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International Symposium on Wireless and Pervasive Computing (ISWPC 2011)

Conference Programme

Wednesday 23rd

of Feb 2011

o Context- aware Computing

o Sensor Networks

o MIMO Systems

o Ad-hoc Networks & Routing

Thursday 24th of Feb 2011

o Wireless Computing

o Air Interfaces

o Sensor Networks (II)

o Wireless Multimedia

Friday 25th of Feb 2011

o Ad-hoc Networks & Routing (II)

o Emerging Networks

o Air Interfaces (II)

International Symposium on Wireless and Pervasive Computing (ISWPC 2011) Wednesday 23rd of Feb 2011

Context- aware Computing Wed 23 Feb 2011, 10:30 – 12:30 hrs

Context-aware pervasive speech recognition system

Meghdad Aynehband; Amir Masoud Rahmani; Saeed Setayeshi; Mohammad Mosleh

Toward the Ubiquitously Networked Society: QoS-aware Residential Gateway with ZigBee-based Network

Pei-Chen Tseng; Wen-Shyang Hwang

Business Process Specification and Enactment for Context-Aware Environments

Torab Torabi

Toward the Ubiquitously Networked Society: QoS-aware Residential Gateway with

ZigBee-based Network

Pei-Chen Tseng Department of Information Engineering and Informatics, Tzu Chi College of Technology

peichen@tccn.edu.tw

Wen-Shyang Hwangl

Department of Electrical Engineering, National Kaohsiung University of Applied Sciences wshwang@mail.ee.kuas.edu.tw

Abstract

Our earlier embedded QoS-aware residential gateway (EmQRG) for real-time class-based queuing (CBQ) bandwidth management is reviewed and experimentally demonstrated. EmQRG's high QoS is demonstrated in conjunction with a wireless ZigBee network of temperature/humidity monitoring sensors. Critically, the EmQRG sends a top-priority over-temperature alarm when any temperature/humidity module reports a temperature exceeding a preset value. This emergency signal has top EmQRG transmission priority. Experiments verify the over­temperature alarm sends/receives "immediately" regardless of heavy network congestion or bottlenecking. The presented system easily expands to extensive networks containing many parallel systems or embedded sub-systems. The presented system is cost-effective implementable with available hardware and software.

Keywords: Wireless Sensor Network, ZigBee, QoS, Home Network

1. Introduction

The technological future is increasingly perceived as being ubiquitously networked, wherein wireless networks (WN) and smart WN-capable sensing devices form complicated systems of systems. Such systems need to operate unattended for long periods of time in the context of real world communication. This critical mission is driving the need for high confidence WSNs, high inter­compatibility and high ease-of-use.

Wireless Sensor Networks (WSNs) are under study for applications such as search and rescue, disaster relief, surveillance, target tracking, medical monitoring and smart environments. In sensor networks, a node's location is part of the node's state. Node location has been used [1-4] to identity the spatial source of sensor readings in many location-based services.

One WN line of development is the ZigBee system. ZigBee is a high level communication protocol for low­power digital radios based on the IEEE 802.15.4-2006 [5] standard. ZigBee is targeted at radio-frequency applications of low data rate, long battery life, secure networking.

I Corresponding Author: Wen-Shyang Hwang

Zigbee is flexible, scalable, simpler and cheaper than other personal area WNs such as Bluetooth (Table 1).

The ZigBee Alliance [6] is working with IEEE to ensure interoperable networks for consumer electronics, energy management, security, inventory management, body­monitoring, home automation, automated buildings, industrial automation, etc [7]. High QoS is demanded for critical alarm data concurrent with streaming media.

Table 1 : Comparison of wireless network

technologies.

ZigBee Active RFID I

Monitoring Object Target and control, Idontification Market sensor and

network managoment

System Resource Low Proprietary Requirement

,�, =f= I-- -

$4+

Typi cal current 1 18 mA< 5mA< absorbed

Max. 250 Kbps NlA Bandwidth -r-- -

Nodesl 164000 Mesh Master

Nominal Tr.msmlsslon 1-100 m !;'100 m range

Remote Electronic control.

Application battery-card. object

Focus operated tracking.

products. presence

sensors mon�orlng

Bluetooth I

Wi.fl

replacement application Cablo :

Iinternol

:-�i S5 $6-S10

3OmA< 1 �5O

2.1 Mbps Up to 54 Mbps

I-- -

7 32

10m room

High Wireless USB. PDAs.

speed handsets.

wireless

headsets Ethernet access

Ultra Wide Band

Short range high data rate application

Medium

-

NlA

NlA

100 Mbps +

Mesh

10m

Rea�time multimedia data transmitting

Composite wireless, hardwired, ad hoc, LAN and Internet super-systems are increasingly common but result in serious interoperability issues. It is difficult to design efficient and flexible architecture for systems which exchange data between significantly different sub-systems.

Our prior work presented an embedded QoS-aware residential gateway (EmQRG) [8] which focused on a home-scale network. It offered a basic Internet-LAN gateway and server which coordinated and optimized data

978-1-4244-9867-3/11/$26.00 ©2011 IEEE

traffic flow over a network with bandwidth-limited resources. Traffic was optimized by identifYing and classifYing forwarded traffic according to priorities set by the user. Typically, data-intensive streaming, e.g. video and online gaming, were given high priority. Less critical traffic, e.g. email and ftp transfer, were given lower priority. Top priority was given to critical signals, e.g. fire alarms, security alerts and remote medical sensor links. It is anticipated that ZigBee or similar WN systems will be peripheral to and/or embedded in composite networks which will revolve around PC-based systems. Thus, as a step toward the ubiquitiouly networked community, this paper extends our earlier EmQRG system to integrate with wireless ZigBee systems.

The following reviews and demonstrates EmQRG for real-time class-based queuing (CBQ) bandwidth management in a DiffServ-capable CBQ-capable network. EmQRG's ability to deliver high QoS in conjunction with a ZigBee system is demonstrated using EmQRG to integrate ZigBee-based temperature/humidity monitoring (FT-6250 + FT-6251 's) with ongoing streaming multimedia. Third, expanding this prototype system to larger environments is discussed. The presented prototype is implemented with off-the-shelf components and software designed by ourselves. The total system is easily implemented by anybody with reasonable knowledge in the field.

2. Overview of Related Work

Wireless technologies for short- and medium-range communications have been discussed in [1-2] [9-14]. Additional work has been dedicated to developing the ability to support multiple applications and improving cost efficiency, such as smart ducts [1] [10-11] [14].

Home Network Extemal Network

.�-

Figure 1 . Example of multiple embedded networks

with dissimilar component systems.

ZigBee is a symbiosis of the standards of two organizations, namely the IEEE and the ZigBee alliance [6]. Many companies use open software and hardware to manufacture ZigBee platforms [7] [10] [14]. ZigBee devices can work years on the same battery, support transmission rates of 20 Kbps to 250 Kbps, and are very economical indoors from 10 to 100 meters [5] [15-17]. Most modem WSNs work in frequency bands where ZigBee is standardized [2] [12]. Nevertheless (Fig. I and Table 1) ZigBee competes with Bluetooth, Ultra Wideband and 802.11 techniques [13]. The need for intercompatibility is driving vendors to build chipsets that support several

competing WN technologies. EmQRG was designed as a smart-home control center

integrating safety/security tasks by coordinating sharing of digital content, translating communication protocols among various devices, working as a gateway to external networks, and performing the DiffServ-QoS traffic classification mechanism detailed in the next section (Figs. I and 3). This paper adds a FDlXP425-Dev platform [18] to EmORG to demonstrate intercompatibility with a multi-sensor ZigBee­based wireless sensor network. The FDIXP425-Dev platform supports many applications, e.g. embedded network video server platforms, embedded network and communication development platforms, embedded computer communication platforms, the 802.11 a/b/g application development platform, the SOHO router, internet gateways, WLAN AP, network fireproof wall development, VoIP, etc. The manufacture claims that FDlXP425-Dev allows customers to easily finish development tasks.

Wireless communication in the following is accomplished according to the X-lO standard [13], which is an international and open industry standard for inter-device communication. X-lO is the best-known home automation standard, enabling plug-and-play operation with any home appliances. X-lO was designed for home automation using power line wiring with signals composed of brief radio frequency bursts representing digital information. X-I0 transmissions are synchronized to the zero-crossing point of AC power lines and enable control of device status, for example a lamp unit (on, off, dim, bright).

End Device End Device

PC

Figure 2. A star network topology.

In the following, FT-6251 High Power ZigBee Sensor Boards [19] transmit temperature and humidity data to a ZigBee gateway, a FT-6250 High Power ZigBee Base Board in a star network topology (Fig. 2). The FT-6250 links via RS232C with an IXP425 embedded in the FDlXP425-Dev platform embedded in the EmQRG. The coordinator starts the network for the sensor boards to join, then receives sensor data and outputs the readings and the corresponded network addresses to the UART, also sending control data to the end devices via indirect transmission. The end devices periodically take readings from the local sensor, then transmits the data to the coordinator. In periods between sensing and transmission, the end device conserves energy via sleep mode. The coordinator saves network information in a flash memory and retrieves it to maintain an established network after power failure or reboot. The resulting ZigBee system is capable of:

External Network Home Network

Web Brow •• r Power

Line

Figure 3. Network architecture of EmQRG-embedded Zig8ee home network.

• 65,536 network (client) nodes • Optimized for timing-critical applications and

power management

Time to join network: <30ms

Sleeping to active: <I5ms

Channel access time: <15ms • Full mesh networking Support

3. DiffServ-QoS mechanism and application

structure of the FT -62501FT -625 1 ZigBee

network

3.1. DiffServ-QoS Mechanism

EmQRG uses our DiffServ-QoS service architecture, which is classifies forwarded traffic, marking each data packet for special treatment according to preset (user adjustable) behavior aggregates. Packets are forwarded according to the per-hop behavior (PHB) associated with the DiffServ codepoint in the packet header. Details of the DiffServ-QoS processing scenario are available in [20]. Briefly, traffic flow is separated into classes such as safety traffic, multimedia traffic, ICMP traffic, file transfer traffic, web traffic, interactive traffic and BE (best effort for uncategorized traffic) traffic (Table 2). Each class of traffic is assigned a preset DiffServ-QoS value. Emergency alarm services are given the highest priority. This is particularly important in busy multi-service composite systems.

Table 2. Traffic Classification in the EmQRG.

I;CJ ilfiIif. .� 'flir:" ,..., � . . . . .

Safety traffle (HTTP:8077) TCP:8077 9977 EF

Web traffic TCP:80 9980 AF22

(HTTP:80)

File transfer traffic (FlP) TCP: 21 9921 AF 31 TCP: 20 9920

Interactive traffle TCP:22 9922 AF21

(SSH. TELNET) TCP:25 9925

Multimedia traffic (UOP) UOP 9990 EF

Ping (ICMP) ICMP 9910 BE

3.2. Application structure in FT -6250/ FT -6251

ZigBee sensor networks

AppColdStartO is the application entry point. It is called by the boot loader every time there is a reboot or a wake-up from sleep mode without memory hold. AppCoidStartO first calls vWUART_InitO to perform the following tasks [19]:

• Initialize stack and hardware interface. Application Queue API is used, so only the upward queues are monitored.

• Initialize the system state and flags. • Set PAN ID and short address of the coordinator.

Flowchart

System State

• E_STATE_INIT

E STATE ENERGY SCAN { E _ STATE_ENERGY _SCANNING

E_STATE_STA RT_COORDINATOR { E_STATE_RUNNING_UART_APP {

Figure 4. Network formation process.

The coordinator operates in any of these system states: /* System states * / typedef enum {

E_STATE_INIT, E_STATE_START_ENERGY_SCAN, E_STATE_ENERGY_SCANNING, E_STATE_START_COORDINATOR, E_STATE_R��G_UART_APP

} teState;

The first four states create a network (Fig. 4). Then, the coordinator stays at E_STATE_RUNNING_UART_APP

for normal operation. End devices can join the network by performing Active Scan.

Direct transmission is used to transfer data from end devices to the coordinator, which is "power on" at all times.

MAC layer Acknowledgement ensures successful data reception. The end device goes into sleep mode after successful data transmission. If the end device assumes network connection is lost, it reboots to attempt to rejoin the network. Indirect transmission is adopted to transfer data from coordinator to end devices, which poll after every wake-up to check if data is pending from the coordinator.

The coordinator saves network information to flash memory, so the network is maintained after coordinator reboot or power failure. Major network information sCoordData are stored in flash memory by calling vSaveContextO. sCoordData are restored by calling vRestoreContextO, which reads data out of flash memory and saves network information into the MAC hardware register by calling vStartCoordinatorO.

During network operation, both LEDs (Fig. 5) on coordinator and end devices are ON in the initialization stage. After coordinator/end-device connection, the end device sends data periodically with a flash of LED 1. When LED 1 is on, the coordinator also toggles to indicate reception of data. When Button 0 is pressed, LED 0 toggles and the LED 0 of all end devices will also toggle, after a delay.

HmO HUll

Figure 5. LEOs and Buttons on FT-6251 Sensor Board.

4. System Implementation

Figure 7(a) show our demonstration EmQRG with ZigBee-based home-type network, with EmQRG is embedded in an Intel mainboard with Linux as and a ZigBee-based temperaturelhumidity monitoring system. The Internet is simulated by two Cisco 7204 VXR and two 3845 routers. Each device has its own IP address.

The EmQRG interface is based on a FudanTech High­Speed Network Development Platform using an Intel IXP425: FDIXP425-Dev Platform. The FDIXP425-Dev Platform has: 32MByte Flash, 128MByte SDRAM, three independent 1011 OOM Ethernet interfaces, two 32bit 33MHz�66MHz PCI Slots, one MiniPCI slot for a WLAN card for 802.11a/b/g, six high-speed UART interfaces, two TTL UARTs interfaces, two high-speed USB HOST interfaces, one USB device interface, RTC, GPIO and a JTAG debug interface [18].

The coordinator is based on a FT-6250 card, i.e. a development board with a high power ZigBee wireless communication module interfacing with GPIO, UART,

ADC, DAC or Comparator systems. In practice, FT-6250 permits point-to-point transmission up to 700 meters in open outdoor environments. Indoor transmission range is shorter and strongly dependent on the local environment [8]. Individual ZigBee-based templhumid sensors employ a FT-6251 card (development board similar to the FT-6250), each embedded with a digital temperature sensor (ODC � 70 DC) and a humidity sensor (5 � 95%).

A flowchart for the FT-6250/FT-6251 network is shown in Fig. 6, where the coordinator (FT-6250) is connected to the IXP425 embedded system by an RS232C link with a 115200 baud rate. Update the data per 500 ms.

Initial IEEE 802.15.4

Stack

Set Frequencv

Channel

Start Network

Join other device to Network

Yes

Recv data

Figure 6. FT-6250/FT-6251 network formation flowchart.

State 1: Start sampling temperature data by calling vHTSstartReadTempO;

State 2: Get the temperature result by calling u16HTSreadTempResultO;

State 3: Start sampling humidity data by calling vHTSstartReadHumidityO;

State 4: Get the humidity result by calling u16HTSreadHumidityResultO;

State 5: Store temperature and humidity data to the parameter pu8Payload by calling vWUART_TxDataO;

State 6: Output temperature and humidity results to UART by calling vProcesslncomingDataO.

Initial threshold values are set for each sensor, a database with the static node topology is established and also a database for authorized users. In our test case, the temperature system provides a high-priority over­temperature alarm via SMS, FTP, make-a-call, email services, etc.

5. Experimental Results

The schematic layout and physical installation of our real-time laboratory experiment are shown as Figs. 7(a-b),

showing the four Cisco series routers, 7204-1, 7204-2, 3845-1 and 3845-2, configured as DiffServ routers, policing and forward data as per the DiffServ field markings. A network processor IXP425 embedded system is the EmQRG. Three PCs serve, one each, as Client, traffic generator HI and traffic receiver call Server. EmQRG and HI each connect via a 100 Mbps Ethernet link to Cisco router 7204-1. Linking the two DiffServ routers is a 10 Mbps Ethernet link, i.e. a bottleneck intentionally challenging EmQRG's QoS capabilities. Cisco router 7204-2 then connects to the Server over a 100 Mbps Ethernet link. The Cisco router 7204-1 with CBQ traffic control of bandwidth/traffic management is optimized for bounded network resources. DiffServ-QoS traffic classification bandwidth allocation with 5 isolated channels of non-sharable bandwidth, 3 of 1 Mbps for AF (assured forwarding) traffic, 1 of 3 Mbps for BE traffic and 1 of 4 Mbps for EF (expedited forwarding) traffic (10 Mbps bandwidth total). EmQRG assigns forwarded traffic to the classes in Table 2. Security data gets highest priority followed by multimedia and other real-time applications. For laboratory test, the Server simulates an Internet or large LAN environment both without/with background traffic and with without/with the above-mentioned bottleneck.

� Back9round traffic: gIIntf1tor

Figure 7(a). Logical layout of testbed.

Figure 7(b). Physical layout of testbed.

Experiment 1: Experiment 1 tests QoS during multimedia streaming. UDP video is delivered by vIc from Client and HI to the Server, with a different IP for each sender. Congestion is simulated by HI sending background traffic (i.e. BE traffic) streams, 1000 pkts/s, 512 bytes/pkt to the Server. When EmQRG activates the DiffServ-QoS mechanism for classifying forwarded traffic, then the UDP traffic packet headers are changed by DSME to EF as in Table 2.

Statistical analysis of experiment 1 are obtained by the command "sh interfaces accounting" at Cisco router 7204-1, showing: The total traffic has 148298 packets (104907880 bytes) with 48569 packet drops to be sent. BE Traffic is 134164 packets (85713908 bytes) and 2304 packet drops. EF traffic is 14134 packets (19193972 bytes)

and 0 packet drops. Thus the server is showing the film with a 32.75% packet drop rate. QoS during network congestion is seen in Fig. 8(a) at the Server. The upper image is from the Client under EmQRG with DiffServ-QoS activation, showing high QoS without packet loss. The lower image is from HI without DiffServ-QoS activation, showing poor QoS and a 36.20% packet drop rate. Fig. 8(b) shows a Live Graph display of experiment 1 as generated by PRTG Traffic Grapher packet sniffing at the Server. Experiment 2: First integrate the X-I 0 power line network, Host, IXP425 and the FT-6250/FT-6251 ZigBee sensor network as shown in Figs. 7(a-b). Initialize: set the temperature threshold to 28°C. (1) The light bulb of the X-lO power line network is off;

the current temperature/humidity is 26°C/45%, which is displayed on the home page of the FT -6200 sensor system (Fig. 9(a)).

(2) Experiment: use the index finger to touch the sensor to raise the temperatureihumidity > 28°C176%, which is displayed on the home page of the FT -6200 sensor system. This temperature has reached the alarm/alert threshold (Figs. 9(b-c)).

(3) The light bulb of the X -10 power line network turns on. The system sends an emergency over-temperature alarm to the user or administrator.

-"" --

"" I� .• -.. .. ---.. .. .. .

Figure 8(a). Film results of experiment 1 .

���--=-----��----�------�--�� I ___ _ ___ ' __ D

Figure 8(b). Live Graph display of experiment 1 .

Figure 9(a). Bulb-off results of experiment 2.

Figure 9(b). Bulb-on results of experiment 2.

Figure 9(c). Home page of experiment 2.

The above 2 experiments represent a home-type network or comer office network. The experiments were implemented on real hardware. The QoS of the basic EmQRG home network was shown to function well, even under congested and bottlenecked conditions. The experimental over-temperature alarm of the ZigBee­equipped system was received almost immediately under all experimental conditions.

Chaining our SOA (service-oriented architecture)-based EmQRG as parallel or embedded networks presents no special challenges. SOA-EmQRG details are available in [21]. Chaining means the basic hardware is duplicated for each new network. The biggest issue is the specific set-up of each new component in each network. The SOA nature of the architecture simplifies much of this issue, making new component systems relatively easy to install.

Figure 1 's embedded networking of dissimilar and composite networks will become increasingly common. QoS will need to combine data-intensive media streaming with WSN s such as ZigBee network. The presented system offers and expedites all these features with use of presently available hardware and software.

7. Conclusions and Future Work

Our previous EmQRG home-network was expanded to support a multi-platform multi-user network to help develop the pending ubiquitously networked world. Experiments confirm multimedia QoS, even during bottlenecked and congested network conditions. A ZigBee­based multi-module temperatureihumidity network, sending an over-temperature alarm when the temperature exceeds a preset value, is sent/received "immediately" regardless of congestion. The presented system is cost­effective, expandable to networks with many parallel systems or embedded sub-systems, and can be implemented with available hardware and software.

8. References

[I] T. He, C. Huang, B. M. Blum, 1. A. Stankovic, T. Abdelzaher, "Range-Free Localization Schemes for Large Scale Sensor Networks," MobiCom 2003, 2003.

[2] J. Heidemann and R. Govindan, "An Overview of Embedded Sensor Networks," Handbook of Networked and Embedded Control Systems, Springer-Verlag, 2004.

[3] L. M. Ni, Y. Liu, Y. C. Lau and A. P. Pati!, "LANDMARC: indoor location sensing using active RFID," Wireless Networks, 10 (6), pp. 701-710, 2004.

[4] G. Shreve and D. Kel1, "A precision location network using ultra wideband WLAN radios," The Third IEEE Workshop on Wireless LANs, 2001.

[5] "Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate

Wireless Personal Area Networks (WPANs)," IEEE Computer Society, 2006. http://standards.ieee.org/getieee802/download/802. 15.4-2006.pdf

[6] ZigBee Alliance, http://www.zigbee.org

[7] http://www.sinp.com.tw/rcm3700.html

[8] P. C. Tseng, 1. W. Wang and W. S. Hwang, "Securing traffic at QoS-aware residential gateway using biometric signatures," IEEE Transactions on Consumer Electronics, vo1.54, no.3, pp. 1148-1156, 2008.

[9] G. Leen, D. Heffernan, "Expanding automotive electronic systems," Computer, vol. 35, no. I, pp. 88-93, Jan 2002.

[10] Kay Romer and Friedemann Mattern, "The Design Space of Wireless Sensor Networks," IEEE Wireless Communications, vol II, no. 6, pp. 54-61, 2004.

[II] S. Hadim and N. Mohamed, "Middleware Chal1enges and Approaches for Wireless Sensor Networks," IEEE Distributed Systems Online 7 (3), 2006.

[12] I. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci,

"Wireless sensor networks: a survey," Computer Networks, vol. 38, Issue 4, pp. 393-422, Mar. 2002.

[13] M. Galeev, "Home networking with Zigbee," Embedded Systems Design, 2004. http://www.embedded.com/columns/technical insights/ 1890 243l? reguestid=253263

[14] 1. K. Hart and K. Martinez, "Environmental Sensor Networks: A revolution in the earth system science?" Earth-Science Reviews, 78, pp. 177-191,2006.

[15] W. C. Park and M. H. Yoon, "The implementation of indoor location system to control ZigBee home network," SICE-ICASE International Joint Conference 2006, pp. 2158-2161,2006.

[16] M. Norris, "Single-chip ZigBee for indoor mobile telemetry," The lEE Seminar on Telemetry and Telematics, pp. 10/1-10/4, 2005.

[17] M. Sugano, T. Kawazoe, Y. Ohta and M. Murata, "Indoor localization system using rssi measurement of wireless sensor network based on zigbee standard," Wireless Sensor

network, 2006.

[18] FDIXP-425, http://www.fudantech.com/cp9.asp [19] Fontal Technology, http://www.fontaltech.com/fonweb/e­

product-evk.htm

[20] W. S. Hwang and P. C. Tseng, "A QoS-aware residential gateway with bandwidth management," IEEE Transactions on Consumer Electronics, vo1.51, no.3, pp. 840-848, 2005.

[21] P. C. Tseng, C. Y. Chen, W. S. Hwang, 1. S. Pan and B. Y. Liao, "QoS-aware Residential Gateway Supporting ZigBee­related Services Based on a Service-oriented Architect International Journal of Innovative Computing, Information and Control (IJICIC), vol. 6, no. 6, pp. 2803-2816, Jun. 2010.