Middleware for volunteer computing

The client software of the early volunteer computing projects consisted of a single program that combined the scientific computation and the distributed computing infrastructure. This monolithic architecture was inflexible; for example, it was difficult to deploy new application versions.

More recently, volunteer computing has moved to middleware systems that provide a distributed computing infrastructure independently of the scientific computation. Examples include:

* The Berkeley Open Infrastructure for Network Computing (BOINC). BOINC is the most widely-used middleware system. It is open source (LGPL) and is developed by an NSF-funded research project located at the UC Berkeley Space Sciences Laboratory. It offers client software for Windows, Mac OS X, Linux, and other Unix variants.

* XtremWeb is used primarily as a research tool. It is developed by a group based a University of Paris - South.

* Xgrid is developed by Apple. Its client and server components run only on Mac OS X.

* Grid MP is a commercial middleware platform developed by United Devices and has been used in volunteer computing projects including grid.org, World Community Grid, Cell Computing, and Hikari Grid.

Most of these systems have the same basic structure: a client program runs on the volunteer's computer. It periodically contacts project-operated servers over the Internet, requesting jobs and reporting the results of completed jobs. This "pull" model is necessary because many volunteer computers are behind firewalls that don't allow incoming connections. The system keeps track of each user's "credit", a numerical measure of how much work that user's computers have done for the project.

Volunteer computing systems must deal with several problematic aspects of the volunteered computers: their heterogeneity, their churn (that is, the arrival and departure of hosts), their sporadic availability, and the need to not interfere with their performance during regular use.

In addition, volunteer computing systems must deal with several related problems related to correctness:

* Volunteers are unaccountable and essentially anonymous.
* Some volunteer computers (especially those that are overclocked) occasionally malfunction and return incorrect results.
* Some volunteers intentionally return incorrect results or claim excessive credit for results.

One common approach to these problems is "replicated computing", in which each job is performed on at least two computers. The results (and the corresponding credit) is accepted only if they agree sufficiently.

History if Volunteer Computing

The first volunteer computing project was the Great Internet Mersenne Prime Search, which was started in January 1996 . It was followed in 1997 by distributed.net. In 1997 and 1998 several academic research projects developed Java-based systems for volunteer computing; examples include Bayanihan, Popcorn, Superweb and Charlotte

The term "volunteer computing" was coined by Luis F. G. Sarmenta, the developer of Bayanihan. It is also appealing for global efforts on social responsibility, or Corporate Social Responsibility as reported in a Harvard Business Review or used in the Responsible IT forum.

In 1999 the SETI@home and Folding@home projects were launched. These projects received considerable media coverage, and each one attracted several hundred thousand volunteers.

Between 1998 and 2002, several companies were formed with business models involving volunteer computing. Examples include Popular Power, Porivo, Entropia, and United Devices

Volunteer computing

Volunteer computing is a type of distributed computing in which computer owners donate their computing resources (such as processing power and storage) to one or more "projects". It is distinct from Grid computing, which involves sharing of managed computing resources within and between organizations.

Theory of computation

The theory of computation is the branch of computer science that deals with whether and how efficiently problems can be solved on a model of computation, using an algorithm. The field is divided into two major branches: computability theory and complexity theory, but both branches deal with formal models of computation.

In order to perform a rigorous study of computation, computer scientists work with a mathematical abstraction of computers called a model of computation. There are several models in use, but the most commonly examined is the Turing machine. A Turing machine can be thought of as a desktop PC with a potentially infinite memory capacity, though it can only access this memory in small discrete chunks. Computer scientists study the Turing machine because it is simple to formulate, can be analyzed and used to prove results, and because it represents what many consider the most powerful possible "reasonable" model of computation. It might seem that the potentially infinite memory capacity is an unrealizable attribute, but any decidable problem solved by a Turing machine will always require only a finite amount of memory. So in principle, any problem that can be solved (decided) by a Turing machine can be solved by a computer that has a bounded amount of memory.

Computer science

Computer science (or computing science) is the study of the theoretical foundations of information and computation and their implementation and application in computer systems.[1][2][3] Computer science has many sub-fields; some emphasize the computation of specific results (such as computer graphics), while others relate to properties of computational problems (such as computational complexity theory). Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems. A further subfield, human-computer interaction, focuses on the challenges in making computers and computations useful, usable and universally accessible to people.