Distributed Programming  
Lecture 01 - Introduction to Distributed Systems  
and Distributed Programming  
Edirlei Soares de Lima  
What is Distributed Programming?  
Distributed computing is a field of  
computer science that studies  
distributed systems.  
A distributed system is a system  
whose components are located on  
different networked computers,  
which then communicate and  
coordinate their actions by passing  
messages to each other.  
Distributed programming involves  
the implementation of distributed  
Distributed Programming Concurrency  
Process vs. Thread:  
A process runs in its own address space (managed  
by the OS), while a thread runs within the address  
space of a single process and its managed by the  
Parallel vs. Concurrent:  
Parallel refers usually to cases where two  
computation are taking place physically  
independently of each other (e.g.: in two different  
machines, or in two different processors) while  
concurrent is an abstraction that allows us to have  
apparent parallelism even in the cases of one  
Concurrent Programming  
Main challenge: synchronize the execution of different  
processes and enable them to communicate with each other.  
Type of systems:  
Multitasking System: concurrent execution of multiple processes in a  
single CPU.  
Multiprocessor Systems: parallel execution of multiple processes in  
multiple CPUs.  
Distributed Systems: parallel execution of multiple processes in  
multiple computers connected through a network.  
Multitasking Systems  
Concurrency is based on interleaving  
instructions from different processes  
on a single CPU.  
Multitasking does not require parallel  
execution of multiple tasks at exactly  
the same time; instead, it allows more  
than one task to advance over a given  
period of time.  
Multiprocessor Systems  
Parallelism is achieved by executing processes in multiple  
CPUs on the same computer.  
Each processor has access to both local memory and global  
Distributed Systems  
Parallelism is achieved by executing processes in multiple  
computers that are connected through a network.  
Distributed Systems Examples  
Web Services: WEB (HTTP), E-Mail (SMTP), VoIP, Instant  
Messaging, …  
Distributed Systems Examples  
Cloud Computing: Google Docs, Google Drive, Dropbox,  
Amazon Web Services, …  
Distributed Systems Examples  
MMORPGs: require fast response times and real-time  
propagation of events.  
Multiplayer Games History  
Empire (1973): turn-based strategy game  
with support for networked multiplayer.  
Maze War (1973): networked multiplayer  
first-person shooter.  
Both games were designed run on small  
networks composed of mainframe  
computers (PLATO system).  
Multiplayer Games History  
Doom (1993) was the progenitor of the modern networked  
The first-person shooter supported up to four players in a single  
game session (in a local area network LAN), with the option to play  
cooperatively or competitively.  
Multiplayer Games History  
Quake (1996) allowed players to  
connect to a server (which may be a  
dedicated machine or on one of the  
player's computers), where they  
could either play cooperatively or  
Unreal (1998) followed the same  
model of Quake with a multiplayer  
mode that allowed up to 16 players  
to play over the Internet.  
Multiplayer Games History  
Ultima Online (1997) was one of  
the first persistent MMORPGs.  
EverQuest (1999) was the first  
commercially successful MMORPG  
to employ a three-dimensional  
game engine.  
World of Warcraft (2004) is one of  
the most successful MMORPGs,  
with a peak of 12 million  
subscriptions in 2010.  
Why are Distributed Systems Needed?  
General access without location restrictions (e.g.: banking  
network, games);  
Sharing resources across many users (hardware and  
Load balancing (e.g.: distributing game players across many  
servers instead of overloading a single server);  
Fault tolerance (when a fraction of the processors fail, the  
remaining processes can take over the tasks and keep the  
application running);  
Flexibility and adaptability by decomposing a global system  
into smaller (and simpler) systems;  
Distributed Systems Challenges  
Heterogeneity: hardware, operating systems, programming  
languages, …  
The knowledge of a process is local: no process is expected to  
have global knowledge about either the network topology or  
the global state.  
Communication, cooperation and synchronization between  
processes is done through message exchange.  
The handling of failures is an important and complex part of a  
distributed system.  
Scalability: a distributed system is considered scalable when  
its performance is not influenced by the final scale of the  
system or the number of users.  
Distributed Computing Common Problems  
Leader election: when a number of processes cooperate for  
solving a problem, many implementations prefer to elect one  
of them as the leader and the remaining processes as  
followers. If the leader crashes, then one of the followers is  
elected the leader.  
Distributed Computing Common Problems  
Mutual exclusion: when the access to a resource or shared  
data is critical, it is necessary to guarantee that only one  
process will acquire the resource or perform critical  
operations on a shared data at any time.  
Distributed Computing Common Problems  
Multicasting: sending of a given data to multiple processes in  
a distributed system is a common subtask in many  
applications. As an example, in group communication, one  
may want to send some breaking news to millions of  
members as quickly as possible.  
Replica management: to support fault tolerance and improve  
system availability, the use of process replicas is quite  
common. When the main server is down, one of the replica  
servers replaces the main server.  
Further Reading  
Coulouris, G., Dollimore, J., Kindberg, T., Blair, G. (2004). Distributed  
Systems: Concepts and Design (5th edition), Pearson.  
ISBN: 978-0132143011.  
Chapter 1: Characterization of Distributed Systems  
Glazer, J., Madhav, S. (2015). Multiplayer Game Programming:  
Architecting Networked Games. Addison-Wesley Professional.  
ISBN: 978-0134034300.  
Chapter 1: Overview of Networked Games