Telehaptic data communication (transmission of touch signals) is known to be extremely sensitive to packet loss and jitter, the primary consequences of network congestion. Existing studies have established the Quality of Service (QoS) conditions that need to be guaranteed for smooth telehaptic communication. Specifically, the telehaptic communication can tolerate no more than 10% packet loss and 10 ms jitter. In this paper, we conduct a detailed investigation of the impact of TCP cross-traffic (pre-dominant traffic on shared networks) on telehaptic packet loss and jitter. The important contribution of our study is twofold. Firstly, we discover that even during scenarios where the long term average packet loss is comfortably below its QoS limit, the instantaneous loss can far exceed this limit. Secondly, we demonstrate that the probability of jitter QoS violation increases with the number of concurrent TCP sources in the network. These effects could potentially be harmful to the telehaptic activity, thereby raising serious concerns on designing efficient communication frameworks for minimizing telehaptic packet loss and jitter on shared networks.
Everyday activities that the humans perform are largely dependent on our sensory mechanisms that aid in learning the physical properties of any real object such as size, shape, weight, texture, hardness, smell, and so on. The touch perception forms an integral part of our sensory mechanism. When an object is held, it exerts certain forces on the hand. The muscles and the joints of the hand capture these forces and they are then transmitted to the brain, generating a perception map of the object. This sensory mechanism is the fundamental driving force behind the innumerous forms of seamless interaction between humans and the physical world. Life would be lot harder if one was to light a matchstick, drive a car, or play a game of golf without the ability to feel the physical object.
Haptics relates to the science behind the different mechanisms of perception of real objects through the sense of touch. The deep research insights in this field have led to the design of elegant electro-mechanical systems that have enabled us to interact and manipulate virtual as well as remote objects through the feeling of touch.
Telehaptic communication – the science of coding, and
subsequent transmission of haptic signals over a network – has
witnessed rapid progress over the past decade. Such
communication has been envisaged to redefine the way we
interact with a remote world. For example, a surgeon could
perform telesurgery on a distant patient through a robotic
telemanipulator with the feeling of touching the patient’s body
[
Figure 1 depicts a typical telehaptic communication
framework over a shared network. The human operator (OP),
using the force, audio, and video feedback from the remote
environment, makes certain movements in an attempt to
interact with and/or manipulate a remote physical object. The
position and velocity signals thus generated are transmitted to
the remote environment via the forward channel. The robotic
teleoperator (TOP) at the remote location utilizes these
coordinates in order to replicate OP’s movements accurately.
Any contact between the remote object and the TOP generates
forces, which are transmitted back to the OP along with audio
and video feedback on the backward channel. The presence of
haptic feedback has been shown to increase the immersion into
the remote environment, and further improve the precision of
the telehaptic activity significantly [
Fig. 1. Schematic representation of a telehaptic communication framework depicting the signal exchange between the human operator (OP) and the robotic teleoperator (TOP).
Naturally, such highly sensitive operations necessitate accurate replication of the OP’s movements by the TOP, and also timely delivery of the feedback signals to the OP. For example, large delays in haptic feedback result in sluggish perception of the patient’s body, thereby (potentially) leading to a wrong action by the surgeon. Additionally, large telehaptic jitter leads to perceiving the same remote object as having variable mass, which is absurd. Note that jitter refers to the variation in the packet delays. High packet losses may cause improper replication of the OP’s movements accurately and/or OP being severely deprived of the feedback signals. Both these scenarios could have catastrophic effects on the ongoing telehaptic activity. Note that the packet loss in the network is a consequence of queue overflows during congestion. These effects can, at times, cause irreparable damage to the patient. Hence, the communication network that transfers the telehaptic feedback plays an instrumental role in determining the quality of the telehaptic interaction.
Experimental studies, such as [
It is important to note that the work in [
It is important to remark that in a real world scenario the
perception of remote objects (potentially) depends on the
instantaneous packet loss rather than the long term average
loss. For example, in a few network settings the instantaneous
packet loss is way higher than 10% (see Figures 4 and 5)
despite its long term average value being below 10%. This
means that a vast majority of the telehaptic samples (up to 80%
in our simulations) do not reach the destination. As per the
claim in [
A telehaptic stream on a shared network, like the Internet,
has to contend with other cross-traffic streams that are
concurrently being served by the network. Hence, it is crucial
to study the influence of the coexisting cross-traffic streams on
the telehaptic stream in terms of instantaneous packet loss and
jitter. On a shared network, the telehaptic stream is guaranteed
to encounter Transmission Control Protocol (TCP) traffic
since TCP amounts to over 90% of the overall traffic [
For our investigation in this paper, we consider a specific
flavor of TCP named TCP NewReno [
In this paper, we intend to study the impact of multiple TCP cross-traffic sources on a telehaptic stream. The objective of this investigation is to gain insights into the characteristics of the instantaneous telehaptic packet loss and jitter under the influence of coexisting TCP cross-traffic sources. The contribution of our work is as follows. (i) We demonstrate that in a wide range of settings, even though the long term average packet loss meets the QoS criteria, the instantaneous packet loss can be much higher. (ii) We show that the peak telehaptic jitter can far exceed the 10 ms deadline for standard network settings, and hence is extremely prone to QoS violations.
The remainder of the paper is organized as follows. In Section II, we discuss in brief a few prior works available in the literature related to the interplay between TCP and telehaptic streams. Section III describes the detailed simulation setup that we designed for our investigation. In Section IV, we present the results of our experiments, and in Section V, we state our conclusions and mention potential directions for future research.
Only a handful of works have attempted to study the
behavior of telehaptic streams on a shared network [
In this section, we give a detailed description of the
experimental settings considered in our simulations. The goal
of this section is to develop an understanding of the dynamics
of interplay between TCP and telehaptic streams when the two
traffic types share a single bottleneck link. We carry out our
investigation using NS3 – a discrete event network simulator
[
The propagation delay of each link is set to 5 ms, and hence
the one-way propagation delay between a source and its
corresponding receiver is 15 ms. The channel capacity of L1 is
set to 3 Mbps. The access links to L1 have high capacities of 5
Gbps. The queue size at the B1 is configured to 15 kB. The
TCP and the telehaptic packets have sizes 578 B and 512 B,
respectively, unless mentioned otherwise. For the purpose of
our simulations, we consider n in the range [
All sources begin the transmissions simultaneously at t = 0. We run each simulation until t = 100 s. Throughout the simulations, we record the packet loss and jitter encountered by the telehaptic sources.
In this section, we present the results of our investigation of telehaptic packet loss and jitter induced by the coexisting TCP streams. We begin by reporting the packet loss, and then move to the jitter part.
In Figure 3, we report the long term average packet loss seen by the telehaptic source by varying n over the considered range. It can be seen that the long term average packet loss is an increasing function of n. However, for n < 10, the long term average packet loss complies to the QoS limit of 10%. However, we note that for higher n, the average loss exceeds the QoS limit severely. For brevity, we do not report the telehaptic packet loss in the higher n regime.
We now move to studying the behavior of the instantaneous telehaptic packet loss for a specific value of n for which the average loss meets the telehaptic packet loss criteria. For this purpose, we choose n = 10. Note, from Figure 3, that the long term average loss for n = 10 is approximately 10%. From Figure 4, it can be seen that the instantaneous telehaptic packet loss varies rapidly between 0 and 50%. In addition to the peak loss measurement of 50%, it can also be seen that the packet loss QoS criteria gets violated regularly. Although we report the instantaneous packet loss only for n = 10, we observe similar behavior for other values of n as well. In short, even though the long term average packet loss meets the QoS criteria, the instantaneous loss can be significantly higher. This confirms our conjecture that the instantaneous packet loss should be considered as the performance metric rather than the long term average packet loss.
It is important to remark that even though the interval over which the QoS violation occurs is small (a maximum of 300 ms), this could potentially have severe artifacts considering the scale of sensitivity that a telehaptic activity, like telesurgery, requires. Having seen the instantaneous loss, we now turn towards determining the peak instantaneous telehaptic packet loss in the simulations. Figure 5 shows the variation of the peak packet loss in the considered range of n. It can indeed be observed that the instantaneous packet losses are substantially higher despite the long term average packet loss complying to the QoS requirement. Therefore, we demonstrate through experiments that any guarantees on the long term average packet loss do not imply any guarantees on the peak instantaneous packet loss. This suggests that in order to ensure a seamless telehaptic activity, one must design communication frameworks that can provide QoS guarantees on the instantaneous telehaptic packet loss.
It has been shown in the past that smaller telehaptic packets
(relative to TCP packets) are less susceptible to losses [
We now move to the peak telehaptic jitter measurements. For the packet sizes mentioned in Section III, we notice that the peak telehaptic jitter varies in the range [2.55, 6.69] ms, which satisfies the QoS constraint. Since the jitter is known to be heavily dependent on the TCP packet size, for concreteness in exposition, we run the simulations with TCP packets of size 1042 B, which is also another standard value. In Figure 6, we plot the peak instantaneous telehaptic jitter as a function of n. It can be seen that the peak jitter is a non-decreasing function of n. Further, for n > 5, the jitter QoS condition is severely violated. This implies that higher the number of concurrent TCP streams, larger is the probability of violation of the telehaptic jitter QoS violation.
Based on the analysis in [
Fig. 6. Variation of peak instantaneous telehaptic jitter with TCP packets of size 1042 B.
In this paper, we conducted an extensive investigation of the interplay between TCP NewReno and telehaptic streams. We demonstrated that even though the long term average telehaptic packet loss satisfies the QoS criteria, the instantaneous loss can far exceed the QoS limit of 10%. Additionally, we showed that the telehaptic stream faces extreme jitter QoS violations for TCP packets of standard sizes. Hence, we conclude that it is crucial to monitor and control the number of TCP streams, as well as the size of TCP packets in order to achieve seamless telehaptic communication on a shared network.
In a future version of this article, we intend to propose a telehaptic communication framework that mitigates the detrimental effects of TCP sources. Also, studying the effects of other variants of TCP on telehaptic stream could be another interesting avenue for future research.