Hyung-Ju Cho

A safe exit algorithm for continuous nearest neighbor monitoring in road networks

Query processing in road networks has been studied extensively in recent years. However, the processing of moving queries in road networks has received little attention. In this paper, we introduce a new algorithm called the Safe Exit Algorithm SEA, which can efficiently compute the safe exit points of a moving nearest neighbor NN query on road networks. The safe region of a query is an area where the query result remains unchanged, provided that the query remains inside the safe region At each safe exit point, the safe region of a query and its non-safe region meet so that a set of safe exit points represents the border of the safe region. Before reaching a safe exit point, the client query object does not have to request the server to re-evaluate the query This significantly reduces the server processing costs and the communication costs between the server and moving clients. Extensive experimental results show that SEA outperforms a conventional algorithm by up to two orders of magnitude in terms of communication costs and computation costs

Continuous range k-nearest neighbor queries in vehicular ad hoc networks

A driver should constantly keep an eye on nearby vehicles in order to avoid collisions. Unfortunately, the driver often does not see nearby vehicles because of obstacles (e.g., other vehicles, trees, buildings, etc.). This paper introduces a novel type of query, called a continuous range k-nearest neighbor (CRNN) query, in vehicular ad hoc networks, and it presents a new approach to process such a query. Most existing solutions to continuous nearest neighbor (CNN) queries focus on static objects, such as gas stations and restaurants, while this work concentrates on CRNN queries over moving vehicles. This is a challenging problem due to the high mobility of the vehicles. The CRNN query has characteristics in common with continuous range (CR) and CNN queries. In terms of CNN queries, the proposed approach achieves the same goal as the existing solutions, which is to decide effectively on valid intervals during which the query result remains unchanged. The proposed scheme aims to minimize the use of wireless network bandwidth, the computational cost, and the local storage while preserving information on the continuous movement of vehicles within the broadcast range of a given vehicle. Extensive experimental results confirm the effectiveness and superiority of the proposed scheme in comparison with an existing method.

An efficient algorithm for computing safe exit points of moving range queries in directed road networks

In this paper, we investigate the problem of computing the safe exit points of moving range queries in directed road networks where each road segment has a particular orientation. The safe exit point of query object q indicates the point at which the safe region and non-safe region of q meet. A safe region indicates a region where the query result remains unchanged provided q remains inside this region. Unfortunately, the existing state-of-the-art algorithm focuses on computing the safe exit points of moving range queries in undirected road networks where every road segment is undirected. What is worse, far too little attention has been paid to moving range queries in dynamic road networks where the network distance changes depending on the traffic conditions. In this paper, we address these problems by proposing an efficient algorithm called CRUISE for computing the safe exit points of moving range queries in directed road networks. Our experimental results demonstrate that CRUISE significantly outperforms a conventional solution in terms of both computational and communication costs.

A distributed approach to continuous monitoring of constrained k-nearest neighbor queries in road networks

Given two positive parameters k and r, a constrained k-nearest neighbor CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

ALPS: an efficient algorithm for top-k spatial preference search in road networks

In this paper, we study the processing of top-k spatial preference queries in road networks. A top-k spatial preference query retrieves a ranked list of the k best data objects based on the scores (e.g., qualities) of feature objects in their spatial neighborhoods. Several solutions have been proposed for top-k spatial preference queries in Euclidean space. However, far too little attention has been paid to top-k spatial preference queries in road networks, where the distance between two points is defined by the length of the shortest path connecting them. A simple way to answer top-k spatial preference queries is to examine the scores of feature objects in the proximity of each data object before returning a ranked list of the k best data objects. However, this simple method causes intolerable computation delays, thus rendering online processing inapplicable. Therefore, in this paper, we address this problem by presenting a new algorithm, called ALPS, for top-k spatial preference searches in road networks. Our experimental results demonstrate the superiority and effectiveness of ALPS for a wide range of problem settings.

A group round robin based b-tree index storage scheme for flash memory devices

Flash memory is rapidly deployed as data storage for embedded and tablet PCs due to its shock resistance, fast access, and low power consumption. However, it has some intractable characteristics such as erase-before-write, asymmetric read/write/erase speed, and limited number of write/erase cycles. Due to these hardware limitations, the magnetic disk-based systems and applications could hardly make full use of the advantages of flash memory when directly adopting themselves on it. For example, the frequent changes of B-tree can degrade the storage performance of flash memory. Most of the recent studies on flash-aware index design focused mainly on the buffer management scheme whereby they can reduce the costly write operations to flash. However, in this paper, we present a novel B-tree storage scheme, a group round robin based B-tree index storage scheme, which applies a dynamic grouping and round robin techniques for erase-minimized storage of B-tree in flash memory under heavy-update workload. Experiment results show that the proposed scheme is efficient for frequently changed B-tree structure and improves the I/O performance by 2.14X at best, compared to the related work.

Lazy-split B+-tree: a novel B+-tree index scheme for flash-based database systems

Flash memory is rapidly being deployed as a data storage medium for embedded systems and tablet computers due to its shock resistance, fast access, and low power consumption, etc. However, it has some intractable characteristics, such as erase-before-write, asymmetric read/write/erase speed, and a limited number of write/erase cycles. Due to these hardware limitations, magnetic disk-based systems and applications can hardly make full use of the advantages of flash memory when adopting it directly for storage. For example, the frequent changes of B-tree can degrade the performance and negatively influence the lifespan of flash memory. Most state-of-the-art studies on flash-aware index design focused mainly on buffer and storage mechanisms whereby they can obtain efficient I/Os to flash memory. In this paper, we identify the problems inherent in the related studies, and then introduce the concepts of lazy-split, modify-two-node, and semi-clean, which make possible the construction of a novel index solution, the Lazy-Split B+-tree (LSB+-tree). In detail, by their introduction, the first concept of LSB+-tree can efficiently reduce the number of node splits, the second can reduce the number of node modifications, and the last can make a further improvement on buffer space utilization and flash writes reduction.

Three-state log-aware buffer management scheme for flash-based consumer electronics

Major digital consumer electronics such as smartphones and tablet PCs are equipped with flash memory because of its many advantages. However, its distinguishing characteristics, including erase-before-update, asymmetric read/write/erase cost and limited number of erase cycles, make it necessary to reconsider existing storage access designs in order to explore the hardware potential. For example, the buffer replacement scheme for flash-based systems should not only consider the cache hit ratio, but also the relatively heavy write and erase costs that are caused by flushing dirty pages. Most of the recent studies on buffer design focus on a clean-first LRU (Least Recently Used) strategy that evicts clean pages prior to dirty pages, in order to minimize the write access to flash. However, all of them failed to distinguish the cached pages that may have different effects on the flash device under various storage mangers. This paper proposes a three-state log-aware buffer management scheme, called TSLA, which considers not only the imbalance of read/write costs of flash memory but also the log block thrashing, associativity, and space utilization problems of log-based FTLs (flash translation layers). Experimental results show that the proposed solution is effective for reducing the garbage collection overhead under various FTLs, such as BAST, FAST and IPL.

A Group Based In-Block Logging for Flash Based Systems

This paper presents a novel B-tree storage scheme that reduces the number of time-consuming erase operations on flash memory-based systems. The scheme adopts group-based round robin fashion and in-block logging technique for efficiently maintaining the B- tree nodes in the heavy-update workloads. Experimental results show that the proposed scheme improves the I/O performance by up to 3X , compared to the related work.

Hybrid Associative Flash Translation Layer for the Performance Optimization of Chip-Level Parallel Flash Memory

Flash memory is used widely in the data storage market, particularly low-price MultiLevel Cell (MLC) flash memory, which has been adopted by large-scale storage systems despite its low performance. To overcome the poor performance of MLC flash memory, a system architecture has been designed to optimize chip-level parallelism. This design increases the size of the page unit and the block unit, thereby simultaneously executing operations on multiple chips. Unfortunately, its Flash Translation Layer (FTL) generates many unused sectors in each page, which leads to unnecessary write operations. Furthermore, it reuses an earlier log block scheme, although it generates many erase operations because of its low space utilization. To solve these problems, we propose a hybrid associative FTL (Hybrid-FTL) to enhance the performance of the chip-level parallel flash memory system. Hybrid-FTL reduces the number of write operations by utilizing all of the unused sectors. Furthermore, it reduces the overall number of erase operations by classifying data as hot, cold, or fragment data. Hybrid-FTL requires less mapping information in the DRAM and in the flash memory compared with previous FTL algorithms.