Development of a Physics-Aware Dead Reckoning Mechanism for Distributed Interactive Applications

Distributed Interactive Applications (DIAs) are a class of software that allow geographically remote users to interact within a shared virtual environment. Many DIAs seek to present a rich and realistic virtual world to users, both on a visual and behavioural level. A relatively recent addition to virtual environments (both distributed and single user) to achieve the latter has been the simulation of realistic physical phenomena between objects in the environment. However, the application of physics simulation to virtual environments in DIAs currently lags that of single user environments. This is primarily due to the unavailability of entity state update mechanisms which can maintain consistency in such physics-rich environments. The difference is particularly evident in applications built on a peer-to-peer architecture, as a lack of a single authority presents additional challenges in synchronising the state of shared objects while also presenting a responsive simulation. This thesis proposes a novel state maintenance mechanism for physics-rich environments in peer-to-peer DIAs composed of two parts: a dynamic authority scheme for shared objects, and a physics-aware dead reckoning model with an adaptive error threshold. The first part is intended to place a bound on the overall inconsistency present in shared objects, while the second is implemented to minimise the instantaneous inconsistency during users’ interactions with shared objects. A testbed application is also described, which is used to validate the performance of the proposed mechanism. The state maintenance mechanism is implemented for a single type of physicsaware application, and demonstrates a marked improvement in consistency for that application. However, several flexible terms are described in its implementation, as well as their potential relevance to alternative applications. Finally, it should be noted that the physics-aware dead reckoning model does not depend on the authority scheme, and can therefore be employed with alternative authority scheme

An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications

Distributed Interactive Applications (DIAs) enable geographically dispersed users to interact with each other in a virtual environment. A key factor to the success of a DIA is the maintenance of a consistent view of the shared virtual world for all the participants. However, maintaining consistent states in DIAs is difficult under real networks. State changes communicated by messages over such networks suffer latency leading to inconsistency across the application. Predictive Contract Mechanisms (PCMs) combat this problem through reducing the number of messages transmitted in return for perceptually tolerable inconsistency. This thesis examines the operation of PCMs using concepts and methods derived from information theory. This information theory perspective results in a novel information model of PCMs that quantifies and analyzes the efficiency of such methods in communicating the reduced state information, and a new adaptive multiple-model-based framework for improving consistency in DIAs. The first part of this thesis introduces information measurements of user behavior in DIAs and formalizes the information model for PCM operation. In presenting the information model, the statistical dependence in the entity state, which makes using extrapolation models to predict future user behavior possible, is evaluated. The efficiency of a PCM to exploit such predictability to reduce the amount of network resources required to maintain consistency is also investigated. It is demonstrated that from the information theory perspective, PCMs can be interpreted as a form of information reduction and compression. The second part of this thesis proposes an Information-Based Dynamic Extrapolation Model for dynamically selecting between extrapolation algorithms based on information evaluation and inferred network conditions. This model adapts PCM configurations to both user behavior and network conditions, and makes the most information-efficient use of the available network resources. In doing so, it improves PCM performance and consistency in DIAs

Dead Reckoning Using Play Patterns in a Simple 2D Multiplayer Online Game

In today’s gaming world, a player expects the same play experience whether playing on a local network or online with many geographically distant players on congested networks. Because of delay and loss, there may be discrepancies in the simulated environment from player to player, likely resulting in incorrect perception of events. It is desirable to develop methods that minimize this problem. Dead reckoning is one such method. Traditional dead reckoning schemes typically predict a player’s position linearly by assuming players move with constant force or velocity. In this paper, we consider team-based 2D online action games. In such games, player movement is rarely linear. Consequently, we implemented such a game to act as a test harness we used to collect a large amount of data from playing sessions involving a large number of experienced players. From analyzing this data, we identified play patterns, which we used to create three dead reckoning algorithms. We then used an extensive set of simulations to compare our algorithms with the IEEE standard dead reckoning algorithm and with the recent “Interest Scheme” algorithm. Our results are promising especially with respect to the average export error and the number of hits

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

Energy-efficient Continuous Context Sensing on Mobile Phones

With the ever increasing adoption of smartphones worldwide, researchers have found the perfect sensor platform to perform context-based research and to prepare for context-based services to be also deployed for the end-users. However, continuous context sensing imposes a considerable challenge in balancing the energy consumption of the sensors, the accuracy of the recognized context and its latency. After outlining the common characteristics of continuous sensing systems, we present a detailed overview of the state of the art, from sensors sub-systems to context inference algorithms. Then, we present the three main contribution of this thesis. The first approach we present is based on the use of local communications to exchange sensing information with neighboring devices. As proximity, location and environmental information can be obtained from nearby smartphones, we design a protocol for synchronizing the exchanges and fairly distribute the sensing tasks. We show both theoretically and experimentally the reduction in energy needed when the devices can collaborate. The second approach focuses on the way to schedule mobile sensors, optimizing for both the accuracy and energy needs. We formulate the optimal sensing problem as a decision problem and propose a two-tier framework for approximating its solution. The first tier is responsible for segmenting the sensor measurement time series, by fitting various models. The second tier takes care of estimating the optimal sampling, selecting the measurements that contributes the most to the model accuracy. We provide near-optimal heuristics for both tiers and evaluate their performances using environmental sensor data. In the third approach we propose an online algorithm that identifies repeated patterns in time series and produces a compressed symbolic stream. The first symbolic transformation is based on clustering with the raw sensor data. Whereas the next iterations encode repetitive sequences of symbols into new symbols. We define also a metric to evaluate the symbolization methods with regard to their capacity at preserving the systems' states. We also show that the output of symbols can be used directly for various data mining tasks, such as classification or forecasting, without impacting much the accuracy, but greatly reducing the complexity and running time. In addition, we also present an example of application, assessing the user's exposure to air pollutants, which demonstrates the many opportunities to enhance contextual information when fusing sensor data from different sources. On one side we gather fine grained air quality information from mobile sensor deployments and aggregate them with an interpolation model. And, on the other side, we continuously capture the user's context, including location, activity and surrounding air quality. We also present the various models used for fusing all these information in order to produce the exposure estimation

Consistency Algorithms and Protocols for Distributed Interactive Applications

The Internet has a major impact not only on how people retrieve information but also on how they communicate. Distributed interactive applications support the communication and collaboration of people through the sharing and manipulation of rich multimedia content via the Internet. Aside from shared text editors, meeting support systems, and distributed virtual environments, shared whiteboards are a prominent example of distributed interactive applications. They allow the presentation and joint editing of documents in video conferencing scenarios. The design of such a shared whiteboard application, the multimedia lecture board (mlb), is a main contribution of this thesis. Like many other distributed interactive applications, the mlb has a replicated architecture where each user runs an instance of the application. This has the distinct advantage that the application can be deployed in a lightweight fashion, without relying on a supporting server infrastructure. But at the same time, this peer-to-peer architecture raises a number of challenging problems: First, application data needs to be distributed among all instances. For this purpose, we present the network protocol RTP/I for the standardized communication of distributed interactive applications, and a novel application-level multicast protocol that realizes efficient group communication while taking application-level knowledge into account. Second, consistency control mechanisms are required to keep the replicated application data synchronized. We present the consistency control algorithms “local lag”, “Timewarp”, and “state request”, show how they can be combined, and discuss how to provide visual feedback so that the session members are able to handle conflicting actions. Finally, late-joining participants need to be initialized with the current application state before they are able to participate in a collaborative session. We propose a novel late-join algorithm, which is both flexible and scalable. All algorithms and protocols presented in this dissertation solve the aforementioned problems in a generic way. We demonstrate how they can be employed for the mlb as well as for other distributed interactive applications

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp