Performance Evaluation of Wireless Networks for

Supporting Real Time Collaborative Interactions in

Distributed Haptic Virtual Environments

Kian Meng Yap1, Tsung-Han Lee2

1 Sunway University

Bandar Sunway, Petaling Jaya,

Selangor, Malaysia

Email: kmyap@sunway.edu.my

2 National Taichung University

Taichung, Taiwan

Email: thlee@mail.ntcu.edu.tw

Abstract. This paper presents a performance evaluation based on experimental

study of a new peer-to-peer application for supporting real time force feedback

operation in distributed haptic virtual environments (DHVEs). The new peer-to-

peer architecture is able to support haptic interactions over different wireless

network architecture. Experiments have been conducted to show the

performance of different wireless architecture, i. e. wireless-B/G/N.

Experiments have also been conducted to investigate the performance of this

architecture. Findings of the study are presented in this paper and it shows the

challenges in conducting haptic collaboration over wireless IP networks. This is

especially true when the wireless hops increase.

Keywords: distributed virtual environment, haptic, multi-sensory traffic, peer-

to-peer, wireless haptic.

1 Introduction

The effective transmission of sense of touch (haptics1) traffic presents a significant

challenge to the current Internet architecture. The future Internet will have to carry a

wide range of applications, and many of these will incorporate new types of traffic.

There has been recent interest in the transmission of multimodal information over the

Internet [1], and in particular the transmission of haptic data [2][3]. Currently all

interactions that occur between ourselves and communications networks especially

the Internet involve only two senses (aural and visual). Moreover all these networks,

including the wired or wireless, have been designed to carry application information

pertaining to these two senses (e.g. telephony, video, graphics, and text). The

1 Hap•tic ('hap-tik) adj.of or relating to the sense of touch; tactile. Haptic is from the word in

Greek “haptikos”. [Greek haptikos, from haptesthai, to grasp, touch. (1890)].

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provision of haptic feedback in the future internet can profoundly improve the way

humans interact with information and perform tasks. It is clear that augmenting

current systems such as wireless tele- robotic with the ability to send back information

pertaining to our sense of touch (as well as vision) will greatly improve the fidelity

(and hence complexity) of tasks that can be performed, as well as opening up a much

wider range of applications.

Tele-operation [4] has been a popular research area since the invention of a haptic

device by going through a network medium such as Ethernet in wired transmission,

i.e. tele-haptic. While it is common to have Internet as a transmission carrier, it posted

an even more challenging task for tele-haptic by using the wireless transmission. This

is largely due to the stability issue of wireless medium in which the packets will be re-

transmitted or delayed when there is any collision. Some research activities on tele-

operation focusing on the transmission of video or audio data, but there is very little

research on transmission of additional force data in wireless medium. The

introduction of the haptic sense of touch (i.e. reflected force) in addition to traditional

multimodal senses such as audio and visual, refers to the perceptual kinaesthesia

sensing of events such as heat, pressure, force, or vibration. We are investigating

potential research area for carrying haptic collaborative activities through wireless

medium. The impact for this research will contribute to a new era of research area

whereby it will no longer follow the traditional way of tele-haptic or tele-haptic

communication. For example, in the recent Japan Fukushima nuclear crisis, instead of

sending real people, we can send a robot troop into a dangerous zone. The troop could

be controlled wirelessly. This poses a safer working condition for the operators

because most of the dangerous tasks can be done by robots through wireless medium.

The IEEE 802.11 standard [5][6] specifies two different medium access control

(MAC) mechanisms in WLANs: the contention-based distributed coordination

function (DCF), and the polling-based point coordination function (PCF). PCF adopts

a poll-and-response protocol to control the access to the shared wireless medium and

reduce contention among wireless stations. It makes use of the priority inter-frame

space (PIFS) to maintain control of the medium. Once the PC has control of the

medium, it may start transmitting downlink traffic to stations. Alternatively, the PC

can also send contention-free poll (CF-Poll) frames to those stations that have

requested contention-free services for their uplink traffic. During a CFP (Contention-

Free Period), a wireless station can only transmit after being polled by the PC. If a

polled station has uplink traffic to send, it may transmit one frame for each CF-Poll

received. Otherwise, it will respond with a NULL frame, which is a data frame

without any payload. Also, in order to utilize the medium more efficiently during the

CFP, it is possible to piggyback both the acknowledgment (CF-Ack) and the CF-Poll

onto data frames.

The contributions of the work presented in this paper are: (i) a new peer-to-peer

architecture and an associated algorithm for supporting force collaboration and

position synchronization in wireless networked haptic applications, (ii) an empirical

investigation of the different wireless architecture ( 802.11-B/G/N) to support haptic

collaboration with our proposed algorithm, (iii) we also show the effect of network

impairments, i.e. delay, on collaborative force with our proposed algorithm together

over wireless IP switched network.

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2 Exiting Research in Networked Haptics

Norman [7] examines the current challenges in the deployment of haptic-based

distributed systems and progress to overcome the network impairment challenges.

Lindeman [8] designs a wireless tactor prototype which allows haptic feedback in

virtual reality. However, their prototype is based on a simple wireless broadcasting

and doesn’t consider wireless networked system. Many research studies have studied

this tradeoff for manipulators with controllable torques, i.e., electrically actuated

manipulators [9]. The control scheme is made particularly challenging whenever the

communications channel is non-ideal, for example over wireless networks. Huang

[10] designs a virtual coupler in a mixed virtual environment by transmitting position

and torque information over wireless communication link. The system is tested with

haptic controller but their networked architecture is only carried out with a constant

delay.

Marugame [11] analysed the wireless performance with a bilateral robot system by

using Adaptive Carrier Selection and Kalman Filter. Their result shows that ACS

improved tracking performance, while Kalman filter further mitigates fluctuation to

less than a centimeter. Their other research [12] showed that haptic information is less

effected by Additive White Gaussion Noise (AWGN) than burst error due to Rayleigh

fading in wireless communication system. Their system is evaluated by using both

simulation model and experimental setup. Kabranov [13] deploys a DIVE system

with a “bidding” and “auction” mechanism to match with different QoS level for

supporting the traffic over a simulated wireless network. Suzuki [14] investigated

bilateral wireless haptic communication system by evaluating TCP, UDP and

invalidated Nagle algorithm in TCP. The master-slave system showed that by

invalidated Nagle algorithm in TCP, the system performed better in transmitting

position and force in their haptic communication system.

The majority of the preceding works have concentrated on wired haptic

collaboration or standalone haptic systems. Some of the works are conducted only by

using client-server architecture. There is also little research for transmission of

position and force data in a peer-to-peer network in which the calculation of those

data are performed locally. We have developed an experimental platform based on a

wireless peer-to-peer network architecture in order to study the performance of

impairment (e.g. delay) for haptic feedback in distributed virtual environments.

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3 Haptic Communication via Wireless Network

In this section, the problems in the haptic communication system over IP network are

discussed. Subsequently, the algorithm used to develop the peer-to-peer architecture

is also presented.

3.1 Network Issues on Haptic Interactions

Network impairments can have severe (and different) impacts on the user’s haptic

experience. Network QoS performance is generally described using four basic

parameters. These are: (i) Delay: the difference between the time when the packet has

been sent and the time when it is received, (ii) Jitter: the statistical variance of delay

measured as the average time between two successively received IP packets, (iii)

Packet Loss: expressed as a percentage of the number of packets not received, to the

number of packets sent, (iv) Throughput: the number of packets that can be

transmitted in a fixed amount of time. Delay makes the user’s device go through a

virtual object before it is felt. This degrades the users’ perception of “effective

collaboration”. Delay also desynchronizes the different copies of the virtual

environment.

4 Position Synchronization and Force Interaction Algorithm

Positional synchronization is a major challenge in distributed shared virtual

environments [15]. This becomes even more challenging in peer-to-peer architectures.

In our peer-to-peer architecture, position synchronization is achieved by transmitting

the difference in position, which is calculated from current and previous positions.

The difference in position of the local peer is transmitted to the remote peer who adds

this difference to its local position in order to achieve position synchronization.

Fig.1. Force feedback in collaborative action to a moving object

The force feedback device used in this paper is the PHANToM Omni [16] from

SensAble Technologies Inc. It is used to manipulate moving virtual objects and to

provide the user with feedback from the virtual environment. When two forces push a

virtual object at the same time, their vector sum will decide in which direction the

virtual object will move. As shown in Fig. 1, the reaction force is computed in

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proportion to the remote force, the depth of the PHANToM cursor inside the virtual

object, and velocity between the cursor and the virtual object. When there are two

forces applied to a single virtual object the resultant force is the vector summation of

these forces. Therefore, the movement of the virtual object follows that of the

resulting force. The differences in position, force and time at the local peer are sent to

the remote peer and vice versa.

5 Design of Experimental Peer-to-Peer Architecture

Fig.2. Experimental model of peer-to-peer wireless architecture

The objective of the experimental system is to enable us to study the effects of delay

on the force collaboration and the virtual object’s trajectory. In the test system, two

PCs are used to carry out the tasks and they are connected by wireless links by using

Wireless Distribution System (WDS). In Fig. 2, the peer-to-peer wireless architecture

can provide up to four wireless hops. For example, one or more wireless hop is

obtained by connecting two wireless routers (D-Link DIR-615) to each of the Cisco

2091 router. Hence, the traffic flows from one end to the other end thru the WDS

network. Each haptic traffic flow between computers A and B contains the HIP

position, virtual object position, a timestamp and the force magnitude, as shown in

Fig. 2. The packet rate between the two computers is 1000 packets/second (UDP

packets). The haptic data packet size is 184 bytes, UDP packet header is 8 bytes and

IP is 20 bytes. This adds up to be 226 bytes of data in addition to the Ethernet header

of 14 bytes. Thus, the total throughput of the haptic flow is 1.808 Mbps. The haptic

virtual environment of our experiment consists of a work platform, one moving cube,

one static cube and two ball spheres which represent local and remote PHANToM

cursors (HIPs). Subjects are able to push the moving blue cube by using two

PHANToM devices and feel the momentum, force, and velocity of the virtual cube.

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6 Experimental Results

This section shows the effects of varies wireless architecture on delay and virtual

cube x-position when two subjects are performing the haptic collaboration. When the

virtual cube position is transmitted under wireless network, it behaves differently with

different wireless hopping.

6.1 Haptic Traffic End-to-End Delay

Fig. 3 shows the real time haptic traffic delay captured between Computer A and B in

Fig. 2. In Fig. 3(b), the end-to-end delay of wireless-B and wireless-G is 1800ms and

1100ms respectively at three wireless hops. However, the end-to-end delay of

wireless-N is less than 50ms at two wireless hops and less than 500ms at three

wireless hops. This shows that wireless-N is better than wireless-B and wireless-G in

transmitting the haptic traffic.

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6.2 X-Position Discrepancies

Fig. 4 shows the x-position discrepancy between the two peers (computer A and B in

Fig. 2) over three wireless hops, with our position and force algorithm. With wireless-

N (channel width 40MHz), our position and force algorithm can still follow the

trajectory of the virtual cube’s position. Fig. 4(a) - 4(b) shows wireless-B and

wireless-G made the system totally unusable because the virtual cube’s position

moved vigorously and its trajectory was not able to follow the curve of the virtual

cube position. The x-position discrepancy of wireless-B and wireless-G (approx. 0.2 -

0.3 metre) is much bigger than in the case of wireless-N (approx. 0.025 metre). This is

because wireless-N still can maintain the throughput (approx. 2Mbps) needed for the

haptic traffic. This shows that our basic position and force algorithm, and wireless-N

architecture is able to support haptic collaboration. Wireless-N performs much better

than wireless-B and wireless-G in the case of two wireless hops. In contrast, wireless-

B and wireless-G are not suitable for transmission of haptic traffic in DHVEs.

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Fig. 4. X-position discrepancies of virtual cube over three wireless hops for (a) wireless-B, (b)

wireless-G, (c)wireless-N

7 Conclusion and Future Work

The work presented in this paper is an experimental architecture for networked haptic

interactions with wireless-B/G/N. Different network architecture is shown to be the

main problem when positional compensation is employed. It is also found to be more

difficult to perform force collaboration under the influence of wireless hopping. We

have tested the same setup up to four wireless hops with wireless-B/G/N, but found

that it is very challenging to support the collaborative task after that. It is particularly

very hard to perform the collaborative task at three wireless hops for wireless-B and

wireless-G. The experience of force collaboration has been deteriorated as a result of

higher delay and loss. For peer-to-peer systems to which collaboration with force

feedback is of concern, wireless-N would be suitable for up to wireless hops. In

summary, there are challenges for wireless network to support force collaborative

operations across wireless networked peers when both HIP pushing the virtual object

together under network impairments. In the future, we intend to investigate the

possibility of a better network architecture to support >3 wireless hops that allows

consistency force and position collaboration. One of the potential solutions we are

investigating is a new higher gain antenna to serve its purpose.

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