Difference between revisions of "WCPS: Wireless Cyber-Physical Simulator"

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Wireless Cyber-Physical Simulator (WCPS) is an open-source simulation environment for wireless control systems. By integrating Simulink and the TOSSIM wireless sensor simulator in a holistic simulation environment, WCPS accurately captures the dynamics of both the physical systems and the wireless sensor-actuator networks used for control. WCPS has been used for [http://research.engineering.wustl.edu/~boli/papers/iccps13.pdf realistic case studies of wireless structural control systems for civil infrastructure], [http://www.cse.wustl.edu/~lu/papers/iccps16.pdf studying routing and control of cyber physical system], and [http://research.engineering.wustl.edu/~boli/papers/iccps15_final.pdf incorporating emergency alarms in reliable wireless process control]. The broad application of WCPS is to support cyber-physical systems research on large-scale wireless control systems through high-fidelity joint cyber and physical simulations. This site includes the code release, tutorial, and simulation examples for wireless structural control systems.
  
−
| image = {{#if:{{{altimage|}}}|{{{altimage|}}}|[[File:Ambox warning blue construction.svg|50x40px|link=|page is in the middle of an expansion or major revamping]]}}
+
== What's New ==
 +
* '''[Software Release]''' WCPS-EC is released. [https://github.com/WU-CPSL/WCPS-EC here].
 +
* '''[Software Release]''' WCPS-RT is released. [https://github.com/WU-CPSL/WCPS-RT here].
 +
* '''[Software Release]''' Dockerized [[WCPS v3.0]] for industrial process control is released. [http://wsn.cse.wustl.edu/index.php/WCPS_v3.0 here].
 +
* '''[Software Release]''' [https://nees.org/groups/wireless_control_benchmark Benchmark Problem in Active Structural Control with Wireless Sensor Network].
 +
* '''[Software Release]''' WCPS v2.0 is released.
 +
* '''[Software Update]''' [https://nees.org/groups/wireless_control_benchmark Benchmark Wireless Structural Control Problem], July 29, 2014.
 +
* '''[News]''' [http://spectrum.ieee.org/podcast/at-work/test-and-measurement/smart-bridges Smart Bridges - Interview and Podcast on Cyber-Physical Systems for Resilient Bridges], August 07, 2013.
 +
* '''[News]''' [http://news.medill.northwestern.edu/chicago/news.aspx?id=222339 Washington Bridge Collapse Could Be a Wake-up Call], May 30, 2013.
 +
* '''[News]''' [http://www.indyposted.com/195455/matthew-roblez-structural-engineering-saves-lives/#.UZ7GqGSAAy8 Matthew Roblez: Structural Engineering Saves Lives], May 22, 2013.
 +
* '''[News Release]''' [http://news.wustl.edu/news/Pages/25358.aspx Engineering Professor Working to Help Bridges Survive Natural Disaster], April 26, 2013.
 +
* '''[Paper]''' [http://research.engineering.wustl.edu/~boli/papers/iccps13.pdf Realistic Case Studies of Wireless Structural Control], ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'13), April 2013.
 +
* '''[Software Update]''' A complete package of Cygwin with TinyOS 2.1.1, MLA, TOSSIM pre-installed was released [http://wsn.cse.wustl.edu/index.php/WCPS:_Wireless_Cyber-Physical_Simulator#Download_WCPS here], April 01, 2013.
 +
* '''[Software Update]''' WCPS v0.1.1 and the four cases studies for the ICCPS'13 paper was released [http://wsn.cse.wustl.edu/index.php/WCPS:_Wireless_Cyber-Physical_Simulator#Download_WCPS here], March 10, 2013.
 +
* '''[Tutorial]''' Wireless structural control examples from a [http://research.engineering.wustl.edu/~boli/downloads/wcps_structural_perspective.pdf structural perspective], March 09, 2013.
  
−
'''This page is under construction and thus incomplete, please contact boli@seas.wustl.edu before using materials below.'''
+
== WCPS Architecture ==
 +
[[File:Wcps_architecture_wcpsv3.png|600px|thumb|right|Figure 1. WCPS Architecture]]
 +
In the Fig.1, WCPS simulates
 +
the feedback control loop of the control system as follows.
 +
Sensor data is generated from plant models such as structures and water tanks. 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
 +
extracts packet delivery information(the delay and loss)from the message pool. Sensor
 +
data and their loss and delay are provided to the Data Block,
 +
which can 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.
  
−
End-user's Tutorial on using WCPS: Wireless Cyber-Physical Simulator
+
User inputs to WCPS includes reference signals of the plants and wireless traces used
 +
as input to TOSSIM.
 +
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, as is shown in Fig.2. 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.
 +
[[File:simulink.png|600px|thumb|center|Figure 2. Simulink Model]]
  
−
Normal User Tutorial on the Wireless Cyber-Physical Simulator(WCPS)
+
==Environment Installation==
−
WCPS is design for, but not limited to, realistic Wireless Structural Control simulations. The layered infrastructure and efficient integration of state-of-the-art control and wireless networking tools, i.e., Simulink and TOSSIM, have made WCPS an ideal choice for general wireless control simulations with Simulink and TOSSIM.
+
* Install TinyOS
  
−
The following tutorial introduces in detail how to configure general MATLAB, TinyOS, and PYTHON environments, as well as the WCPS framework. The tutorial herein is an end-user version specifically for end-users that do not do much development but instead trying to do wireless control simulations with Simulink, TOSSIM and WCPS. An advanced tutorial on in-depth TinyOS development (e.g., routing protoocls, MAC layer development) with WCPS can be found [here].
+
<pre>
−
 
 
−
==Software Environment Setup==
 
−
*1. Install TinyOS
 
 
WCPS is implemented and tested on MacOS X (snowleopard), Windows XP, and Windows 7.  
 
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 three methods.
+
Current release of WCPS is under  TinyOS 2.1.1, which can be installed following the two methods.
−
(1) Follow the TinyOS official tutorial on installation of TinyOS for your specific platform: [http://docs.tinyos.net/tinywiki/index.php/Getting_started#User_Contributed_Methods Link]
+
</pre>
−
(2) Directly download the pre-tested TinyOS 2.1.1 image from here:  [under construction Cygwin]  [under construction Mac OS X]
+
* Follow the TinyOS official tutorial on installation of TinyOS for your specific platform: [http://docs.tinyos.net/tinywiki/index.php/Getting_started#User_Contributed_Methods Link]
−
*2 Install Mac Layer Architecture(MLA)
+
* Directly download the pre-tested TinyOS 2.1.1 image from here: [http://research.engineering.wustl.edu/~boli/downloads/tinyos-2.1.1.dmg TinyOS2.1.1 for SnowLeopard(and possibly later versions)] [Cygwin package coming soon.]
−
Follow the instructions here: [http://wsn.cse.wustl.edu/index.php?title=MAC_Layer_Architecture Install MLA].
 
−
*3 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: [http://www.mathworks.com/help/install/index.html install MATLAB]
 
−
*4 Install Python
 
−
If you already have Python 2.7.2 or later version installed, skip this step. Otherwise, follow the manual here: [http://www.python.org/getit/ install Python]
 
−
*5 Environment Setup Testing
 
−
 
 
−
== Building a Wireless Network in TOSSIM ==
 
−
*1. Makefile
 
−
"Makefile" takes advantage of the fact that it's not necessary to recompile all the project files that has not been changed.
 
−
To have the "Makefile" for our project, copy the code below into a txt file and save as "Makefile" without any suffix, or simply download it here: [Makefile]
 
  
 +
* Install Mac Layer Architecture(MLA)
 
<pre>
 
<pre>
−
# target file
+
The MAC Layer Architecture (MLA) provides a component-based architecture for MAC protocols in wireless sensor networks. MLA extends the Unified Power
−
COMPONENT=TestNetworkAppC
+
Management Architecture to provide the hardware-independent interfaces required by timing sensitive MAC protocols, and defines platform-independent
−
# dependencies of the target
+
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
−
include $(UPMA_DIR)/Makefile.include
+
MAC implementations, with little or no further effort required to adapt these implementations to new hardware platforms. Our current implementation of MLA
−
BUILD_EXTRA_DEPS = TestNetworkMsg.py
+
is built on top of TinyOS 2.1.1. It currently supports platforms which use the CC2420 radio stack and has been tested on TelosB motes. In addition to providing
−
CFLAGS += -DTOSH_DATA_LENGTH=156
+
interfaces and components for building new MAC layer implementations, MLA includes implementations of five representative MAC layers. Specifically for WCPS, we
−
CFLAGS += -I$(TOSDIR)/lib/T2Hack
+
adopt and further change the pure-TDMA MAC protocol for centralized data communication.  
−
PFLAGS += -I../../../pure-tdma
 
−
CFLAGS += -I$(TOSDIR)/lib/printf
 
−
CFLAGS += -DFOOTER_SIZE=0 -DTDMA -DUPMA
 
−
#TDMA mac layer
 
−
UPMA_MAC = pure-tdma
 
−
#mig information for python
 
−
TestNetworkMsg.py: TestNetwork.h
 
−
mig python -target=$(PLATFORM) $(CFLAGS) -python-classname=TestNetworkMsg TestNetwork.h TestNetworkMsg -o $@
 
−
CLEAN_EXTRA = TestNetworkMsg.py TestNetworkMsg.class TestNetworkMsg.java TestNetworkMsg.pyc
 
−
include $(MAKERULES)
 
−
migclean:
 
−
rm -rf $(MIGFILES)
 
 
</pre>
 
</pre>
  
−
*2. TestNetwork.h
+
* Follow the instructions here: [http://wsn.cse.wustl.edu/index.php?title=MAC_Layer_Architecture Install MLA].
−
"TestNetwork.h" defines necessary message structures for the wireless communication. Copy the code below into a txt file and save as "TestNetwork.h", or simply download it here: [TestNetwork.h]
+
 
 +
* 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: [http://www.mathworks.com/help/install/index.html install MATLAB]
 +
 
 +
* Install Python
 +
If you already have Python 2.7.2 or later version installed, skip this step. Otherwise, follow the manual here: [http://www.python.org/getit/ install Python]
 +
 
 
<pre>
 
<pre>
−
#ifndef TEST_NETWORK_C_H
+
Below is the installation guide of WCPS v3.0.
−
#define TEST_NETWORK_C_H
+
For Mac OSX Users who would like to run WCPS on their own computer, please follow first instruction link below for a detailed installation and test procedures.
−
enum {
+
For OSX/Linux/UNIX/Windows users, please follow the second instruction link below for ruining Dockerized WCPS in a Docker container.
−
AM_TESTNETWORKMSG = 0x05,
 
−
AM_TESTNETWORKMSGG = 0x06,
 
−
SAMPLE_RATE_KEY = 0x1,
 
−
CL_TEST = 0xee,
 
−
TEST_NETWORK_QUEUE_SIZE = 8,
 
−
};
 
−
#endif
 
 
</pre>
 
</pre>
  
−
*3. TestNetworkAppC.nc
+
*Install [[WCPS v3.0]] on Mac. [[Run_WCPS_On_Mac_Guide]]
−
"TestNetworkAppC.nc" connects claimed application interfaces to interfaces that are defined in the hardware librare. Copy the code below into a txt file and save as "TestNetworkAppC.nc", or simply download it here: [TestNetworkAppC.nc]
+
*Run [[WCPS v3.0]] using Docker Container. [[Run_WCPS_In_Docker_Container_Guide]]
 +
 
 +
== Download WCPS ==
 +
* Dockerized WCPSv3: [https://hub.docker.com/r/yehan/wcpsv3/ Docker image], [https://github.com/WU-CPSL/WCPSv3_docker local Matlab folder].
 +
* [https://github.com/WU-CPSL/WCPSv3 Local WCPSv3 installation folder].
 +
* [http://research.engineering.wustl.edu/~boli/downloads/cygwin.zip A complete package of Cygwin with TinyOS 2.1.1, MLA, TOSSIM pre-installed] with a [http://research.engineering.wustl.edu/~boli/downloads/WCPS_Cygwin_Installation_Usage_Tutorial.txt WCPS Cygwin Installation & Usage Tutorial]
 +
* [http://research.engineering.wustl.edu/~boli/downloads/wcpsv0.1.1.zip WCPS v0.1.1 and four extensive case studies] for [http://research.engineering.wustl.edu/~boli/papers/iccps13.pdf ICCPS'13 paper]
  
−
<pre>
+
== Use WCPS ==
  
−
/**
+
Wireless network plays a critical role in close-loop wireless control system. Sitting on top of WCPS, simulating
−
* Testnework for TDMA simulation in Tossim.  
+
a wireless TDMA network is as easy as collecting these NesC files below:
−
* @author Bo Li
 
−
* @version $Revision: 0.1 $ $Date: 2011/03/25 21:53:58 $
 
−
*/
 
−
#include "TestNetwork.h"
 
  
−
configuration TestNetworkAppC {
+
* "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.
−
implementation {
+
* "TestNetworkAppC.nc" connects claimed application interfaces to interfaces that are defined in the hardware library.
−
  components TestNetworkC, MainC, ActiveMessageC;
+
* "TestNetworkC.nc" implements send/receive functionality of a wireless node.
−
  components new AMSenderC(AM_TESTNETWORKMSG) as Sender; 
+
* "tossim-call.py" configures TOSSIM network and does packet injection into the Tossim network.[http://research.engineering.wustl.edu/~boli/downloads/TinyosFiles.zip All above necessary files.].
−
  components new AMReceiverC(AM_TESTNETWORKMSG) as Receiver; 
+
* Re-implemented TOSSIM libraries for TDMA simulation.[http://research.engineering.wustl.edu/~boli/downloads/pure-tdma.zip TDMA components for TOSSIM.].
−
  components new AMReceiverC(AM_TESTNETWORKMSG) as AMReceiver;
+
* Wireless traces: [http://research.engineering.wustl.edu/~boli/downloads/building_noise_n_rssi.zip Traces for 5-sensor wireless network in a building].
−
  components new TimerMilliC() as InjectionTimer;
 
−
  components SerialActiveMessageC as SerialAM;
 
−
 
 
−
  TestNetworkC.RadioControl -> SerialAM;
 
−
  TestNetworkC.SerialReceive -> SerialAM.Receive[AM_TESTNETWORKMSG];
 
−
  TestNetworkC.SerialSend -> SerialAM.AMSend[AM_TESTNETWORKMSG];
 
−
 
 
−
  TestNetworkC.Boot -> MainC;
 
−
  TestNetworkC.RadioControl -> ActiveMessageC;
 
−
  TestNetworkC.Send -> Sender; 
 
−
  TestNetworkC.Receive -> Receiver;
 
−
  TestNetworkC.AMReceive -> AMReceiver;
 
−
  TestNetworkC.InjectionTimer -> InjectionTimer;
 
−
}
 
  
 +
Put all the above files into the same folder, prompt a terminal (or a Cygwin window), and in the terminal run
 +
<pre>
 +
Make micaz sim
 
</pre>
 
</pre>
  
−
*4. TestNetworkC.nc
+
If TinyOS and python is configured correctly, go ahead and run in the terminal:
−
"TestNetworkC.nc" Implements send/receive functionality of a wireless node. Copy the code below into a txt file and save as "TestNetworkC.nc", or simply download it here: [TestNetworkC.nc]
 
−
 
 
 
<pre>
 
<pre>
 +
./tossim-call.py
 +
</pre>
  
−
/**
+
Having collected aforementioned TinyOS files, a simplified example that uses key networking Interfacing Block and Data Block of WCPS is shown in Fig. 3.
−
* Testnework for TDMA simulation in Tossim.  
+
[[File:Simple_wcps_example.png|500px|thumb|center|Figure 3. A Simple Example that uses Interfacing and Data Block of WCPS. ]]
−
* @author Bo Li
 
−
* @version $Revision: 0.1 $ $Date: 2011/03/25 21:53:58 $
 
−
*/
 
−
#include <Timer.h>
 
−
#include "TestNetwork.h"
 
−
module TestNetworkC {
 
−
  uses interface Boot;
 
−
  uses interface SplitControl as RadioControl;
 
−
  uses interface StdControl as RoutingControl;
 
−
 
 
−
  uses interface AMSend as Send;
 
−
  uses interface Receive;
 
−
  uses interface Receive as AMReceive;
 
−
  uses interface Timer<TMilli> as InjectionTimer;
 
−
 
 
−
  uses interface Receive as SerialReceive;
 
−
  uses interface AMSend as SerialSend;
 
−
}
 
−
implementation {
 
−
  message_t packet;
 
−
  TestNetworkMsg* rcm;
 
−
  TestNetworkMsg* rcmr;
 
−
  TestNetworkMsg* msgamr;
 
−
  TestNetworkMsg tnmsg_in_transit;
 
−
  uint8_t msglen;
 
−
  enum {
 
−
    RECEIVER=0,
 
−
  };
 
−
  event void Boot.booted() {
 
−
    call RadioControl.start();
 
−
  }
 
−
  event void RadioControl.startDone(error_t err) {
 
−
    if (err != SUCCESS) {
 
−
      call RadioControl.start();
 
−
    }
 
−
    else {
 
−
    }
 
−
  }
 
−
  void failedSend() {
 
−
    dbg("App", "%s: Send failed.\n", __FUNCTION__);
 
−
  }
 
−
  event void Send.sendDone(message_t* m, error_t err) {
 
−
    if (err != SUCCESS) {
 
−
    }
 
−
    dbg("TestNetworkC", "Send completed.\n");
 
−
  }
 
−
  uint8_t prevSeq = 0;
 
−
  uint8_t firstMsg = 0;
 
−
  event message_t*
 
−
  Receive.receive(message_t* msg, void* payload, uint8_t len) {
 
−
  rcmr = (TestNetworkMsg*)payload;
 
−
  if (TOS_NODE_ID % 500 == 0){
 
−
  if (rcmr->data1==1)
 
−
  {
 
−
  //printf("This is sensor %d\n", TOS_NODE_ID);
 
−
  printf("%u %u %u \n", rcmr->data2, 2, rcmr->data1);
 
−
  }
 
−
  else{
 
−
  //printf("This is sensor %d\n", TOS_NODE_ID);
 
−
  printf("%u %u %u \n", rcmr->data2, 1, rcmr->data1);
 
−
  }
 
−
  }
 
−
  if (TOS_NODE_ID % 500 == 3){
 
−
  //printf("This is sensor %d\n", TOS_NODE_ID);
 
−
  call Send.send(0, rcm, sizeof(TestNetworkMsg));
 
−
  }
 
−
  return msg;
 
−
}
 
−
event message_t* AMReceive.receive(message_t* bufPtr, void* payload, uint8_t len) {
 
−
rcm = (TestNetworkMsg*)payload;
 
−
    msgamr = (TestNetworkMsg*)call Send.getPayload(&packet, sizeof(TestNetworkMsg));
 
−
    if (msgamr == NULL) {
 
−
    return;
 
−
    }
 
−
    memcpy(msgamr, rcm, sizeof(TestNetworkMsg));
 
−
    if (len != sizeof(TestNetworkMsg)) {
 
−
    return bufPtr;
 
−
    }
 
−
  if (TOS_NODE_ID!=0){
 
−
  if (TOS_NODE_ID  % 500 == 1){
 
−
  if (call Send.send(3, &packet, sizeof(TestNetworkMsg)) != SUCCESS) {
 
−
  failedSend();
 
−
  }else {
 
−
      }
 
−
    }else if (TOS_NODE_ID  % 500 !=0 && TOS_NODE_ID  % 500 != 1){
 
−
    if (call Send.send(0, &packet, sizeof(TestNetworkMsg)) != SUCCESS) {
 
−
      failedSend();
 
−
      }else {
 
−
      }
 
−
    }
 
−
  } 
 
−
  return bufPtr;
 
−
  }
 
−
  event void InjectionTimer.fired(){}
 
−
  event void RadioControl.stopDone(error_t err) {}
 
−
  void sendMessage() {}
 
−
  event void SerialSend.sendDone(message_t* m, error_t err) {}
 
−
  event message_t* SerialReceive.receive(message_t* msg, void* payload, uint8_t len) {
 
−
  return msg;
 
−
  }
 
−
}
 
  
−
</pre>
+
This examples shows:
  
 +
* How input data in Simulink is injected to TOSSIM network;
 +
* How TOSSIM Interfacing Block runs as a Matlab Embedded function;
 +
* What type of data is output from the Interfacing Block;
 +
* How data usage strategies are applied to the data in the Data Block.
 +
* What type of data is eventually output from the Data Block and provided for future control use.
  
−
*5. tossim-call.py
+
Source code for the example can be found [http://research.engineering.wustl.edu/~boli/downloads/simple_example.zip here].
−
"tossim-call.py" configures TOSSIM network and does packet injection into the Tossim network. Copy the code below into a txt file and save as "tossim-call.py", or simply download it here: [tossim-call.py]
+
To run this integrated example, simply download, unzip the source code, and run Run_delay_data_func.m in Matlab.
  
−
<pre>
+
== WCPS-RT ==
  
−
#from TOSSIM import *
+
[[File:Wcps_architecture_wcps_RT.png|300px|thumb|right|Figure 4. WCPS-RT Architecture]]
−
from TOSSIM import Tossim
+
Given the complexity of wireless communication in physical environments, simulators cannot always capture the real-world behavior of WSANs.  Network-in-the-loop simulations have been developed to address the limitation of wireless simulations by incorporating physical wireless networks.
−
from random import *
 
−
from TestNetworkMsg import *
 
−
import sys
 
  
−
def main():
+
To experiment with wireless control over real-world WSANs, we develop wireless cyber-physical simulator real-time (WCPS-RT). WCPS-RT integrates MATLAB/Simulink Desktop Real-time (SLDRT) and a 3-floor WSAN testbed. It captures realistic wireless dynamics that are hard to simulate accurately, and leverages simulation support for controllers and physical plants.
−
    sensor_num_mn=sys.argv[1]
+
The architecture of WCPS-RT is shown in Fig. 4.
−
    sensor_data_mn=sys.argv[2]
 
−
    cm_code=sys.argv[3]
 
−
    return {'y0':sensor_num_mn,'y1':sensor_data_mn,'y2':cm_code}
 
−
sensor_num=int(main()['y0'])
 
−
sensor_data=main()['y1']
 
−
cmmd_code=main()['y2']
 
−
t = Tossim([])
 
−
r = t.radio()
 
−
L_topo=[0, 1, 2, 3, 4];
 
  
−
L=list()
+
SLDRT is used to simulate the physical part of the WNCS: physical plants, controllers, state observers, and physical disturbance.
−
lines=sensor_data
+
In practice, industrial plants usually operate continuously or at very high rates. However, the wireless communication and controller execute at a relatively low rate because of the communication and computation latencies. Therefore, SLDRT modules are operated at different rates in our design.
−
#channel 26
 
−
f = open("topo_building_all_channel_26-1000.txt", "r")
 
−
#channel 18
 
−
#f = open("topo_building_all_channel_18.txt", "r");
 
−
lines = f.readlines()
 
−
for line in lines:
 
−
s = line.split()
 
−
if (len(s) > 0):
 
−
r.add(int(s[0]), int(s[1]), float(s[2]))
 
−
for i in L_topo:
 
−
i_int=int(i)
 
−
m = t.getNode(i_int);
 
−
if (i_int==1):
 
−
noise_flr = open("Noise-floor-channel26-1-1000.txt", "r")
 
−
#noise_flr = open("Noise-floor-channel18-1.txt", "r")
 
−
elif(i_int==2):
 
−
noise_flr = open("Noise-floor-channel26-2-1000.txt", "r")
 
−
#noise_flr = open("Noise-floor-channel18-2.txt", "r")
 
−
elif(i_int==3):
 
−
noise_flr = open("Noise-floor-channel26-3-1000.txt", "r")
 
−
#noise_flr = open("Noise-floor-channel18-3.txt", "r")
 
−
elif(i_int==4):
 
−
noise_flr = open("Noise-floor-channel26-4-1000.txt", "r")
 
−
#noise_flr = open("Noise-floor-channel18-4.txt", "r")
 
−
elif(i_int==0):
 
−
noise_flr = open("Noise-floor-channel26-4-1000.txt", "r")
 
−
#noise_flr = open("Noise-floor-channel18-4.txt", "r")
 
−
lines_noise = noise_flr.readlines()
 
−
for line_noise in lines_noise:
 
−
strrr = line_noise.strip()
 
−
if (strrr != ""):
 
−
val = int(strrr)
 
−
m = t.getNode(i_int);
 
−
m.addNoiseTraceReading(val)
 
−
m.createNoiseModel();
 
−
m.turnOn()
 
−
m.bootAtTime(0)
 
−
#print "Booting ", i_int, " at time ", str(0)
 
−
msg = TestNetworkMsg()
 
−
ii=1;
 
−
for i in range(4, 0, -1):
 
−
#for k in range(1,round_remainder/sensor_num+1):
 
−
# mycode = "msg.set_data"+str(k)+"("+str(L[(i-1)*(round_remainder/sensor_num)+k-1])+")"
 
−
# print mycode
 
−
# exec mycode
 
−
node=i
 
−
msg.set_data1(node)
 
−
msg.set_data2(1)
 
−
pkt = t.newPacket();
 
−
pkt.setData(msg.data)
 
−
pkt.setType(msg.get_amType())
 
−
pkt.setSource(node);
 
−
pkt.setDestination(node)
 
−
tm=2000000000+(ii)*100000000
 
−
pkt.deliver(node, t.time()+tm)
 
−
#print "At injectTime: "+str(float((float)(t.time()+tm)/10000000000.0))+" we inject packet to "+str(node);
 
−
ii=ii+1;
 
−
t.addChannel('printf', sys.stdout)
 
−
t.addChannel("DataFeedback", sys.stdout)
 
−
#while (t.time() < 100000000000*5):
 
−
while (t.time() < 10000000000):
 
−
t.runNextEvent()
 
−
#print "Completed simulation at" +str(float(t.time())/10000000000)
 
  
−
</pre>
+
The 3-floor WSAN testbed is deployed on the 3rd to 5th floors of Jolley Hall at Washington University in St. Louis. It consists of 70 TelosB motes.
 +
Each mote is equipped with Chipcon CC2420 radio compliant with the IEEE 802.15.4 standard and a TI MSP430 microcontroller.
 +
40 Raspberry Pis with a backplane network are used for the management of the WSAN.
  
−
== Simulink Modeling in WCPS==
+
The interfaces between SLDRT and WSAN are  socket connections between the PCs that run SLDRT and the Pis, and serial connections between the Pis and the end nodes. In this way, the end nodes of the sensing and actuation flows  can be any nodes in the testbed.
−
=== General simulink modeling===
 
−
=== Structural models in WCPS===
 
−
=== Example ===
 
−
Application layer code:
 
−
<pre>
 
−
* navigation
 
−
** mainpage|mainpage
 
−
** Special:Recentchanges|Recent changes
 
−
</pre>
 
  
−
== Integrated Simulation with WCPS ==
+
== WCPS-EC ==
−
== WSC Examples with WCPS ==
 
−
===Wireless Building Control===
 
−
Application layer code:
 
−
<pre>
 
−
* navigation
 
−
** mainpage|mainpage
 
−
** Special:Recentchanges|Recent changes
 
−
</pre>
 
  
−
===Wireless Bridge Control===
+
[[File:Wcps_architecture_wcps_EC.png|350px|thumb|right|Figure 5. WCPS-EC Architecture]]
−
Application layer code:
 
−
<pre>
 
−
* navigation
 
−
** mainpage|mainpage
 
−
** Special:Recentchanges|Recent changes
 
−
</pre>
 
  
 +
We built a real-time hybrid simulator, wireless cyber-physical simulator edge-computing (WCPS-EC), which integrates (1) Real controllers running on various computation platforms; (2) Real Wi-Fi network and Ethernet, or simulated network using TOSSIM; (3) Simulink Desktop Real-time (SLDRT), which simulates robotic arm in real-time.
  
−
==References==
+
The architecture of WCPS-EC is shown in Fig. 5. Compared with WCPS-RT, WCPS-EC includes immigrated controllers running on various computation platforms instead of controllers running in MATLAB/Simulink. In addition, WCPS-EC can reflect the impacts of real communication network and computation platform during run-time.
−
* 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, 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.
+
In WCPS-RT, the worst-case end-to-end latency is below one sampling period. Hence the actuation commands are set to have fixed latency of one sampling period. However, in multi-tier control systems, the end-to-end latency can be longer than one sampling period. In addition, we consider a more realistic control system setup with (1) clock-driven sensors that sample the plant outputs periodically every sampling period; (2) an event-driven controller which calculates the actuation commands as soon as the sensor data arrives; and (3) event-driven actuators, which means actuators can respond to updated actuation commands immediately.
  
−
* H. Lee, A. Cerpa, and P. Levis. Improving wireless simulation through noise modeling. In IPSN, 2007.
+
== Talks ==
 +
*Y. Ma, C. Lu, B. Sinopoli and S. Zeng, [http://cps.cse.wustl.edu/index.php/File:EMSOFT.pdf Exploring Edge Computing for Multi-Tier Industrial Control], ESWEEK 2020 - ACM International Conference on Embedded Software (EMSOFT), September 2020.
 +
* Yehan Ma, [http://cps.cse.wustl.edu/index.php/File:ICII.pdf Efficient Holistic Control over Industrial Wireless Sensor Actuator Networks] , IEEE International Conference on Industrial Internet (ICII'18), Seattle, October 23, 2018.
 +
* Chenyang Lu, [http://www.cse.wustl.edu/~lu/talks/iccps16.pdf Wireless Routing and Control: a Cyber-Physical Case Study] , ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'16), Vienna, April 11, 2016.
 +
* Chenyang Lu, [http://spectrum.ieee.org/podcast/at-work/test-and-measurement/smart-bridges Smart Bridges - Interview and Podcast on Cyber-Physical Systems for Resilient Bridges], IEEE Spectrum, August 07, 2013.
 +
* Chenyang Lu, [http://www.cse.wustl.edu/~lu/talks/temple-wcn.pdf Real-Time Wireless Control Networks for Cyber-Physical Systems], Computer Science Colloquium, Temple University, April 12, 2013.
 +
* Bo Li, [http://research.engineering.wustl.edu/~boli/papers/WCPS-iccps13.pdf Realistic Case Studies of Wireless Structural Control], ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'13), Philadelphia, PA, April 11, 2013.
  
−
* P. Levis, N. Lee, M. Welsh, and D. Culler. Tossim: Accurate and scalable simulation of entire tinyos applications. In Sensys, 2003.
+
==Publication==
 +
*Y. Ma, C. Lu, B. Sinopoli and S. Zeng, [https://www.cse.wustl.edu/~lu/papers/emsoft20.pdf Exploring Edge Computing for Multi-Tier Industrial Control], IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Special Issue on ESWEEK 2020 - Proceedings of ACM International Conference on Embedded Software (EMSOFT), September 2020.
 +
*Y. Ma, C. Lu and Y. Wang, [https://www.cse.wustl.edu/~lu/papers/tcps20.pdf Efficient Holistic Control: Self-Awareness across Controllers and Wireless Networks], ACM Transactions on Cyber-Physical Systems, Special Issue on Self-Awareness in Resource Constrained Cyber-Physical Systems, 4(4), Article 41, June 2020.
 +
*Y. Ma and C. Lu, [https://www.cse.wustl.edu/~lu/papers/icii18-holistic-control.pdf Efficient Holistic Control over Industrial Wireless Sensor-Actuator Networks], IEEE International Conference on Industrial Internet (ICII'18), October 2018.
 +
* Y. Ma, D. Gunatilaka, B. Li, H. Gonzalez and C. Lu, [http://www.cse.wustl.edu/~lu/papers/tcps18.pdf Holistic Cyber-Physical Management for Dependable Wireless Control Systems], ACM Transactions on Cyber-Physical Systems, Special Issue on Dependability in Cyber Physical Systems and Applications, 3(1), Article No. 3, August 2018.
 +
* B. Li, Y. Ma, T. Westenbroek, C. Wu, H. Gonzalez, C. Lu. (2016, April). [http://www.cse.wustl.edu/~lu/papers/iccps16.pdf Wireless Routing and Control: a Cyber-Physical Case Study]. ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS'16), April 2016.
 +
* B. Li, L. Nie, C. Wu, H. Gonzalez, C. Lu.[http://research.engineering.wustl.edu/~boli/papers/iccps15_final.pdf Incorporating Emergency Alarms in Reliable Wireless Process Control]. ACM/IEEE 6th International Conference on Cyber-Physical Systems (ICCPS'15), April 2015.
 +
* B. Li, Z. Sun, K. Mechitov, G. Hackmann, C. Lu, S. Dyke, G. Agha and B. Spencer, "[http://research.engineering.wustl.edu/~boli/papers/iccps13.pdf Realistic Case Studies of Wireless Structural Control]," ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS'13), April 2013.
  
−
== Contact the Authors: ==
+
== Get Support ==
−
Bo Li: boli@seas.wustl.edu
+
*WCPS v3.0: Yehan Ma: yehan.ma@wustl.edu

Latest revision as of 07:59, 23 November 2020

Wireless Cyber-Physical Simulator (WCPS) is an open-source simulation environment for wireless control systems. By integrating Simulink and the TOSSIM wireless sensor simulator in a holistic simulation environment, WCPS accurately captures the dynamics of both the physical systems and the wireless sensor-actuator networks used for control. WCPS has been used for realistic case studies of wireless structural control systems for civil infrastructure, studying routing and control of cyber physical system, and incorporating emergency alarms in reliable wireless process control. The broad application of WCPS is to support cyber-physical systems research on large-scale wireless control systems through high-fidelity joint cyber and physical simulations. This site includes the code release, tutorial, and simulation examples for wireless structural control systems.

What's New

WCPS Architecture

Figure 1. WCPS Architecture

In the Fig.1, WCPS simulates the feedback control loop of the control system as follows. Sensor data is generated from plant models such as structures and water tanks. 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 extracts packet delivery information(the delay and loss)from the message pool. Sensor data and their loss and delay are provided to the Data Block, which can 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 reference signals of the plants and wireless traces used as input to TOSSIM. 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, as is shown in Fig.2. 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.

Figure 2. Simulink Model

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 

Below is the installation guide of WCPS v3.0. 
For Mac OSX Users who would like to run WCPS on their own computer, please follow first instruction link below for a detailed installation and test procedures.
For OSX/Linux/UNIX/Windows users, please follow the second instruction link below for ruining Dockerized WCPS in a Docker container.

Download WCPS

Use WCPS

Wireless network plays a critical role in close-loop wireless control system. 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.

Put all the above files into the same folder, prompt a terminal (or a Cygwin window), and in the terminal run 

 Make micaz sim

If TinyOS and python is configured correctly, go ahead and run in the terminal: 

./tossim-call.py

Having collected aforementioned TinyOS files, a simplified example that uses key networking Interfacing Block and Data Block of WCPS is shown in Fig. 3.

Figure 3. A Simple Example that uses Interfacing and Data Block of WCPS.

This examples shows:

  • How input data in Simulink is injected to TOSSIM network;
  • How TOSSIM Interfacing Block runs as a Matlab Embedded function;
  • What type of data is output from the Interfacing Block;
  • How data usage strategies are applied to the data in the Data Block.
  • What type of data is eventually output from the Data Block and provided for future control use.

Source code for the example can be found here. To run this integrated example, simply download, unzip the source code, and run Run_delay_data_func.m in Matlab.

WCPS-RT

Figure 4. WCPS-RT Architecture

Given the complexity of wireless communication in physical environments, simulators cannot always capture the real-world behavior of WSANs. Network-in-the-loop simulations have been developed to address the limitation of wireless simulations by incorporating physical wireless networks.

To experiment with wireless control over real-world WSANs, we develop wireless cyber-physical simulator real-time (WCPS-RT). WCPS-RT integrates MATLAB/Simulink Desktop Real-time (SLDRT) and a 3-floor WSAN testbed. It captures realistic wireless dynamics that are hard to simulate accurately, and leverages simulation support for controllers and physical plants. The architecture of WCPS-RT is shown in Fig. 4.

SLDRT is used to simulate the physical part of the WNCS: physical plants, controllers, state observers, and physical disturbance. In practice, industrial plants usually operate continuously or at very high rates. However, the wireless communication and controller execute at a relatively low rate because of the communication and computation latencies. Therefore, SLDRT modules are operated at different rates in our design.

The 3-floor WSAN testbed is deployed on the 3rd to 5th floors of Jolley Hall at Washington University in St. Louis. It consists of 70 TelosB motes. Each mote is equipped with Chipcon CC2420 radio compliant with the IEEE 802.15.4 standard and a TI MSP430 microcontroller. 40 Raspberry Pis with a backplane network are used for the management of the WSAN.

The interfaces between SLDRT and WSAN are socket connections between the PCs that run SLDRT and the Pis, and serial connections between the Pis and the end nodes. In this way, the end nodes of the sensing and actuation flows can be any nodes in the testbed.

WCPS-EC

Figure 5. WCPS-EC Architecture

We built a real-time hybrid simulator, wireless cyber-physical simulator edge-computing (WCPS-EC), which integrates (1) Real controllers running on various computation platforms; (2) Real Wi-Fi network and Ethernet, or simulated network using TOSSIM; (3) Simulink Desktop Real-time (SLDRT), which simulates robotic arm in real-time.

The architecture of WCPS-EC is shown in Fig. 5. Compared with WCPS-RT, WCPS-EC includes immigrated controllers running on various computation platforms instead of controllers running in MATLAB/Simulink. In addition, WCPS-EC can reflect the impacts of real communication network and computation platform during run-time.

In WCPS-RT, the worst-case end-to-end latency is below one sampling period. Hence the actuation commands are set to have fixed latency of one sampling period. However, in multi-tier control systems, the end-to-end latency can be longer than one sampling period. In addition, we consider a more realistic control system setup with (1) clock-driven sensors that sample the plant outputs periodically every sampling period; (2) an event-driven controller which calculates the actuation commands as soon as the sensor data arrives; and (3) event-driven actuators, which means actuators can respond to updated actuation commands immediately.

Talks

Publication

Get Support

  • WCPS v3.0: Yehan Ma: yehan.ma@wustl.edu
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