WCPS: Wireless Cyber-Physical Simulator

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End-user's Tutorial on using WCPS: The Wireless Cyber-Physical Simulator

WCPS is design for, but not limited to, realistic Wireless Structural Control simulations. The efficient integration of Simulink and TOSSIM has made WCPS an ideal choice for realistic wireless control simulations. The following tutorial introduces how to install and configure MATLAB, TinyOS, and PYTHON environments, as well as the WCPS framework. The tutorial herein is specifically organized for end-users who do not do much development but instead trying to do wireless control simulations with Simulink and TOSSIM. A more advanced tutorial for developers can be found [here].

WCPS Architecture

WCPS Architecture

As shown in the right figure, WCPS simulates the feedback control loop of the control system as follows. Sensor data is generated from structural models. Through a cross-platform function call from Simulink, sensor data is injected to the corresponding wireless sensors in TOSSIM. Following the routes and transmission schedule calculated by the network manager module, TOSSIM simulates the end-to-end wireless communication of the sensor data packets from the sensors to the base station, and then return the packet delay and loss to the Interfacing Block in Simulink through the Python interface. The Packet Collector module then extracts packet delivery information(the delay and loss)from the message pool. Sensor data and their loss and delay are then provided to the Data Block, which then feed the sensor data to the controller at the right time based on the packet delay (if the packet is not lost). WCPS utilizes basic API (e.g., the dos, UNIX command) of MATLAB to do cross-platform function calls. In TOSSIM, we re-implement a printf method in TinyOS to send simulation results to the Interfacing Block.

User inputs to WCPS includes excitation signals to the structure (e.g., acceleration caused by earthquakes) and wireless traces used as input to TOSSIM. Excitation signal of the structure is provided to the structure models in the format of MAT files. The scheduler module calculates transmission schedules. Networking schedule is then deployed into the MAC layer code of wireless nodes and becomes effective after a TinyOS compilation. The TDMA MAC layer in WCPS is developed based on the MAC Layer Architecture (MLA) library and further adapted for TOSSIM under TinyOS 2.1.1. Received Signal Strength Indication( RSSI) and wireless noises traces are collected from real-world environments and provided to the wireless model used by TOSSIM for realistic wireless network simulations. The interfaces between the Simulink model and TOSSIM are encapsulated as two MATLAB embedded functions in Simulink: the Interfacing Block and the Data Block. The Interfacing Block extracts delay and loss information from TOSSIM messages, and the Data Block decides what data will be used for discrete control during each sampling period. The federated architecture of WCPS provides great flexibilities to incorporate different structural models and implement alternative scheduling-control approaches.

WCPS Capabilities

This section briefly reviews application of WCPS in extensive Wireless Structural Control studies, which shows capability of WCPS enabling in-depth tradeoff among sensing synchronization, wireless network delays, as well as reliability of the wireless network. Specifically for the wireless network presented in this section, wireless traces in TOSSIM were collected from a 5-sensor testbed located at Bryan Hall of Washington University, as in Fig. 1. All results presented here uses the TDMA MAC layer.

Fig. 1. Wireless Network in A Building
Fig. 2. Network Statistics

Fig. 2 shows end-to-end network ratio changes with different re-transmission mechanisms in WCPS. Sensor 1 has the lowest delivery ratio because it has a 2-hop route to the base station. Since OTDC-1 does not perform any retransmission, while OTDC-2 and OTDC-3 performs retransmit each packet once and twice, respectively. Under OTDC-1 Sensors 1 and 4 have delivery ratios of 70% and over 95%, respectively. As expected more retransmissions improve the deliver ratios of all sensors at the cost of longer delays as described earlier.

Figure 3. Tradeoff Among Data Synchronization, Network Reliability and Network Delay.

Fig. 3 shows changes of required resource for building control. Underlying tradeoffs are: better sensing synchronization vs. larger delays (e.g., OTDC-1 vs. SC), and larger network delays trading for better reliability (e.g., OTDC-3, OTDC-2 vs. OTDC-1). In Fig.3(a), OTDC-k approaches consistently require less control power than SC. As k increases, OTDC-k requires slightly less control power. Similarly, as shown in Fig. 2(b), OTDC-1 reduces control force by 80% when compared to SC. The differences in control force among different OTDC-k approaches are negligible. The results that OTDC-1 outperforms SC in both metrics indicate resource requirements are more sensitive to data synchronization than to sensing delays in this building control system. OTDC-k with larger k results in negligible reduction of control power and force, indicating resource requirements are not sensitive to network reliability in this case study.

Fig. 4 shows control performance regarding structural response. In term of peak inter-story drift in Fig. 4(a), OTDC- k achieves more reduction in inter-story drift than SC. Interestingly, higher k in OTDC-k increases peak inter-story drift. Recall a higher k leads to higher communication reliability but longer sensing delay. Inter-story drift is thus more sensitive to sensing delays than to data loss in this case study. Similarly, as shown in Fig. 4(b), OTDC-3 causes worse peak acceleration than all the other approaches. Hence, building structural responses are more sensitive to sensing delays than to data loss. In addition, OTDC-1 only slightly outperforms SC, which indicates limited impact of data synchronization on structural response.

Figure 4. Tradeoff Among Data Synchronization, Network Reliability and Network Delay.

WCPS has efficiently integrated TOSSIM and Simulink. Fig. 2-4 shows that there exist complex tradeoffs among data synchronization, sensing delay, and network reliability under realistic wireless structural control settings. A realistic, integrated wireless control simulator like WCPS is critical in exploring these design tradeoffs in wireless control design. Our cyber-physical simulation methodology and scheduling-control co-design approaches presented here not only represent a promising step toward smart civil infrastructure, but also provide useful insights and tools that can be generalized to other cyber-physical systems employing wireless control.

Environment Installation

  • Install TinyOS
 WCPS is implemented and tested on MacOS X (snowleopard), Windows XP, and Windows 7. Current release of WCPS is under  TinyOS 2.1.1, which can be installed following the two methods.
  • Install Mac Layer Architecture(MLA)
The MAC Layer Architecture (MLA) provides a component-based architecture for MAC protocols in wireless sensor networks. MLA extends the Unified Power 
Management Architecture to provide the hardware-independent interfaces required by timing sensitive MAC protocols, and defines platform-independent 
reusable components that implement MAC layer logic on top of them. The MLA architecture can be used to develop a large number of platform-independent 
MAC implementations, with little or no further effort required to adapt these implementations to new hardware platforms. Our current implementation of MLA
is built on top of TinyOS 2.1.1. It currently supports platforms which use the CC2420 radio stack and has been tested on TelosB motes. In addition to providing
interfaces and components for building new MAC layer implementations, MLA includes implementations of five representative MAC layers. Specifically for WCPS, we 
adopt and further change the pure-TDMA MAC protocol for centralized data communication.
  • Install MATLAB and Simulink
  • If you already have MATLAB MATLAB 7.11.0.584 (2010b) or later version, skip this step. Otherwise, follow the

tutorial here: install MATLAB

  • Install Python

If you already have Python 2.7.2 or later version installed, skip this step. Otherwise, follow the manual here: install Python

Download WCPS

Use WCPS

Simulate a TDMA wireless network Wireless network as the communication media of a close-loop control system plays a critical role. Sitting on top of WCPS, simulating a wireless TDMA network is as easy as collecting these NesC files below:

  • "Makefile" takes advantage of the fact that it's not necessary to recompile all the files not changed while specifying all necessary libraries.
  • "TestNetwork.h" defines necessary message structures for the wireless communication.
  • "TestNetworkAppC.nc" connects claimed application interfaces to interfaces that are defined in the hardware library.
  • "TestNetworkC.nc" implements send/receive functionality of a wireless node.
  • "tossim-call.py" configures TOSSIM network and does packet injection into the Tossim network.All above necessary files..
  • Re-implemented TOSSIM libraries for TDMA simulation.TDMA components for TOSSIM..
  • Wireless traces: Traces for 5-sensor wireless network in a building.

A simple Simulink Model Coming soon...

Joint Simulation Put all the above files into the same folder, prompt a terminal (or a Cygwin window), and:

  • In the terminal run Make micaz sim
  • In the terminal run ./tossim-call.py

Change Log

  • Coming soon: multi-channel TOSSIM.
  • Release: March 10, 2013, WCPS v0.1.1 and the four cases studies for the ICCPS'13 paper was released.
  • Tutorial: March 09, 2013, WSC Examples from a structural perspective.

Get Support

  • TinyOS and TOSSIM: Bo Li: boli@seas.wustl.edu
  • Simulink Models: Zhuoxiong Sun: SUN152@purdue.edu

References

  • B. Li, Z. Sun, K. Mechitov, G. Hackmann, C. Lu, S. Dyke, G. Agha and B. Spencer, "Realistic Case Studies of Wireless Structural Control," ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'13), April 2013.
  • Z. Sun, B. Li, D. Dyke, and C. Lu. "A novel data utilization and control strategy for wireless structural control systems with tdma network," In 2013 ASCE International Workshop on Computing in Civil Engineering (ASCE IWCCE 2013).
  • Z. Sun, B. Li, S.J. Dyke and C. Lu, "Evaluation of Performances of Structural Control Benchmark Problem with Time Delays from Wireless Sensor Network," Joint Conference of the Engineering Mechanics Institute and ASCE Joint Specialty Conference on Probabilistic Mechanics and Structural Reliability (EMI/PMC'12), June 2012.
  • H. Lee, A. Cerpa, and P. Levis. Improving wireless simulation through noise modeling. In IPSN, 2007.
  • P. Levis, N. Lee, M. Welsh, and D. Culler. Tossim: Accurate and scalable simulation of entire tinyos applications. In Sensys, 2003.
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