Simulation and Analysis of Wireless Mesh Network In Smart Grid / Advanced Metering Infrastructure

Simulation and Analysis of

Wireless Mesh Network In

Smart Grid / Advanced Metering

Infrastructure

Masters Thesis

Philip Huynh

Spring 2011

University of Colorado at Colorado Springs

Outline of the Talk

Introduction Related work Real-time Smart Grid Meter Data Collection using

Hybrid WiMAX/Wi-Fi Networks Smart Grid Wireless Infrastructure Planning (SG-

WIP) Tool. Simulation Results of SG-SIM Lessons Learned Future Direction Conclusion

Masters Thesis Philip Huynh Spring 2011


Introduction What is the Advanced Metering Infrastructure (AMI)? The need to collect metering data in real-time

Save the material usage for the electric power generation by correctly predict the load demand and build the load profile



Wireless Mesh Network for AMI Low cost installation and maintenance Can deploy on the large service areas: urban, suburb Scalable, high performance technologies Secured standards: IEEE802.16, IEEE 802.11s



Wi-Fi mesh networks with WiMAX backhaul Wireless technologies (source: Intel)

CSU AMI Infrastructure



Related Work “Wireless Mesh Networks: A Survey” [AWW05]

The author presented many open research issues needed to be solved such as scalability, self-organization and self-configuration, security, network integration. The critical factors influencing protocol design were discussed for improvement objectives.

“The Nominal Capacity of Wireless Mesh Networks” [JS03]

The authors shown that for WMNs the throughput of each node decreases as O(1/n), where n is total number of nodes in the network. Moreover, for a given topology and the set of active nodes, the upper bounds on the throughput of any node can be exactly calculated.

“Capacity of Grid-Oriented Wireless Mesh Networks” [ANMK08]

The author presented an analytical framework for determining the nominal capacity of multi-radio multi-channel Wireless Mesh Network (WMN). As the research conclusion, the effects of WMN design parameters such as network topology, network size, routing methods, channel assignment schemes etc. are interlinked and a judicious selection is essential to maximize capacity.



Related Work (2) “Architecture and Algorithms for an IEEE 802.11-based Multi-

channel Wireless Mesh Network” [RC05]

The author proposed a novel multi-channel WMN architecture that effectively addresses the bandwidth problem by fully exploiting non-overlapped radio channels that the IEEE 802.11 standards make available.

“Multi-Channel Mesh Networks: Challenges and Protocols” [KSCV06]

The authors considered the use of multi-channel to improve the throughput of Wireless Mesh Network (WMN). The main challenges were highlighted and two link-layer protocols were presented for utilizing multiple channels

“Coverage and capacity of a wireless mesh network” [HWC05]

The authors proposed a scalable multi-channel ring-based WMN architecture and developed an analytical framework to evaluate the capacity and coverage of such a network.



Related Work (3)

“The IEEE 802.11s Extended Service Set Mesh Networking Standard” [CK08]

The author presented how the developing IEEE 802.11s ESS Mesh Networking Standard draft addresses technical challenges of the pervasive development of wireless mesh networks (WMNs), the efficient allocation of mesh resources (routing and MAC layers), the protection of network resources (security and power savings), and the elimination of spatial bias (congestion control).

“An Improved IEEE 802.16 WiMAX Module for the ns-3 Simulator” [IPGT10]

The authors presented the new features and enhancements that were integrated within the ns-3 WiMAX module. These proposed features can make easier and more realistic the evaluation and design of WiMAX systems.



Challenges & Approach Challenges in Design and Deployment AMI Network

using WMN How to evaluate the network performance: hundred thousands of

smart meters, complicated architecture How the scalability affects to the performance

Approach Develop a Network Topology Planning Tool Develop a Network Simulator for AMI Communication Network Simulate the network model and Analyze the results

Goals Develop techniques and tools to evaluate the performance of

AMI WMN.



Hybrid WiMAX/Wi-Fi Network Model


Hybrid WiMAX/Wi-Fi Network Model

(a) Example of WiMAX network (WAN) (b) Example of Wi-Fi mesh network (NAN)

(a)

(b)


SG-WIP Tool A mashup that overlays the wireless

infrastructure and GIS data (street light poles, housing units) on the Google Maps

Visually planning the Antenna mounting place for the WiMAX/Wi-Fi network

Export the network topology as XML file for further research

Can be integrated to the network simulator



SG-WIP: GUI


GUI includes components: Main Menu, Network Topology Overlay, Google Maps, and Topology Information Panel.


SG-WIP: Navigating Topologies


MAN: Grid 10x10, 10 km x 10 km (WxH) NAN: Grid 10x10, 1 km x 1 km (WxH)


SG-WIP: Exporting Topology


LAN: Square, 100 m x 100 m (WxH) Exporting the LAN topology as an XML file


SG-WIP: Changing Antennae Position


WiMAX base station’s antennae: (a) Before changing, location at (5, 5); (b) After changing, location at (6, 9)

(a) (b)


SG-WIP: Code// Calculate the center point of the Colo Sprgs boundary house/building units

// Show the map of Colorado Springs

var csCenter = getCenter(new GeoRectangle(csSW, csNE));

var latlng = new google.maps.LatLng(csCenter.Latitude, csCenter.Longitude);

// Map's options

var myOptions = {

zoom: startZoom,

center: latlng,

mapTypeId: google.maps.MapTypeId.ROADMAP,

mapTypeControl: true,

navigationControl: true,

scaleControl: true

};

// Map object instance

map = new google.maps.Map(document.getElementById("map-canvas"), myOptions);

// Add the network topology as an overlay object on map

polygon = new google.maps.Polygon({

paths: paths,

strokeColor: FillColor,

strokeOpacity: 1,

strokeWeight: LineWeight,

fillColor: FillColor,

fillOpacity: 0.01

});

polygon.setMap(map);

overlaysArray.push(polygon);



// Handle the Click event on the network topologygoogle.maps.event.addListener(polygon, 'click',

function(event) {var lat = event.latLng.lat();var lng = event.latLng.lng(); Network.clickEvent(lat, lng); }

// Geographical coordinates helper functions//This uses the ‘haversine’ formula to calculate great-circle

distances between //the two points – that is, the shortest distance over the

earth’s surface – // giving an ‘as-the-crow-flies’ distance between the points

(ignoring any hills!).function distance_between(lat1, lon1, lat2, lon2){ var dLat = (lat2-lat1)*degrees_to_radians; var dLon = (lon2-lon1)*degrees_to_radians; var a = Math.sin(dLat/2) * Math.sin(dLat/2) + Math.cos(lat1*degrees_to_radians) *

Math.cos(lat2*degrees_to_radians) * Math.sin(dLon/2) * Math.sin(dLon/2); var c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a)); var d = earth_radius * c; return d;}

});

SG-SIM Simulator Implements the proposed hybrid

WiMAX/Wi-Fi Network Model on NS-3 platform

The network simulator NS-3 isOpen source projectPopular and accepted by network research

community Parameters of the Simulator

Network types: WAN, MAN, NAN, LANNumber of nodes, Transmission RateOthers: network initialization time,…



SG-SIM: Code// Install node location for WiMAX base station, gateways

MobilityHelper mobility;

mobility.SetPositionAllocator ("ns3::GridPositionAllocator",

"MinX", DoubleValue (0.0),

"MinY", DoubleValue (0.0),

"DeltaX", DoubleValue (1000),

"DeltaY", DoubleValue (1000),

"GridWidth", UintegerValue (5),

"LayoutType", StringValue ("RowFirst"));

mobility.SetMobilityModel ("ns3::ConstantPositionMobilityModel");

mobility.Install (bsNodes);

mobility.Install (ssNodes);

// Create a packet sink to receive these packets

Address sinkLocalAddress (InetSocketAddress

(Ipv4Address::GetAny (), 50000));

PacketSinkHelper sinkHelper ("ns3::UdpSocketFactory",

sinkLocalAddress);

ApplicationContainer sinkApp = sinkHelper.Install (serverNode);

sinkApp.Start (Seconds (start));

sinkApp.Stop (Seconds (duration));



// Install the app on the SS nodes

for (int i=0; i<nbSS; i++) {

// build the application

Ptr<SgOnOffApplication> sgOnOff =

CreateObject<SgOnOffApplication>();

sgOnOff->SetAttribute ("Protocol",

StringValue ("ns3::UdpSocketFactory"));

sgOnOff->SetAttribute ("OnTime",

RandomVariableValue (ConstantVariable (1)));

sgOnOff->SetAttribute ("OffTime",

RandomVariableValue (ConstantVariable (0)));

sgOnOff->SetAttribute ("DataRate",

DataRateValue (DataRate (m_packetDataRate)));

sgOnOff->SetAttribute ("PacketSize",

UintegerValue (lenPacket));

sgOnOff->SetAttribute ("Remote",

remoteAddress);

sgOnOff->SetStartTime (Seconds (start + 0.000001*i));

ssNodes.Get (i)->AddApplication(sgOnOff);

}

Simulation Experiments

Experiment Design VisionEvaluate the performance of AMI InfrastructureHow the scalability affects to the performance

Measure the performance of network with many source nodes at the specific Constant Bit Rate (CBR)

Confirm to smart meter density analysis (using SG-WIP)



LAN Simulation Results

0 20 40 60 80 100 1200

20

40

60

80

100

120

0

5,000

10,000

15,000

20,000

25,000

WLAN (IEEE 802.11a) w/ variable SMs Simula-tion

Packets Tx Packets Rx

Total Processing Delay (us)

SMs

Pac

kets

Tim

e (u

s)


•Tx packets = Rx packets•Total processing delay increases linearly with the number of smart meter


NAN Simulation Results

0 1 2 3 4 5 6 7 8 90

100

200

300

400

500

0

5,000

10,000

15,000

20,000

25,000

30,000

WNAN (IEEE 802.11s Mesh) w/ variable APs Simulation

Packets Tx Avg. Packets Rx


APs

Pac

kets

Tim

e (u

s)


•Tx packets = Rx packets•Total processing delay increases rapidly with the number of mesh routers.


MAN Simulation Results

0 1 2 3 4 5 6 7 8 9 100

200400600800

1,0001,2001,4001,6001,8002,000

920,000

930,000

940,000

950,000

960,000

970,000

980,000

990,000

1,000,000

WMAN (IEEE 802.16d) w/ variable GWs Simula-tion

Packets Tx Avg. Packets Rx


GWs

Pac

kets

Tim

e (u

s)


•Tx packets = Rx packets•Total processing delay converges to 930 msecs. It caused by 5 msecs fixed frame time in IEEE 802.16 standard.


MAN Simulation Results (2)

0 2 4 6 8 10 12 14 16 180

5,000

10,000

15,000

20,000

25,000

30,000

35,000

940,000945,000950,000955,000960,000965,000970,000975,000980,000985,000990,000

WMAN (IEEE 802.16d) w/ 10 GWs, various sub-packet lengths simulation

Packets Tx Packets Rx Total Sub Packet Tx

Total Sub Packet Rx Total Processing Delay (us)

Number of meter data packets

Pac

kets

Tim

e (u

s)


Impact on the network performance by aggregating meter data at the gateway•Tx packets = Rx packets when number of meter packets < 16•Tx packets > Rx packets when number of meter packets >= 16 (caused by UDP packet fragmentation)•Total processing delay increases slowly with the number of meter packets


WAN Simulation Results

0 1 2 3 4 5 6 7 80

50,000

100,000

150,000

200,000

0

100,000

200,000

300,000

400,000

500,000

600,000

WAN (Star Topology) w/ various BSs simula-tion

Packets Tx Packets Rx

Total Meter Packet Tx Total Meter Packet Rx


BSs

Pac

kets

Tim

e (u

s)


•Tx packets = Rx packets•Total processing delay is independent from the number of base stations (BSs). However, it is affected by the distribution of BSs around the data centers.


WAN Simulation Results (2)

0 20 40 60 80 100 1200

5,000

10,000

15,000

20,000

25,000

30,000

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

WAN (Star Topology) w/ various cable lengths simulation

Packets Tx Packets Rx Total Meter Packet Tx

Total Meter Packet Rx Total Processing Delay (us)

Cable Length (km)

Pac

kets

Tim

e (u

s)


•The total processing time was linearly increased with the length of the optical cables.


Lessons Learned

• Development of SG-WIP Tool- Challenges in testing and debugging source code for

Web application (used PHP/JavaScript)- GIS Information Acquisition: time consuming process

• Development of SG-SIM Simulator - Found the bug in NS-3 WiMAX module that can affect

the simulation results and reported to NS-3 community at: http://www.nsnam.org/bugzilla/show_bug.cgi?id=1025

• Simulation Experiments in NS-3- The initialization phase of wireless networks- Bugs in Wi-Fi Mesh, WiMAX modules



http://www.nsnam.org/bugzilla/show_bug.cgi?id=1025

Future Direction

• Fully integrate the SG-WIP tool with SG-SIM simulator

• Improve the antenna placement algorithm- Increase availability of wireless networks

• Database systems for storing the real-time meter data



Conclusion The proposed WiMAX/Wi-Fi WMN can transport the

meter data from 160,000 smart meters in the CSU service areas to the data center in one second.

The high scalability property of WiMAX/Wi-Fi WMN helps flexibly extend the coverage area of the AMI wireless infrastructure without degrading the network performance.

The proposed WiMAX/Wi-Fi infrastructure allows the utilities deploying an AMI wireless communication infrastructure not only at low cost of installation and maintenance but also with high performance, scalability, and security.



Demo

Illustrate network topology planning with SG-WIP Toolhttp://scad.eas.uccs.edu/sgwip/wan.html

Some demonstrations of SG-SIM simulator



http://scad.eas.uccs.edu/sgwip/wan.html

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http://www.oe.energy.gov/smartgrid.htm

http://www.oe.energy.gov/SmartGridIntroduction.htm

http://en.wikipedia.org/wiki/MetroFi

http://skypilot.trilliantinc.com/

http://www.ekasystems.com/ekanet.htm

http://code.google.com/apis/maps/documentation/javascript/

Documents

Simulation and Analysis of Wireless Mesh Network In Smart Grid / Advanced Metering Infrastructure