Fusion Tree Research Articles

D2F: A Routing Protocol for Distributed Data Fusion in Wireless Sensor Networks

Data fusion can be distributed into network and executed on network nodes, to reduce data from redundant sensor nodes, to fuse the information from complementary sensor nodes and to get the complete view from cooperative nodes. Consequently only the inference of interest is sent to end user. This distributed data fusion can significantly reduce the data transmission cost and there is no need for a powerful centralized node to process the collected information. However, to achieve the advantages of distributed data fusion and better utilization of network resources, each fusion function needs to be performed at particular network node for minimizing energy cost of data fusion application, both data transmission cost and computation cost. In this paper, distributed data fusion routing (D2F) is proposed, which is designed for deploying distributed data fusion application in wireless sensor networks. D2F can find the optimal route path and fusion placements for a given data fusion tree, which obtains the optimal energy consumption for in-network data fusion. D2F can also handle different link failures and maintain the optimality of energy cost of data fusion by adapting to the dynamic change of network.

Distributed Information Fusion Structure Based on Data Fusion Tree

A distributed information fusion structure based on data fusion tree is built to realize precise localization and efficient navigation for the mobile robot. The multi-class, multi-level information from robot and environment is fused using different algorithms in different levels, and make the robot have a deeper understanding to the whole environment. Experiments demonstrate that the new model proposed in the paper can improve the positioning precision of robot greatly, and the search efficiency and success rate are also better than traditional mode.

Data Fusion with Desired Reliability in Wireless Sensor Networks

Energy-efficient and reliable transmission of sensory information is a key problem in wireless sensor networks. To save more energy, in-network processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes in the data fusion tree. Traditional schemes aim at providing reliable transmission to individual data packets from source node to the sink, but seldom offer the desired reliability to a data fusion tree. In this paper, we explore the problem of Minimum Energy Reliable Information Gathering (MERIG) when performing data fusion. By adaptively using redundant transmission on fusion routes without acknowledgments, packets with more information are delivered with higher reliability. For different data fusion topologies, such as star, chain, and tree, we provide optimal solutions to compute the number of transmissions for each node. We also propose practical, distributed approximation algorithms for chain and tree topologies. Analytical proofs and simulation results show that energy-efficient information reliability can be guaranteed in an unreliable wireless environment with the help of our proposed schemes.

A high speed networked signal processing platform for multi-element radio telescopes

A new architecture is presented for a Networked Signal Processing System (NSPS) suitable for handling the real-time signal processing of multi-element radio telescopes. In this system, a multi-element radio telescope is viewed as an application of a multi-sensor, data fusion problem which can be decomposed into a general set of computing and network components for which a practical and scalable architecture is enabled by current technology. The need for such a system arose in the context of an ongoing program for reconfiguring the Ooty Radio Telescope (ORT) as a programmable 264-element array, which will enable several new observing capabilities for large scale surveys on this mature telescope. For this application, it is necessary to manage, route and combine large volumes of data whose real-time collation requires large I/O bandwidths to be sustained. Since these are general requirements of many multi-sensor fusion applications, we first describe the basic architecture of the NSPS in terms of a Fusion Tree before elaborating on its application for the ORT. The paper addresses issues relating to high speed distributed data acquisition, Field Programmable Gate Array (FPGA) based peer-to-peer networks supporting significant on-the fly processing while routing, and providing a last mile interface to a typical commodity network like Gigabit Ethernet. The system is fundamentally a pair of two co-operative networks, among which one is part of a commodity high performance computer cluster and the other is based on Commercial-Off The-Shelf (COTS) technology with support from software/firmware components in the public domain.

Data fusion in the Internet of Things

The application prospect in the market with huge thing networking are buzzing the third wave of information technology, its one of the core technology on two wireless sensor networks with energy, storage capacity, computing power, communications bandwidth resource constraints of the salient characteristics of data fusion, implementation is the inevitable choice. This paper briefly describes the Internet of things in the characteristics of data acquisition and data fusion of things in the meaning and role of data fusion described things to be addressed key issues and requirements. Briefly describes the data fusion tree formation and fusion of the principles of TGA

Multi-Attribute Data Fusion for Energy Equilibrium Routing in Wireless Sensor Networks

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

Examining Computational Geometry, Van Emde Boas Trees, and Hashing from the Perspective of the Fusion Tree

This article illustrates several examples of computer science problems whose performance can be improved with the use of either the fusion trees [Fredman and Willard, J. Comput. System Sci., 47 (1993), pp. 424--436; Fredman and Willard, J. Comput. System Sci., 48 (1994), pp. 533--551] or one of several recent improvements to this data structure. It is likely that many other data structures can also have their performance improved with fusion trees. The examples here are only illustrative.

Trans-dichotomous algorithms for minimum spanning trees and shortest paths

Two algorithms are presented: a linear time algorithm for the minimum spanning tree problem and an O ( m + n log n /log log n ) implementation of Dijkstra's shortest-path algorithm for a graph with n vertices and m edges. The second algorithm surpasses information theoretic limitations applicable to comparison-based algorithms. Both algorithms utilize new data structures that extend the fusion tree method.

Surpassing the information theoretic bound with fusion trees

This paper introduces a new sublogarithmic data structure for searching, the fusion tree. These trees lead to improved worst-case algorithms for sorting and searching, surpassing the limitations of the information theoretic lower bound.