Ken Higuchi

History-Pattern Implementation for Large-Scale Dynamic Multidimensional Datasets and Its Evaluations

In this paper, we present a novel encoding/decoding method for dynamic multidimensional datasets and its implementation scheme. Our method encodes an n-dimensional tuple into a pair of scalar values even if n is sufficiently large. The method also encodes and decodes tuples using only shift and and/or register instructions. One of the most serious problems in multidimensional array based tuple encoding is that the size of an encoded result may often exceed the machine word size for large-scale tuple sets. This problem is efficiently resolved in our scheme. We confirmed the advantages of our scheme by analytical and experimental evaluations. The experimental evaluations were conducted to compare our constructed prototype system with other systems; (1) a system based on a similar encoding scheme called history-offset encoding, and (2) PostgreSQL RDBMS. In most cases, both the storage and retrieval costs of our system significantly outperformed those of the other systems.

Performance evaluation of routing algorithms for distributed key-value store based on order preserving linear hashing and Skip graph

In this paper, routing algorithms for the distributed key-value store based on order preserving linear hashing and Skip Graph are evaluated. In this system, data are divided by linear hashing and Skip Graph is used for overlay network. The routing table of this system is very uniform. Then, short detours can exist in the route of forwarding. In this paper, by comparison with an exact shortest route, it proved that the routing algorithm using detour is effective.

A Partitioning Scheme for Big Dynamic Trees

In this paper, we propose a scheme for partitioning dynamically growing big trees and its implementation. The scheme is based on the history-pattern encoding scheme for dynamic multidimensional datasets. Our scheme of handling big dynamic trees is relying on the history-pattern encoding, by which large scale datasets can be treated efficiently. In order to partition these dynamic trees efficiently, the encoding scheme will be improved and adapted to the partitioning. In our partitioning scheme of a tree T, the path from the T’s root node to the root node of a partitioned subtree, is treated as an index for selecting the subtree. The path is split into a shared path and the local path in the subtree and each path is encoded by using the history-pattern encoding. The partitioning scheme contributes to the reduction of the storage cost and the improvement of the retrieval cost. In this paper, after our tree encoding scheme designed for the partitioning is described, some problems caused in the encoding are addressed and their countermeasure is presented. Finally, an implemented prototype system is described and evaluated.

A scheme of dynamic attributes addition for tuple datasets

Nowadays in response to the expansion and diversification of business operations, demands for dynamic change of dataset definitions (schema evolution) such as new attribute additions is increasing. However, in order to handle the tuples after the attribute additions efficiently, reorganization of the dataset is necessitated and high operation cost would be accompanied. History-pattern encoding scheme for dynamic multidimensional datasets is based on the notion of multidimensional extendible array. It can provide fast retrieval capability of the datasets while suppressing storage cost minimally. In this paper, using the history-pattern encoding scheme, we will presents the schemes of dynamic attribute addition for dynamically extending tuple datasets, and evaluate them.

A Routing Algorithm for Distributed Key-Value Store Based on Order Preserving Linear Hashing and Skip Graph

In this paper, a routing algorithm for the distributed key-value store based on order preserving linear hashing and Skip Graph is proposed. In this system, data are divided by linear hashing and Skip Graph is used for overlay network. The routing table of this system is very uniform. Then, short detours can exist in the route of message forwarding. The proposed algorithm detects such detours and changes the route. By using the proposed algorithm, reduction of the number of hops are expected. From experimental results, it proved that the proposed algorithm is effective.

Design and Evaluation of a Storage Framework for Supply Chain Management

Radio-frequency identification (RFID) technology is widely available and actively used in business areas such as supply chain management. We propose a storage framework for a supply chain management system to administer the movement and time history of a product with an RFID tag. The storage structure is adapted to handle movement and time history data based on an encoding scheme for multidimensional datasets. Three types of encoded value compactly keep all the routing path and temporal information of a product from factory shipment, and the information can be quickly traced by using these encoded values. This paper describes our storage framework for supply chain management and evaluates the database constructed based on the encoding scheme.