Master Thesis Proposal SIMULATION AND ANALYSIS OF WIRELESS MESH NETWORK IN ADVANCED METERING INFRASTRUCTURE PHILIP HUYNH

1. COMMITTEE MEMBERS AND SIGNATURES Approved by Date

__________________________________ _____________ Advisor: Dr. EDWARD CHOW

__________________________________ _____________ Committee member: Dr. JUGAL KALITA

__________________________________ _____________ Committee member: Dr. RORY LEWIS

2. INTRODUCTIONMOTIVATIONSGROWING THE NEED FOR SMART GRIDA smart grid [1] delivers electricity from suppliers to consumers using two-way digital communication technology. Smart grid allows controlling appliances at consumer’s homes to save energy, and reduce cost. The operation status of the smart grids can be monitored in real time, so the smart grids are more reliable. Many governments are promoting such a modernized electricity network as a way of addressing energy independence, global warming and emergency resilience issues.

Utilities can archive energy efficiency and maintain the competitive of services by taking advantages of the smart grid and its market benefits. The smart grid solutions that utilize the information technology for data collection, monitoring and control, data analysis and information communication infrastructure, will cost-effectively protect revenues today, while laying the foundations for future services.

ADVANCED METERING INFRASTRUCTURE (AMI)Advanced Metering Infrastructure (AMI) [2] that is as part of larger Smart Grid initiatives, is implemented by government agencies and utilities to meet the above challenges. Extending from the current Automatic Meter Reading (AMR) technology, AMI provides two way meter communications, and allows commands to be sent toward the home for multi purposes, including Time-of-Use pricing information, demand-response actions, or remote service disconnects.

The Department of Energy estimates that over 280 Giga-watts of new generating capacity will be needed by 2025 [5]. It results in new power plants would be built in the future. The energy industry is facing the critical issues such as the need for new plants, maintaining overburdened infrastructure, coping with an aging workforce, complying with regulations, and environmental concerns. For a long time, the energy industry has rightfully focused on the supply side of this challenge. But now, the demand side of the equation can be significantly impacted by the existing of the wireless mesh networking [3]. Wireless mesh networking can use as the backbone of the AMI solutions to enable two-way intelligent networked communications with smart meters. With the AMI, the value added services such as demand response and demand side management would be enabled, besides meter reading. AMI solutions allows interoperable networks and systems across the entire power structure aid in the management and control of energy consumption, improve operations management, conserve the environment, and adhere to evolving regulations.

WIRELESS MESH NETWORK AS AN OPTION FOR THE AMI’S COMMUNICATION NETWORKA Wireless Mesh Network (WMN) [3, 4] is a communications network made up of radio nodes organized in a mesh topology. Wireless mesh networks often consist of mesh clients, mesh routers and gateways. The mesh clients are often laptops, cell phones and other wireless devices while the mesh routers forward traffic to and from the gateways which may but need not connect to the Internet. A mesh network is reliable and offers redundancy. When one node can no longer operate, the rest of the nodes can still communicate with each other, directly or through one or more intermediate nodes. Wireless mesh networks can be implemented with various wireless technology including 802.11 [12], 802.15 [13], 802.16 [14], cellular technologies or combinations of more than one type.

When the WMN technology is applied in AMI solutions, it can bring new components to the electrical grids, such as self-managing and self-healing mesh networking, intelligent meters, and bridging to Home Area Networks (HAN) [2] for connectivity with energy consuming appliances. The real time communication between the smart meters and the utility’s data center provides detailed usage data while also receives and display Time-of-Use (TOU) pricing information, and offers other on-demand abilities such as remote connect or disconnect, unrestricted monitoring and control, etc. Customers are able to access the usage data for tailoring consumption and minimizing energy expenses while helping balance overall network demand.

When WMNs are used in the AMI, they can provide the following features [5]: Low cost of management and maintenance - WMNs are self-organizing and require

no manual address/route/channel assignments. It is simple to manage thousands or millions of devices resulting in the lowest total cost of ownership.

Increased reliability – The WMN routing mechanisms provide the redundant paths between the sender and receiver of the wireless connection. Communication reliability is significantly increased because of the eliminations of single point failures and potential bottleneck links. Network robustness against potential problems, e.g.,

node failures and path failures due to RF interferences or obstacles, can also be ensured by the existence of multiple possible alternative routes.

Scalability, flexibility and lower costs - WMNs are self-organizing and allow true scalability. Nodes and Gateways are easily added at a very low cost with:

o No limitation on number of hops o No network address configuration o No managed hierarchical architecture o No hard limitation on number of Nodes per Gateway

Robust security – WMNs have the security standards that allows all communications in AMI are protected by mutual device authentication and derived per-session keys using high bit rate AES encryption. This hardened security approach allows for authentication as well as confidentiality and integrity protection in each communication exchange between every pair of network devices – Smart meters, Relays, or Wireless Gateways.

PROBLEM STATEMENTSThe advantages of the WMNsBeside the above advantages, the WMNs are more reliable and scalable than other wireless topologies such as Point-To-Point or Point-To-Multi Point.

Some AMI application and its network performance requirements Meter Data Collection application: allow High end-to-end Latency Outage Notification application: requires Low end-to-end Latency

The challenge questions for WMN as a solution for AMI’s Communication Network Given an AMI application, such as Meter Data Collector, How can we calculate the

Round Trip Time of the messages in the Multi hops routing manner, or the End-to-End Delay of the WMN communication network?

Most of AMI applications need the large coverage of the WMN for the wide area deployment, what is the maximum number of hops on the routing path that can be extended while the End-to-end network performance is still qualified for the applications?

This thesis will find the answers for these challenge questions by using the network simulation.

GOALSThe thesis will focus on the simulation and analysis of WMN in term of Scalability, Performance and Security, which are the important requirements for the design of the AMI’s communication network [1, 2].

The simulation results will be analyzed for understanding the capacity and scalability of the WMN, as well as the trade-off between these two properties. The balance between the capacity and scalability is an important design issue because more coverage area the

network is, less cost the deployment process will be. However more coverage area also means to less bandwidth.

APPROACHThis thesis presents the potential benefits of WMNs in terms of Scalability, Capacity and Security properties.

Suggest a Hybrid WMN architecture for the AMI’s communication networkThe communication network of AMI should be a Metropolitan Area Network (MAN) [6] to coverage a wide area such as a city, or town. We suggest a network model that uses the Hybrid WMN architecture [4].

When the coverage area increases to serve more wireless clients and to lower the total infrastructure cost, the multi-hop wireless networking suffers from the scalability issue [4]. The scalability and performance of Hybrid WMN have been analyzed and discussed in [7-9]. The scalability issue is also addressed from a network deployment perspective. Two scalable WMN deployment strategies for the dense-urban and wide-area scenarios were proposed in [10].

In the simulation, we use the WiMAX technology [14] for the backhaul network and the Wi-Fi technology [12] for the local networks to build the MAN model [6].

The security issue of the WMN was categorized and discussed in [3, 20]. Some network security mechanisms such as Virtual Private Network (VPN), Authentication and Authorization, and Key management are discussed in [6].

Propose a simulation scenarioWe propose an AMI application scenario for researching on the given network model. With the simulation scenario, we need to research the performance of the communication network. And because of the scalability issue, we also need to experience the trade-off between the performance and scalability properties of the network.

To simulate the network traffic of AMI’s Meter Reading Collection process, we build an AMI application called SmartGridSim that run on top of the Networking (or Internet) Layer [11]. SmartGridSim simulates the process of exchanging data between the AMI’s Meter Reading Collector and the Smart Meters through the communication network.

Simulate and analyze the resultsThen, we simulate the proposed network scenario with a set of pre-defined parameters such as number of hops, client nodes, and distance between mesh routers, bandwidth. The simulation results are analyzed to understand the network performance, and the trade-off between the scalability and the performance properties under different values of pre-defined parameters of network model.

CONTRIBUTIONThe thesis provides a network model of WMN that is implemented in a Network Simulation platform. The network model can help the researchers, network designers archiving the WMN experiments from the simulation. Developing AMI applications can employ the network model as a Communication Network for simulation purposes.

We also discuss the trade-off between the Scalability and Performance properties. The Security of the proposed network model will be discussed. Therefore, this thesis serves as a baseline for the network designer or decision makers for the AMI Communication Network.

3. THESIS PLAN3.1 TASKS

3.1.1 Work flow

----------------------------------------------------------------------------------------------------------------------RESEARCH STEPS BASELINES TIME----------------------------------------------------------------------------------------------------------------------

Simulate Integrated WMN in AMI context

Research Smart Grid – AMI

Research WMN

AMI Knowledge Fall-2009

Fall-2009

Spring-2010

Spring-2010

Spring-2010

3.1.2 Already Complete• Research Smart Grid, and AMI• Research Wireless Mesh Networks• Research network simulator software: NS-2 [16] and NCTUns 6.0 [17-19].

3.1.3. In Progress• Propose the AMI’s communication network model: uses Hybrid WMN architecture.

The backhaul network uses WiMAX [14]. The local mesh network uses Wi-Fi [12].

Scenario: The Hybrid Wireless Mesh Network as a Communication Network for AMI.The AMI has three components that are Meter Reading Collector, Wireless Mesh (WM) Communication Network, and Wi-Fi (WF) Smart Meter.

The Meter Reading Collector component accesses the WF Smart Meter’s reading via the WM Communication Network.

Basically, the WM Communication Network component provides the data transportation services. The requests and responses from Meter Reading Collector component and Wi-Fi Smart Meter component respectively will be delivered by the calling to transportation services of WM Communication Network component.

The WM Communication Network component has three layers of network services like the first three layers of the OSI model [11]:

Wireless Mesh Network Knowledge

Propose the AMI’s Communication Network

architecture: Hybrid WMN (WiMAX, Wi-Fi)

Conclusions

Simulation Scenario

Meter Reading CollectorWi-Fi Smart Meter

WM Communication Network

Networking Layer(Internet Protocol: w/

multi-hop routing)

Data Link Layer

Physical Layer

Simulation Results

Simulation Based Network Performance

Analysis

Trade-off between network scalability and network performance

SmartGridSim AMI Application

The WM Communication Network is a Hybrid Wireless Mesh Network (WMN), which uses Wi-Fi for local networks and WiMAX for backhaul networks [4, 6]. The WM Communication Network has the WiMAX Base Station, the WiMAX/Wi-Fi Gateway, and Wi-Fi Dual Band Mesh Routers. (More detailed information about the functionality of these components can be found in the included documents)

The above Design has been implemented in the NCTUns 6.0 network simulation software [17-19]. The background picture is a portion of the Colorado Springs city map which has been extracted from the Google map. The distance between the WiMAX base station and the Subscriber Station (WiMAX/Wi-Fi Gateway) is about 600m. The distance between two Wi-Fi Dual Band Routers in the same cluster is 200m.

3.1.4. Future• Develop and implement SmartGridSim application, a network application that will

simulate the process of data transmission between the Meter Reading Collector (MRC) and the Smart Meters (SM). As a part of the simulation scenario, the SmartGridSim will run on top of the NCTUns Network simulation, so that we can record and analysis the performance of the communication network.

SmartGridSim has two programs. One runs at the Meter Reading Collector, and called Communication Server (CS). Other one runs at the Smart Meter and called Communication Terminal (CT). The traffic pattern is the requests that are issued from the CS to CT.

For example, the usage scenario of the SmartGridSim is as following:

1. Communication Server (CS) is started with the arguments such as “IP address of the target Smart Meter”, “Number of times to read”, “Number of bytes to read”2. Communication Terminal (CT) is started with arguments such as “Number of bytes to send”. 3. As the end of the running, the output from the programs will be such as the following:

Output by the CS:o Total of time spent to collect data from the meterso Total number of times data request successfulo Total number of times data request failedo Average/Minimum/Maximum time spent to collect data per meter

Output by the CT:o Total number of times data response

• Simulate the network scenario with different values of parameters such as number of hops, client nodes (or Smart meters), wireless link bandwidth, distance between mesh routers.

• Analyze the simulation results:o Evaluate the network performance measures such as throughput, delayo Trade-off between scalability and performance

• Write the thesis report

3.2 DELIVERABLES• The SmartGridSim AMI application that simulates the process of Meter Reading

Collection. The application runs on top of the NCTUns 6.0 network simulation for helping the analyzing of network performance and scalability.

• The thesis report documents the technologies of wireless mesh networks, the proposed network architecture, the network model, the simulation scenario, and various pre-defined simulation parameters such as simulation area, radio models, number of hops, distances between mesh routers, number of client nodes, MAC protocols, routing protocols. We discuss about the trade-off between the network scalability and performance properties, as well as the security property of the proposed network model.

REFERENCES

[1] “Smart Grid”, <http://en.wikipedia.org/wiki/Smart_grid>[2] “Advanced Metering infrastructure”, National Energy Technology Laboratory white paper,

February 2008.[3] Prasant Mohapatra, “Wireless Mesh Networks”, Department of Computer Science

University of California, Davis.[4] I. F. Akyildiz, X. Wang, and W. Wang, "Wireless Mesh Networks: A Survey," Computer

Networks Journal (Elsevier), vol. 47, no. 4, pp. 445-487, Mar. 2005.[5] Srini Krishnamurthy, “Smart AMI Network Solutions Enable the Smart Grid”,

ElectricEnergyOnline.com, <http://www.electricenergyonline.com/?page=show_article&mag=55&article=395>

[6] “Understanding Wi-Fi and WiMAX as Metro-Access Solutions”, Intel Corporation white paper, 2004.

[7] B. Liu, Z. Liu, and D. Towsley, "On the capacity of hybrid wireless networks", in Proceedings of IEEE INFOCOM, Mar. 2003, vol. 2, pp. 1543-1552.

[8] S. Zhao and D. Raychaudhuri, "On the Scalability of Hierarchical Hybrid Wireless Networks, Proceedings of the Conference on Information Sciences and Systems (CISS 2006), March 2006, pp. 711-716.

[9] S. Zhao, I. Seskar and D. Raychaudhuri, "Performance and Scalability of Self-Organizing Hierarchical Ad-Hoc Wireless Networks," Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC'04), Atlanta, GA. March 2004, pp. 132-137.

[10] J. –H. Huang, L. -C. Wang, C. -J. Chang, “Wireless Mesh Network: Architecture and Protocols”, chapter title “Architectures and Deployment Strategies for Wireless Mesh Networks”, Springer 2008.

[11] “OSI Model”, <http://en.wikipedia.org/wiki/OSI_model>[12] IEEE Standard 802 Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer

(PHY) Specifications, 2007.[13] IEEE Standard 802 Part 15.1: Wireless Medium Access Control (MAC) and Physical Layer

(PHY) Specifications for Personal Area Networks (WPANs), 2005.[14] IEEE Standard 802 Part 16: Air Interface for Broadband Wireless Access Systems, 2009.[15] WiMAX community, <http://www.wimax.com>[16] The Network Simulator Ns-2, <http://www.isi.edu/nsnam/ns/>[17] NCTUns 6.0 Network Simulator and Emulator, <http://nsl.csie.nctu.edu.tw/nctuns.html>[18] “The Protocol Developer Manual for the NCTUns 6.0”, Network and System Laboratory,

Department of Computer Science, National Chiao Tung University, Taiwan 2010.[19] S.M. Huang, Y.C. Sung, S.Y. Wang, and Y.B. Lin, “NCTUns Simulation Tool for WiMAX

Modeling,” Third Annual International Wireless Internet Conference, October 22 – 24, 2007, Austin, Texas, USA. (EI and ISI indexed, sponsored by ICST, ACM, and EURASIP)

[20] N.B. Salem and J.-P. Hubaux, "Securing Wireless Mesh Networks," Wireless Comm., vol. 13, no. 2, 2006, pp. 50–55.