Topology Formation and

Public PolicyJeff Pang

15-848E

Topology Formation Overview

• Principles and Protocols for Power Control in Ad Hoc Networks, V. Kawadia and P. R. Kumar, IEEE Journal on Selected Areas in Communications.

• Vikas Kawadia and P. R. Kumar, ``A Cautionary Perspective on Cross Layer Design.'' To appear in IEEE Wireless Communication Magazine.

• Roger Wattenhofer, Li Erran Li, Victor Bahl and Yi-Min Wang, Distributed Topology Control for Power Efficient Operation in Multihop Wireless Ad Hoc Networks. Proc. of IEEE INFOCOM, pages 1388-1397, April 2001

• Ning Li and Jennifer C. Hou, Topology control in heterogeneous wireless networks: problems and solutions, in Proc. of IEEE INFOCOM 2004, March, 2004.

Power Control

1 mW

4 mW

1mW

4mW

Power Control: Cross-Layer Design Issues

• Physical Layer– Power control affects quality of signal

• Link Layer– Power control affects number of clients sharing channel

• Network Layer– Power control affects topology/routing

• Transport Layer– Power control changes interference, which causes

congestion

• Application/OS Layer– Power control affects energy consumption

Cross Layer Design Example:Rate Adaptive MAC

• 802.11 MAC adapts rate to minimize errors

• DSDV routes using shortest hop-count paths– Uses lowest rate to

determine links

• “short” paths can have less bandwidth than longer paths!

4Mbps

1Mbps

Cross Layer Design Example:Rate Adaptive MAC

Adaptive

Plain

Cross Layer Design Example:Topology Control

• Goal: choose node degree to maximize end-to-end throughput

• Set transmit power to achieve target-degree– Short time-scale

• Modify target-degree to increase end-to-end throughput– i.e., try to follow gradient to a maxima– Long time-scale

• Problem: can cause oscillations– Topology can oscillate between connected and

disconnected states

Cross Layer Design Example:Topology Control

Topology Control Protocols

• Kawadia and Kumar– COMPOW– CLUSTERPOW– Tunneled CLUSTERPOW– MINPOW

• Wattenhofer, et al.– Angle-based

• Li and Hou– Directed Relative Neighbor Graph (DRNG)– Directed Local Minimum Spanning Tree (DLMST)

COMPOW

• Everyone transmits at same power– Find minimum power s.t. topology remains

connected

• Pros:– Ensures all links bidirectional– Allows higher layers to work properly

• Cons:– Single outlying node causes high-power

CLUSTERPOW

• Run a separate routing protocol at each power level pi

• Route packets using routing table at minimum pi where destination is present

• Pros:– “Clustering” is distributed– Any base routing protocol works– Routing is loop-free (power levels monotonically decrease)

• Cons:– Routing overhead (one per power-level)– Can’t use initial lower-power hops

CLUSTERPOW

Tunneled CLUSTERPOW

• Recursively lookup path to next hop– e.g., if D is reachable through N1, search for min-

power route to N1, etc.

Tunneled CLUSTERPOW• Simple recursion is not loop-free

• Solution: Tunnel packet to intermediate hop

MINPOW• Goal: Route using min-energy route• Energy cost of using a link at power level p:

– PTotal(p) = PTx + PTxRad(p) + PRx

• Topology:– Graph is union of topology at all power levels– Link-cost = minreachable-p(PTotal(p))– Run DSDV (Bellman-Ford) on resulting graph

• Pros:– Globally optimal in terms of energy consumption– Loop-free (just DSDV)

• Cons:– Not optimal for capacity (but close if PTxRad(p) dominates)– Does not take into account interference! (i.e., retransmits)

COMPOW/CLUSTERPOWThroughput vs. Delay

(clustered topology -- mostly 1 hop paths)

COMPOW/CLUSTERPOWRouting Overhead

Cone-based

• Goal: topology with power efficient routes

• Assumptions:– Transmit power dominates energy cost– Nodes can determine angle of reception– Trasmit power p(d) = Ω(dx) for x >= 2

• Basic Idea:– Use min power needed to reach at least

1 node in each cone of 2π/3 around node (π/2 for optimal efficiency)

– Refine by removing unneeded neighbors

X

Cone-based Properties

• Topology is connected– Pf. Intuition: consider disconnected u,v with min d(u,v). For

any neighbor w, > π/3

• Routes are minimum power– Pf. Intuition: multiple short hops cheaper than one long hop

Cone-based Topology

Max Power After Phase 1 Final

Cone-based Results

DLMST Motivation

• Goal: Topology formation for nodes with heterogeneous max power levels

• Problem with Cone-based topology (any MRNG based method):

DLMST Protocol

• Each node broadcasts HELLO at its max power• With knowledge of directed graph in its

neighborhood, construct minimum spanning tree• Pros:

– Connectivity guaranteed– Node degree bounded by constant (limits interference)

• Cons:– Links not necessarily bidirectional (can fix, but may sacrifice

global connectivity)

DLMST Results

Average Radius Average Degree

Topology Control Discussion

• What else besides transmit power affects topology?

• Is power control a problem in infrastructure AP networks?

• How can power control affect fairness?

Public Policy: Spectrum Management

• Spectrum Management Policy Options, Jon Peha, IEEE Communications Surveys, Fourth Quarter 1998, Vol. 1, No. 1.

• Approaches to Spectrum Sharing, Jon M. Peha, Feb. 2005.

• Dynamic Spectrum Policies: Promises and Challenges, Paul J Kolodzy, Jan 2004.

The Bigger Picture

Technology

Society Economy

Government

• 9 million hotspot users in 2003 (30 million in 2004)

• Approx 4.5 million WiFi access points sold in 3Q04

• Sales will triple by 2009• Many more non-802.11 devices

Staggering Market Statistics

US Spectrum Allocation

802.11Bluetooth802.11Bluetooth

The Status Quo

• Government licenses spectrum– By frequency: e.g., for a television channel– By location: e.g., for the Pittsburgh area– Only licensees allowed to transmit

• Licenses are temporary– Allows change in spectrum policy– New spectrum usually auctioned– But 99.9% always renewed

• A small number of unlicensed bands– Industry, Science, and Medicine (prev. slide)– PCS, NII– Anyone can transmit (with limitations)

Governing Spectrum Blocks

• Open access: “Flexible use doctrine”– Let market forces decide applications– => most value, innovation, competition

• Exclusive access:– Government chooses application/transmission standard– => international interoperability, positive “externalities” (e.g., for

police, fire fighters), standardization

Distributing Licenses

• Lotteries– Avoids political favoritism– Does not necessarily maximize value

• Auctions– Tries to maximize value of application– Can be synchronized to allow buyers to get larger chunks

Alternatives to Licensing

• “Property Rights”– Treat spectrum same as land– Allows resale, renting, etc. => opens up secondary

markets for spectrum– But interference (“trespassing”) on region boundaries

unavoidable

• “Commons”– WiFi model: cooperative sharing– Maximize spectrum use if transmission is bursty– Requires some common protocol for cooperation– Requires some altruism

Dynamic Spectrum Management

• Goal: Allocate spectrum more dynamically– For example, without humans in the loop

• Why? Lots of spectrum is wasted!– Time of day (some radio stations turn off at night)– Location (rural areas don’t use all TV frequencies)– Workload (data applications are bursty)

• Enabling Technology– Software Defined Radios– Adaptive Cognitive Radios– Example: Cordless phones vs. Baby monitors -- manual to

automatic freq. adjustment

Enabling Technologies

• Flexibility– Can change waveform on the fly (i.e., modulation protocol)

• Agility– Can change the freq. on the fly (i.e., channel)

• Sensing– Aware of environmental conditions (i.e., interference)

• Networking– Can interact with other radios (i.e., ad hoc nets)

Dynamic Policy Options

• Can policy be varied by:– Transmission duration? (e.g., “TDM”)– RF condition? (e.g., interference sensing)– Short time scales?– Via negotiation between radios?– Impact on environment? (e.g., interference)

• Implementation Options:– High power beacon to all devices?– “P2P” networked radio enforcement?

Implementation Challenges• Quantifying interference

– FCC definition: “unwanted energy”

• Measurement infrastructure– Analog to “pollution monitors”– Dedicated or networked P2P based?

• Liability policies– How to punish policy non-

compliance– Do devices need to be certified?

What about software?

• Identity management– How to identify violators

“Example”

Public Policy Discussion

• How could more dynamic spectrum allocation impact:– WiFi Testbeds?– Community Mesh Networks?– Mixed Networks?– Other topics?