1) Massively distributed systems will interconnect billions of nodes to support applications at a massive scale. 2) These systems will be driven by the rise of ubiquitous embedded systems and will require offloading computational tasks. 3) Massively distributed systems will be engineered as distributed utilities to support industries like energy, transportation, and media delivery through sensor networks, transportation systems, and control algorithms.

1. THE ADVANCED COMPUTING SYSTEMS ASSOCIATION
The following paper was originally published in the
Proceedings of the Embedded Systems Workshop
Cambridge, Massachusetts, USA, March 29–31, 1999
Massively Distributed Systems:
Design Issues and Challenges
Dan Nessett
3Com Corporation
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2. Massively Distributed Systems: Design Issues and Challenges
Dan Nessett
Technology Development Center
3Com Corporation
Dan_Nessett@3com.com
Abstract 1. Introduction
This paper explores trends in distributed system archi-
The forty year trend in the computing industry is away tecture and implementation that will have far-reaching
from centralized, high unit cost, low unit volume prod- consequences in the next 5-10 years. The paper’s central
ucts toward distributed, low unit cost, high unit volume thesis is that applications will become massively dis-
products. The next step in this process is the emergence tributed during this interval and in so doing generate
of massively distributed systems. These systems will significant engineering problems, the solution of which
penetrate even more deeply into the fabric of society and will change the nature of distributed computing. Fol-
become the information power grids of the 21st century. lowing this trend, networking technology will change
They will be ubiquitous. Most will operate outside the in order better to serve the communications require-
normal cognizance of the people they serve and most ments of this new class of applications.
will be based on embedded systems that present non-
One major driver of massively distributed applications
traditional computing interfaces to their users. They
is the advent of ubiquitous embedded systems. While
will be engineered to operate as distributed utilities,
embedded systems will not always communicate either
much like the energy, water, transportation and media
with their peers or with traditional computing equip-
broadcast businesses do today. The first deployment of
ment, important applications will require the intercon-
massively distributed systems is likely to occur as sup-
nection of them in large numbers. Several examples are
port structures for these industries.
given in section 2. Furthermore, these applications will
Massively distributed systems will differ from existing require computing architectures that off-load heavy
distributed systems in important ways. Such systems computational tasks from embedded systems onto more
eventually will interconnect billions of nodes. This will powerful and capable equipment. Consequently, mas-
necessitate changes in the way nodes interact with one sively distributed applications will present problems to
another. One-to-many communications will be the architects and implementers that transcend those of
norm, rather than one-to-one. The size of on-line appli- stand-alone embedded system applications.
cation communities will necessitate the use of statisti-
The paper examines the motivation for and engineering
cally correct rather than deterministic algorithms for
problems of massively distributed systems. In the next
resource accounting, fault detection and correction, and
section, a case is made why massively distributed sys-
system management. These communities will coalesce
tems will arise. Section 3 presents an analysis of their
and dissolve rapidly in order to host events that are of
engineering design issues. Finally, section 4 presents a
interest to groups formed specifically for this purpose.
summary of the paper.
This will require new approaches to naming, routing,
security and privacy, resource management and synchro-
nization. Heterogeneity will be even more of a factor in 2. Motivation
the design, implementation and operation of massively Massively distributed systems are the next step in the
distributed systems development of computing. From a commercial per-
This paper explores the nature and characteristics of spective, this process started with centralized, high unit
massively distributed systems by proposing some ex- cost, low unit volume systems in the fifties and sixties.
amples and then using them to characterize nine major It then moved to less centralized, but still more or less
design issues. Seven of these are drawn from seminal stand-alone systems in the seventies. In the eighties,
work in the area of distributed systems. Two others are Network Service Providers (NSPs), such as Compuserv,
based on experience in distributed system design and Genie and America On-line, became popular providing
implementation subsequent to that work. email and bulletin board services to businesses and
some advanced home users. In the first half of this dec-

3. ade, internet access became popular, supporting truly to the day-to-day operations of companies close to the
distributed applications, such as the World Wide Web. consumer. This will require the development and de-
In the first decade of the 21st century, massively dis- ployment of massively distributed systems that reach
tributed systems will appear and become ubiquitous. In into the home, office, public pathways, and private in-
direct contrast to the systems of the fifties through the stitutions.
early nineties, these systems will be decentralized, low
While the problems presented by these massively dis-
unit cost and high unit volume. They will be pervasive.
tributed applications will display certain differences,
Most will operate outside the normal cognizance of the
there will be a surprising amount of commonality.
people they serve and most will be based on embedded
Managing flows, whether they consist of information,
systems that present non-traditional computing inter-
paper, dishwashing detergent, gasoline, or other com-
faces to their users. They will be engineered to operate
modities, requires sensors at the points where the prod-
as distributed utilities, much like the energy, water,
uct is consumed, quickly configurable transportation
transportation and media broadcast businesses do today.
systems to move those commodities (e.g., trucks,
Indeed, the first deployment of massively distributed
power switching systems, airplanes, a communications
systems is likely to occur as support structures for these
fabric), and control algorithms and equipment to match
industries.
the ingress of raw materials to the egress of the con-
Massively distributed systems will not be limited in sumed products.
scope to the interconnection of and interaction between
In many distributed systems, such as those concerned
embedded systems alone. While large numbers of em-
with power, water, natural gas, vehicle fuel, and mass
bedded systems will participate in massively distributed
market goods delivery, embedded processors will meas-
systems, at least some will interact with traditional
ure resource use and relay consumption information up
computing equipment. The latter will provide control,
the supply-chain. Control systems will utilize this in-
information storage, intensive computation and other
formation to schedule raw material inventory replen-
services to massively distributed applications. Embedded
ishment and organize the management of resource
systems will provide specialized point-of-presence serv-
flows. Embedded systems close to the consumer (e.g.,
ices.
in appliances, yard sprinkler systems, home heating
Several hypothetical examples illustrate the future im- systems) will schedule resource consumption to mini-
pact of massively distributed systems. These will arise mize resource demand spikes, thereby reducing the peak
as natural extensions to current practice. They will be capacity requirements of delivery systems [1].
used subsequently to illustrate some of the distinguish-
An important supply chain that will dramatically influ-
ing characteristics of massively distributed systems,
ence how massively distributed systems are imple-
which are significantly different from those of smaller
mented is information flow. The resource management
scale distributed systems operating today.
systems mentioned in the previous paragraph are geo-
graphically hierarchical, since they control physical
2.1. Ubiquitous supply-chain processes characterized by the movement of mass or
management energy. Information flows as easily over large as small
distances, a characteristic that distinguishes it from
Managing large distribution processes in the face of these other supply chains. Consequently, information
increasing governmental regulation, resource scarcity supply chains will present significantly different prob-
and system complexity will become increasingly impor- lems to designers and implementers of massively dis-
tant and open up markets for massively distributed sys- tributed systems. Embedded systems will play a large
tems. The classic utility businesses, e.g., the electrical, role in information supply chains, as discussed in the
water, natural gas, and telephone companies, will be next section.
joined by other flow based service industries, e.g., It will be necessary to use massively distributed sys-
transportation conglomerates, oil companies (especially tems to solve this new class of flow control problems,
those which own and operate service stations), large since the ratio of control points to production facilities
retail companies, including food, clothing, soft and hard will grow to be several orders of magnitude larger than
goods businesses, and the information industries, such it is today. This adjustment will encourage new control
as newspaper, television, entertainment and advertise- algorithms based not on deterministic concepts, but
ment concerns to concentrate on improving their mar- rather on statistical notions of correctness. Profits will
gins by the efficient control of their product flow. Sup- be maximized by ensuring a less than 100% accounting
ply-chain management will spread from manufacturing of resource usage and payment, since reaching the last

4. few percent will impose significant marginal costs that ware. Embedded processors will run transportable code,
will exceed the marginal return. Banks already employ such as Java, in order to support active networking [2].
this philosophy in response to ATM fraud. The money
To protect consumers from unwanted intrusions into
that could be used to make their equipment more secure
their lives, products will be developed to filter the in-
earns more interest than the losses they would prevent.
formation flowing to an end-system. These filters will
Of course, to ensure an equitable and legally defensible
range from those that allow parents to control the in-
operation (not to mention keeping stockholders happy),
formation available to their children (eliminating offen-
control algorithms must eliminate systematic fraud
sive material such as pornography) to those that elimi-
whereby one or a small group of individuals consis-
nate the probable increase in junk information broadcast
tently benefit from a system's non-deterministic behav-
to consumers. Specialized processors implementing
ior.
pattern recognition algorithms and embedded in rout-
ing, switching and end systems will provide powerful
2.2. Agile distributed information and customizable filtering capabilities to achieve these
services objectives.
Perhaps the most dramatic development of the past 5 To solve the problem of locating communities that
years is the growth of information distribution channels might interest an individual, services will form offering
based on the Internet and their rapid penetration into electronic real-time catalogues. These will be the suc-
areas not normally associated with computing. The cessors of the WWW index and search engines that exist
World Wide Web, email, and Internet news groups are currently. Electronic advisory services will inform con-
prominent examples. This trend will not only continue sumers which communities offer the best value, using a
it will accelerate. The maturation of multi-media broad- value metric tailored for the customer's specific objec-
cast technology running over the Internet, assisted by tives. Specialized processors embedded in database and
extremely high capacity networking infrastructure will information repository systems will continuously index
encourage the formation of virtual information commu- and catalogue information as it arrives.
nities. Unlike more traditional groupings, these com-
munities will be ephemeral, lasting anywhere from Needless to say, participation in these communities will
weeks or months to periods as short as several hours or require payment, ranging from that necessary simply to
less. Primitive examples of these communities now reimburse common carriers, when the content is free
exist, e.g., everyone reading the same newspaper and all (e.g., broadcasts of school plays, candidate sponsored
those watching the same TV program. However, the political events, religious events), to payments for ex-
information communities of tomorrow will not be clusive information commodities (e.g., pay-per-view
based on rigidly structured broadcast hierarchies; rather sporting events, specialized financial broadcasts). Such
they will encourage interactions between people who are payments will require the development and deployment
members of a community at a particular moment. Mul- of an electronic monetary system that utilizes a combi-
ticast interest groups centered around a wide variety of nation of digital cash, electronic credit systems (i.e.,
subjects will form, much as internet news groups form electronic analogues of the credit card, bank line of
today. Small production companies will present a play, credit, and checks), and point of presence payment ter-
host a debate, cover a sporting event or sponsor an elec- minals. Processors embedded in cash cards and other
tronic interactive event, such as a networked game that payment tokens will play an important role in such
millions play simultaneously. The large media con- systems.
glomerates will gradually evolve into distributed infor-
mation and entertainment production companies offering 2.3. The new economics
a wider variety of programming material than they do Electronic commerce is now a common feature of many
now. commercial enterprises. However, most designers and
Managing such rapidly changing information communi- implementers of electronic commerce systems have
ties will require more capable networks than currently concentrated on the provision of electronic payment.
exist. Switching and routing equipment will include Other aspects of electronic commerce have received less
embedded systems to monitor resource use and adjust attention, in particular, many components that are well
allocations to meet fluctuating demand. These systems matched to implementation on massively distributed
will control resources that are traditionally static, such systems. Commerce involves not only payment for
as device backplane bandwidth, encryption and compres- goods and services, but also their creation, advertise-
sion hardware, and agile error detection/correction hard- ment, delivery, maintenance, and disposal.

5. The downward spiraling cost of communication is uted systems. This work identified seven major design
changing profit models in many businesses. Hard prod- issues. Two additional issues are added to the seven pre-
uct companies will change their businesses to adapt to viously identified based on experience subsequent to that
the new micro-economic environment. The creation of work. The classical design issues are : 1) naming, 2)
hard goods will become increasingly automated. Their error control, 3) resource management, 4) protection
advertisement will become more interactive, consumers (security and privacy), 5) synchronization, 6) objects
will use third party search and evaluation companies (representation, encoding and translation), and 7) meas-
that recommend products according to a detailed specifi- urement, testing and debugging. The additional design
cation. Since consumers are rarely expert enough to issues are : 8) heterogeneity, and 9) scale.
create a useful and detailed description of their require-
Each of these issues is used to show how massively
ments, such companies will develop interactive systems
distributed systems differ significantly from existing
with friendly customer interfaces that will lead a cus-
distributed systems. For pedagogical reasons, the issues
tomer in the development of these requirements.
are addressed in the following order : scale, heterogene-
Customers will not travel to a remote location to use ity, objects (representation, encoding and translation),
these systems. They will be accessed through commu- resource management, protection (security and privacy),
nications facilities terminated in the customer's home or naming, error control, synchronization, and measure-
place of business. Eventually, requirement specifica- ment, testing and debugging.
tions will drive the creation of the product at an auto-
mated facility, create a just-in-time delivery plan to 3.1. Scale
move the product from the manufacturing facility to the
shipping end-point, schedule the resources to conduct The main characteristic of massively distributed systems
warranted and purchased maintenance on the product, and is their scale. While current distributed system are com-
arrange for the disposal of old equipment the customer posed of hundreds of nodes1, during the first decade of
no longer needs (or that was traded in for new equip- the 21st century massively distributed systems will be
ment). Companies will optimize costs by coordinating composed of thousands to billions of nodes, supporting
this with the warehousing and shipment of the pur- hundreds to millions of users [4].
chased equipment as well as with the disposal of the The scaling issue for massively distributed systems has
equipment of other customers. a number of dimensions. In the area of communications
Embedded systems will play an important role in the capacity, recent events in the telecommunications indus-
new economics. Once a manufacturing facility receives try promise to dramatically change the available world-
a product specification, embedded processors in robotic wide bandwidth for networking. For example, Project
equipment will tailor its mechanical assets to create that Oxygen of the CTR Group, Ltd. intends to lay fiber
product. Embedded processors will sense resource usage across the ocean floors resulting in bandwidth of 1.28
and work with control systems to ensure parts are deliv- terabits/sec on any segment [5]. Current schedules call
ered when necessary. Embedded systems will monitor for the completion of an Atlantic ring by Q4 2000 and a
and schedule warehouse and delivery capacity, cooperat- Pacific ring by Q2 2001. The pricing schedules pro-
ing with control systems to move the product to the posed by CTR Group will result in transoceanic band-
customer. Embedded systems in robots will manage the width offered at 1.5% of current satellite circuit prices
repair of products returned for maintenance. and 1% of marine cable prices.
Power, water, natural gas, vehicle fuel and mass market
3. Design issues supply chains are naturally large scale. Traditional in-
formation supply chains (e.g., radio, television, motion
Massively distributed systems are not only quantita-
picture, the printed news media) are broadcast based and
tively different, but also qualitatively different than the
characterized by a small producer-to-consumer ratio.
distributed systems in place today. Their size and scope
However, this is undergoing radical change. The growth
introduce new problems in design and implementation.
of the world wide web has greatly increased the pro-
However, to a certain extent we can use the experience
we have gained building moderately scaled distributed
systems to guide us in solving these problems. 1
Some may object to this assertion, observing that the current Inter-
net is composed of millions of nodes. However, the term distributed
This section presents a taxonomy of design issues for system here means a cohesive set of computing resources acting
together to achieve a common objective. While the routing infra-
massively distributed systems. It is based on seminal structure of the Internet can be considered to be a massively distrib-
work [3] that analyzed the current generation of distrib- uted application, no other system of this scale exists currently.

6. ducer-to-consumer ratio in data communications and this per-use approach, which is suited to their ephemeral
trend will continue. There may even come a time when nature. Longer-lived communities may be more in-
the ratio approaches 1. This one factor has the potential clined to charge a subscription fee for their services.
to completely change how information supply chains Some communities with external financial backing
are implemented and could be the major driver behind may choose to charge no fee, transferring value to
massively distributed systems. their sponsors through advertising, indirect persua-
sion, or charitable benefit. Each of these costing
Geographically, massively distributed applications sup-
models must be supported by the massively distrib-
porting information supply chains will be global in
uted system infrastructure in a way that allows such
extent. A single application running over a massively
diverse activities to exist concurrently.
distributed system will interconnect users of signifi-
cantly different languages, cultures and views. Commu-
• To support cost recovery for distributed applications,
nication costs will be structured so that they scale loga-
several efforts are underway to build and deploy elec-
rithmically with the number of destinations, thereby
tronic monetary systems. Existing applications are
utilizing efficiencies inherent in broadcast and multicast
able to use a single funds transfer system, since
communications. Individual subscribers will be able
many serve a limited customer base. Massively dis-
affordably to communicate with one to a hundred other
tributed systems, on the other hand, will be global
subscribers. One-to-many communications will be the
in scope and normally serve customers in many
norm, as opposed to one-to-one transfers, which are
countries who use a large variety of payment sys-
most common today.
tems. For some, only traditional methods, such as a
credit card or cash payment card will be available;
3.2. Heterogeneity while others may use different electronic systems,
While heterogeneity is an important design issue for such as digital cash, digital checks, or digital credit
existing distributed systems, its extent in massively cards. Embedded systems will play an important
distributed systems will be significantly greater. In par- role in the latter class of payment system. Mas-
ticular: sively distributed systems must accommodate the
use of all such systems by a single application.
• The communications infrastructure will be composed This will necessitate the development of funds trans-
of channels of very different capacities. Very low fer transaction clearinghouses that will convert funds
bandwidth channels (e.g., 1200 BPS) will still be in from one system to the other.
use in developing nations during the next decade,
while the developed world will support very high • Distributed systems currently run on equipment man-
bandwidth channels in the core services (e.g., 1 aged by different administrations, which desire to
Tbps). Communications between embedded systems keep its use under their control. Current practice is
and their peers or higher-level facilities will occur to rely on the users of this equipment to properly
over channels of significantly lower bandwidth than employ it according to policies promulgated by
that available in the core of the network. Building these administrations. However, this approach is
applications that run over bandwidth diverse com- changing as organizational IT budgets become larger
munication infrastructure will require new ways of and as Board of Directors, stock holders and other in-
organizing data flows. terested parties hold management more strictly ac-
countable for information processing equipment use.
• Similarly, end-systems will possess a wide variety of Organizationally imposed constraints on distributed
presentation techniques, from interactive HDTV to applications have a deleterious effect on their opera-
personal digital assistants and personal phone tion. A clear example of this is how router based
equipment. Applications will combine these end- firewalls not only provide protection against intruder
systems into coherent interactive subsystems. In attacks, but also prevent certain distributed applica-
fact, it is possible today to create a communications tions, such as those using UDP, Java applets or
conferencing system that patches together video- those using the X window system from running
teleconferencing equipment, multicast capable work- across firewall boundaries. Massively distributed
stations and cellular phones. systems will experience even greater impediments to
their operation, since not only will locally imposed
• Participatory communities, formed on demand, will constraints interfere with their operation, but other
choose from an array of costing options for their constraints will hinder them, such as national re-
members. Short-lived communities may elect a pay- strictions on transborder data flows and encrypted

7. data as well as the mandated use of certain standards also on a wide variety of embedded systems sup-
for communications protocols. ported by their own proprietary operating systems
and hardware (e.g., automobile control systems,
• Distributed applications are composed of software PDAs). For example, a massively distributed appli-
components2 that run on various platforms and are cation for remote conferencing may have compo-
organized into component classes (e.g., file servers, nents that run on workstations, on equipment pro-
public key distribution systems, file system clients, vided by a manufacturer for the TV cable industry,
various clients on embedded systems), each of which on cellular phones, on PCS based personal commu-
performs a different function. Current distributed ap- nication devices, and so forth. This will increase the
plications either assume that all components run the number of different implementations of the software
same version of software, or are structured according for a single component type and thereby increase the
to a simple client/server model that must concur- effort necessary to ensure the application works cor-
rently accommodate different versions on a small rectly.
number of system (e.g., two or three). Massively
distributed applications, because of other heterogene-
ity requirements, such as the use of different presen- 3.3. Objects (representation,
tation formats, costing and cost recovery schemes, encoding and translation)
naming techniques and administration constraints, A variety of efforts are underway to determine the best
will be constructed of a significantly larger number programming model for distributed objects (e.g.,
of component types. Components of these types in CORBA, Java). Lessons from these investigations will
general will not run the same version of software. directly affect how objects are handled in massively dis-
Designing and implementing these applications will tributed systems. However, there are certain issues aris-
therefore require engineering techniques that allow ing from the scale of these systems that will introduce
them to operate in the face of software versioning new constraints on how objects are represented, encoded
heterogeneity. and translated.
• One of the fundamental mistakes made when building • Massively distributed system by their nature will re-
distributed systems is ignoring legacy applications quire the creation, movement, modification and de-
and infrastructure. This invariably leads to poor cus- struction of massive objects, which conceivably
tomer acceptance of new technology. Customers could contain thousands to millions of other ob-
cannot simply discard their existing applications jects. The size of these objects will affect how they
when new infrastructure becomes available. In many are represented. For example, it will be infeasible to
cases these applications and their supporting infra- incorporate a copy of each contained object within
structure represent billions of investment dollars and the massive object. Instead, object references will be
reimplementing them according to the interfaces used within massive objects to represent its con-
presented by new technology is economically infea- stituents. These objects will themselves be con-
sible. Massively distributed systems will be no dif- structed using references to their contained objects,
ferent in this regard. However, existing distributed leading to a hierarchical object anatomy. However,
systems generally must accommodate stand-alone several well-known problems associated with refer-
legacy systems and applications. Massively distrib- encing distributed objects will require attention. For
uted systems, on the other hand, must accommodate example, implementers of massively distributed sys-
both stand-alone as well as current distributed sys- tems will have to solve the lost object problem,
tem legacy infrastructure and applications. which occurs when an object is destroyed without
destroying all its references in other objects. Rely-
• While most existing distributed applications run on a ing on manual techniques to recover from this error
number of different computing platforms, they are condition will not be an option, because of its scale.
generally limited to a small number of common Similarly, revoking access to an object will be
families, e.g., Unix, Windows, and perhaps MVS. much more problematic for massively distributed
Massively distributed applications, on the other systems than for existing distributed systems. It
hand, will run not only on the legacy platforms, but will be infeasible to locate all references to an object
and delete them, even if the underlying object repre-
2
The term “component” is used here in its general sense. Distrib- sentation allows that. While using access lists can
uted system components may or may not be constructed as object-
oriented software components. mitigate the problem of revocation, their use in
massively distributed systems will be problematic,

8. since their size may make this approach unattrac- new problems in object store performance, error
tive. This problem is discussed in more detail in control and correctness. Object implementers will
section 3.5. have to deal with the internal synchronization of ob-
ject constituents, in regards to their creation,
• Not only will the representation of massively distrib- movement, modification and destruction. They also
uted objects require new techniques, their presenta- will have to deal with these issues when designing
tion to users will also require innovation. Some re- and implementing object caches.
searchers have examined this problem. A new class
of user interface represents objects as virtual spaces. • The algorithms used to manipulate massively distrib-
This technique is eminently suitable for presenting uted objects will utilize techniques that differ from
massively distributed objects to end users. For ex- those commonly used today. They will be replaced
ample, a first level object might be represented as a by those that use multi-cast communications in or-
virtual world, its constituent objects as countries, der to avoid object components understanding the
then cities, streets, houses, rooms, and so on, the object's global architecture. Voting and distributed
exact structure depending on the size of the first agreement algorithms will become common. Pro-
level object and its relationship to its constituents grammers will create active objects, i.e., those
as well as the relationship of the constituents to which include active on-going computing, that blur
each other. Such presentation paradigms will be re- the distinction between data and processing. While
quired to make massively distributed objects acces- some existing distributed systems support active ob-
sible to the technologically naive user. jects, massively distributed systems will organize
large parallel computations around this concept,
• Since massively distributed applications will be global forming these computations by creating a first level
in scope, their users will belong to multiple cul- object containing a large number of active objects
tures and countries. This will increase the necessity residing on geographically disperse and administra-
for the internationalization of data. While current tively heterogeneous systems.
applications can be configured to use different char-
acter sets, depending on choices made when the sys-
tem is installed, massively distributed systems will 3.4. Resource management
have to internationalize data on-the-fly. This is es- In order to design and build massively distributed appli-
pecially true of embedded systems, which com- cations, engineers will have to grapple with new prob-
monly will exist in mobile equipment. There will lems in resource management. Many existing distrib-
be no point when a system administrator can select uted systems operate according to a local resource con-
a particular internationalized presentation set. Users trol model. Local processing manages its own
of massively distributed applications will come and resources, interacting with other threads of control
go during its lifetime, requiring run-time configura- through message passing or remote procedure
tion of this data. Perhaps more importantly, there call/method invocation. In massively distributed sys-
will not be a single system administrator who con- tems, objects will be composed of resources located in a
trols a massively distributed application. Its control large number of different places. Controlling the re-
will be distributed as well. Not only will character sources associated with an object will only be possible
set data require internationalization, the application through a distributed global object resource management
will have to internationalize other data such as fi- mechanism. This will introduce several new issues in
nancial, length/mass/time, and timezone. For exam- distributed system resource control:
ple, an application that presents financial data may
have to convert between dollars, yen and marks, de- • Routing will become an issue not only at the network
pending on where the end-point system is located layer of the distributed system, but also at the appli-
and how it has been configured by the customer. cation layer. Composite objects containing active
objects will require routing services so the compos-
• The storage of massively distributed objects will re- ites can interact with each other, especially if ob-
quire new techniques. Current object storage sys- jects are allowed to move. For example, an embed-
tems assume objects are located on resources con- ded system such as a mobile PDA will move and
trolled by a single administration. The storage of a connect to different portals in a network. If upon
single massively distributed object, however, may connecting, objects are moved from the PDA to
use the resources of many storage systems, con- execution environments hosted near the portal, in-
trolled by different administrations. This will lead to vocation of those object's methods by other objects

9. will require a routing protocol to identify a path be- • Massively distributed systems will contain extremely
tween them. The interactions between active objects large volumes of data and enormous processing
and passive objects will require routing so active ob- power. Effectively managing these resources will
jects can locate and contact passive object methods. challenge implementers. Distributed system archi-
Congestion control within composite objects will tects will merge the two prevalent ways to organize
be an issue. Programmers and object implementers computations in a distributed system, i.e., move
will organize objects to avoid computational hot data to the processing (used by NFS, World Wide
spots, similar to those experienced by massively Web, FTP, gopher) and move processing to the data
parallel algorithms. Due to their scale, object (used by active networking and Java applets) into a
implementers will require adaptive routing and con- single scheme. Such objects will be moved within
gestion control within massively distributed objects, the distributed system and carry with them both code
manual configuration will not be an option. and data [6]. If the object consists primarily of data,
it will closely approximate moving data to the proc-
• Resource management in a massively distributed sys- essing. If it consists primarily of code, it will
tem will interact strongly with its heterogeneous na- closely approximate moving processing to the data.
ture. Applications will compose resources under the RPC and other procedure-oriented paradigms will be
control of many administrations into a single dis- emulated by including a single high level instruc-
tributed resource. Management of the distributed re- tion in the code section, specifically a procedure
source must accommodate the usage policies of the identifier, which will be interpreted at the RPC
separate administrations. For example, cost recovery server.
for a massively distributed object must accrete and
disseminate sufficient funds to cover the costs of the • The deployment of massively distributed systems will
composite objects. Since massively distributed ob- encourage the trend towards a new valuation model
jects may be highly recursive, cost recovery will re- for information. Specifically, the independent vari-
quire the composition of recursively discovered able driving value will be how long the information
composite costs. As objects evolve, their cost re- has existed. Massively distributed systems will in-
covery anatomy will change, forcing object crease the difficulty in keeping information private.
implementers to dynamically configure the object's Consequently, customers will pay for fresh informa-
cost recovery algorithm. Since it will be difficult tion, which will rapidly decrease in value once it is
and expensive to continually track the exact cost produced. For example, stock market ticker data is
structure of an object at any point in time, cost re- now available electronically, making automated trad-
covery will use statistical algorithms, assessing ing programs possible. However, this implies that
charges and dispersing payments so that the owners most of the value of the ticker data is consumed in a
of component resources receive their payments, but very short period of time. Its public release without
avoiding too fine an accounting of usage. Periodic cost routinely occurs today 15 minutes after its gen-
audits will ensure systematic fraud is minimized. eration. As massively distributed systems become
Operators of massively distributed objects will adopt common, more and more stock traders will be forced
a fixed cost model, allowing users of the object to to use automatic trading programs, which will re-
flexibly utilize its resources without charging for its duce the value of the ticker data even faster. It is
components use. likely that eventually ticker data will be available
without cost within a few minutes of its production.
• Object implementers will devise algorithms enforcing This paradigm will apply to other data, such as li-
restrictions on object use that are required by restric- brary searches, financial analyses and market re-
tions on their components. Unlike existing distrib- search.
uted resource management, these algorithms will
have to be adaptive, since implementers will not • Upgrading software in a massively distributed system
know all possible component resource usage poli- will pose new problems for software companies. It
cies, a priori. Object implementers will be chal- will become more difficult to locate all users of a
lenged to understand object behavior, since dynami- particular version of software and users will become
cally changing an object's components, which may less cognizant of the version they are using. This
introduce new resource usage restrictions, will make situation will arise because objects will contain and
this difficult. use other objects implemented by software not di-
rectly visible to the user. To meet this new chal-
lenge, software companies will move from a pure

10. product business model to a combination of product which a user is capable of manually examining for
and service model. Indeed, this is already happening. interest, usefulness, or suitability. Various filtering
Many software companies offers a subscription pur- techniques will be developed and used by customers
chase agreement for their products that provides the to ensure their systems only present to them infor-
customer with one year of upgrades. Engineers will mation in which they are interested. Additionally,
design their software to periodically query mainte- once these filtration systems are common, applica-
nance centers that will upgrade it automatically, if tions will use feedback controls to gather and em-
the software's maintenance contract is still active. ploy end-system supplied filtration data to decrease
Again, this is current practice. For example, the vi- the amount of information sent to an end-point that
rus detection software that is part of the Norton Sys- is automatically discarded. Massively distributed
tem Tools product for Windows 95/98 periodically systems will provide tools to applications that al-
communicates with a maintenance site on the Inter- low them to support this type of customization for
net and downloads new virus checking features as large numbers of end-point systems.
they are released. Customers will be forced to use
maintenance contracts to keep their applications
running. In the future, customers will force software 3.5. Protection (security and
manufacturers to provide open interfaces to their privacy)
software and negotiate maintenance agreements with Protection of distributed system assets, including base
secondary companies, much like the hardware busi- resources such as processing, storage, communications
ness does today. and user-interface I/O as well as higher-level composites
of these resources, e.g., processes, files, messages, dis-
• Massively distributed systems will force a reexamina- play windows and more complex objects is not a
tion of the way communication interfaces work. In strength of existing distributed systems. While engi-
particular, they will have to scale to accommodate a neers are currently engaged in developing solutions to
large number of correspondents. For example, a the many problems that exist in this area, they are not
simple mass-market purchase application that al- addressing protection issues that will arise as massively
lows customers to choose between several products distributed systems become prominent. Specifically:
may receive millions of requests in a short period of
time. Current programming interfaces to communi- • Massively distributed systems for the most part will
cation services are totally inadequate to handle such support a large number of end-systems, many of
a high rate of transactions. Furthermore, individu- which will be embedded in other equipment and used
ally acknowledging each of these transactions would by technologically naive customers. These systems
impose a significant processing burden on the sys- will require management, which very probably will
tems running the application. This will encourage occur through the use of systems under the control
engineers to design communication interfaces and of service providers. Since many end-systems will
protocols that are better suited to high rate and vol- either generate or contain data that customers con-
ume transactions. sider private, the management technology for mas-
sively distributed systems must guarantee, to a rea-
• Since massively distributed systems will dramatically sonable extent, that unaggregated data is not com-
increase the amount of traffic handled by a commu- promised either by individuals operating the
nications fabric, engineers will investigate how to management sub-system or by the service providers
efficiently move extremely large volumes of traffic as part of their corporate strategy, e.g., during the
over the internet. In addition much of this traffic collection of marketing data. To meet this objective,
will belong to one of several different quality of end-systems must be customer anonymous with re-
service classes (e.g., best effort delivery data, stream spect to the management sub-system. That is, there
data) and so understanding how to accommodate dif- must be no tie between the identifiers used to man-
ferent quality of service parameters in the internet is age end-systems and those used for billing, warranty
a problem with high priority. Fortunately, this or other services that require the identification of the
problem is currently receiving significant attention individuals who own or use these end-systems.
by the Internet Engineering Task Force and the
IEEE. • Since one-to-many communications will play a major
role in massively distributed systems, engineers will
• Massively distributed systems will support a volume have to address the problems of deletion, modifica-
of information flow to an end-system beyond that tion, insertion, replay, release of secret state, and

11. masquerade for this type of communications. Exist- forcing these legal constraints will be just as hard as
ing techniques are designed to protect one-to-one implementing the technology that satisfies them,
communications against these threats. New proto- over time the constraints may be relaxed or even
cols and processing algorithms will be required to eliminated. However, while they are in force, the
provide these services for one-to-many communica- technical problems they raise will be formidable.
tions.
• Commercial enterprises will play a large role in mas-
• The scale of massively distributed systems will intro- sively distributed applications. Consequently, new
duce new problems in resource access control for threats will arise as the value of these applications
both end-systems and infrastructure support sys- increases. One concern is the security of internet-
tems. Currently, most systems use access control work routing. Massively distributed systems will
lists or their approximations (e.g., Unix file access introduce new factors into this problem. The infra-
permission bits). However, massively distributed structure required for such systems will necessarily
systems will support millions of principals, which federate other large networks into a global commu-
would lead to access control lists of unmanageable nications fabric. However, routing service providers
size, if implemented as they are currently. may wish to limit the traffic that transits their net-
Implementers will require new techniques, such as works and subscribers may demand guarantees that
access list caching hierarchies, capability systems the quality of service advertised by routing service
that solve the revocation and lost object problems, providers is actually delivered. The former problem
and access control techniques that combine the ad- has received a great deal of attention, leading to the
vantages and characteristics of access control lists formulation of policy routing techniques. The latter
with capability access control and eliminate the dis- problem on the other hand, has received less atten-
advantages of each. Since massively distributed sys- tion and will require further study.
tems will be highly heterogeneous and require the
support of legacy distributed systems, engineers will
be forced to grapple with the hazards of composing 3.6. Naming
systems that use access control lists with those us- Engineers have devoted considerable attention to the
ing capability based access control [7]. issue of naming in distributed systems over the last 20
years. Pioneering efforts, such as Grapevine [8], the
• When confronted with the problem of information Domain Name System (DNS) [9] and NIS [10], devel-
protection, existing distributed systems already must oped the concepts for the next generation of distributed
cope with the controls governments have placed on naming systems, such as X.500 and LDAP accessed
cryptographic technology. These constraints have directories. To some extent these second-generation sys-
hampered engineers in providing appropriate levels tems, especially X.500, are designed for large scale dis-
of security to the users of distributed systems. Mas- tributed systems. In particular, X.500 supports the stor-
sively distributed systems will generate new prob- age and retrieval of customer defined data structures, a
lems in this area. Since communications will occur hierarchically structured and distributed naming context
between large numbers of end-systems, security mechanism and decentralized authentication services.
service implementations will be hard pressed to as- The Open Group's Distributed Computing Environment
certain which systems are constrained by particular (DCE) uses either X.500 or DNS to construct a large
national laws concerning encryption and what those scale naming system from its local Cell Directory Sys-
limitations might be. As mobile systems become tem [11].
more prevalent and as they are integrated into mas-
sively distributed systems, enforcement of these Even though the designers of second generation distrib-
constraints, even if they are known, would require uted naming systems have attempted to accommodate
tracking the position of a mobile system, identify- massively distributed systems in their design, there are a
ing the constraints imposed by its locality, and number of naming issues that transcend these designs
communicating these constraints to all systems in- and require attention:
teracting with it. For the number of end-systems • The volume of data within a massively distributed
that will engage in a massively distributed applica- naming system will be so large, tens to hundreds of
tion and for the frequency with which a mobile sys- millions of entries, that customers will not know
tem's position might change (e.g., those used from where to start when looking for an item. Hierarchi-
or embedded in an automobile, train, boat or air- cal structures have the advantage of logarithmically
plane), this will be technically infeasible. Since en-

12. scaling the name space, given a specific choice of around, which will in turn require meta-naming
how the data should be organized. They have the services (i.e., to name the naming context). Trans-
disadvantage of constraining efficient queries to lating naming contexts will necessitate the discov-
those whose unknowns are at the bottom of the hi- ery of the relationships between the different con-
erarchy. Since a single massively distributed system texts. Furthermore, object sharing requires the nam-
will be used for a wide variety of purposes, multiple ing of objects by different entities. Communicating
indexes into its naming data will be required. Inde- names for the purpose of sharing requires moving
pendent services will manage these indexes and each the associated naming contexts.
will need to update their meta-data as the foundation
data changes. This already exists for indexes of web- • Different cultures may require different naming
page data. However, as anyone who has used inter- schemes, some hierarchical, some local. These must
net search engines realizes, the volume of data re- be coalesced into a usable massively distributed sys-
turned for many queries is too large for efficient use. tem naming scheme. The same object may be
Higher-level indexing services will use the services named differently depending on the use of the name
of lower-level services, leading to a hierarchy of and its characteristics (e.g., native language, avail-
naming data accessible by customers. This web will able character set).
contain data of varying degrees of freshness, which
will require new methods and algorithms to present
a consistent and coherent view to customers. 3.7 Error Control
To a certain extent the problem of error control in
• As stated previously, a large number of the organiza- global networks has not been solved for existing dis-
tional structures within a massively distributed sys- tributed systems. For example, multicast links fail dur-
tem will be ephemeral, e.g., information communi- ing video teleconferences, ftp sites become unreachable
ties which will unite around a particular event and during a transfer due to firewall, router or link failure,
then dissolve. However, many who would be candi- and end-system failure results in broadcast storms that
dates to participate in such an event may not be cripple local communications. All of these events are
aware, a priori, that it exists. The scale of a mas- difficult to analyze and correct automatically. They in-
sively distributed system invalidates traditional ad- variably require the use of out-of-band channels to no-
vertising techniques, since the volume and rate of tify a responsible technician or system administrator. In
the advertising information arriving at an end- a massively distributed system, however, the identifica-
system using these approaches would overload it. tion and use of an appropriate out-of-band channel will
Consequently, engineers will devise new pro- be problematic. Furthermore, service providers must
ducer/consumer models of advertising. For example, provide error control in ways that conform to other re-
one possibility is a hierarchically structured reverse quirements, such as privacy protection, high perform-
advertising technique, whereby the customer adver- ance and scalability. Such constraints lead to the follow-
tises desirable product attributes to first tier brokers, ing problems:
which accrete these into reverse advertisements to
higher level brokers. From other leaves in the hier- • Fault isolation and correction in massively distributed
archy, product producers advertise their products to systems will require new infrastructure services to
other first-tier brokers, which likewise accrete them monitor communications quality and deliver excep-
into advertisements to higher level brokers. Some- tion alarms to service providers when quality falls
where within the hierarchy a rendezvous occurs and below a given threshold. Since the number of dis-
direct advertisements are sent or otherwise made tributed applications running in a massively distrib-
available to customers. A simple example of this uted system will be too large for manual monitoring
strategy for advertising and using computing re- to be cost effective, service providers and distributed
sources has already been prototyped [12] system implementers will design, implement and
deploy automatic fault detection and isolation
• Moving objects requires moving names embedded in mechanisms to ensure service remains available dur-
the object. This necessitates either retaining the con- ing various resource outages. This will be especially
text in which those names are interpreted or translat- important for distributed embedded systems. The
ing them into contexts available at the new object functions of existing network operation centers will
site. Massively distributed systems makes either become automated. Network operation centers will
strategy difficult. Retaining contexts will compel an focus on higher level fault isolation and control,
object to maintain contact with them as it moves

13. such as rerouting communication services when a within communication protocols, but also within
catastrophic event takes down large subsystems. objects so their state driven algorithms are fault tol-
erant. To achieve this objective, there will be an in-
• Engineers of massively distributed systems will intro- creased use of voting protocols and algorithms.
duce new ways to process a large volume of infor-
mation and number of transactions. As previously • It will be impossible to keep track of all the identifiers
described for costing strategies, statistical algo- or other processing state associated with an object.
rithms will be used to cope with the decreasing Massively distributed systems must be designed to
probability that all necessary fault identification in- work in the face of lost objects, which will be the
formation is available in a reasonable amount of rule rather than the exception. Loss of identifiers
time. For example, consider the problem of auto- will also increase the incidence of orphaned objects,
mating the collection of payments for a video serv- which will increasingly require the use of global ob-
ice. Errors in transmission, bugs in software, unre- ject garbage collection.
sponsiveness of end-system equipment due to mal-
function and operator error will lead to a certain • One-to-many communications on a large scale will
amount of imprecision in the accounting and collec- encourage the development of forward error correc-
tion processes. An automated billing and collection tion techniques, which will replace feedback error
application will record all funds received, match control in many cases. Feedback error control re-
them with outstanding balances on accounts and at- quires the retention of a large amount of state and a
tempt to resolve the amount received with the over- high level of processing when applied to one-to-
all outstanding balance. A discrepancy below a cer- many communications. Idempotent operations will
tain threshold will be charged to the cost of doing become the paradigm of choice when one-to-many
business. Auditing processes will attempt to ensure communications support remote procedure or object
that these discrepancies are not systematically occur- method calls.
ring as the result of fraud. Such techniques will also
be used for automated opinion polling, physical re- • Error control will move more and more into the appli-
source flow monitoring (e.g., power, water), and cation layer as the error characteristics of lower lay-
distributed system infrastructure maintenance. ers become heterogeneous (especially for one-to-
many communications) and as applications are
• Massively distributed systems will require the use of widely distributed. [13]. To manage application error
highly available subsystems, including a redundant control, management systems will expand their con-
communications fabric provided by multiple service cerns from the network layer and below to all layers
providers, fault-tolerant distributed processing for of the protocol hierarchy. This will lead to the stan-
control and accounting, and high availability end- dardization of management protocols and interfaces.
systems for content providers, which will be the
next logical step beyond the high availability file
systems currently deployed. Fault-isolation will 3.8 Synchronization
have to operate in the face of privacy services, such One of the most difficult problems that engineers of
as encryption, that are virtually non-existent today, massively distributed systems will encounter is syn-
but that will become prominent in the next decade. chronizing computations consisting of thousands to
Service providers will have to respond to subscriber millions of components. Current methods of synchroni-
problem reports, even when the ultimate source and zation, such as semaphores, monitors, barriers, remote
destination of traffic causing the problem is un- procedure call, object method invocation, and message
known. They will gravitate toward a scaled cost passing, do not scale well. Generally, they are suitable
structure for various grades of service, from high either for synchronizing closely coupled computations
grade indemnified service ("you lose service, we lose (e.g., semaphores, monitors and barriers), or for unicast
revenue"), to lower grades of best effort service. distributed applications (e.g., remote procedure calls,
object method invocations and message passing). Engi-
• Detection of inconsistent state will be difficult in neers have not yet devised efficient synchronization
massively distributed systems, since the distributed techniques for group computations, when groups con-
state will not be available for centralized processing. tain thousands to millions of active elements. Specific
Consequently, algorithms for communications and problems in the area of synchronization include:
processing will be developed that are tolerant of in-
consistencies. They will use redundancy not only

14. • Caching will become pervasive to accommodate per- • To accommodate the improbability of a component
formance, error control and resource management knowing all other components with which it should
objectives. Keeping all cached copies synchronized synchronize, multicast communications will be-
will require new cache coherency algorithms, since come a major synchronization technique. Thus, a
simple write-back or write-through schemes do not component might multicast a message that an-
scale properly. This will lead to synchronization nounces the occurrence of an event to a multicast
marker algorithms where an authoritative copy of group without knowing exactly which other com-
information is broadcast periodically to resync ponents belong to that group. Use of this technique
cached state. Resolution of differences will occur as will rely on the designer making a trade-off between
a result of this synchronization activity. However, synchronization and resource consumption.
there will be many locations where portions of a
large database are authoritative and redundancy in the • Synchronization and fault tolerance will interact
data will accommodate failures. strongly. Synchronization mechanisms will be re-
quired to operate in the face of a certain level of
• The scale of massively distributed applications will component and communications failure. However,
encourage engineers to use asynchronous comput- synchronization algorithms will be designed to
ing, mimicking the way live organisms function. move the distributed application towards a well-
This will be a revolution in the way computations defined goal even when failures occur. Thus, mas-
are designed, implemented and operated. It will no sively distributed applications will make significant
longer be possible to assume or reason that the state use of probabilistic algorithms that complete with a
of some distributed application equals a given value probability less than unity in a given length of
at any point in time. Instead, engineers will design time, but that ensure this probability always mono-
distributed application algorithms so that an invari- tonically increases in time.
ant is always true with high probability.
• The use of pre-agreement algorithms based on roughly 3.9 Measurement, testing and
synchronized clocks will emerge as a major syn- debugging
chronization technique for massively distributed ap- The implementation of massively distributed applica-
plications [14]. The accuracy and drift of local tions requires measurement, testing and debugging to
clocks will become a major engineering problem. ensure applications behave correctly and perform well.
Separate synchronization systems (e.g., the NIST These services are also required to correct implementa-
time standard broadcast over WWV) will be used to tions when they fail to meet either of these criteria. The
decouple clock synchronization from resource deple- scale of massively distributed systems makes the execu-
tion problems and other errors of massively distrib- tion of these tasks difficult. In particular:
uted applications. The use of geographically distant
physical clocks on high-precision real-time applica- • Gathering the necessary measurement data to determine
tions will require the transmission of both clock and whether massively distributed applications are per-
location in a synchronization schedule to accommo- forming properly will be problematic. Directing this
date relativistic effects. data to a single destination will almost certainly in-
terfere with the phenomena being measured. Conse-
• It will be virtually impossible for thousands of com- quently, measurement will occur through an auxil-
ponents to synchronize using communications when iary distributed application, running in tandem with
it is not possible to use an external synchronizing the target application. The measurement application
signal. If synchronized clocks are not achievable, for will itself be massively distributed, requiring its
example, because some components do not have own control infrastructure as well as new monitor-
real-time clocks (e.g., simple embedded systems), ing techniques that allow it to maintain contact with
barrier synchronization implemented as a hierarchi- the measured application even when parts of it are
cal tree will be necessary. Because of the attendant created, destroyed and moved.
performance degradation associated with barrier syn-
chronization, it will only be employed at major • Testing massively distributed applications will require
synchronization points separated by long intervals new techniques to ensure the application scales.
of time. Current approaches used by testing engineers, which
concentrate on determining whether the application
works properly on a single machine will be inade-

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