduling
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4 CA
Path 5 CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
32
ready transmissions =
{(CA), (CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4 CA
Path 5
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
33
ready transmissions =
{(CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA CA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4
Path 5
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Path-Dependent Schedule Activation
34
CA BAMB
period k:
Data forwarding over Path 5
period k+1:
Data forwarding over Path 2
Path-Dependent Schedule Activation
ECME
CACACAMA
MC
BA
period k period k+1
Actual Transmission Schedules Assignment
MB
DC
MD
EC
ME CACACAMA
MC
BA
MB
DC
MD
EC
ME
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
35
For a flow i, two transmissions belonging to two different paths
can be combined in one entry of the scheduling matrix.
A
B
C
E
D
M
For Example:
• Transmissions (MA), (MB), (MC), (MD) and (ME) can be combined.
• Transmissions (MC), (DC) and (EC) can be combined.
• …
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
36
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
37
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
…
ready transmissions =
{(BA), (CA), (DC), (EC)}
D = 2
D = 1
D = 2
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2 BA
Path 3 CA
Path 4 DC CA
Path 5 EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
38
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
CA
CA
…
ready transmissions =
{(CA), (CA)}
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4 CA
Path 5 CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
39
The scheduling matrix produced by employing:
Schedule Combination
3 entries of the scheduling matrix are used
We have scheduled the five paths more efficiently
However:
Data flows over these five paths can be coordinated
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
CA
CA
…
We propose the Flow Coordination technique to:
Reduce the number of transmissions scheduled in each entry
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
40
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
Without Flow Coordination With Flow Coordination
Transmission CA is scheduled once
after transmissions MC, DC, and EC have been scheduled
Replicated transmission schedules can be eliminated through
coordinating the scheduling of potential communication paths
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
41
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
42
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
…
ready transmissions =
{(BA), (DC), (EC)}
D = 1
D = 2
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2 BA
Path 3
Path 4 DC
Path 5 EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
43
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
…
ready transmissions =
{(CA)}
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4
Path 5 CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
44
0 1 2 …
A
B
C
D
E
For Example:
Using forward scheduling, node A is blocked
in 3 slots, i.e., node A cannot be used for
scheduling other flows in time slots 0, 1, 2
• So far we have employed “forward scheduling”
—Forward Scheduling:
• We perform link scheduling starting from the flow generator
—Cannot effectively use the schedule combination technique
0 1 2 ..
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
……
A
B
C
E
D
M
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
45
—Forward Scheduling:
• The set of ready transmissions initially includes the transmissions that
origin from the flow generator
• Scheduling is started from time slot 0
Unfortunately, forward scheduling does not effectively benefit from the
schedule combination technique we proposed earlier
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
Transmissions MA and BA could be
scheduled in the same entry as that of CA
Blocking slots of A is
reduced from 3 to 1
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
46
• We propose “Reverse Scheduling” to improve schedule combination
—Reverse Scheduling:
• We perform link scheduling from the destination
… 5 6 7
A
B
C
D
E
For Example:
Using reverse scheduling, node A is
blocked in 1 slot only.
… 5 6 7
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
……
A
B
C
E
D
M
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
47
• To improve the efficiency of Flow Merging, we propose “Reverse Scheduling”
—Reverse Scheduling:
• The set of ready transmissions initially includes the transmissions that
deliver a flow to its destination
• Scheduling is started from the deadline of the flow
Forward
Scheduling
Reverse
Scheduling
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
48
0 1 2 3 4 5 6 7 8 9 10 …
c1
MA
BA
CA
…
ready transmissions =
{(CA), (BA), (MA)}
D = 1
D = 1
D = 1
Potential Communication Paths
A
B
C
E
D
M
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
49
0 1 2 3 4 5 6 7 8 9 10 …
c1
MB
DC
EC
MC
MA
BA
CA
…
ready transmissions =
{(MB), (DC), (EC), (MC)}
D = 2
D = 2
D = 2A
B
C
E
D
M
D = 2
Potential Communication Paths
Path 1
Path 2 MB
Path 3 MC
Path 4 MD DC
Path 5 ME EC
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
50
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
…
ready transmissions =
{(ME), (MD)}
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4 MD
Path 5 ME
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Slot Blocking: Forward and Reverse Scheduling
51
0 1 2 ..
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
……
0 1 2 …
A
B
C
D
E
Slot Blocking with “Forward Scheduling”
… 5 6 7
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
……
… 5 6 7
A
B
C
D
E
Slot Blocking with “Reverse Scheduling”
blocked in
3 slots
blocked in
1 slot
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS)
52
Request for Admission
Reserve bandwidth for:
new mobile node + existing nodes
Distribute the schedules for:
new mobile node + existing nodes
Reject
Approve
FO-MARS
Gateway
— Input:
• new mobile node’s flows +
existing flows
— Output:
• Approve: The algorithm has
scheduled all the flows
• Reject: The algorithm cannot
schedule all the flows
— Operation Summary:
• Schedule flows in the order of
their deadlines
• Employ the techniques we
proposed earlier
FO-MARS
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Algorithm may-schedule()
53Frequency-Time Division Multiple Access
In time slot s, what is the best
channel in which the given
transmission can be scheduled?
This is the best channel found
Based on the rules presented earlier
Scheduling
Matrix
Start
sender | receiver | flow: i | slot | scheduling matrix: S
sender or
receiver used
for scheduling
another flow?
A channel in
which sender or
receiver have
been used?
A channel in which
a transmission of
flow i has been
scheduled?
return
None
return
channel
Yes
Yes
No No
return
channel
Yes
An empty
channel?
return
channel
Yes
No
No
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
54
• Schedules one flow at a time
• The order of flow scheduling is based on flows’ deadlines
NOTE: Scheduling a flow with longer period may reduce the schedulability
chance of flows with shorter periods…
EXAMPLE:
• f1:<m1, 32, 32> requires 4 transmissions
• f2:<m2, 8, 8> requires 4 transmissions
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
We cannot
schedule f2 here
Ordering 1: f1:<m1, 32, 32> , then f2:<m2, 8, 8>
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Ordering 2: f2:<m2, 8, 8>, then f1:<m1, 32, 32>
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
55
Two shortcomings of FO-MARS:
1. When a request for bandwidth reservation is received, all the existing
flows with shorter period must also be rescheduled
Significant control data dissemination
Long node join delay
2. A newly received schedule can be used at the beginning of the next
hyper period
Long node join delay
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
56
We cannot switch to a new scheduling matrix at any time
✦ Example:
… s-1 s s+1 s+2 …
*
… s-1 s s+1 s+2 …
*
Reception of new
scheduling matrix
Existing Scheduling Matrix New Scheduling Matrix
Switch to the new
scheduling matrix
Transmission * never happens
because that is scheduled for slot
s in the new scheduling matrix
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS)
57
Request for Admission
Reserve bandwidth for:
new mobile node + existing nodes
Distribute the schedules for:
new mobile node + existing nodes
Reject
Approve
FO-MARS
Gateway
Request for
Node Admission
All the red schedules
should be disseminated
LONG
Node Admission Delay
Problem
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Additive Mobility-Aware Real-Time Scheduling (A-MARS)
58
Request for Admission
Reserve bandwidth for:
new mobile node
Distribute the schedules for:
new mobile node
Reject
Approve
A-MARS
Gateway
Request for
Node Admission
Only the red schedules
should be disseminated
SHORT
Node Admission DelayProblem Solved
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Challenge of Additive Scheduling
59
time
The flows of each node should be scheduled
so that future mobile nodes can be scheduled as well
A B C
We need a smart bandwidth reservation algorithm that
predicts the future to enhance the schedulability of future flows
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Challenge of Additive Scheduling
60
• Assume Pγ = 16 and Pβ = 8
• γ and β require 5 transmissions
• γ and β cannot be scheduled using the same time slots
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow γ (Scheduling ok!)
γ γ γ γ γ
nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling fail!)
β β β β β γ γ γ γ γ
Failed admission of flow β
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow γ (Scheduling ok!)
γ γ γ γ γ
nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling ok!)
β β β β β γ γ β β β β β γ γ γ
Successful admission of flow β
How to know which slots should be used for scheduling a flow?
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow Classes and Slot Prioritization
61
• Assume the network services a set of flow classes γ, β, α,…
• All the flows in a flow class have similar period and deadline
• We prepare a prioritized list of slots for scheduling each flow class
How using a slot for
scheduling γ would affect
the schedulability of β and α
Prepare a prioritized list of
slots for scheduling a flow γ
For flow class γ : Flow
Class
Period/
Deadline
Heart
Rate
γ Pγ, Dγ
Pulse
Oximetry
β Pβ , Dβ
Blood
Pressure
α Pα, Dα
Dα < Dβ < Dγ
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Slot Prioritization
62
• We propose the notion of Potential Utilization (PU) to measure the
effect of choosing each slot
Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow β n+1th Period of flow β
PU for class β 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31
Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow β n+1th Period of flow β
PU for class β 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31
Choose slot 7 and update PU
choosing from these slots:
increase PU by 0.31
choosing from these slots:
increase PU by 0.39
demand = percentage of flows belonging to class β x #required transmissions
available slots
(0.5 X 5)/8
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
63
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
• Correctness depends on both functionality and timeliness
• Real-time networks are required for mission-critical applications
• Mission-critical applications:
• Industrial process control
• Clinical patient monitoring
• …
• Several organizations: HART, ISA, WINA, ZigBee
Setup
64
Mobility Paths
Links of the Routing Graph
Infrastructure Nodes
Gateway
• Trace-driven simulator using exhaustive floor plan measurements
• Realistic and repeatable experimentation
Performance Evaluation
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Flow Period [second]
(a)
0.64 1.28 2.56 5.12
MaxMobil
0
50
100
Flow Period [second]
(b)
0.64,1.28,2.56 0.64,1.28,5.12 0.64,2.56,5.12 1.28,2.56,5.12
MaxMobileNodesSupported
0
10
20
30
40
50
60
70
80
90
100
Performance Evaluation
Scalability: How Many Mobile Nodes can be Supported?
65
Mobile nodes generate
reports with different rates
FO-MARS vs SRS
14x
5.12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
Proposed Algorithms
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
Admission Delay
66
Number of Mobile Nodes
(a)
10 20 30 40 50
AdmissionDelay[s]
0
50
100
150
200
250
Flow Period = 1:28
Number of Mobile Nodes
(b)
50 100 150
AdmissionDelay[s]
0
50
100
150
200
250
Flow Period = 5:12
Number of Mobile Nodes
(c)
10 20 30 40 50
AdmissionDelay[s]
0
100
200
300
400
Flow Period 2f0:64; 1:28; 2:56g
Number of Mobile Nodes
(d)
20 40 60 80 100
AdmissionDelay[s]
0
100
200
300
400
Flow Period 2f1:28; 2:56; 5:12g
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
= 1:28
missionDelay[s]
50
100
150
200
250
Flow Period = 5:12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
Proposed Algorithms
A-MARS’S Admission delay
< 20 seconds
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
Network Lifetime
67
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
= 1:28
missionDelay[s]
50
100
150
200
250
Flow Period = 5:12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
Proposed Algorithms
odes
70
Number of Mobile Nodes
(b)
10 20 30 40
NodeLifetime[hour]
500
1000
1500
2000
2500
3000
3500
Pdata 2f64; 128; 256g
Number of Mobile Nodes
(c)
10 20 30 40 50 60
NodeLifetime[hour]
0
1000
2000
3000
4000
5000
6000
7000
Flow Period 2f1:28; 2:56; 5:12g
LLF-ESRS LLF-CERS FO-MARS A-MARS
Higher network lifetime
achieved with
FO-MARS and A-MARS
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Conclusion
68
• Real-time wireless networks can be used in mission-critical
applications such as industrial process control and medical
monitoring
• Existing real-time networks do not efficiently handle network
dynamics such as mobility and flow addition/removal
• We proposed scheduling techniques for efficient bandwidth
reservation for mobile nodes
• We proposed an additive scheduling algorithm for effective
handling of flow admission and removal
• Compared to the algorithms designed for stationary real-time
networks, our proposed network admits a significantly higher
number of mobile nodes, archives short admission delay, and
handles network dynamics efficiently
Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Acknowledgement
69
Behnam Dezfouli
University of Iowa
Iowa City, IA, USA
Marjan Radi
University of Iowa
Iowa City, IA, USA
Octav Chipara
University of Iowa
Iowa City, IA, USA
This work was supported by
the National Science Foundation and
the Roy J. Carver Charitable Trust

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Mobility-Aware Real-Time Scheduling for Low-Power Wireless Networks

  • 1. Mobility-Aware Real-Time Scheduling for Low-Power Wireless Networks • Behnam Dezfouli • Marjan Radi • Octav Chipara Contact: http://behnam.dezfouli.com dezfouli [at] ieee [dot] org IEEE 35th International Conference on Computer Communications (INFOCOM’16) 10-15 April 2016 San Francisco, CA, USA Department of Computer Science The University of Iowa
  • 2. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Introduction Non Real-Time vs Real-Time Wireless Networks 2 Nodes contend for transmission whenever they have data Non Real-Time Networks • Provide a best-effort service • No guarantee of timeliness or reliability • Network dynamics affect the service provided • For example: Connecting devices using WiFi Real-Time Networks • Packets should be delivered in a timely and reliable manner • Network dynamics do not affect the service provided • For example: Connecting devices using WirelessHART Nodes’ transmission schedules are predetermined
  • 3. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Introduction • Wireless devices in industrial applications: annual growth rate of 27.2% • 43.5 million devices by 2020 Industrial Real-Time Wireless Networks 3 Make wireless technology an attractive solution for process monitoring and control applications • Reducing the cost • Simplifying the deployment
  • 4. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Introduction WirelessHART 4 4-20 mA Access Point Access Point HART All-Digital Multidrop Mode Security Manager Network Manager Host Application (e.g. Asset Management) Process Automation Controller AcAcAAccececesssssss AcAcAcAccecececesssssss WirelessHART Devices WirelessHART Adapter WirelessHART Adapter WirelessHART Devices WirelessHART Gateway WirelessHART Gateway Connections HART-IP Modbus Ethernet more WIRELESSHART MESH NETWORK HART Device + WirelessHART Adapter Non-HART Device + WirelessHART Adapter Time Slot Channel The schedules assigned to the red and blue links Courtesy of: Field Comm Group Gateway is responsible for managing medium access schedules Through time slot and channel assignment (FTDMA: Frequency-Time Division Multiple Access) Central Network Management
  • 5. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Introduction 1. Shortcomings of contention-based medium access: • Does not guarantee end-to-end delay • Significant packet collision and loss 2. Shortcomings of distributed schedule-based medium access: • Does not guarantee end-to-end delay • Moderate packet loss due to intra-network interference Why Centralized Medium Access Scheduling? 5 3. Benefits of centralized schedule-based medium access: • Guaranteed end-to-end delay • Avoids packet loss due to intra-network interference
  • 6. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Introduction Research Gap 6 Existing real-time wireless networks assume: Nodes are stationary, and The set of traffic flows are fixed Limits the applicability of these solutions to dynamic applications with mobile entities such as patients, robots, firefighters, etc. How to support real-time communication with mobile nodes?
  • 7. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Objective 7
  • 8. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Objective Sample Application 8 — Timely and reliable delivery of patients’ vital signs to the Gateway Gateway Patient (Mobile) Ready Ready Deadline Deadline Time Ready
  • 9. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Basic Assumptions and Requirements 9 • Each mobile node can generate one or more data flows • Each flow i is characterized by its period (Pi) and deadline (Di) • The mobility pattern of the mobile nodes is unknown • Packets of each data flow should be delivered to the Gateway before their deadline • For example: • A mobile node samples heart rate every 1 sec • The sample should be delivered to the Gateway no later than 0.9 sec after its generation Ready Ready Ready Deadline Deadline Time Objective 9 packet generation packet delivery
  • 10. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design 10
  • 11. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Architecture 11 A Low-Power Wireless Infrastructure Node • Communicates in a real-time manner with the Gateway Gateway • Communicates with the nodes • Computes and distributes nodes’ schedules A Low-Power Wireless Mobile Node • Communicates in a real-time manner with the Gateway Communication Between Infrastructure Nodes
  • 12. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Architecture 12 • Base stations are connected through wire links • Similar to cellular (3G, 4G) and most WiFi networks • Hard network deployment • Bandwidth reservation only between mobile-infrastructure • A multi-hop wireless infrastructure • Easy network deployment • Bandwidth reservation between infrastructure-infrastructure as well as mobile-infrastructure Wireless Link Wire LinkWire Link Wireless Link Wireless Link Wireless Link Wired infrastructure Wireless infrastructure (our choice)
  • 13. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Implication of Assumptions on Scheduling 13 Unpredictable mobility paths Low energy consumption: Short communication ranges The need to deliver data in a timely and reliable manner How these assumptions affect our network design? Network Design
  • 14. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Mobility and Data Forwarding Paths 14 Low Power Consumption Short Communication Range Frequent Association with Infrastructure Nodes Frequent Changes in Data Forwarding Paths Bandwidth Reservation Upon Node Admission
  • 15. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Two Bandwidth Reservation Strategies 15 • Whenever a mobile node needs to communicate over a path, it sends a request to the Gateway • Shortcoming #1: Huge bandwidth should be reserved for exchanging control data • Gateway performs bandwidth reservation over the new communication path after receiving a request • Shortcoming #2: The Gateway may not be able to reserve bandwidth over the new communication path: CONNECTION LOSS! 1: On-Demand Bandwidth Reservation Mobile Node Gateway Request for bandwidth reservation over Path i New transmission schedules Mobile Node Gateway Request for bandwidth reservation over Path i Failed scheduling
  • 16. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Two Bandwidth Reservation Strategies 16 • Bandwidth is reserved over all the potential communication paths upon node join • Gateway admits a mobile node if bandwidth reservation over all the potential communications paths was successful • Shortcoming: If performed naively, the number of admitted mobile nodes would be very small • We propose techniques to address this shortcoming 2: On-Join Bandwidth Reservation (our choice) Mobile Node Gateway Request for admission Successful scheduling: New transmission schedules Unsuccessful scheduling: Rejection
  • 17. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Mobile Node Admission 17 Admitting a mobile node: 1. Beaconing: • Infrastructure nodes periodically broadcast beacon packets • Mobile node can discover nearby infrastructure nodes 2. Request for Join: • Mobile node sends a request for join • Infrastructure nodes forward the request towards the Gateway 3. Schedule Computation and Dissemination • The Gateway computes a new schedule to accommodate for the new node • Infrastructure nodes distribute the computed schedule • The mobile node receives the schedule Network Design 17
  • 18. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Admission: First Step 18 1. Beaconing • Infrastructure nodes regularly broadcast beacon packets • Mobile nodes discover nearby nodes
  • 19. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Admission: Second Step 19 2. Join Request • The mobile node sends a join request • Infrastructure nodes forward the request to the Gateway • Gateway decides about the admission of the mobile node Gateway implements a scheduling algorithm that reserves bandwidth for the new mobile node
  • 20. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Admission: Third Step 20 3. Schedule Computation and Dissemination If: The mobile node can be admitted Then: Distribute transmission schedules How much data should be distributed?
  • 21. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Network Design Schedule Computation and Dissemination 21 How much data should be distributed when a mobile node is admitted? Existing scheduling strategies: Scheduling a new flow may modify the schedules of existing flows Every admission requires distributing the transmissions of: new mobile node + existing mobile nodes A huge amount of control data should be distributed after each join Long node admission delay Increasing #Admitted Nodes Increasing Admission Delay
  • 22. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Observations 22 We should employ on-join scheduling instead of on-demand scheduling Observation 1 We propose mechanisms that increase real-time capacity We should minimize the amount of control data required for schedule dissemination We propose additive scheduling Contribution: Observation 2 Contribution: Network Design 22
  • 23. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access 23
  • 24. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Mobility, Association, and Routing Paths 24 • To forward a flow i: • M associates with infrastructures nodes, depending on its location — On-join bandwidth reservation: • Reserve bandwidth for M over all the potential communication paths • How a scheduling algorithm designed for stationary real-time networks would perform the scheduling? • We refer to this algorithm as Static Real-time Scheduling (SRS) Potential Communication Paths A B C E D MPath 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 ME EC CA
  • 25. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 25 The scheduling matrix produced by SRS 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC MA CA CA CA c2 EC DC BA c3 … This schedule is inefficient ! Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 ME EC CA A B C E D M Scheduling Constraints: • A node cannot send and receive simultaneously • On a path, a transmission BC can be scheduled after transmission AB has been scheduled
  • 26. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 26 0 1 2 3 4 5 6 7 8 9 10 … c1 ME c2 c3 … ready transmissions = {(ME), (MD), (MC), (MB), (MA)} highest depth: higher priority lowest depth: lower priority D = 1 D = 2 D = 2 D = 3 D = 3 Potential Communication Paths A B C E D M Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 ME EC CA
  • 27. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 27 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD c2 EC c3 … ready transmissions = {(MD), (EC), (MC), (MB), (MA)} D = 1 D = 2 D = 2 D = 3 D = 2 A B C E D M Potential Communication Paths Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 EC CA
  • 28. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 28 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB c2 EC DC c3 … ready transmissions = {(MB), (MC), (DC), (MA), (CA)} D = 1 D = 2 D = 2 D = 2 D = 1 A B C E D M Potential Communication Paths Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 DC CA Path 5 CA
  • 29. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 29 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC c2 EC DC BA c3 … ready transmissions = {(MC), (BA), (MA), (CA), (CA)} D = 1 D = 1 D = 2 A B C E D M Potential Communication Paths Path 1 MA Path 2 BA Path 3 MC CA Path 4 CA Path 5 CA D = 1
  • 30. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 30 ready transmissions = {(MA), (CA), (CA), (CA)} D = 1 D = 1 A B C E D M 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC MA c2 EC DC BA c3 … Potential Communication Paths Path 1 MA Path 2 Path 3 CA Path 4 CA Path 5 CA
  • 31. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Static Real-time Scheduling 31 ready transmissions = {(CA), (CA), (CA)} D = 1 A B C E D M 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC MA CA c2 EC DC BA c3 … SRS: Static Real-time Scheduling Potential Communication Paths Path 1 Path 2 Path 3 CA Path 4 CA Path 5 CA
  • 32. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 32 ready transmissions = {(CA), (CA)} D = 1 A B C E D M 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC MA CA CA c2 EC DC BA c3 … Potential Communication Paths Path 1 Path 2 Path 3 CA Path 4 CA Path 5
  • 33. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access SRS: Static Real-time Scheduling 33 ready transmissions = {(CA)} D = 1 A B C E D M 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB MC MA CA CA CA c2 EC DC BA c3 … Potential Communication Paths Path 1 Path 2 Path 3 CA Path 4 Path 5
  • 34. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Path-Dependent Schedule Activation 34 CA BAMB period k: Data forwarding over Path 5 period k+1: Data forwarding over Path 2 Path-Dependent Schedule Activation ECME CACACAMA MC BA period k period k+1 Actual Transmission Schedules Assignment MB DC MD EC ME CACACAMA MC BA MB DC MD EC ME
  • 35. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 1: Schedule Combination 35 For a flow i, two transmissions belonging to two different paths can be combined in one entry of the scheduling matrix. A B C E D M For Example: • Transmissions (MA), (MB), (MC), (MD) and (ME) can be combined. • Transmissions (MC), (DC) and (EC) can be combined. • …
  • 36. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 1: Schedule Combination 36 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA … ready transmissions = {(ME), (MD), (MC), (MB), (MA)} D = 1 D = 2 D = 2 D = 3 D = 3 A B C E D M Potential Communication Paths Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 ME EC CA
  • 37. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 1: Schedule Combination 37 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA CA DC EC … ready transmissions = {(BA), (CA), (DC), (EC)} D = 2 D = 1 D = 2 D = 2 A B C E D M Potential Communication Paths Path 1 Path 2 BA Path 3 CA Path 4 DC CA Path 5 EC CA
  • 38. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 1: Schedule Combination 38 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA CA DC EC CA CA … ready transmissions = {(CA), (CA)} D = 1 A B C E D M Potential Communication Paths Path 1 Path 2 Path 3 Path 4 CA Path 5 CA
  • 39. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 1: Schedule Combination 39 The scheduling matrix produced by employing: Schedule Combination 3 entries of the scheduling matrix are used We have scheduled the five paths more efficiently However: Data flows over these five paths can be coordinated 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA CA DC EC CA CA … We propose the Flow Coordination technique to: Reduce the number of transmissions scheduled in each entry
  • 40. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 2: Flow Coordination 40 Path 1 MA Path 2 MB BA Path 3 MC Path 4 MD DC Path 5 ME EC CA Path 1 MA Path 2 MB BA Path 3 MC CA Path 4 MD DC CA Path 5 ME EC CA Without Flow Coordination With Flow Coordination Transmission CA is scheduled once after transmissions MC, DC, and EC have been scheduled Replicated transmission schedules can be eliminated through coordinating the scheduling of potential communication paths
  • 41. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 2: Flow Coordination 41 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA … ready transmissions = {(ME), (MD), (MC), (MB), (MA)} D = 1 D = 2 D = 2 D = 3 D = 3 A B C E D M Potential Communication Paths Path 1 MA Path 2 MB BA Path 3 MC Path 4 MD DC Path 5 ME EC CA
  • 42. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 2: Flow Coordination 42 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA DC EC … ready transmissions = {(BA), (DC), (EC)} D = 1 D = 2 D = 2 A B C E D M Potential Communication Paths Path 1 Path 2 BA Path 3 Path 4 DC Path 5 EC CA
  • 43. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 2: Flow Coordination 43 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA DC EC CA … ready transmissions = {(CA)} D = 1 A B C E D M Potential Communication Paths Path 1 Path 2 Path 3 Path 4 Path 5 CA
  • 44. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 44 0 1 2 … A B C D E For Example: Using forward scheduling, node A is blocked in 3 slots, i.e., node A cannot be used for scheduling other flows in time slots 0, 1, 2 • So far we have employed “forward scheduling” —Forward Scheduling: • We perform link scheduling starting from the flow generator —Cannot effectively use the schedule combination technique 0 1 2 .. c1 ME MD MC MB MA BA DC EC CA …… A B C E D M
  • 45. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 45 —Forward Scheduling: • The set of ready transmissions initially includes the transmissions that origin from the flow generator • Scheduling is started from time slot 0 Unfortunately, forward scheduling does not effectively benefit from the schedule combination technique we proposed earlier 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MC MB MA BA DC EC CA Transmissions MA and BA could be scheduled in the same entry as that of CA Blocking slots of A is reduced from 3 to 1
  • 46. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 46 • We propose “Reverse Scheduling” to improve schedule combination —Reverse Scheduling: • We perform link scheduling from the destination … 5 6 7 A B C D E For Example: Using reverse scheduling, node A is blocked in 1 slot only. … 5 6 7 c1 ME MD MB DC EC MC MA BA CA …… A B C E D M
  • 47. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 47 • To improve the efficiency of Flow Merging, we propose “Reverse Scheduling” —Reverse Scheduling: • The set of ready transmissions initially includes the transmissions that deliver a flow to its destination • Scheduling is started from the deadline of the flow Forward Scheduling Reverse Scheduling
  • 48. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 48 0 1 2 3 4 5 6 7 8 9 10 … c1 MA BA CA … ready transmissions = {(CA), (BA), (MA)} D = 1 D = 1 D = 1 Potential Communication Paths A B C E D M Path 1 MA Path 2 MB BA Path 3 MC Path 4 MD DC Path 5 ME EC CA
  • 49. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 49 0 1 2 3 4 5 6 7 8 9 10 … c1 MB DC EC MC MA BA CA … ready transmissions = {(MB), (DC), (EC), (MC)} D = 2 D = 2 D = 2A B C E D M D = 2 Potential Communication Paths Path 1 Path 2 MB Path 3 MC Path 4 MD DC Path 5 ME EC
  • 50. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Technique 3: Reverse Scheduling 50 0 1 2 3 4 5 6 7 8 9 10 … c1 ME MD MB DC EC MC MA BA CA … ready transmissions = {(ME), (MD)} D = 3 D = 3 A B C E D M Potential Communication Paths Path 1 Path 2 Path 3 Path 4 MD Path 5 ME
  • 51. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Slot Blocking: Forward and Reverse Scheduling 51 0 1 2 .. c1 ME MD MC MB MA BA DC EC CA …… 0 1 2 … A B C D E Slot Blocking with “Forward Scheduling” … 5 6 7 c1 ME MD MB DC EC MC MA BA CA …… … 5 6 7 A B C D E Slot Blocking with “Reverse Scheduling” blocked in 3 slots blocked in 1 slot
  • 52. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS) 52 Request for Admission Reserve bandwidth for: new mobile node + existing nodes Distribute the schedules for: new mobile node + existing nodes Reject Approve FO-MARS Gateway — Input: • new mobile node’s flows + existing flows — Output: • Approve: The algorithm has scheduled all the flows • Reject: The algorithm cannot schedule all the flows — Operation Summary: • Schedule flows in the order of their deadlines • Employ the techniques we proposed earlier FO-MARS
  • 53. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Algorithm may-schedule() 53Frequency-Time Division Multiple Access In time slot s, what is the best channel in which the given transmission can be scheduled? This is the best channel found Based on the rules presented earlier Scheduling Matrix Start sender | receiver | flow: i | slot | scheduling matrix: S sender or receiver used for scheduling another flow? A channel in which sender or receiver have been used? A channel in which a transmission of flow i has been scheduled? return None return channel Yes Yes No No return channel Yes An empty channel? return channel Yes No No
  • 54. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS) 54 • Schedules one flow at a time • The order of flow scheduling is based on flows’ deadlines NOTE: Scheduling a flow with longer period may reduce the schedulability chance of flows with shorter periods… EXAMPLE: • f1:<m1, 32, 32> requires 4 transmissions • f2:<m2, 8, 8> requires 4 transmissions 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 We cannot schedule f2 here Ordering 1: f1:<m1, 32, 32> , then f2:<m2, 8, 8> 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Ordering 2: f2:<m2, 8, 8>, then f1:<m1, 32, 32>
  • 55. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS) 55 Two shortcomings of FO-MARS: 1. When a request for bandwidth reservation is received, all the existing flows with shorter period must also be rescheduled Significant control data dissemination Long node join delay 2. A newly received schedule can be used at the beginning of the next hyper period Long node join delay
  • 56. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS) 56 We cannot switch to a new scheduling matrix at any time ✦ Example: … s-1 s s+1 s+2 … * … s-1 s s+1 s+2 … * Reception of new scheduling matrix Existing Scheduling Matrix New Scheduling Matrix Switch to the new scheduling matrix Transmission * never happens because that is scheduled for slot s in the new scheduling matrix
  • 57. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS) 57 Request for Admission Reserve bandwidth for: new mobile node + existing nodes Distribute the schedules for: new mobile node + existing nodes Reject Approve FO-MARS Gateway Request for Node Admission All the red schedules should be disseminated LONG Node Admission Delay Problem
  • 58. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Additive Mobility-Aware Real-Time Scheduling (A-MARS) 58 Request for Admission Reserve bandwidth for: new mobile node Distribute the schedules for: new mobile node Reject Approve A-MARS Gateway Request for Node Admission Only the red schedules should be disseminated SHORT Node Admission DelayProblem Solved
  • 59. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Challenge of Additive Scheduling 59 time The flows of each node should be scheduled so that future mobile nodes can be scheduled as well A B C We need a smart bandwidth reservation algorithm that predicts the future to enhance the schedulability of future flows
  • 60. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Challenge of Additive Scheduling 60 • Assume Pγ = 16 and Pβ = 8 • γ and β require 5 transmissions • γ and β cannot be scheduled using the same time slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 nth Period of flow γ (Scheduling ok!) γ γ γ γ γ nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling fail!) β β β β β γ γ γ γ γ Failed admission of flow β 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 nth Period of flow γ (Scheduling ok!) γ γ γ γ γ nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling ok!) β β β β β γ γ β β β β β γ γ γ Successful admission of flow β How to know which slots should be used for scheduling a flow?
  • 61. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Flow Classes and Slot Prioritization 61 • Assume the network services a set of flow classes γ, β, α,… • All the flows in a flow class have similar period and deadline • We prepare a prioritized list of slots for scheduling each flow class How using a slot for scheduling γ would affect the schedulability of β and α Prepare a prioritized list of slots for scheduling a flow γ For flow class γ : Flow Class Period/ Deadline Heart Rate γ Pγ, Dγ Pulse Oximetry β Pβ , Dβ Blood Pressure α Pα, Dα Dα < Dβ < Dγ
  • 62. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Frequency-Time Division Multiple Access Slot Prioritization 62 • We propose the notion of Potential Utilization (PU) to measure the effect of choosing each slot Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 nth Period of flow β n+1th Period of flow β PU for class β 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 nth Period of flow β n+1th Period of flow β PU for class β 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 Choose slot 7 and update PU choosing from these slots: increase PU by 0.31 choosing from these slots: increase PU by 0.39 demand = percentage of flows belonging to class β x #required transmissions available slots (0.5 X 5)/8
  • 63. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Performance Evaluation 63
  • 64. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa • Correctness depends on both functionality and timeliness • Real-time networks are required for mission-critical applications • Mission-critical applications: • Industrial process control • Clinical patient monitoring • … • Several organizations: HART, ISA, WINA, ZigBee Setup 64 Mobility Paths Links of the Routing Graph Infrastructure Nodes Gateway • Trace-driven simulator using exhaustive floor plan measurements • Realistic and repeatable experimentation Performance Evaluation
  • 65. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Flow Period [second] (a) 0.64 1.28 2.56 5.12 MaxMobil 0 50 100 Flow Period [second] (b) 0.64,1.28,2.56 0.64,1.28,5.12 0.64,2.56,5.12 1.28,2.56,5.12 MaxMobileNodesSupported 0 10 20 30 40 50 60 70 80 90 100 Performance Evaluation Scalability: How Many Mobile Nodes can be Supported? 65 Mobile nodes generate reports with different rates FO-MARS vs SRS 14x 5.12 LLF-SRS LLF-ESRS LLF-CERS FO-MARS A-MARS SRS: Designed for Static Networks ESRS: SRS + Flow Coordination CERS: SRS + Flow Coordination + Schedule Combination Proposed Algorithms
  • 66. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Performance Evaluation Admission Delay 66 Number of Mobile Nodes (a) 10 20 30 40 50 AdmissionDelay[s] 0 50 100 150 200 250 Flow Period = 1:28 Number of Mobile Nodes (b) 50 100 150 AdmissionDelay[s] 0 50 100 150 200 250 Flow Period = 5:12 Number of Mobile Nodes (c) 10 20 30 40 50 AdmissionDelay[s] 0 100 200 300 400 Flow Period 2f0:64; 1:28; 2:56g Number of Mobile Nodes (d) 20 40 60 80 100 AdmissionDelay[s] 0 100 200 300 400 Flow Period 2f1:28; 2:56; 5:12g SRS: Designed for Static Networks ESRS: SRS + Flow Coordination CERS: SRS + Flow Coordination + Schedule Combination = 1:28 missionDelay[s] 50 100 150 200 250 Flow Period = 5:12 LLF-SRS LLF-ESRS LLF-CERS FO-MARS A-MARS Proposed Algorithms A-MARS’S Admission delay < 20 seconds
  • 67. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Performance Evaluation Network Lifetime 67 SRS: Designed for Static Networks ESRS: SRS + Flow Coordination CERS: SRS + Flow Coordination + Schedule Combination = 1:28 missionDelay[s] 50 100 150 200 250 Flow Period = 5:12 LLF-SRS LLF-ESRS LLF-CERS FO-MARS A-MARS Proposed Algorithms odes 70 Number of Mobile Nodes (b) 10 20 30 40 NodeLifetime[hour] 500 1000 1500 2000 2500 3000 3500 Pdata 2f64; 128; 256g Number of Mobile Nodes (c) 10 20 30 40 50 60 NodeLifetime[hour] 0 1000 2000 3000 4000 5000 6000 7000 Flow Period 2f1:28; 2:56; 5:12g LLF-ESRS LLF-CERS FO-MARS A-MARS Higher network lifetime achieved with FO-MARS and A-MARS
  • 68. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Conclusion 68 • Real-time wireless networks can be used in mission-critical applications such as industrial process control and medical monitoring • Existing real-time networks do not efficiently handle network dynamics such as mobility and flow addition/removal • We proposed scheduling techniques for efficient bandwidth reservation for mobile nodes • We proposed an additive scheduling algorithm for effective handling of flow admission and removal • Compared to the algorithms designed for stationary real-time networks, our proposed network admits a significantly higher number of mobile nodes, archives short admission delay, and handles network dynamics efficiently
  • 69. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa Acknowledgement 69 Behnam Dezfouli University of Iowa Iowa City, IA, USA Marjan Radi University of Iowa Iowa City, IA, USA Octav Chipara University of Iowa Iowa City, IA, USA This work was supported by the National Science Foundation and the Roy J. Carver Charitable Trust