3172403
On overlay schemes to support point-in-range queries for scalable grid resource discovery
A resource directory is a critical component of a grid architecture. P2P computing paradigm could address some of the scalability issues that make distributed resource discovery services challenging. Unfortunately, most existing distributed hash table (DHT) based P2P overlays have difficulty in treating attribute range queries that are common in resource discovery lookups. This paper proposes a general framework for range-based resource discovery. In particular, the proposed framework maps tree-structured logical data (i.e., range indexing) onto a DHT-based physical node space (i.e., resource brokers). In this paper, we consider three mapping schemes from the logical space onto the physical space. Each mapping scheme uses a different replication mechanism to reduce range search time and to achieve load balance. We analytically and experimentally compare the performance characteristics (query/update costs and workload distributions) of these schemes and discuss their applicability under different resource discovery service scenarios.
2673173
State Aware Data Dissemination over Structured Overlays
We describe the problem of data dissemination in stream-oriented applications where the required filter is a function of the current state. We call such functions dynamic filters. A state aware data dissemination network (SA-DDN) is proposed to support dynamic filters. Two approaches single-level filtering (SF) and multilevel filter decomposition (MFD) are proposed to facilitate the data dissemination. We show how MFD improves performance over SF. We then describe a realization of SA-DDN on top of an improved bi-directional Chord overlay with a built-in multicast mechanism. An application of stock price monitoring is implemented based on SA-DDN and real life stock quotes are collected to demonstrate the feasibility of our system. Extensive simulations are performed to compare the performance of both approaches and provide insight into the advantages of MFD
206977606
Priority Based Overlay Multicast for Distributed Interactive Applications
Distributed Interactive Applications (DIAs) is different with other network-based applications, since the data should be delivered to the receiver node according to its priority. Among the existing overlay multicast protocols the "priority-based directed minimum spanning tree" (PST) is designed for DIAs. But in PST the available bandwidth (avail-bw) is used inefficiently and the system becomes unstable when its scale increases. This paper proposed a novel overlay multicast protocol named Priority Based Overlay Multicast (POM), which uses the entities’ priority, links’ delay and node’s avail-bw to build multicast tree. By using POM the nodes with high priority receive the data in short delay, while the nodes with low priority tolerate a long delay in order to balance the available bandwidth usage among the nodes. The simulation results show that POM uses the avail-bw efficiently and keeps the system stable when its scale increases. Keywords: DIAs; Priority; Available bandwidth.
17553402
Efficient Parallel Algorithms for Euclidean Distance Transform
The Euclidean Distance Transform (EDT) converts a binary image into one where each pixel has a value equal to its distance to the nearest foreground pixel. Two parallel algorithms for EDT transform on linear array with reconfigurable pipeline bus system (LARPBS) are presented. For an image with n×n pixels, the first algorithm can complete EDT transform in ) log log log log log log ( n n n O time using n processors. The second algorithm can compute the EDT in O( log n loglog n) time using n n log log 2 processors.
9617419
Hybrid critiquing-based recommender systems
We propose a novel critiquing-based recommender interface, the hybrid critiquing interface that integrates the user self-motivated critiquing facility to compensate for the limitations of system-proposed critiques. The results from our user study show that the integration of such self-motivated critiquing support enables users to achieve a higher level of decision accuracy while consuming less cognitive effort. In addition, users expressed higher subjective opinions of the hybrid critiquing interface than the interface simply providing system-proposed critiques, and they would more likely return to it for future use.
24161285
Effects of Local-Lag Mechanism on Task Performance in a Desktop CVE System
Consistency maintenance is a kernel problem in Collaborative Virtual Environment (CVE) research. The approaches used in Networked Virtual Environments (e.g., DR algorithm) could not be used in CVEs, for they could not prevent short-term inconsistency. Therefore, local-lag mechanism has been proposed to eliminate short-term inconsistency in CVEs. Choosing a proper lag value is a key problem in local-lag mechanism. This paper studied the effects of lag value (0ms–900ms) on task performance in a desktop CVE system. Experimental results indicate that the effect of lag value on task performance is not linear. The effect could be separated into four segments by three dividing points: 150ms, 300ms and 600ms. Lag has no effect on task performance while ranging from 0ms to 150ms. From 150ms to 300ms, lag slightly affects task performance. Lag deteriorates task performance seriously while ranging from 300ms to 600ms. When lag is longer than 600ms, the task cannot be accomplished sometimes.
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.