|
For Full-Text PDF, please login, if you are a member of IEICE,
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
|
Dynamic Load-Distribution Method of uTupleSpace Data-Sharing Mechanism for Ubiquitous Data
Yutaka ARAKAWA Keiichiro KASHIWAGI Takayuki NAKAMURA Motonori NAKAMURA
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E97-D
No.4
pp.644-653 Publication Date: 2014/04/01 Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.644 Type of Manuscript: Special Section PAPER (Special Section on Data Engineering and Information Management) Category: Keyword: tuple space, load distribution, DHT,
Full Text: FreePDF
Summary:
The number of networked devices of sensors and actuators continues to increase. We are developing a data-sharing mechanism called uTupleSpace as middleware for storing and retrieving ubiquitous data that are input or output by such devices. uTupleSpace enables flexible retrieval of sensor data and flexible control of actuator devices, and it simplifies the development of various applications. Though uTupleSpace requires scalability against increasing amounts of ubiquitous data, traditional load-distribution methods using a distributed hash table (DHT) are unsuitable for our case because of the ununiformity of the data. Data are nonuniformly generated at some particular times, in some particular positions, and by some particular devices, and their hash values focus on some particular values. This feature makes it difficult for the traditional methods to sufficiently distribute the load by using the hash values. Therefore, we propose a new load-distribution method using a DHT called the dynamic-help method. The proposed method enables one or more peers to handle loads related to the same hash value redundantly. This makes it possible to handle the large load related to one hash value by distributing the load among peers. Moreover, the proposed method reduces the load caused by dynamic load-redistribution. Evaluation experiments showed that the proposed method achieved sufficient load-distribution even when the load was concentrated on one hash value with low overhead. We also confirmed that the proposed method enabled uTupleSpace to accommodate the increasing load with simple operational rules stably and with economic efficiency.
|
|