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The Hierarchically Distributed Tree (HD Tree) is a novel distributed data structure built over a complete tree. The purpose of proposing this new data structure is to better support multi-dimensional range query in the distributed environment. HD Tree doubles the number of neighbors at the cost of doubling total links of a tree. The routing operation in HD Tree is supposed to be highly error-resilient...
The Hierarchically Distributed Tree (HD Tree) is a novel distributed data structure. The purpose of proposing this new data structure is for better maintaining data localities with exponentially expanding and extending rate, and at the same time adapting the hierarchical structure to the distributed environment. In HD Tree, the routing table size is determined by the system parameter k, the performance...
There are two basic concerns for supporting multi-dimensional range query in P2P overlay networks. The first is to preserve data locality in the process of data space partitioning, and the second is the maintenance of data locality among data items with an exponentially expanding rate and an exponentially extending rate. The first problem has been well addressed by using recursive decomposition schemes,...
Multi-casting and data distribution management (DDM) play a critical role in the design of future generations of large-scale distributed simulation systems, in which a large number of DDM messages are exchanged between the participating entities. Thus, communication overhead is one of the most challenging issues that needs to be studied and it must be investigated further whether each message should...
Microfluidic devices for glucose detection have been constructed and developed by integration of glucose oxidase covalently immobilised single-walled carbon nanotube arrays into a poly (dimethylsiloxane)-based microfluidic channel. This microfluidic device was tested for electrochemical glucose detection, and the results showed that the glucose can be detected with a linear response up to a concentration...
The goal of this paper is to provide an optimal solution for data distribution management (DDM) in large-scale distributed simulations. Until now, all existing DDM approaches have tried to make DDM more efficient in different ways; however, none has been able to optimize performance. The main reason for this inability is that these approaches manipulate the data generated in a simulation without evaluating...
This paper presents a novel adaptive dynamic grid-based data distribution management (DDM) scheme, which we refer to as ADGB. The main objective of our protocol is to optimize DDM time through matching probability (MP) and federates' performance. A distribution rate (DR) along with MP are used as part of the ADGB method to select, throughout the simulation, from different devised advertisement schemes,...
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