An efficient lock protocol for home-based lazy release consistency
Home-based lazy release consistency (HLRC) shows poor performance on lock based applications because of two reasons: a whole page is fetched on a page fault while actual modification is much smaller; and a home is at the fixed location while the access pattern is migratory. We present an efficient lock protocol for HLRC. In this protocol, the pages that are expected to be used by the acquirer are selectively updated using diffs. The diff accumulation problem is minimized by limiting the size of diffs to be sent for each page. Our protocol reduces the number of page faults inside critical sections because pages can be updated by applying locally stored diffs. This reduction yields the reduction of average lock waiting time and the reduction of message amount. The experiment with five applications shows that our protocol archives 2%-40% speedup against base HLRC for four applications.

title: Design and implementation of a multi-threaded TMN agent system
abstract: A telecommunications management network adopts the OSI manager-agent model in which an agent system plays a more important role than a manager system. Because the existing agent systems sequentially perform a CMIS operation on selected managed objects, it cannot guarantee quick response time when many managed objects are selected. We propose a multi-threaded process structure for the agent system which performs CMIS operations concurrently on managed objects. We implemented our agent system using OSIMIS-4.O TMN platform in Solaris. We measured response time to a CMIS operation to evaluate the performance of our system. Experimental results show that the performance of our system is not so good when network resources reside within the agent system, but very good when network resources reside outside the agent system.

title: Out-of-Core Remeshing of Large Polygonal Meshes
abstract: We propose an out-of-core method for creating semi-regular surface representations from large input surface meshes. Our approach is based on a streaming implementation of the MAPS remesher of Lee et al. Our remeshing procedure consists of two stages. First, a simplification process is used to obtain the base domain. During simplification, we maintain the mapping information between the input and the simplified meshes. The second stage of remeshing uses the mapping information to produce samples of the output semi-regular mesh. The out-of-core operation of our method is enabled by the synchronous streaming of a simplified mesh and the mapping information stored at the original vertices. The synchronicity of two streaming buffers is maintained using a specially designed write strategy for each buffer. Experimental results demonstrate the remeshing performance of the proposed method, as well as other applications that use the created mapping between the simplified and the original surface representations

title: FERMA: An Efficient Geocasting Protocol for Wireless Sensor Networks with Multiple Target Regions
abstract: Some sensor applications are interested in collecting data from multiple regions. For supporting such applications with multiple target regions, most conventional protocols are based on either a network flooding or multiple unicastig to cover those more than one target region. Either one will result in a lot of redundant packets to transmit by energy scared sensor nodes. To alleviate this problem, we propose a novel geocasting scheme which can make a suitable shared path among multiple target regions. We utilize the theorem of “Fermat Point,” in order to find an optimal junction point branching into each region. By using this shared path, an interest dissemination can be performed very efficiently. Our simulation study shows that the proposed scheme FERMA reduces a lot of network traffic and achieves significant energy saving as the number of target regions increase.

title: Video Data Indexing by 2D C-Trees
abstract: Video data contains a large amount of spatial and temporal information. The changes of video frames are quite useful for motion analysis and cannot be provided by other media easily. Chang et al. had proposed an effective 2D string approach for spatial indexing of image data. In this paper, we extend this iconic approach and apply it to video data indexing. We propose 2D C-trees to represent the spatial content within individual frames. A video sequence can then be represented and indexed by a temporal set or an ordering set of 2D C-trees. The similarity retrieval of video matching problem becomes the problem of video sequence matching by computing the similarity, or the minimum cost of matched frames. We present three schemes, full-sequence matching, segment matching and subsequence matching, for video information retrieval. The matching schemes can be modified and extended to approximate sequence matching by computing the partial distance for providing a comprehensive retrieval of video data. A prototype video information system is also developed to validate the effectiveness of video data indexing by 2D C-trees.

title: Context Awarable Self-configuration System for Distributed Resource Management
abstract: Today's system administrator is forced to perform individual configuration and maintenance tasks (i.e. installation, reconfiguration, update) on numerous systems, in various formats. These tasks are time-consuming and labor intensive. Several research projects have attempted to resolve these issues with the development of an integrated, centralized management system. However, many tasks are still left to the system administrator for manual handling. A customized configuration system that reflects comprehensive context has not yet been fully realized. This paper proposes a context aware self-configuration system by employing multi-agents to collectively gather contextual information based on the system resources and user's system usage patterns. This proposed system, then analyzes the collected information and performs automatic configuration as and when required. This system will allow not only enable automation of the previously manual tasks, but also allow, in effect, a more customized configuration.

title: Neural mesh ensembles
abstract: This work proposes the use of neural network ensembles to boost the performance of a neural network based surface reconstruction algorithm. Ensemble is a very popular and powerful statistical technique based on the idea of averaging several outputs of a probabilistic algorithm. In the context of surface reconstruction, two main problems arise. The first is finding an efficient way to average meshes with different connectivity, and the second is tuning the parameters for surface reconstruction to maximize the performance of the ensemble. We solve the first problem by voxelizing all the meshes on the same regular grid and taking majority vote on each voxel. We tune the parameters experimentally, borrowing ideas from weak learning methods.