Tae-Sun Chung

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

Flash SSD vs HDD: High performance oriented modern embedded and multimedia storage systems

Flash memory is continuously been dominating on HDD for performance oriented modern applications by last more than two decades. Currently the high capacity MLC flash SSDs are becoming center of attraction for large size multimedia systems to support their increasing storage and throughput demands. The advantage of MLC flash over SLC flash is lower cost, higher capacity and increased throughput. However, MLC flash SSDs suffer for lesser data reliability, higher bit error ratio and reduced erasure cycles compare to SLC flash SSDs. In this paper, the performance is evaluated and compared of both types of NAND flash memories with HDD. Experimental results based on two modern real-time benchmarks are provided and discussed to give the better idea to users for suitable storage devices for their embedded and multimedia applications.

Data storage framework on flash memory based SSD RAID 0 for performance oriented applications

Flash memory is hugely been using for small handheld to large enterprise applications due to its attractive characteristics like fast access speed, shock resistance and others. Performance oriented applications like multimedia, robotics, OLTP and further require fault tolerant more reliable high throughput. Therefore, flash memory with its remarkable features is an outstanding choice to meet their business needs. In this paper, we propose a firmware/driver based data storage framework to implement RAID 0 on flash memory platform to support the increasing requirements of data reliability and system performance. In our knowledge, this is the first research presented in concerned area. The real time experimental results prove the effectiveness of our technique.

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.

Moving range k nearest neighbor queries with quality guarantee over uncertain moving objects

To avoid traffic accidents, drivers must constantly be aware of nearby vehicles. Unfortunately, nearby vehicles often go unnoticed because of various obstacles such as other vehicles, buildings, or poor weather. In this paper, we study Moving range k-nearest neighbor (MRkNN) queries as a tool for continuously monitoring nearby moving objects. A simple approach to processing MRkNN queries is to have each object periodically broadcast information regarding its movements (i.e., location and velocity at a particular time) to other objects. However, this simple technique cannot be used to process MRkNN queries owing to the limited network bandwidth in mobile peer-to-peer environments. Therefore, we address this bandwidth limitation by proposing a probabilistic algorithm, called MINT, for MovIng range k-NN queries with qualiTy guarantee over uncertain moving objects. MINT provides users with approximate answers with a quality guarantee, rather than exact answers, with near optimal communication costs. Using a series of simulations, we demonstrate the efficiency and efficacy of?MINT in evaluating MRkNN queries with a quality guarantee.

VAQAR: Flash memory based long term in-network vital data sustainability and availability for data centric wireless sensor network applications

Sensor nodes collect data in normal and event-driven situations for monitoring environment and performing in-network computation. Such critical event-driven data deletes later carelessly due to context-less storage mechanisms. This causes data failure for network applications and loses support for reliable in-network computation. Therefore, for wireless sensor networks supporting sense, merge, store and send schemes, an efficient data organization technique is highly required. In this paper, we propose an advanced log structured external NAND flash memory based data management method called Varying Aggressive data Quality Access Reference (VAQAR) for data centric wireless sensor network applications. We focus particularly on critical data to provide long term sustainability and rapid availability for effective in-network computations. Experimental results show VAQAR an ideal memory management system software scheme proposing high performance for vital in-network data organization for wireless sensor network applications.

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.

A Safe-Region Approach to a Moving k-RNN Queries in a Directed Road Network

In road networks, k-range nearest neighbor (k-RNN) queries locate the k-closest neighbors for every point on the road segments, within a given query region defined by the user, based on the network distance. This is an important task because the users location information may be inaccurate; furthermore, users may be unwilling to reveal their exact location for privacy reasons. Therefore, under this type of specific situation, the server returns candidate objects for every point on the road segments and the client evaluates and chooses exact k nearest objects from the candidate objects. Evaluating the query results at each timestamp to keep the freshness of the query answer, while the query object is moving, will create significant computation burden for the client. We therefore propose an efficient approach called a safe-region-based approach (SRA) for computing a safe segment region and the safe exit points of a moving nearest neighbor (NN) query in a road network. SRA avoids evaluation of candidate answers returned by the location-based server since it will have high computation cost in the query side. Additionally, we applied SRA for a directed road network, where each road network has a particular orientation and the network distances are not symmetric. Our experimental results demonstrate that SRA significantly outperforms a conventional solution in terms of both computational and communication costs.