jennifer c. hou department of computer science university of illinois at urbana-champaign june 11,...

Jennifer C. HouJennifer C. HouDepartment of Computer ScienceDepartment of Computer Science

University of Illinois at Urbana-ChampaignUniversity of Illinois at Urbana-ChampaignApril 18, 2023April 18, 2023

Jennifer C. HouJennifer C. HouDepartment of Computer ScienceDepartment of Computer Science

University of Illinois at Urbana-ChampaignUniversity of Illinois at Urbana-ChampaignApril 18, 2023April 18, 2023

DAWN: Dynamic Ad-hoc Wireless NetworksProgress Report Presentation

DAWN: Dynamic Ad-hoc Wireless NetworksProgress Report Presentation

Energy Efficient Network TrackPower, CS Threshold, and Rate Control

DEPARTMENT OF COMPUTER SCIENCEDEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGNUNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGNJennifer Hou Jennifer Hou

PHY/MAC Control KnobsPHY/MAC Control Knobs

To mitigate interference and maximize the network capacity, there are several control knobs:

Transmit power power/topology control

Carrier sense threshold trade-off between spatial reuse and interference level

Spatial diversity scheduling consecutive transmission for interference-free connections

Channel diversity use of non-overlapping channels


Power ControlPower Control

Definition: Each node adjusts its transmission power so as to maintain network connectivity using the minimum possible power.

Objectives: Maintaining network connectivity Reducing energy consumption Mitigating MAC interference Achieving network capacity and spatial reuse


Preliminary Work on Power Control Preliminary Work on Power Control

Local minimum spanning tree (LMST) [INFOCOM’03, IEEE TWC, IEEE TPDS]Localized algorithm Relies only on local information

Preserves connectivity.

Ensures bi-directional links.

Handles node heterogeneity (i.e., nodes have different maximal transmit powers)

Bounds the degree of any node by 6.


Xi : location of node i

Ri : transmission range of node i

Link (ji) exists if Rj | Xi – Xj |:

Transmission power of node i

Total power:k-connectivity: requires to remove at least k nodes to disconnect the networkCritical total power Wc: minimum total power W for maintaining k-connectivity

i iW R

i ii iW W R

1

1

Ri

RjXj

Xi

Preliminary Work on Total PowerRequired for K-Connectivity

Preliminary Work on Total PowerRequired for K-Connectivity

Poisson point process with density n in a unit-

area square


Question To AskQuestion To AskIn what order does the critical total power Wc

increase/decrease as the node density increases?All nodes choose common power

[Gupta & Kumar 98] studied the critical transmission range rn for 1-connectivity

[Wan & Yi 04] for k-connectivity

All nodes choose different power[Blough 02] critical total power for 1-connectivity

Based on the total weight of minimum spanning tree

Our study: critical total power or k-connectivity

log, where ,as n

n n

nr n

n


Major ResultsMajor Results

Main theory: [Infocom 2005, ACM/IEEE ToN 2006]

The critical total power for maintaining k-connectivity

is with probability approaching 1

Comparison with common powerThe critical total power for k-connectivity with common power is

Allowing power control at each node reduces the total power by a factor of

1 / 2( / 2 )( )

( 1)!

kn

k

1 / 2 / 2( (log ) )n n

/ 2((log ) )n


Rescaling to Expanded Networks

Rescaling to Expanded Networks

Expanded networks Node density fixed

Side length L

Expected number of nodes n= L2

Allowing power controlAverage power is bounded

Using common power The common power grows as

(1)

/ 2((log ) )n

1

1ijd

L

L 'ijd

ijd

'ij ijd L d


Cross Layer Aspects of Power ControlCross Layer Aspects of Power Control

Physical LayerPhysical Layer

MAC LayerMAC Layer

Network LayerNetwork Layer

Po

wer C

on

trol

Po

wer C

on

trol Incorporating

Physical Layer Characteristics

Incorporating Physical Layer Characteristics

Cross Layer Design

Cross Layer Design

Effect of MAC-Layer Interference

Effect of MAC-Layer Interference

Dynamic Topology Control w.r.t.

Network Traffic

Dynamic Topology Control w.r.t.

Network Traffic

Network Capacity

Network Lifetime

Critical Power

Analysis

Network Capacity

Network Lifetime

Critical Power

Analysis

Physical LayerPhysical Layer




When Power Control Meets SINR


All the topology control algorithms in literature defined the neighbor relation based on the protocol model

A link exists between nodes i and j if dij <= dmax.

TC: L(n) T(n)

The protocol model ignores the effect of SINR.

What is more appropriate to define a link is the use of physical model

A link exists between i and j if

TC: L(n) x C(n) T(n)

Set of node locationsSet of configurations (, max/min transmit power)

Topology that defines the neighbor relations




All existing topology control algorithms fail (i.e., cannot maintain network connectivity) under the physical model.We are re-investigating topology control under the physical model.


Controlling Carrier Sense Threshold


• The contending area can also be adapted through tuning the carrier-sensing threshold

AB C D

distance

Sig

nal

Str

eng

th

CS Threshold

E F


A large CS threshold leads tosmaller contending area

Less contending nodes within the contending area

More concurrent transmission

Higher interference

Transmission rate depends on Signal-to-Interference-Noise Ratio



AB C D

distance

Sig

nal

Str

eng

th

CS Threshold

E F


Tradeoff AnalysisTradeoff Analysis

Spatial reuse can be achieved at the cost of higher interference level and lower transmission rate

High rate links Low rate links

What is the optimal CS Threshold? How does it relate to the transmit power?


Network CapacityNetwork Capacity

Network capacity as a function of transmit power and carrier sense threshold [ACM Mobicom 2006]


Power Control vs. Data RatePower Control vs. Data Rate

RX1

r2SINR :

d1

RX2

r1SINR :

d2

Power: P

CS Threshold:

Tx1

Tx2Rx

1

Rx2

d1

r2

r1

d2D1 D

2

SINR requirements

Power: P

CS Threshold:

DR[2]thrSINR

DR[3]thrSINR

DR[1]thrSINR


Power Control vs Data RatePower Control vs Data Rate

Power: P

CS Threshold:

'Power: P (>P)

CS Threshold:

'

RX1

P r2SINR : *

P d1

Tx1

Tx2Rx

1

Rx2

d1

r2

r1

d2D1

D2

RX2 '

P r1SINR : *

P d2

SINR requirements

DR[2]thrSINR

DR[3]thrSINR

DR[1]thrSINR


Power and Rate ControlPower and Rate ControlPRC algorithm:

A localized algorithm that enables each transmitter to adapt to the interference level that it perceives and determines its transmit power.

The transmit power is so determined that the transmitter can sustain the highest possible data rate, while keeping the adverse interference effect on the other neighboring concurrent transmissions minimal.


Simulation SetupSimulation SetupModified ns-2 Ver. 2.28

The interference perceived at a receiver is the collective aggregate interference from all the concurrent transmissionsEach node uses physical carrier sense to determine if the medium is freeIEEE 802.11a radios supporting 8 discrete data rate (6 ~ 54 Mbps)

Random topology3, 10, 20, 30, and 50 transmitter-receiver pairs are randomly generated in a 300m X 300m area, and represent sparsely, moderately, and densely populated networks, respectively,.

Algorithms used for evaluationsStaticGreedy Power Control (GPC)Power and Rate Control (PRC)


Simulation ResultsSimulation Results

Performance gain mainly because ofHigher concurrent transmissions

Simulation Track1. Expediting Wireless Simulation2. Incorporating Model Checking into Simulation


Expediting Wireless Simulation

Expediting Wireless Simulation

Our profiling work indicates more than 50% of the execution time is spent on event scheduling and channel related activity handling.Can we expedite simulation by reducing the number of unnecessary events while not impairing the accuracy.

Proportion of the execution time that is spent on event enqueueing in a 100-node ad hoc network over a 1000mX1000m field. There are 40 CBR connections carrying a total of 120 packets/sec. Traffic (pkt. Size = 512B)

[1] Chunyu Hu and Jennifer C. Hou, ``A reactive channel model for expediting wireless network simulation,'' ACM SIGMETRICS, Banff, Alberta, Canada, June 2005


Reactive Channel ModelReactive Channel Model

R

L

The channel only notifies nodes in the following sets of the signal-arrival event

Nodes in range RNodes in (range L but not R) that are registered

When does a node register?

Whenever it needs to monitor the channel status, e.g., when it would like to gain access to the channel or when it is in the process of receiving a signal


A Case Study: IEEE 802.11 MAC

A Case Study: IEEE 802.11 MAC

State To register?

transmitting * ☒

receiving ☑

idle

backing-off ☑

deferring ☑

-- ☒

sleep ☒

turn-off ☒

*: assuming half-duplex radio is used


RCM Performance (Execution Time)

RCM Performance (Execution Time) RCM


RCM Performance(Memory Consumption)

RCM Performance(Memory Consumption)


Virtual Wireless Ad-Hoc Network (J-Sim)

Champaign-Urbana Wireless Community Network(Currently 40 wireless nodesin downtown Urbana; expectedto extend to 100 nodes providingfull coverage of Champaign and Urbana).

Integration of Real/Virtual Integration of Real/Virtual WorldsWorlds

• Channel behavior modeling• Physical capacity analysis• Incentive-based resource management• Multi-radio, multi-path routing• Cross-layer optimization


Marriage of Modeling Checking and SimulationMarriage of Modeling Checking and Simulation

s0

s1

s2

s3

s4

s5

s6

s7

X

J-Sim

[1] Ahmed Sobeih, Mahesh Viswanathan and Jennifer C. Hou, “Check and Simulate: A Case for Incorporating Model Checking in Network Simulation,” Proceedings of the ACM-IEEE International Conference on Formal Methods and Models for Codesign (ACM-IEEE MEMOCODE 2005), San Diego, CA, June 2005.

s0

s1

s2

s3

s4

s5

s6

s7

X

J-Sim w/ MC

• Stateful on-the-fly explicit-state model checking into J-Sim• Explore the state space of a network protocol up to a (configurable) maximum depth of transitions• No changes to the core design and implementation of J-Sim


An Overview of Our WorkAn Overview of Our Work• Build the model checker as a component in J-Sim

P1 P2 Pn

Model Checker

J-Sim

Error Trace / No Error

Initial State

Current State

Next State

Component

Port

Communication via ports


Evaluation and ResultsEvaluation and Results

• Two case studies: AODV and Directed Diffusion• Representative routing and data dissemination protocols• Reasonably complex network protocols

• 1200 – 1400 LOC (excluding the J-Sim library)• Safety property:

• The loop-free property of routing/data dissemination paths

[2] Ahmed Sobeih, Mahesh Viswanathan, Darko Marinov and Jennifer C. Hou, “Finding Bugs in Network Protocols Using Simulation Code and Protocol-Specific Heuristics,” Proceedings of the International Conference on Formal Engineering Methods (ICFEM 2005), Springer-Verlag LNCS 3785, Manchester, United Kingdom, November 2005.

• Summary of our discoveries: • A previously unknown bug in the J-Sim implementation of AODV• A previously unknown deficiency in directed diffusion


Guiding Model Checking with Network Properties

Guiding Model Checking with Network PropertiesWe have developed search heuristics that exploit properties inherent to the network protocol and the safety property being checked and better guide the model checker to discover counter examples. An interesting and important research question is how to determine a suitable BeFS strategy for a specific network protocol.

jennifer c. hou department of computer science university of illinois at urbana-champaign june 11,...

Documents

transmission power of

minimum total power

connectivity slide

minimum possible power

network connectivity

different power blough

common power gupta kumar

rate control slide