Ye-In Chang

Neighbor-finding based on space-filling curves

Nearest-neighbor-finding is one of the most important spatial operations in the field of spatial data structures concerned with proximity. Because the goal of the space-filling curves is to preserve the spatial proximity, the nearest neighbor queries can be handled by these space-filling curves. When data are ordered by the Peano curve, we can directly compute the sequence numbers of the neighboring blocks next to the query block in eight directions in the 2D- space based on its bit shuffling property. But when data are ordered by the RBG curve or the Hilbert curve, neighbor-finding is complex. However, we observe that there is some relationship between the RBG curve and the Peano curve, as with the Hilbert curve. Therefore, in this paper, we first show the strategy based on the Peano curve for the nearest-neighbor query. Next, we present the rules for transformation between the Peano curve and the other two curves, including the RBG curve and the Hilbert curve, such that we can also efficiently find the nearest neighbor by the strategies based on these two curves. From our simulation, we show that the strategy based on the Hilbert curve requires the least total time (the CPU-time and the I/O time) to process the nearest-neighbor query among our three strategies, since it can provide the good clustering property.

A fault tolerant algorithm for distributed mutual exclusion

A fault-tolerant mutual exclusion algorithm for distributed systems is presented. The algorithm uses a distributed queue strategy and maintains alternative paths at each site to provide a high degree of fault tolerance. However, owing to these alternative paths, the algorithm must use reverse messages to avoid the occurrence of directed cycles, which may form when the direction of edges is reversed after the token passes through. If there is no alternative path, the total number of the messages exchanged is O (2*log N) in light traffic and two messages in heavy traffic; however, in this case the system cannot tolerate even a single communication link or site failure. If there are alternative paths between sites, the system can achieve a higher degree of fault tolerance at the expense of increased message traffic (owing to reverse messages). Thus, there is a tradeoff between efficiency and reliability, and a system can be designed to balance these two criteria properly. A recovery procedure for restoring a recovering site consistently into the system is also presented.<<ETX>>

A Simulation Study on Distributed Mutual Exclusion

In the problem of mutual exclusion, concurrent access to a shared resource using a structural program abstraction called acritical section(CS) must be synchronized such that at any time only one process can enter the CS. In a distributed system, due to the lack of both a shared memory and a global clock, and due to unpredictable message delay, the design of a distributed mutual exclusion algorithm that is free from deadlock and starvation is much more complex than that in a centralized system. Based on different assumptions about communication topologies and a widely varying amount of information maintained by each site about other sites, several distributed mutual exclusion algorithms have been proposed. In this paper, we suvrey and analyze several well-known distributed mutual exclusion algorithms according to their related characteristics. We also compare the performance of these algorithms by a simulation study. Finally, we present a comparative analysis of these algorithms.

A dynamic token-based distributed mutual exclusion algorithm

The authors present a dynamic token-based mutual exclusion algorithm for distributed systems. In the algorithm, a site invoking mutual exclusion sends token request messages to a set of sites possibly holding the token as opposed to all the sites as in the algorithm proposed by I. Suzuki and T. Kasami (1985). A request set is used to record the identifiers of such a set of sites in the system. The algorithm is dynamic because the request set is dynamically changed as the algorithm is executed. As the size of the request set is reduced, the number of the messages exchanged per critical section (CS) execution is reduced. Compared with Suzuki and Kasamis algorithm, the proposed algorithm can reduce the number of the messages exchanged by 40% when the traffic is light. Finally, the authors discuss relationship between the token-based and non-token-based mutual exclusion algorithms. This relationship motivated the authors to design such a dynamic token-based algorithm.<<ETX>>

All-nearest-neighbors finding based on the Hilbert curve

Research highlights? We develop the ANHC finding strategy for an all-nearest-neighbors (ANN) query. ? Our strategy uses orientations, orders, and quaternary numbers in the Hilbert curve. ? Our strategy computes the relative locations of the query and the neighboring point. ? Our ANHC strategy access all neighboring points directly based on the Hilbert curve. ? Our ANHC strategy outperforms the strategy based on R?-trees for an ANN query. An all-nearest-neighbors (ANN) query retrieves all nearest neighbors to all query objects. We may perform large number of one-nearest-neighbor queries to answer such an ANN query. Due to no total ordering of spatial proximity among spatial objects, the Hilbert curve approach has proposed to preserve the spatial locality. Chen and Chang have proposed a neighbor finding strategy (denoted as the CCSF strategy) based on the Hilbert curve to compute the absolute location of the neighboring blocks. However, it costs much time during the transformation between the Hilbert curve and the Peano curve. On the other hand, in the strategy based on R or R?-trees for an ANN query, large number of unnecessary distance comparisons have to be done due to the problem of overlaps within the R-tree, resulting in many redundant disk accesses. Therefore, in this paper, we first propose the one-nearest-neighbor finding strategy directly based on the Hilbert curve (denoted as the ONHC strategy) for a one-nearest-neighbor query. By relations among orientations, orders, and quaternary numbers, we compute the relative locations of the query block and the neighboring block in the Hilbert curve. Then, the nearest neighbor of one query point can be found directly from these neighboring blocks. Next, by using our ONHC strategy, we propose the all-nearest-neighbors finding strategy based on the Hilbert curve (denoted as the ANHC strategy) for an ANN query. Finally, from the simulation result, we show that our ONHC strategy needs less response time (the CPU-time and the I/O time) than the CCSF strategy for the one-nearest-neighbor query. We also show that our ANHC strategy needs less response time than the strategy based on R?-trees for an ANN query.

A skewed distributed indexing for skewed access patterns on the wireless broadcast

Data broadcast is an efficient way to disseminate information to a large number of mobile clients in the wireless environment. Adding an index data organization to the broadcast file can save client power consumption with little increase in client waiting time. The existing index technologies only consider equal access probabilities of data items. However, in real-life applications, some data items may be more popular than others; that is, access patterns of clients are skewed. In this paper, we propose a skewed distributed indexing, SDI, which considers the access probabilities of data items and the replication of index nodes. The proposed algorithm traverses an index tree to determine whether an index node should be replicated by considering the access probability of its child node. In our experimental results, we have shown that our proposed algorithm outperforms the variant-fanout index tree and the distributed indexing.

An efficient scheduling method for query-set-based broadcasting in mobile environments

Most of the previous researches assume that each mobile client needs only one data item. However, in many situations, a mobile client might need more than one data item. In this paper, we propose an efficient scheduling method for query-set-based broadcasting, which integrates with query expansion method (QEM) and the mining association rules technique. The mining association rules can globally find the data item sets (large itemsets) which are requested by clients frequently. From our simulation results, we show that, as compared to the local optimal approach in the previous methods, our improved-QEM can construct the schedule with the smaller TQD than QEM and modified-QEM, where TQD denotes total query distance and is proportional to the average access time.

A unique-ID-based matrix strategy for efficient iconic indexing of symbolic pictures

Abstract In this paper, we propose an efficient iconic indexing strategy called unique-ID-based matrix (UID matrix) for symbolic pictures, in which each spatial relationship between any two objects is assigned with a unique identifier (ID) and is recorded in a matrix. Basically, the proposed strategy can represent those complex relationships that are represented in 2D C-strings in a matrix, and an efficient range checking operation can be used to support pictorial query, spatial reasoning and similarity retrieval; therefore, they are efficient enough as compared to the previous approaches. From our simulation, we show that the proposed UID matrix strategy requires shorter time to convert the input data into the corresponding representation than the 2D C-string strategy, so is the case with query processing. Moreover, our proposed UID matrix strategy may require lesser storage cost than the 2D C-string strategy in some cases.

A complementary approach to data broadcasting in mobile information systems

Acharya et al. have proposed the use of a periodic dissemination architecture in the context of mobile systems, called Broadcast disks. This strategy can construct a memory hierarchy where the highest level contains a few items and broadcasts them with high frequency while subsequent levels contain more and more items and broadcast them with less and less frequency. In this way, one can establish a trade-off between access time for high-priority data and that of the low-priority items, where access time means the time elapsed from the moment a client submits a query to the receipt of data of his (her) interest on the broadcast channel. However, based on Acharya et al.s algorithm, some broadcast slots may be unused, which results in the waste of bandwidth and the increase of access time. Therefore, in this paper, we propose an efficient broadcast program, the complementary approach, in which no empty slot is wasted. The basic idea of the complementary approach is to move some pages which are located near the end of a broadcast cycle to those empty slots which occur before these pages. Therefore, finally, the total number of slots in a broadcast cycle is equal to the one computed from Acharya et al.s algorithm minus the number of empty slots. Obviously, our complementary approach generates a small number of slots in one broadcast cycle and shorter mean access time than Acharya et al.s algorithm.

A new storage and retrieval method to support editing operations in a multi-disk-based video server

Since the storage ordering is assumed the same as the retrieval ordering in all the previous storage placement strategies, there is a requirement of a large amount of file copying or merging operations when users insert/delete some data into/from the media data. The observation is also important for video applications because features, like video editing, require the support of random access on individual video frames. We propose a new strategy for the insert/delete operations on continuous media that are striped into multi-disks without reorganization of the whole data. From our performance analysis and simulation, the proposed algorithms for insertion/deletion may require only some additional movement cost.