16327059
Globally synchronized dead-reckoning with local lag for continuous distributed multiplayer games
Dead-Reckoning (DR) is an effective method to maintain consistency for Continuous Distributed Multiplayer Games (CDMG). Since DR can filter most unnecessary state updates and improve the scalability of a system, it is widely used in commercial CDMG. However, DR cannot maintain high consistency, and this constrains its application in highly interactive games. With the help of global synchronization, DR can achieve higher consistency, but it still cannot eliminate before inconsistency. In this paper, a method named Globally Synchronized DR with Local Lag (GS-DR-LL), which combines local lag and Globally Synchronized DR (GS-DR), is presented. Performance evaluation shows that GS-DR-LL can effectively decrease before inconsistency, and the effects increase with the lag.
17619661
Your way your missions: from location-based to route-based pervasive gaming
In this paper, we describe the design and implementation of a route-based pervasive game named Your Way Your Missions (YWYM). Since the game obtains the planned routes of players and returns missions in the routes, players can play the game in a casual way, without changing their routes to respond to picked up missions. A self-reporting method is proposed to obtain the planned routes of players, and a corresponding route defining tool is developed upon Google Maps. Two approaches to realize route-based mission adaptation with spatial databases are presented.
11794423
An adaptive consistency maintenance approach for replicated continuous applications
Consistency maintenance is a key problem to replicated continuous applications and dead reckoning (DR) algorithm is widely used in this area. In order to eliminate short-term inconsistency caused by DR algorithm, local-lag approach was proposed. For the purpose of simplicity, fixed lag value is used by local-lag approach and the performance of the approach is greatly deteriorated. In this paper, an adaptive consistency maintenance approach, which is based on local-lag approach, is proposed. The new approach can adjust lag value according to the estimated typical network latency. In order to ensure the criterion of consistency correctness, a lag value adjustment method is also proposed. Through two experiments, the performance of the new approach is evaluated and the results indicate that it is feasible and can greatly improve the performance of the application.
14850996
Effects of network characteristics on task performance in a desktop CVE system
The influences of network characteristics on the task performance in a desktop collaborative virtual environment (CVE) system were studied. In the experiment, two participants worked together to accomplish a collaborative task and a network emulator was utilized to simulate real network characteristics. The task used in the experiment was designed to be highly interactive and had rigid requirements on network characteristics (e.g. latency and packet loss). The objective performance and subjective assessment were recorded and analyzed quantitatively as a function of network latency and packet loss rate. The experiment results show that network latency has no distinct effect on task performance when network latency is less than 200 ms and lightly affect task performance when network latency is between 200 and 600 ms; packet loss has no effect on task performance when there are 40 state update messages received per second and lightly affect task performance when there are between 15 and 40 state update messages received per second.
44509988
A threshold criterion, auto-detection and its use in MST-based clustering
Clustering is to group data points into homogenous clusters so that data points within the same cluster are more similar than data points belonging to different clusters. There are many effective clustering algorithms for discovering arbitrary shaped clusters, but one common problem of many algorithms is the difficulty for users to decide appropriate parameters for these algorithms. To reduce the dependence of clustering performance on parameters, this paper proposes a threshold criterion for the single linkage cluster analysis and incorporates it into the Minimum Spanning Tree (MST) based clustering method. Since the threshold can be automatically decided according to the underlying data distributions, arbitrary shaped clusters can be discovered with little human intervention. The experimental results on spatial data are very encouraging.
60542101
A novel ant clustering algorithm based on cellular automata
Based on the principle of cellular automata in artificial life, an artificial ant sleeping model (ASM) and an ant algorithm for cluster analysis (A4C) are presented. Inspired by the behaviors of gregarious ant colonies, we use the ant agent to represent a data object. In ASM, each ant has two states: a sleeping state and an active state. The ant's state is controlled by a function of the ant's fitness to the environment it locates and a probability for the ants becoming active. The state of an ant is determined only by its local information. By moving dynamically, the ants form different subgroups adaptively, and hence the data objects they represent are clustered. Experimental results show that the A4C algorithm on ASM is significantly better than other clustering methods in terms of both speed and quality. It is adaptive, robust and efficient, achieving high autonomy, simplicity and efficiency.
2039675
On Detection of Bounded Global Predicates
Distributed programs often follow some bounded global predicates, for example, the total number of certain tokens is always the same or bounded in a range. In order to detect bounded global predicates, we can first derive the minimum and maximum global snapshots and then check if the minimum and maximum are out of the range. Recently, Chase and Garg proposed an efficient method to derive the minimum global snapshot by reducing this problem to a maximum network flow problem. A restriction of this method is that all message values (e.g., the token number in messages) must be zero and all process state values (e.g., the token number in processes) must be non-negative. In this paper, we propose an elegant technique, called normalization. By using this technique, we can remove the above restriction and also derive the minimum and maximum global snapshots at the same time.
32197027
A hardware accelerator for video segmentation using programmable morphology PE array
Video segmentation is a key operation for MPEG-4 and MPEG-7. It is a computationally intensive task and cannot be afforded by general microprocessors. In this paper, we propose a hardware accelerator for video segmentation. Since most of the core operations of video segmentation algorithms can be mapped to morphological operations, the core of this accelerator is a programmable morphology PE array. With the programmable ability of each PE and the interconnection between them, this accelerator can achieve both high throughput and high flexibility. Simulation shows the proposed hardware accelerator can speed up the most important video segmentation algorithms 20 times to achieve realtime performance and has high programmability with a little hardware cost overhead.
2454682
Mining Association Rules from Structural Deltas of Historical XML Documents
Previous work on XML association rule mining focuses on mining from the data existing in XML documents at a certain time point. However, due to the dynamic nature of online information, an XML document typically evolves over time. Knowledge obtained from mining the evolvement of an XML document would be useful in a wide range of applications, such as XML indexing, XML clustering. In this paper, we propose to mine a novel type of association rules from a sequence of changes to XML structure, which we call XML Structural Delta Association Rule (XSD-AR). We formulate the problem of XSD-AR mining by considering both the frequency and the degree of changes to XML structure. An algorithm, which is derived from the FP-growth, and its optimizing strategy are developed for the problem. Preliminary experiment results show that our algorithm is efficient and scalable at discovering a complete set of XSD-ARs.