Complexity Management: A Major Issue for Telecommunications
David G. Messerschmitt
Department of Electrical Engineering
and Computer Sciences
University of California at Berkeley
Proc. International Conference on Communications,
Computing, Control, and Signal Processing,
Stanford University, Palo Alto, CA, June 22-26, 1995.
To appear in Kailath Festschrift,
A. Paulraj, V. Roychowdhury, C. Schaper, Editors,
Kluwer Academic Publishers, 1996.
Regents of the University of California,
all rights reserved.
Acrobat version (best for printing).
- 1.0 - ABSTRACT
- 2.0 - INTRODUCTION
- 3.0 - THE CHANGING ENVIRONMENT FOR RESEARCH
- 3.1 - Advances in the underlying technology
- 3.2 - Advanced applications
- 3.3 - Heterogeneity
- 4.0 - SHORT TUTORIAL ON COMPLEXITY MANAGEMENT
- Figure 1. - Three basic elements of complexity
- 4.1 - Architecture
- Figure 2. - A simplified and familiar
example of an architecture.
- 4.2 - Abstraction
- Figure 3. - A familiar example of the
use of abstraction in a computing system ALU.
- 4.3 - Reusability: configurability, scalability,
- 5.0 - A TELECOMMUNICATIONS EXAMPLE
- Figure 4. - Transcoder architecture for
JSCC in a heterogeneous transport environment.
- Figure 5. - A substream architecture manages
JSCC as well as heterogeneous transport and terminal environment in unicast
and multicast connections.
- 6.0 - CONCLUSIONS
- 7.0 - REFERENCES
As a result of years of geometrical advances in underlying electronics
and photonics technology, traditional efficiency and performance considerations
(which have been dominant activities in telecommunications research) will
play a somewhat diminished role in the future. Simultaneously we are accumulating
multiple standards, protocols, and transmission media, proliferating a variety
of user-oriented applications, and seeing cost-effective software implementations
and hardware systems with enormous complexity. These trends imply that an
increasing barrier to progress in telecommunications is not cost or efficiency,
but managing the tremendous complexity of heterogeneous networks, media,
terminals, and applications in a multi-vendor environment. More generally,
while complexity management has been a traditional issue in software engineering,
and later in integrated circuit design, for the future it will be an increasingly
important issue in large-scale system design. Our hypothesis is that complexity
management will be an increasing factor in telecommunications research and
development. This does not imply that interesting issues in signal processing
and communications theory disappear; to the contrary, complexity management
considerations raise a number of new issues and will doubtless revitalize
these fields. We briefly describe complexity management methodologies that
have arisen in the software domain, and speculate on the nature of complexity
management in large system design. Is it largely an issue in the management
of the development process, or is it amenable to systematic and rigorous
approaches? To be more concrete, we give examples from the telecommunications
realm drawing on our own work.
Telecommunications has traditionally been driven by advances in underlying
electronics and photonics technologies, and had focused on a small set of
universal applications -- namely voice telephony, video conferencing, and
data transmission -- with most of the effort devoted to lowering costs and
increasing efficiency. The dominant research themes have been largely efficiency-driven,
such as the classical problems of increasing the bit rate derived from a
transmission medium and minimizing the bit rate required to represent a
given source. Our thesis is that this situation is rapidly changing, with
complexity management considerations replacing efficiency as the dominant
challenge in telecommunications research. We outline arguments in favor
of this thesis, describe some general techniques available for complexity
management, and give examples from telecommunications.
3.0 THE CHANGING ENVIRONMENT FOR RESEARCH
3.1 Advances in the underlying technology
Advances in electronics technology, roughly doubling in cost-performance
every couple years, have greatly contributed to advances in communications
efficiency by making sophisticated compression and coding techniques both
feasible and affordable. However, in many transmission media, we appear
to be approaching fundamental limits, even in the context of affordable
implementations, as a result in the accumulated research in compression
and coding. Simultaneously, photonics and storage technology have been advancing
at the same rate as electronics, or even faster, making efficiency less
crucial in backbone networks and storage environments. Indeed, traditional
communication theory has made little headway in affecting the practice of
fiber optics transmission.
In considering appropriate research themes, we should differentiate between
bottlenecks that will disappear with advances in the underlying processing
and transmission technologies, as contrasted with more fundamental problems
that are not subject to mere technological solution. Premier examples of
the latter include traffic capacity of wireless multiaccess channels, and
achieving adequate interactive response in the face of latency (which is
lower bounded by propagation delay, already significant in global networks).
In contrast, continuing advances in fiber optics, optical networking, electronic
switching, and magnetic and optical storage media are providing ample (and
increasing) bandwidth resources in backbone networks and storage capacity.
There is of course continuing interest in better utilizing existing facilities
like wirepair and the voiceband telephone channel -- where efficiency is
critical -- but here technology is approaching fundamental limits. Further,
we seem poised to finally provide widespread broadband access through some
combination of new fiber and existing coaxial facilities.
Advances in electronics technology not only provide ample performance, but
they also have two other important impacts:
Both of these factors imply an increasing convergence between the technical
problems faced in the telecommunications and applications software industries.
This has long been the case in the signalling, control, and switching aspects
of telecommunications as well, where the dominance of software is legendary.
- The feasible number of devices per chip is increasing, from millions
today to hundreds of millions within the next decade. A dominant design
problem for such chips is architecture and complexity management; indeed
the functional design of such chips is conceptually similar to developing
a large software system.
- Software implementation of most functions becomes feasible. Today, audio-frequency
functions are typically implemented in software (often on a specialized,
but increasingly on a general purpose, processor). In the future, video
signal processing will fall in the same category, and customized hardware
design will be relegated to radio and microwave frequencies.
3.2 Advanced applications
Most of the telecommunications applications available today are functionally
simple applications with universal interest, like voice telephony and point-to-point
video teleconferencing. Indeed, the telecommunications industry perceives
itself as selling and provisioning these universal applications, rather
than underlying services like audio, video, and data transport.
However, as desktop and untethered programmable platforms become standard
foundations for networked applications, the cost-effective software realization
of functionally complex applications becomes feasible. In addition, we can
expect dynamic deployment of software-defined applications over the network
to dramatically speed up the rate of innovation in commercially available
telecommunications applications; that is, the telecommunications marketplace
will begin to look more and more like desktop computing .
Most new applications will be functionally complex, often involving multipoint
participants and integrated multimedia like audio, video, and graphics and
In the distant past, telecommunications was characterized by a relatively
straightforward homogeneous network providing a single application: voice
telephony. As time has passed, this simple environment has evolved in different
From a technical perspective, these developments imply a rapidly increasing
level of heterogeneity in applications, heterogeneity in transport
systems, and heterogeneity in terminals. Meanwhile, application
developers, and especially end users, would like to be isolated from the
myriad technologies and enterprises involved in their provisioning. They
want applications to operate seamlessly across the telecommunications infrastructure,
with both applications and networks appropriately scaling and configuring
to whatever detailed technological components are involved. It is not acceptable
to users to have their telecommunications applications restricted to only
a portion of the network (and hence to a subset of the other users), or
to equipment from a particular vendor. All parties involved -- users, application
providers, content providers, and equipment vendors -- want a flexible and
dynamic network that can scale and evolve to meet whatever demands are placed
on it, and accommodate new advances without major dislocations or disinvestment.
Users don't want a closed, proprietary network that limits the available
applications to those envisioned by a limited set of vendors and service
providers, but rather an environment in which a variety of competing vendors
and service providers can flourish, and innovation can reign supreme. These
properties that have led to the recent success of the Internet, for example.
- There has been a proliferation of new applications (such as voiceband
data, videophone, and facsimile) utilizing the telephony infrastructure.
- New standards have proliferated for any given application, such as voice
or video encoding or voiceband data.
- New telecommunications media, such as coaxial cable, fiber optics, microwave
radio, and recently mobile radio and wireless infrared have appeared.
- To date, most applications have been realized by dedicated special-purpose
and non-programmable terminals, like telephones. This is rapidly changing,
as programmable platforms such as the desktop computer, notebook computer,
and personal digital assistant are becoming increasingly viewed as communications
- An impact of global telecommunications deregulation is a proliferation
of service providers, often with more than one service provider involved
in provisioning a single application, along with the involvement of new
equipment vendors (like the computer companies).
These factors imply a telecommunications infrastructure in the future that
is vastly more complex than any existing software system. (In fact, the
infrastructure will incorporate many existing and new large software systems,
among other elements, like unreliable physical channels.) Unlike typical
large software systems, it will be designed not by a single organization,
but literally hundreds of equipment and software vendors, and tens of standards
bodies and provider organizations. If experience with the development of
software systems is a guide -- and it should be -- success will
hinge on the containment of the complexity inherent in this large heterogeneous
4.0 SHORT TUTORIAL ON COMPLEXITY MANAGEMENT
We have asserted that management of complexity is a central issue in
the future of telecommunications. What does this mean? How do we accomplish
it? Can it be systematized, or is it largely an organizational management
While large telecommunications systems are different from software systems,
experience with the management of complexity in the latter domain is relevant,
and can serve as a useful starting point in our thinking. Thus, we briefly
summarize some techniques for complexity management from that domain.
Three basic components of complexity management are shown in Figure
Architecture is by far the most critical element, and will now be discussed
in greater detail, including some related elements like interfaces, abstraction,
configurability and scalability, and reuse.
- Architecture is the prior plan of the system that partitions
functionality among a set of interacting modules.
Modules are planned in a way that deliberately constrains their functionality
to a limited set of mutually predictable behaviors, and which avoids interaction
among their internal design details.
- Theory exploits the constrained behavior of architectural modules
to establish certain predictable properties, or perhaps the absence of certain
undesired behaviors (such as deadlock, instability, etc.).
- Tools are software systems that keep track of the large design
databases typical of complex systems, systematically synthesize more routine
parts of the system, etc.
Figure 1. Three basic elements of complexity
The architecture of the system is the basic plan that insures it performs
the functions for which it is intended. The most important aspect of the
architecture is the basic modularity, or partitioning of functionality
into mutually interacting elements. The interacting
modules, which display limited and predictable behaviors, should be as independent
from one another as possible. Further, they are designed with carefully
constructed interfaces, with the internal implementation beyond
what is displayed at those interfaces carefully hidden. By independence
of modules, we mean that the functionality of one module should depend on
the functionality of other modules only the extent appropriate and necessary,
and not on incidental implementation details. This independence makes the
system more open to change and evolution, since changes to the implementation
of one module should not affect other modules.
A familiar example of an architecture is a computing system, shown in Figure
2. This oversimplified architecture divides a computer system into basic
modules of arithmetic and logic unit (ALU), cache memory, main memory, secondary
storage, and a bus that serves to connect the other modules. Each module
has a clearly defined and limited function. The bus is key to insuring independence
of the other modules, since it forces them to communicate in a standardized
(module-independent) way. By being asynchronous (using handshaking techniques),
valid operation can even be insured independent of speed.
Figure 2. A simplified and familiar example
of an architecture.
Abstraction is a key concept underlying modularity, as well
as other aspects of the design process. Abstraction
refers to the conscious hiding of unnecessary implementation or functional
details while making visible behavioral properties that are essential and
important to other modules. Abstraction helps insure the independence of
the architectural modules, as one module cannot be dependent on the hidden
properties of another module. For example, in Figure
2, the visible properties of the memory may be sequenced read or write
requests, information stored in fixed sizes units, an address associated
with each unit, and random access. Deliberately hidden at the interface
are the technology (be it CMOS, bipolar, bubble memory, etc.), the speed
of memory access (variations are accommodated by handshaking), and internal
organization. The internal organization may be quite different than suggested
by the interface abstraction, for example turning streamed access into an
random access by internally performing multiple accesses (as would be the
case in magnetic storage).
Abstraction can be used in other ways that are important to containing the
complexity of a design. One is illustrated in Figure
3, where a layered logical (as opposed to physical or functional) representation
of the same computer system is shown. The electronic device can
be considered an abstraction of the underlying semiconductor physics, hiding
unnecessary details like holes and electronics while preserving terminal
properties like the voltage-current curve. Logic defines modules
(consisting internally of transistors) with limited behaviors like "nor
gates" and "inverters" that hide device properties and circuit
details (like CMOS vs. bipolar technology). The logic layer also defines
arguably one of the most important abstractions of modern technology, the
"bit", which simplifies the logic outputs to have only two states
(the reality is more complicated). Registers define higher-level
modules like "shift registers" and "two's complement adders"
which form specific functions while hiding their internal logic implementation
details (and indeed admitting many possible implementations). The register-transfer
level defines the basic modules used in the architecture of the ALU, which
externally hides such details through the definition of an instruction set.
The instruction set presents a powerful abstraction to the software,
since it separates the latter from all the internal details of the hardware.
Similarly, the operating system layer defines a number of abstractions
that separate the user-level process from the details of memory, storage,
and communications resource management.
Figure 3. A familiar example of the use of
abstraction in a computing system ALU.
4.3 Reusability: configurability, scalability, and adaptability
One basic approach of complexity management is reusability, which has
The simplest implication of reusability is the saving of design costs. In
an operational system, many of the same characteristics that allow reusability
can lead to a system that is self-organizing. Configurable and adaptable
modules that adjust to their observed environment allow a distributed-control
architecture that is in itself a powerful form of complexity management.
- Modularity encourages reusability, since it defines a grouping
of functionality that is carefully defined and documented. Abstraction
at the interface enhances reusability since usage is separated from implementation
- Configurability insures that modules are not designed for a
very specific environment or use, but rather internal parameters can be
modified to accommodate new unanticipated uses.
- Closely associated with configurability is scalability, a property
of the architecture that maximizes the flexibility to configure to different
levels of performance (processing power, bandwidth, number of ports, etc.),
as unconstrained as possible by technology. A scalable architecture is more
- Adaptability requires configurability, and adds the capability
to base the configuration on active observation of the module environment.
5.0 A TELECOMMUNICATIONS EXAMPLE
In addition to the generic issues of heterogeneity, future networks
supporting multimedia datatypes will have a number of objectives, many of
which interact in complicated ways. These include:
Simultaneously satisfying these requirements requires a carefully crafted
architecture. In part this is because these diverse requirements create
dependencies among system elements that must be carefully managed for good
modularity. We will now give illustrative examples from our own work.
- Differing connection topologies, including point-to-point,
multicast, and multisource. (For example, video conferencing requires both
multicast and multisource topologies.)
- Untethered (no wires), nomadic (accessible from different
locations), and mobile (accessible while moving) multimedia applications
will be important for some users.
- Privacy by end-to-end encryption will be demanded
by a subset of the users, as they gain familiarity with privacy in their
- Traffic efficiency, which is particularly an issue on wireless
access links. Wireless access traffic is interference-limited within a given
volume of space and bandwidth, and will become an increasingly serious bottleneck
as backbone networks become faster.
- High subjective quality, which is indirectly impacted by compression
algorithms and by loss and corruption in the transport.
- Low latency is critical for some interactive applications.
Since the propagation delay in terrestrial global networks is significant
(hundreds of milliseconds), there is little headroom to increase latency
through signal processing and queueing for these interactive applications.
Achieving high traffic capacity on wireless links requires joint source/channel
coding (JSCC); that is, coordination of the source coding with resource
costs in the transport. For example, the source coding will display a trade-off
between bitrate and bit-error tolerance, while the transmission media associates
a resource cost to the bitrate, delay, and reliability of each source stream.
Much past source coding research has emphasized the minimization of bitrate
-- without regard for the reliability or delay requirements -- but wireless
links attach a high cost to the stringent reliability requirements that
are often associated with aggressive compression. Maximizing traffic capacity
requires adjusting the source bitrate, reliability and delay trade-offs,
taking into account the resource cost of these quality-of service (QOS)
requirements in the transmission media. The source representation must be
highly scalable to different bitrates and reliability, for example connections
with and without wireless access. Further gains can be achieved by segmenting
information from a single source into different QOS classes, and fine tuning
the transmission resources (like power, coding redundancy, etc.) so that
no source segment receives more transmission resources than required.
The concatenation of transmission media with quite different characteristics
(for example a broadband backbone with wireless access will be common in
the future) is a complication. It is easy in this context to seriously violate
modularity, for example, by using transcoding from one source coding standard
to another as shown in Figure 4a. Using a different
compression standard on each link allows a customized per-link JSCC. (A
past example of this is digital cellular telephony, which utilizes transcoding
from 64 kb/s -255 speech to 13 kb/s VCELP.) Transcoding has poor modularity
because the source coding and the transport are designed tightly as a unit,
and one cannot easily change without the other. Further, it is difficult
to introduce new and improved compression standards if existing standards
are already widely deployed within the network. There are problems related
to the other requirements as well. The transcoder introduces considerable
delay (a serious disadvantage in a global network) and the accumulation
of quantization impairment, and is incompatible with end-to-end encryption.
Figure 4. Transcoder architecture for JSCC
in a heterogeneous transport environment.
Multicast connections (from a single source to two or more sinks) are
a scalable solution to multiple sinks (as in group video conferencing for
example), since the source generates a single stream irrespective of the
number of sinks. However, multicast offers a more serious JSCC challenge,
as illustrated in Figure 4b. Downstream from
a multicast splitting point, there will in general be heterogeneous transport
links that have to be accommodated simultaneously. Again, transcoding is
a feasible solution, but one that has the same difficulties as in unicast.
Fortunately, JSCC in both unicast and multicast connections can be accommodated
utilizing the alternative substream architecture 
shown in Figure 5. The abstraction of the transport
from the source perspective is a set of substreams, with different quality
of service (QOS) requirements (delay and reliability) for each substream.
Those QOS requirements can be negotiated between source and transport at
setup. The source then configures itself for substreams with the expected
QOS, trying to attain the highest subjective quality. To the transport,
the source is abstracted as a set of substreams with specified QOS objectives.
Internally, the transport disaggregates the negotiated QOS for each substream
to configure the QOS of the individual links.
Figure 5. A substream architecture manages
JSCC as well as heterogeneous transport and terminal environment in unicast
and multicast connections.
Multicast presents special scalability challenges. On the one hand,
heterogeneous downstream links and terminals can be accommodated by choosing
a subset of substreams for each downstream multicast subtree. On the other
hand, sinks may be entering or leaving the multicast group at any time.
It is not scalable to presume that the source can negotiate with an indeterminate
(and even varying) number of sinks and transport links, or that all sinks
should be required to reconfigure whenever a sink enters or leaves the multicast
group. Thus, a serious challenge is to configure the source coding and substreams
to simultaneously satisfy the differing needs of a generic and
probably unknown set of downstream transport links and sinks.
The substream abstraction offers good modularity, since the source needs
no knowledge of the details of how the transport achieves a given QOS. The
only details of the transport visible to the source are the fundamental
properties: delay and reliability. The transport has no knowledge of the
service or compression standard being utilized, only the desired QOS (delay
and reliability) and bitrate. Configurability allows reuse of the transport
for new sources or compression standards in the future. Further, the architecture
is consistent with end-to-end encryption, as long as each substream is independently
Having defined an architecture, a number of interesting new research issues
arise. Source coding must interface the variable-QOS substream transport
abstraction, configuring to the available substream QOS while achieving
the highest subjective quality . In addition,
source coding needs scalability to the varying bandwidth, processing, and
display resolution of heterogeneous sinks. (In fact, if multicast connections
are supported, the source representation has to embed these differing requirements
in a common set of substreams.) Another interesting problem is JSCC in the
delay dimension, which we have addressed for both video 
and graphics . Within the transport, exploiting
the substream architecture for higher multiaccess wireless traffic capacity
is particularly interesting, as it leads to the new problem of variable
QOS in multiaccess environments. We have addressed this in CDMA, utilizing
power control to provision variable reliability QOS ,
as well as packet scheduling to provision variable delay QOS .
As we move from homogeneous networks provisioning simple, universal,
largely non-configurable telecommunications applications, to an environment
that is heterogeneous in applications, transport media, and terminals, complexity
management becomes a critical element of success. Carefully crafted architectures
are needed to meet all the functional requirements, achieve adequate levels
of performance, and offer a seamless environment for the provisioning of
applications. Complexity management, far from displacing traditional signal
processing, communications theory, and queuing considerations, raises many
interesting new questions and serious challenges in all the detailed constituent
traditional disciplines, such as compression, encryption, error-control,
modulation, protocols, etc. While efficiency remains an important consideration
in multiaccess wireless systems, many other considerations relating to the
new functional, configurability, and scalability requirements are brought
to the fore. These traditional disciplines will doubtless be revitalized
by these new issues.
- D.G. Messerschmitt, "The convergence
of communications and computing: What are the implications today?",
submitted to IEEE Proceedings. (Also available at http://www.eecs.berkeley.edu/~messer/PAPERS/PRESS/Convergence.html)
- Merriam-Webster's Collegiate Dictionary,
Tenth Edition, Merriam-Webster, Incorporated, 1995.
- P.Haskell and D.G. Messerschmitt, "In
favor of an enhanced network interface for multimedia services", to
appear in IEEE Multimedia Magazine.
- L.C. Yun and D.G. Messerschmitt, "Digital
Video in a Fading Interference Wireless Environment", IEEE Int.
Conf. on Acoustics, Speech, and Signal Processing, Atlanta, GA., May
- Lao, A., Reason, J., and Messerschmitt, D.G.,
"Layered asynchronous video for wireless services", IEEE Workshop
on Mobile Computing Systems and Applications, Santa Cruz, CA., Dec.
- J.M. Reason, L.C. Yun, A.Y. Lao, D.G. Messerschmitt,
``Asynchronous Video: Coordinated Video Coding and Transport for Heterogeneous
Networks with Wireless Access'', Mobile Computing, H. F. Korth
and T. Imielinski, Ed., Kluwer Academic Press, Boston, MA., 1995.
- R. Han and D.G. Messerschmitt, ``Asymptotically
Reliable Transport of Text/Graphics Over Wireless Channels", Proc.
Multimedia Computing and Networking, San Jose, January 29-31, 1996.
- L.C.Yun and D.G. Messerschmitt, "Power
Control and Coding for Variable QOS on a CDMA Channel", Proc. IEEE
Military Communications Conference, Oct. 1994.
- L.C. Yun and D.G. Messerschmitt, "Variable
quality of service in CDMA systems by statistical power control'",
Proc. IEEE International Conference on Communications, June 18-21,
1995, Seattle, WA.
 We distinguish between applications, which
provide functionality to the end user, and services, like audio, video,
and data transport, which are available to be incorporated in those applications.
 It is interesting to compare with the more
general dictionary definition of these terms. Architecture is defined
as "the manner in which the components of a computer or computer system
are organized and integrated" .
 Theory is defined as "the analysis
of a set of facts in their relation to one another" .
 A tool is defined as "something
(as an instrument or apparatus) used in performing an operation or necessary
in the practice of a vocation or profession" .
 A module is defined as "an
independently-operable unit that is a part of the total structure"
is defined as "disassociated from any specific instance" .
Complexity management - 18 FEB 1996
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