iGridMedia: The system to provide low delay peer-to-peer live streaming service over internet

Commercial peer-to-peer live streaming services are getting popular nowadays, however, almost all systems target non-interactive applications. Few systems can address how to support interactive applications (such as online auction, person interview, video sharing & commenting, etc.) with peer-to-peer streaming technology. In an interactive channel, all or part of the participants can interact with the presenter or publisher at the source. Unlike existing P2P streaming service, there is different level of delay and synchronization requirements in interactive applications, meanwhile, the participant number in each channel is relatively small but the concurrent channel number is large. With such challenges, how much server bandwidth can be saved in P2P streaming is an interesting problem. We propose a very practical protocol iGridMedia and fully implement it. The basic tradeoff between consumed server bandwidth and the required delay is carefully studied. Simulation and real-world experiments show that our system consumes little server bandwidth under low delay even if the peer churn rate is very high and the peer bandwidth resource index is very limited.     

GPU-accelerated DXT and JPEG compression schemes for low-latency network transmissions of HD, 2K,and 4K video

Low-latency transmissions of high resolution video such as HD, 2K, or 4K over both Internet and private IP networks have found a foothold in many interactive applications, ranging from collaborative environments in science and medicine to the arts and entertainment industry. In this paper we demonstrate how the power of commodity graphics processing units can be used for efficient implementation of JPEG and DXT compression. We propose an approach to fine-grained parallelization of JPEG compression and the use of auxiliary indexes for efficient decompression, which are backward compatible with the JPEG standard. In-depth performance analysis is provided to show various aspects of the proposed parallelization including the dependency on image content and on various settings of the compression algorithm, as well as the impact of compression for interactive applications in terms of end-to-end latency. The applicability of these compression schemes in medicine and cinematography has also been evaluated using double-blind ABX tests compared with uncompressed video. We describe selected successful real-world deployment use cases based on our open-source implementation within the UltraGrid framework, such as trans-Atlantic 4K interactive video streaming during the CineGrid 2011 workshop. As discussed in the paper, the proposed approaches to parallelization provide sufficient performance even for the future generation of 8K video processing systems, currently limited by availability of camera and display hardware.     

Predictive haptic guidance: intelligent user assistance for the control of dynamic tasks

Intelligent systems are increasingly able to offer real-time information relevant to a user's manual control of an interactive system, such as dynamic system control space constraints for animation control and driving. However, it is difficult to present this information in a usable manner and other approaches which have employed haptic cues for manual control in "slow" systems often lead to instabilities in highly dynamic tasks. We present a predictive haptic guidance method based on a look-ahead algorithm, along with a user evaluation which compares it with other approaches (no guidance and a standard potential-field method) in a 1-DoF steered path-following scenario. Look-ahead guidance outperformed the other methods in both quantitative performance and subjective preference across a range of path complexity and visibility and a force analysis demonstrated that it applied smaller and fewer forces to users. These results (which appear to derive from the predictive guidance's supporting users in taking earlier and more subtle corrective action) suggest the potential of predictive methods in aiding manual control of dynamic interactive tasks where intelligent support is available.     

Listener latency profiling: Measuring the perceptible performance of interactive Java applications

When developers need to improve the performance of their applications, they usually use one of the many existing profilers. These profilers generally capture a profile that represents the execution time spent in each method. The developer can thus focus her optimization efforts on the methods that consume the most time. In this paper we argue that this type of profile is insufficient for tuning interactive applications. Interactive applications respond to user events, such as mouse clicks and key presses. The perceived performance of interactive applications is directly related to the response time of the program.In this paper we present listener latency profiling, a profiling approach with two distinctive characteristics. First, we call it latency profiling because it helps developers to find long latency operations. Second, we call it listener profiling because it abstracts away from method-level profiles to compute the latency of the various listeners. This allows a developer to reason about performance with respect to listeners, also called observers, the high level abstraction at the core of any interactive Java application.We present our listener latency profiling approach, describe LiLa, our implementation, validate it on a set of microbenchmarks, and evaluate it on a complex real-world interactive application. We then perform case studies where we use LiLa to tune the perceptible performance of two interactive applications, and we show that LiLa is able to pinpoint performance problems even if their causes are embedded in the largest interactive Java application we are aware of.     

The message is the medium

We are exploring the use of visual imagery which simultaneously provides the content and control of web-based interactive services. We describe four unconventional web-based services we have implemented for: messaging, a bulletin board, broadcast messages, and browsing through a set of hyperlinked objects. We implement each service using a real-world metaphor which serves as the basis for the visual presentation as well as the service itself; thus form and function are tightly coupled. The use of universal imagery eliminates the need for wordy explanations and hence increases accessibility to an international audience. During the course of development, we devised techniques to enhance the shared experiences of the visitors to our sites, including automatically generated 2D animations. These approaches can be applied to a variety of web-sites and are also described.     

Automated GUI performance testing

A significant body of prior work has devised approaches for automating the functional testing of interactive applications. However, little work exists for automatically testing their performance. Performance testing imposes additional requirements upon GUI test automation tools: the tools have to be able to replay complex interactive sessions, and they have to avoid perturbing the application’s performance. We study the feasibility of using five Java GUI capture and replay tools for GUI performance test automation. Besides confirming the severity of the previously known GUI element identification problem, we also describe a related problem, the temporal synchronization problem, which is of increasing importance for GUI applications that use timer-driven activity. We find that most of the tools we study have severe limitations when used for recording and replaying realistic sessions of real-world Java applications and that all of them suffer from the temporal synchronization problem. However, we find that the most reliable tool, Pounder, causes only limited perturbation and thus can be used to automate performance testing. Based on an investigation of Pounder’s approach, we further improve its robustness and reduce its perturbation. Finally, we demonstrate in a set of case studies that the conclusions about perceptible performance drawn from manual tests still hold when using automated tests driven by Pounder. Besides the significance of our findings to GUI performance testing, the results are also relevant to capture and replay-based functional GUI test automation approaches.     

An extensible analysable system model

Analysing real-world systems for vulnerabilities with respect to security and safety threats is a difficult undertaking, not least due to a lack of availability of formalisations for those systems. While both formalisations and analyses can be found for artificial systems such as software, this does not hold for real physical systems. Approaches such as threat modelling try to target the formalisation of the real-world domain, but still are far from the rigid techniques available in security research. Many currently available approaches to assurance of critical infrastructure security are based on (quite successful) ad-hoc techniques. We believe they can be significantly improved beyond the state-of-the-art by pairing them with static analyses techniques.In this paper we present an approach to both formalising those real-world systems, as well as providing an underlying semantics, which allows for easy development of analyses for the abstracted systems. We briefly present one application of our approach, namely the analysis of systems for potential insider threats.     

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). SLAs define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.     

Web-based three-dimensional geo-referenced visualization

This paper addresses several approaches to implementing web-based, three-dimensional (3-D), geo-referenced visualization. The discussion focuses on the relationship between multi-dimensional data sets and applications, as well as the thick/thin client and heavy/light server structure. Two models of data sets are addressed in this paper. One is the use of traditional 3-D data format such as 3-D Studio Max, Open Inventor 2.0, Vis5D and OBJ. The other is modelled by a web-based language such as VRML. Also, traditional languages such as C and C++, as well as web-based programming tools such as Java, Java3D and ActiveX, can be used for developing applications. The strengths and weaknesses of each approach are elaborated. Four practical solutions for using VRML and Java, Java and Java3D, VRML and ActiveX and Java wrapper classes (Java and C/C++), to develop applications are presented for web-based, real-time interactive and explorative visualization.     

基于边选择的时延抖动受限组播路由算法

组播技术在多媒体通信的实际应用中十分重要,对各种交互式实时组播业务如视频会议等来说,不仅要考虑时延约束,而且要考虑时延抖动约束。对基于边选择的时延抖动受限的启发式算法进行了研究,仿真结果表明算法复杂度较低,性能也较好。     

基于边选择的时延抖动受限组播路由算法

组播技术在多媒体通信的实际应用中十分重要,对各种交互式实时组播业务如视频会议等来说,不仅要考虑时延约束,而且要考虑时延抖动约束。对基于边选择的时延抖动受限的启发式算法进行了研究,仿真结果表明算法复杂度较低,性能也较好。     

A hybrid approach for improving predictive accuracy of collaborative filtering algorithms

Recommender systems represent a class of personalized systems that aim at predicting a user’s interest on information items available in the application domain, operating upon user-driven ratings on items and/or item features. One of the most widely used recommendation methods is collaborative filtering that exploits the assumption that users who have agreed in the past in their ratings on observed items will eventually agree in the future. Despite the success of recommendation methods and collaborative filtering in particular, in real-world applications they suffer from the insufficient number of available ratings, which significantly affects the accuracy of prediction. In this paper, we propose recommendation approaches that follow the collaborative filtering reasoning and utilize the notion of lifestyle as an effective user characteristic that can group consumers in terms of their behavior as indicated in consumer behavior and marketing theory. Emanating from a basic lifestyle-based recommendation algorithm we incrementally proceed to the development of hybrid recommendation approaches that address certain dimensions of the sparsity problem and empirically evaluate them providing further evidence of their effectiveness.     

CyberGIS-enabled decision support platform for biomass supply chain optimization

Biomass supply chain optimization aims to facilitate large-scale production of biofuels by improving the efficiency and effectiveness of biomass feedstock provision. Most existing models are not web based, limited by the accessibility for real-world applications. A CyberGIS-enabled biomass supply chain decision support platform was developed to improve model accessibility and computational performance. The platform includes four major components: BioScope optimization model, GISolve middleware, high-performance cyberinfrastructure, and an interactive web interface. The workflow and functions of each component are provided to illustrate the development and usage of the platform. Case studies and associated system performance have been evaluated to demonstrate the utility of the CyberGIS-enabled decision support platform. Through leveraging cyberinfrastructure resources and interactive web-based interface, the platform enables solving complex biomass supply chain optimization problems. The improved computational performance could provide responsive decision support for group-based applications.     

Effective Annotations Over 3D Models

Annotation support in interactive systems is often considered a simple task by the CG community, since it entails the apparently easy selection of a region and its connection with some information. The reality appears more complex. The scope of this paper is two-fold: first, to review the status of this domain, discussing and characterizing several approaches proposed in literature to manage annotations over geometric models; second, to present in detail an innovative solution proposed and assessed in the framework of Cultural Heritage (CH) applications, called ClippingVolumes. At the annotation definition stage ClippingVolumes uses 3D data to characterize the annotation region; subsequently, annotations are visualized by adopting a two-pass rendering solution which uses stencil buffers, thus without introducing new geometric elements, changing the topology or duplicating geometry elements. It solves most of the issues that afflict the current state of the art, such as fragmentation, annotation transfer to multiple representations and multi-resolution data encoding. The latter is a mandatory requirement to produce efficient web-based systems. We implemented and we fully tested this approach in the framework of a complex system that supports the documentation of CH restoration projects.     

Customizable execution environments for evolutionary computation using BOINC + virtualization

Evolutionary algorithms (EAs) consume large amounts of computational resources, particularly when they are used to solve real-world problems that require complex fitness evaluations. Beside the lack of resources, scientists face another problem: the absence of the required expertise to adapt applications for parallel and distributed computing models. Moreover, the computing power of PCs is frequently underused at institutions, as desktops are usually devoted to administrative tasks. Therefore, the proposal in this work consists of providing a framework that allows researchers to massively deploy EA experiments by exploiting the computing power of their instituions’ PCs by setting up a Desktop Grid System based on the BOINC middleware. This paper presents a new model for running unmodified applications within BOINC with a web-based centralized management system for available resources. Thanks to this proposal, researchers can run scientific applications without modifying the application’s source code, and at the same time manage thousands of computers from a single web page. Summarizing, this model allows the creation of on-demand customized execution environments within BOINC that can be used to harness unused computational resources for complex computational experiments, such as EAs. To show the performance of this model, a real-world application of Genetic Programming was used and tested through a centrally-managed desktop grid infrastructure. Results show the feasibility of the approach that has allowed researchers to generate new solutions by means of an easy to use and manage distributed system.     

Coordinating multiagent applications on the WWW: a referencearchitecture

The original Web did not support multiuser, interactive applications. This shortcoming is being studied, and several approaches have been proposed to use the Web as a platform for programming Internet applications. However, most existing approaches are oriented to centralized applications at servers, or local programs within clients. To overcome this deficit, we introduce PageSpace, that is a reference architecture for designing interactive multiagent applications. We describe how we control agents in PageSpace, using variants of the coordination language Linda to guide their interactions. Coordination technology is integrated with the standard Web technology and the programming language Java. Several kinds of agents live in the PageSpace: user interface agents, personal homeagents, agents that implement applications, and agents which interoperate with legacy systems. Within our architecture, it is possible to support fault-tolerance and mobile agents as well     

Design and analysis of genetic fuzzy systems for intrusion detection in computer networks

The capability of fuzzy systems to solve different kinds of problems has been demonstrated in several previous investigations. Genetic fuzzy systems (GFSs) hybridize the approximate reasoning method of fuzzy systems with the learning capability of evolutionary algorithms. The objective of this paper is to design and analysis of various kinds of genetic fuzzy systems to deal with intrusion detection problem as a new real-world application area which is not previously tackled with GFSs. The resulted intrusion detection system would be capable of detecting normal and abnormal behaviors in computer networks. We have presented three kinds of genetic fuzzy systems based on Michigan, Pittsburgh and iterative rule learning (IRL) approaches to deal with intrusion detection as a high-dimensional classification problem. Experiments were performed with DARPA data sets which have information on computer networks, during normal and intrusive behaviors. The paper presents some results and compares the performance of different generated fuzzy rule sets in detecting intrusion in a computer network according to three different types of genetic fuzzy systems.     

Delay aware querying with Seaweed

Large highly distributed data sets are poorly supported by current query technologies. Applications such as endsystem-based network management are characterized by data stored on large numbers of endsystems, with frequent local updates and relatively infrequent global one-shot queries. The challenges are scale (10³ to 10⁹ endsystems) and endsystem unavailability. In such large systems, a significant fraction of endsystems and their data will be unavailable at any given time. Existing methods to provide high data availability despite endsystem unavailability involve centralizing, redistributing or replicating the data. At large scale these methods are not scalable. We advocate a design that trades query delay for completeness, incrementally returning results as endsystems become available. We also introduce the idea of completeness prediction, which provides the user with explicit feedback about this delay/completeness trade-off. Completeness prediction is based on replication of compact data summaries and availability models. This metadata is orders of magnitude smaller than the data. Seaweed is a scalable query infrastructure supporting incremental results, online in-network aggregation and completeness prediction. It is built on a distributed hash table (DHT) but unlike previous DHT based approaches it does not redistribute data across the network. It exploits the DHT infrastructure for failure-resilient metadata replication, query dissemination, and result aggregation. We analytically compare Seaweed’s scalability against other approaches and also evaluate the Seaweed prototype running on a large-scale network simulator driven by real-world traces.     

Optical information for car following: the driving by visual angle (DVA) model

OBJECTIVE: The present study developed and tested a model of car following by human drivers. BACKGROUND: Previous models of car following are based on 3-D parameters such as lead vehicle speed and distance information, which are not directly available to a driver. In the present paper we present the driving by visual angle (DVA) model, which is based on the visual information (visual angle and rate of change of visual angle) available to the driver. METHOD: Two experiments in a driving simulator examined car-following performance in response to speed variations of a lead vehicle defined by a sum of sine wave oscillations and ramp acceleration functions. In addition, the model was applied to six driving events using real world-driving data. RESULTS: The model provided a good fit to car-following performance in the driving simulation studies as well as in real-world driving performance. A comparison with the advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN) model, which is based on 3-D parameters, suggests that the DVA was more predictive of driver behavior in matching lead vehicle speed and distance headway. CONCLUSION: Car-following behavior can be modeled using only visual information to the driver and can produce performance more predictive of driver performance than models based on 3-D (speed or distance) information. APPLICATION: The DVA model has applications to several traffic safety issues, including automated driving systems and traffic flow models.