Personal Volunteer Computing

We propose personal volunteer computing, a novel paradigm to encourage technical solutions that leverage personal devices, such as smartphones and laptops, for personal applications that require significant computations, such as animation rendering and image processing. The paradigm requires no investment in additional hardware, relying instead on devices that are already owned by users and their community, and favours simple tools that can be implemented part-time by a single developer. We show that samples of personal devices of today are competitive with a top-of-the-line laptop from two years ago. We also propose new directions to extend the paradigm

Pando: Personal Volunteer Computing in Browsers

The large penetration and continued growth in ownership of personal electronic devices represents a freely available and largely untapped source of computing power. To leverage those, we present Pando, a new volunteer computing tool based on a declarative concurrent programming model and implemented using JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying number of failure-prone personal devices contributed by volunteers to parallelize the application of a function on a stream of values, by using the devices' browsers. We show that Pando can provide throughput improvements compared to a single personal device, on a variety of compute-bound applications including animation rendering and image processing. We also show the flexibility of our approach by deploying Pando on personal devices connected over a local network, on Grid5000, a French-wide computing grid in a virtual private network, and seven PlanetLab nodes distributed in a wide area network over Europe.Comment: 14 pages, 12 figures, 2 table

Improving the Productivity of Volunteer Computing

The price of computers has dropped drastically over the past years enabling many households to have at least one computer. At the same time, the performance of computers has skyrocketed, far surpassing what a typical user needs, and most of the computational power of personal computers is wasted. Volunteer computing projects attempt to use this wasted computational power in order to solve problems that would otherwise be computationally infeasible. Some of these problems include medical applications like searching for cures for AIDS and cancer. However, the number of volunteer computing projects is increasing rapidly, requiring improvements in the field of volunteer computing to enable the increasing number of volunteer projects to continue making significant progress. This dissertation examines two ways to increase the productivity of volunteer computing: using the volunteered CPU cycles more effectively and exploring ways to increase the amount of CPU cycles that are donated. Each of the existing volunteer computing projects uses one of two task retrieval policies to enable the volunteered computers participating in projects to retrieve work. This dissertation compares the amount of work completed by the volunteered computers participating in projects based on which of the two task retrieval techniques the project employs. Additional task retrieval policies are also proposed and evaluated. The most commonly used task retrieval policy is shown to be less effective than both the less frequently used policy and a proposed policy. The potential that video game consoles have to be used for volunteer computing is explored, as well as the potential benefits of constructing different types of volunteer computing clients, rather than the most popular client implementation: the screensaver. In addition to examining methods of increasing the productivity of volunteer computing, 140 traces of computer usage detailing when computers are available to participate in volunteer computing is collected and made publicly available. Volunteer computing project-specific information that can be used in researching how to improve volunteer computing is collected and combined into the first summary of which we are aware

Genet: A Quickly Scalable Fat-Tree Overlay for Personal Volunteer Computing using WebRTC

WebRTC enables browsers to exchange data directly but the number of possible concurrent connections to a single source is limited. We overcome the limitation by organizing participants in a fat-tree overlay: when the maximum number of connections of a tree node is reached, the new participants connect to the node's children. Our design quickly scales when a large number of participants join in a short amount of time, by relying on a novel scheme that only requires local information to route connection messages: the destination is derived from the hash value of the combined identifiers of the message's source and of the node that is holding the message. The scheme provides deterministic routing of a sequence of connection messages from a single source and probabilistic balancing of newer connections among the leaves. We show that this design puts at least 83% of nodes at the same depth as a deterministic algorithm, can connect a thousand browser windows in 21-55 seconds in a local network, and can be deployed for volunteer computing to tap into 320 cores in less than 30 seconds on a local network to increase the total throughput on the Collatz application by two orders of magnitude compared to a single core

Mechanisms for Outsourcing Computation via a Decentralized Market

As the number of personal computing and IoT devices grows rapidly, so does the amount of computational power that is available at the edge. Since many of these devices are often idle, there is a vast amount of computational power that is currently untapped, and which could be used for outsourcing computation. Existing solutions for harnessing this power, such as volunteer computing (e.g., BOINC), are centralized platforms in which a single organization or company can control participation and pricing. By contrast, an open market of computational resources, where resource owners and resource users trade directly with each other, could lead to greater participation and more competitive pricing. To provide an open market, we introduce MODiCuM, a decentralized system for outsourcing computation. MODiCuM deters participants from misbehaving-which is a key problem in decentralized systems-by resolving disputes via dedicated mediators and by imposing enforceable fines. However, unlike other decentralized outsourcing solutions, MODiCuM minimizes computational overhead since it does not require global trust in mediation results. We provide analytical results proving that MODiCuM can deter misbehavior, and we evaluate the overhead of MODiCuM using experimental results based on an implementation of our platform

Public grid computing participation: An exploratory study of determinants

Using the Internet, “public” computing grids can be assembled using “volunteered” PCs. To achieve this, volunteers download and install a software application capable of sensing periods of low local processor activity. During such times, this program on the local PC downloads and processes a subset of the project's data. At the completion of processing, the results are uploaded to the project and the cycle repeats. Public grids are being used for a wide range of endeavors, from searching for signals suggesting extraterrestrial life to finding a cure for cancer. Despite the potential benefits, however, participation has been relatively low. The work reported here, drawing from technology acceptance and volunteer literature, suggests that the grid operator's reputation, the project's perceived need, and the level of volunteering activity of the PC owner are significant determinants of participation in grid projects. Attitude, in addition to personal innovativeness and level of volunteering activity, predicted intentions to join the project. Thus, methods traditionally used for motivating volunteer behavior may be effective in promoting the use of grid computing

Learning by volunteer computing, thinking and gaming: What and how are volunteers learning by participating in Virtual Citizen Science?

Citizen Science (CS) refers to a form of research collaboration that engages volunteers without formal scientific training in contributing to empirical scientific projects. Virtual Citizen Science (VCS) projects engage participants in online tasks. VCS has demonstrated its usefulness for research, however little is known about its learning potential for volunteers. This paper reports on research exploring the learning outcomes and processes in VCS. In order to identify different kinds of learning, 32 exploratory interviews of volunteers were conducted in three different VCS projects. We found six main learning outcomes related to different participants' activities in the project. Volunteers learn on four dimensions that are directly related to the scope of the VCS project: they learn at the task/game level, acquire pattern recognition skills, on-topic content knowledge, and improve their scientific literacy. Thanks to indirect opportunities of VCS projects, volunteers learn on two additional dimensions: off topic knowledge and skills, and personal development. Activities through which volunteers learn can be categorized in two levels: at a micro (task/game) level that is direct participation to the task, and at a macro level, i.e. use of project documentation, personal research on the Internet, and practicing specific roles in project communities. Both types are influenced by interactions with others in chat or forums. Most learning happens to be informal, unstructured and social. Volunteers do not only learn from others by interacting with scientists and their peers, but also by working for others: they gain knowledge, new status and skills by acting as active participants, moderators, editors, translators, community managers, etc. in a project community. This research highlights these informal and social aspects in adult learning and science education and also stresses the importance for learning through the indirect opportunities provided by the project: the main one being the opportunity to participate and progress in a project community, according to one's tastes and skills