A comprehensive peer‐to‐peer characterization model

A peer‐to‐peer (P2P) characterization model is proposed in this paper. The purposes of this model are (a) to describe through abstraction the behavior and capability of P2P computing independent of any specific application, and (b) to lead to a cost model of P2P computing. Our approach is based on abstracting the service driven nature of P2P computing separate and distinct from its implementation. This supports the first purpose. Next, we consider the integration of the two aspects. This supports the second purpose. A secondary contribution of our work is a cost model. The cost model is applied to indexing, discovery and resource utilization services. In addition, the characterization model and cost model are applied to a JXTA‐based P2P application. Copyright © 2006 John Wiley & Sons, Ltd.     

Distributed computing with Triana on the Grid

In this paper, we describe Triana, a distributed problem‐solving environment that makes use of the Grid to enable a user to compose applications from a set of components, select resources on which the composed application can be distributed and then execute the application on those resources. We describe Triana's current pluggable architecture that can support many different modes of operation by the use of flexible writers for many popular Web service choreography languages. We further show, that the Triana architecture is middleware‐independent through the use of the Grid Application Toolkit (GAT) API and demonstrate this through the use of a GAT binding to JXTA. We describe how other bindings being developed to Grid infrastructures, such as OGSA, can seamlessly be integrated within the current prototype by using the switching capability of the GAT. Finally, we outline an experiment we conducted using this prototype and discuss its current status. Copyright © 2005 John Wiley & Sons, Ltd.     

Myriad: scalable VR via peer‐to‐peer connectivity,PC clustering,and transient inconsistency

Distributed scene graphs are important in virtual reality, both in collaborative virtual environments and in cluster rendering. Modern scalable visualization systems have high local throughput, but collaborative virtual environments (VEs) over a wide‐area network (WAN) share data at much lower rates. This complicates the use of one scene graph across the whole application. Myriad is an extension of the Syzygy VR toolkit in which individual scene graphs form a peer‐to‐peer network. Myriad connections filter scene graph updates and create flexible relationships between nodes of the scene graph. Myriad's sharing is fine‐grained: the properties of individual scene graph nodes to share are dynamically specified (in C++ or Python). Myriad permits transient inconsistency, relaxing resource requirements in collaborative VEs. A test application, WorldWideCrowd, demonstrates collaborative prototyping of a 300‐avatar crowd animation viewed on two PC‐cluster displays and edited on low‐powered laptops, desktops, and over a WAN. We have further used our framework to facilitate collaborative educational experiences and as a vehicle for undergraduates to experiment with shared virtual worlds. Copyright © 2006 John Wiley & Sons, Ltd.     

Analysis and design of peer‐assisted video‐on‐demand services

We propose a deterministic fluid model to understand the trade‐offs in the design of peer‐assisted video‐on‐demand (VoD) services. There are three entities in this model: peers (or end users), seeders (altruistic users that own one or several complete video items), and cache servers that store and forward videos with a limited capacity. Peers join the network, download one or multiple concurrent video streams (possibly different video items), and abort the system when they wish. Peers are assumed to cooperate in a BitTorrent‐based fashion, governed by tit‐for‐tat and fair availability. The issue is to minimize the expected downloading times, choosing the set of video items that should be stored in each cache server. We first prove that the deterministic model is globally stable, and find closed expressions for the expected waiting times. Then, we introduce a combinatorial optimization problem (COP), whose nature is similar to the multiknapsack problem (where the items are videos, and knapsacks are related with the storage of cache servers). The problem turns out to be NP‐complete. Therefore, we heuristically address the problem following a GRASP (greedy randomized adaptive search procedure) methodology. Finally, we simulate the new caching methodology with real‐life traces taken from YouTube logs. The results suggest that the peer‐to‐peer philosophy is both stable and cost‐effective for on‐demand streaming purposes.     

A database approach for information communication in a peer‐to‐peer collaborative CAD environment

Timely and efficient information communication is a key factor in ensuring successful collaboration in engineering collaborative design. This work proposes a database approach to support information communication between distributed and autonomous CAD systems. It provides the designer with an easy and flexible way, a project‐based propagation meta‐table, to specify what parts of a CAD information model should be communicated to other collaborating designers. A CAD peer manager, containing a peer database that stores information to be exchanged with the other collaborators, wraps each participating CAD system. The peer manager identifies changes made to the CAD model by using stored procedures and active rules in the peer database that are automatically generated based on the propagation meta‐table. The identified updates are propagated in a timely manner to other peers via inter‐database message passing, thereby minimizing the volume of necessary information to be exchanged. Furthermore, remote peer designers can flexibly incorporate, filter, or delete received updates by using a propagation control interface, which is also used to issue user's commands to download the data from the CAD system to the peer database and lookup the received messages in the peer database. The approach is applicable on any CAD system having a CORBA interface and can also be applied to other kinds of object‐oriented interfaces. Copyright © 2007 John Wiley & Sons, Ltd.     

The problem of upload competition in peer‐to‐peer systems with incentive mechanisms

As peer‐to‐peer (P2P) file‐sharing systems revolve around cooperation, the design of upload incentives has been one of the most important topics in P2P research for more than a decade. Several deployed systems, such as private BitTorrent communities, successfully manage to foster cooperation by banning peers when their sharing ratio becomes too low. Interestingly, recent measurements have shown that such systems tend to have an oversupply instead of an undersupply of bandwidth designers that have been obsessed with since the dawn of P2P. In such systems, the ‘selfish peer’ problem is finally solved, but a new problem has arisen: because peers have to keep up their sharing ratios, they now have to compete to upload. In this paper, we explore this new problem and show how even highly cooperative peers might in the end not survive the upload competition. On the basis of recent measurements of over half a million peers in private P2P communities, we propose and analyze several algorithms for uploader selection under oversupply. Our algorithms enable sustained sharing ratio enforcement and are easy to implement in both existing and new systems. Overall, we offer an important design consideration for the new generation of P2P systems in which selfishness is no longer an issue. Copyright © 2012 John Wiley & Sons, Ltd.     

Predicting repayment of borrows in peer‐to‐peer social lending with deep dense convolutional network

In peer‐to‐peer lending, it is important to predict the repayment of the borrower to reduce the lender's financial loss. However, it is difficult to design a powerful feature extractor for predicting the repayment as user and transaction data continue to increase. Convolutional neural networks automatically extract useful features from big data, but they use only high‐level features; hence, it is difficult to capture a variety of representations. In this study, we propose a deep dense convolutional network for repayment prediction in social lending, which maintains the borrower's semantic information and obtains a good representation by automatically extracting important low‐ and high‐level features simultaneously. We predict the repayment of the borrower by learning discriminative features depending on the loan status. Experimental results on the Lending Club dataset show that our model is more effective than other methods. A fivefold cross‐validation is performed to run the experiments.     

ShanghaiGrid: an Information Service Grid

The goal of the ShanghaiGrid is to provide information services to the people. It aims to construct a metropolitan‐area information service infrastructure and establish an open standard for widespread upper‐layer applications from both communities and the government. The Information Service Grid Toolkit and a typical application called the Traffic Information Grid are discussed in detail. Copyright © 2005 John Wiley & Sons, Ltd.     

Efficient resource discovery in self‐organized unstructured peer‐to‐peer networks

In unstructured peer‐to‐peer (P2P) networks, two autonomous peer nodes can be connected if users in those nodes are interested in each other's data. Owing to the similarity between P2P networks and social networks, where peer nodes can be regarded as people and connections can be regarded as relationships, social strategies are useful for improving the performance of resource discovery by self‐organizing autonomous peers on unstructured P2P networks. In this paper, we present an efficient social‐like peer‐to‐peer (ESLP) method for resource discovery by mimicking different human behaviours in social networks. ESLP has been simulated in a dynamic environment with a growing number of peer nodes. From the simulation results and analysis, ESLP achieved better performance than current methods. Copyright © 2008 John Wiley & Sons, Ltd.     

TRUST BY ASSOCIATION: A META‐REPUTATION SYSTEM FOR PEER‐TO‐PEER NETWORKS

Trust mechanisms are used in peer‐to‐peer (P2P) networks to help well‐behaving peers find other well‐behaving peers with which to trade. Unfortunately, these trust mechanisms often do little to keep badly behaving peers from entering and taking advantage of the network, which makes the resulting network difficult or impossible to use for legitimate purposes such as e‐commerce. We propose trust by association, a way of tying peers together in invitation‐only P2P networks in such a way as to encourage the removal of badly behaving peers. We use invitations to create a structure within the otherwise ad hoc P2P network. Using this structure, we create a meta‐reputation system where we measure a peer’s trustworthiness not only by its own behavior, but also by the behavior of the peers it has invited to join. The connection created between the peers takes advantage of the external social relationship that must exist before a peer can be invited into the network. The result is a P2P network where, rather than just trying to marginalize badly behaving peers, there is incentive to kick them out of the network. We present results from a simple simulation showing that our approach works well in general when combined with and compared to an existing trust mechanism.     

A comparative study of awareness methods for peer‐to‐peer distributed virtual environments

The increasing popularity of multi‐player online games is leading to the widespread use of large‐scale Distributed Virtual Environments (DVEs) nowadays. In these systems, peer‐to‐peer (P2P) architectures have been proposed as an efficient and scalable solution for supporting massively multi‐player applications. However, the main challenge for P2P architectures consists of providing each avatar with updated information about which other avatars are its neighbors. This problem is known as the awareness problem. In this paper, we propose a comparative study of the performance provided by those awareness methods that are supposed to fully solve the awareness problem. This study is performed using well‐known performance metrics in distributed systems. Moreover, while the evaluations shown in the literature are performed by executing P2P simulations on a single (sequential) computer, this paper evaluates the performance of the considered methods on actually distributed systems. The evaluation results show that only a single method actually provides full awareness to avatars. This method also provides the best performance results. Copyright © 2008 John Wiley & Sons, Ltd.     

GridBLAST: a Globus‐based high‐throughput implementation of BLAST in a Grid computing framework

Improvements in the performance of processors and networks have made it feasible to treat collections of workstations, servers, clusters and supercomputers as integrated computing resources or Grids. However, the very heterogeneity that is the strength of computational and data Grids can also make application development for such an environment extremely difficult. Application development in a Grid computing environment faces significant challenges in the form of problem granularity, latency and bandwidth issues as well as job scheduling. Currently existing Grid technologies limit the development of Grid applications to certain classes, namely, embarrassingly parallel, hierarchical parallelism, work flow and database applications. Of all these classes, embarrassingly parallel applications are the easiest to develop in a Grid computing framework. The work presented here deals with creating a Grid‐enabled, high‐throughput, standalone version of a bioinformatics application, BLAST, using Globus as the Grid middleware. BLAST is a sequence alignment and search technique that is embarrassingly parallel in nature and thus amenable to adaptation to a Grid environment. A detailed methodology for creating the Grid‐enabled application is presented, which can be used as a template for the development of similar applications. The application has been tested on a ‘mini‐Grid’ testbed and the results presented here show that for large problem sizes, a distributed, Grid‐enabled version can help in significantly reducing execution times. Copyright © 2005 John Wiley & Sons, Ltd.     

From integrative to game‐based integrative peer response: high ability versus low ability

Peer response is useful to improve student writing. However, traditional peer response takes a single mode, which has some problems, such as effort for preparation of documents or ambiguous feedback. To address these problems, this study presents two peer response approaches, that is, an integrative approach and a game‐based integrative approach. Additionally, whether students with these two peer response approaches and those with a non‐peer response approach performed differently is examined in this study, where students' ability levels were also considered. The findings suggest that students with the peer response generally demonstrated better writing performance than those without the peer response. Furthermore, students with the game‐based integrative approach showed better writing quality than those with the integrative approach. Moreover, the former was more helpful in giving direct feedback on surface features and criticism than the latter. However, the usefulness of peer response approaches was associated with ability levels. More specifically, the integrative approach was beneficial for the high‐ability students to improve on their written expression in the aspect of length of composition, while the game‐based integrative approach was advantageous to enhance the low‐ability students' writing quality in the aspect of clear paragraph.     

A replicated information system to enable dynamic collaborations in the Grid

The main advantage of Grid computing over other distributed computing paradigms is its capability to coordinate the access to data and resources in a virtual multi‐institutional environment. To this end, the information system plays a decisive role in selecting the services that meet the applications' needs. This paper presents an information system for the Grid that provides transparent and scalable group communication services to standard Grid applications, with the objective of supporting dynamic collaborations that could help address problems that involve only some participants of a virtual organization. In particular, it enables more flexible delivery mechanisms, which allows applications to select the appropriate services before sending their data to the information system. This significantly enhances the protection of data from unauthorized access, and avoids the transmission of unnecessary messages over the network. The proposed information system is based on the use of XML technologies and replication. It introduces several new advanced features that are not currently supported as a whole by any Grid middleware, such as: several entry points to the information, persistent capabilities, support for advanced queries based on XQuery, and support for the industrial standard WS‐Policy. The information system has been stress tested under realistic workloads in a Grid infrastructure with 50 sites. Scalability has been evaluated in up to 1000 messages that can be up to 10KB in size each, updated with a frequency of 5min. Copyright © 2012 John Wiley & Sons, Ltd.     

The Neutralizer: a self‐configurable failure detector for minimizing distributed storage maintenance cost

To achieve high data availability or reliability in an efficient manner, distributed storage systems must detect whether an observed node failure is permanent or transient, and if necessary, generate replicas to restore the desired level of replication. Given the unpredictability of network dynamics, however, distinguishing permanent and transient failures is extremely difficult. Though timeout‐based detectors can be used to avoid mistaking transient failures as permanent failures, it is unknown how the timeout values should be selected to achieve a better tradeoff between detection latency and accuracy. In this paper, we address this fundamental tradeoff from several perspectives. First, we explore the impact of different timeout values on maintenance cost by examining the probability of their false positives and false negatives. Second, we propose a self‐configurable failure detector called the Neutralizer based on the idea of counteracting false positives with false negatives. The Neutralizer could enable the system to maintain a desired replication level on average with the least amount of bandwidth. We conduct extensive simulations using real trace data from a widely deployed peer‐to‐peer system and synthetic traces based on PlanetLab and Microsoft PCs, showing a significant reduction in aggregate bandwidth usage after applying the Neutralizer (especially in an environment with a low average node availability). Overall, we demonstrate that the Neutralizer closely approximates the performance of a perfect ‘oracle’ detector in many cases. Copyright © 2008 John Wiley & Sons, Ltd.     

A Grid‐enabled problem‐solving environment for advanced reservoir uncertainty analysis

Uncertainty analysis is critical for conducting reservoir performance prediction. However, it is challenging because it relies on (1) massive modeling‐related, geographically distributed, terabyte, or even petabyte scale data sets (geoscience and engineering data), (2) needs to rapidly perform hundreds or thousands of flow simulations, being identical runs with different models calculating the impacts of various uncertainty factors, (3) an integrated, secure, and easy‐to‐use problem‐solving toolkit to assist uncertainty analysis. We leverage Grid computing technologies to address these challenges. We design and implement an integrated problem‐solving environment ResGrid to effectively improve reservoir uncertainty analysis. The ResGrid consists of data management, execution management, and a Grid portal. Data Grid tools, such as metadata, replica, and transfer services, are used to meet massive size and geographically distributed characteristics of data sets. Workflow, task farming, and resource allocation are used to support large‐scale computation. A Grid portal integrates the data management and the computation solution into a unified easy‐to‐use interface, enabling reservoir engineers to specify uncertainty factors of interest and perform large‐scale reservoir studies through a web browser. The ResGrid has been used in petroleum engineering. Copyright © 2008 John Wiley & Sons, Ltd.     

Mining@home: toward a public‐resource computing framework for distributed data mining

Several classes of scientific and commercial applications require the execution of a large number of independent tasks. One highly successful and low‐cost mechanism for acquiring the necessary computing power for these applications is the ‘public‐resource computing’, or ‘desktop Grid’ paradigm, which exploits the computational power of private computers. So far, this paradigm has not been applied to data mining applications for two main reasons. First, it is not straightforward to decompose a data mining algorithm into truly independent sub‐tasks. Second, the large volume of the involved data makes it difficult to handle the communication costs of a parallel paradigm. This paper introduces a general framework for distributed data mining applications called Mining@home. In particular, we focus on one of the main data mining problems: the extraction of closed frequent itemsets from transactional databases. We show that it is possible to decompose this problem into independent tasks, which however need to share a large volume of the data. We thus introduce a data‐intensive computing network, which adopts a P2P topology based on super peers with caching capabilities, aiming to support the dissemination of large amounts of information. Finally, we evaluate the execution of a pattern extraction task on such network. Copyright © 2009 John Wiley & Sons, Ltd.     

Studying protein folding on the Grid: experiences using CHARMM on NPACI resources under Legion

One benefit of a computational Grid is the ability to run high‐performance applications over distributed resources simply and securely. We demonstrated this benefit with an experiment in which we studied the protein‐folding process with the CHARMM molecular simulation package over a Grid managed by Legion, a Grid operating system. High‐performance applications can take advantage of Grid resources if the Grid operating system provides both low‐level functionality as well as high‐level services. We describe the nature of services provided by Legion for high‐performance applications. Our experiences indicate that human factors continue to play a crucial role in the configuration of Grid resources, underlying resources can be problematic, Grid services must tolerate underlying problems or inform the user, and high‐level services must continue to evolve to meet user requirements. Our experiment not only helped a scientist perform an important study, but also showed the viability of an integrated approach such as Legion's for managing a Grid. Copyright © 2004 John Wiley & Sons, Ltd.     

Peer observation of teaching in the online environment: an action research approach

Abstract This paper describes a collaborative action research approach used to explore peer observation of teaching (POT) within the online environment. Although POT has become familiar in face‐to‐face teaching contexts, little is understood of its potential role in online settings. We conducted ‘virtual’ focus groups to explore the experience and views of 28 teachers and subjected our data to a thematic analysis. This informed the implementation of an innovative programme of POT, ‘Peer‐to‐peer Reflection on Pedagogical Practice’ (PROPP) among tutors of a Web‐based MSc in International Primary Health Care at University College London. Modeled on an action learning set, the programme encourages collaborative reflection on teaching practices, based on participants' specific examples of online teaching. The PROPP model is consistent with Quality Enhancement, which we distinguish from Quality Assurance. Here, we describe the implementation of the PROPP programme within an action research framework and identify the factors that we consider critical to the success of peer observation within online courses. We highlight examples of aspects of teaching that have been discussed within the PROPP programme and offer suggestions of the kinds of evidence that could be incorporated into a portfolio to demonstrate the effectiveness of such an initiative.