Tree Construction Algorithm Research Articles

A SEMANTIC INDEX STRUCTURE FOR MULTIMEDIA RETRIEVAL

To be effective multimedia retrieval mechanisms, index methods must provide not only efficient access but also meaningful retrieval by addressing challenges in multimedia retrieval. This article presents the AH+-tree, a height-balanced, tree-based index structure that efficiently incorporates high-level affinity information to support Content-Based Image Retrieval (CBIR) through similarity queries. The incorporation of affinity information allows the AH+-tree to address the problems of semantic gap and user perception subjectivity inherent to multimedia retrieval. Based on the Affinity-Hybrid Tree (AH-Tree), the AH+-tree utilizes affinity information in a novel way to eliminate the I/O overhead of the AH-Tree while maintaining the same functionality and quality of results. We explain the structure of the AH+-tree and implement and analyze algorithms for tree construction and similarity queries (range and nearest neighbor). Experimental results demonstrate the superior I/O efficiency of the AH+-tree over that of the AH-Tree and the M-tree without a detrimental impact on real-time costs of the retrieval process.

Model-based robust fault detection and isolation of an industrial gas turbine prototype using soft computing techniques

This study proposes a model-based robust fault detection and isolation (RFDI) method with hybrid structure. Robust detection and isolation of the realistic faults of an industrial gas turbine in steady-state conditions is mainly considered. For residual generation, a bank of time-delay multilayer perceptron (MLP) models is used, and in fault detection step, a passive approach based on model error modelling is employed to achieve threshold adaptation. To do so, local linear neuro-fuzzy (LLNF) modelling is utilised for constructing error-model to generate uncertainty interval upon the system output in order to make decision whether a fault occurred or not. This model is trained using local linear model tree (LOLIMOT) which is a progressive tree-construction algorithm. Simple thresholding is also used along with adaptive thresholding in fault detection phase for comparative purposes. Besides, another MLP neural network is utilised to isolate the faults. In order to show the effectiveness of proposed RFDI method, it was tested on a single-shaft industrial gas turbine prototype model and has been evaluated based on the gas turbine data. A brief comparative study with the related works done on this gas turbine benchmark is also provided to show the pros and cons of the presented RFDI method.

On-line suffix tree construction with reduced branching

Classical suffix tree construction algorithms by McCreight and Ukkonen spend most of the time looking up the right branch to follow from the current node. However, not all these slow branching operations are necessary. A significant portion of them is used for implicit suffix link simulation and can be avoided by replacing the traditional top-down descent with bottom-up climbing.We describe the bottom-up approach and analyze its costs and benefits. An experimental evaluation on two standard data corpora shows that bottom-up climbing removes forty to sixty six percent of branching operations and consequently saves twenty one to thirty two percent of construction time. However, a theoretical analysis of the worst-case behavior reveals that the time complexity of the bottom-up approach is superlinear. This is remedied by a combination of both approaches that removes nearly as many branching operations as the bottom-up climb, but still runs in linear time like the top-down descent.

Human Action Recognition algorithm based on Minimum Spanning Tree of CPA Models

Human pose recognition algorithm for monocular video was proposed to model human part parameters using video features combination with 3D motion capture data. Firstly Constant Part Appearance (CPA) Models and three-dimensional motion data projection constraint graph structure was defined. To simplify the reasoning process, a constraint graph of the spanning tree construction algorithm and the balancing algorithm were proposed. Combination with the proposed function mechanism, spanning tree of constraint graph and Metropolis-Hastings method, human motion under monocular video can be tracking and recognition, and inferring the 3D motion parameters. By using data-driven (Markov chain Monte Carlo MCMC) and constrain map, human motion limb recognition algorithm is proposed, and the method can be applied to data-driven online human behavior recognition. Experimental results show that the proposed method can recognize human motion action automatically and accurately in monocular video.

Parallel SAH Based KD Tree Construction Algorithm

The best method to construct a high quality KD tree is by using Surface Area Heuristic[1][4] (SAH). However, the computation involved in SAH is expensive. Wald and Havran[2] introduced a sequential algorithm of O(NlogN) complexity, which reached the lower bound of constructing a binary tree. In this paper, we will introduce a parallel SAH KD tree construction algorithm based on the O(NlogN) sequential algorithm. We proposed data structure for parallel constructing process which can minimize the communication among working threads, and a load balance strategy for evenly distributing work load. Our algorithm can achieve 4x speed up on 8-core CPUs architecture.

A Decision Tree Classification Model for University Admission System

Data mining is the science and techniques used to analyze data to discover and extract previously unknown patterns. It is also considered a main part of the process of knowledge discovery in databases (KDD). In this paper, we introduce a supervised learning technique of building a decision tree for King Abdulaziz University (KAU) admission system. The main objective is to build an efficient classification model with high recall under moderate precision to improve the efficiency and effectiveness of the admission process. We used ID3 algorithm for decision tree construction and the final model is evaluated using the common evaluation methods. This model provides an analytical view of the university admission system.

Supervised Hierarchical Clustering in Fuzzy Model Identification

This paper presents a new, supervised, hierarchical clustering algorithm (SUHICLUST) for fuzzy model identification. The presented algorithm solves the problem of global model accuracy, together with the interpretability of local models as valid linearizations of the modeled nonlinear system. The algorithm combines the advantages of supervised, hierarchical algorithms, which are based on heuristic tree-construction algorithms, together with the advantages of fuzzy product space clustering. The high flexibility of the validity functions that is obtained by fuzzy clustering combined with supervised learning results in an efficient partitioning algorithm, which is independent of initialization and results in a parsimonious fuzzy model. Furthermore, the usability of SUHICLUST is very undemanding, because it delivers, in contrast with many other methods, reproducible results. In order to get reasonable results, the user only has to set either a threshold for the maximum number of local models or a value for the maximum allowed global model error as a termination criterion. For fine-tuning, the interpolation smoothness controls the degree of regularization. The performance is illustrated on both analytical examples and benchmark problems from the literature.

Randomized tree construction algorithm to explore energy landscapes

In this work, a new method for exploring conformational energy landscapes is described. The method, called transition-rapidly exploring random tree (T-RRT), combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased toward yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved due to a self-tuning mechanism. The method is able to efficiently find both energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and the alanine dipeptide.

A novel minimum delay maximum flow multicast algorithm to construct a multicast tree in wireless mesh networks

The construction of multicast tree within given constraints, such as delay and capacity, is becoming a major problem in many wireless networks, especially wireless mesh networks (WMN). Due to the limited capacity of the wireless node, a multicast call may be dropped if there is no multicast tree formed within the given constraints. In this paper, we propose a new multicast tree construction algorithm which has maximum traffic flow and minimum delay under capacity constraints. The problem of multicast is formulated as a Linear Programming (LP) problem with associated constraints. A cost function (CF) is defined to choose the less loaded route among the available ones. A Minimum Delay Maximum Flow Multicast (MDMF) algorithm is proposed to solve this problem using CF and associated constraints. The performance of the proposed algorithm and CF is evaluated and compared with well-known algorithms with respect to packet delivery fraction, latency, and network throughput. The results obtained show that the proposed algorithm has a lesser number of transmissions for a given CF. Moreover, the proposed algorithm has high throughput, packet delivery fraction and less latency compared to other well-known algorithms in this category.

Efficient group communications in location aware mobile ad-hoc networks

The highly dynamic and uncertain character of mobile ad-hoc networks poses significant challenges for group management. Node mobility often changes the multicast tree, and therefore, frequent updates from group members are required to refresh the multicast tree at the source node. This paper presents Courier, a group communications algorithm that uses the location and velocity of roaming nodes to provide bandwidth efficient multicast between a source and its destinations (i.e., group members) in location aware mobile environments. Toward that end, Courier offers (1) a bandwidth efficient method for location updates from group members, (2) a mobility prediction model for predicting the movement of mobile group members, and (3) an overlay multicast data distribution tree (OMDDT) construction algorithm that is guided by the mobility prediction model. Comparisons of Courier to related multicast algorithms indicate an increase in data transmission success and a decrease in overall bandwidth consumption.

Peer-to-Peer Streaming Capacity

Peer-to-peer (P2P) systems provide a scalable way to stream content to multiple receivers over the Internet. The maximum rate achievable by all receivers is the capacity of a P2P streaming session. We provide a taxonomy of sixteen problem formulations, depending on whether there is a single P2P session or there are multiple concurrent sessions, whether the given topology is a full mesh graph or an arbitrary graph, whether the number of peers a node can have is bounded or not, and whether there are nonreceiver relay nodes or not. In each formulation, computing P2P streaming capacity requires the computation of an optimal set of multicast trees, with an exponential complexity, except in three simplest formulations that have been recently solved with polynomial time algorithms. These solutions, however, do not extend to the other more general formulations. In this paper, we develop a family of constructive, polynomial-time algorithms that can compute P2P streaming capacity and the associated multicast trees, arbitrarily accurately for seven formulations, to a factor of 4-approximation for two formulations, and to a factor of log of the number of receivers for two formulations. The optimization problem is reformulated in each case so as to convert the combinatorial problem into a linear program with an exponential number of variables. The linear program is then solved using a primal-dual approach. The algorithms combine an outer loop of primal-dual update with an inner loop of smallest price tree construction, driven by the update of dual variables in the outer loop. We show that when the construction of smallest price tree can be carried out arbitrarily accurately in polynomial time, so can the computation of P2P streaming capacity. We also develop several efficient algorithms for smallest price tree construction. Using the developed algorithms, we investigate the impact of several factors on P2P streaming capacity using topologies derived from statistics of uplink capacities of Internet hosts.

Compatibility between Three Well-Known Broadcast Tree Construction Algorithms and Various Metrics

Broadcast routing is a critical component in the routing design. While there are plenty of routing metrics and broadcast routing schemes in current literature, it remains an unsolved problem as to which metrics are compatible with a specific broadcast routing scheme. In particular, in the wireless broadcast routing context where transmission has an inherent broadcast property, there is a potential danger of incompatible combination of broadcast routing algorithms and metrics. This paper shows that different broadcast routing algorithms have different requirements on the properties of broadcast routing metrics. The metric properties for broadcast routing algorithms in both undirected network topologies and directed network topologies are developed and proved. They are successfully used to verify the compatibility between broadcast routing metrics and broadcast routing algorithms.

A Cluster-Based Routing Tree Construction Algorithm for Wireless Sensor Networks

In the architecture of wireless sensor network, routing technology at the network layer is essential. Since the clustering routing leads in good performance on data aggregation, energy minimization and so on, it has become the focus of the study routing. In this paper, a cluster-based routing tree construction algorithm for Wireless Sensor Networks is proposed. The detail of how to select the intermediate nodes to build the routing gathering tree is also described. The experiments show that the algorithm is effective to extend the network lifetime.

피어의 안정성과 지연을 동시에 고려한 P2P 오버레이 멀티캐스트 트리 구성 알고리즘

본 논문은 인터넷상에서 안정적인 멀티미디어 서비스를 제공하기 위한 P2P (Peer-to-Peer) 오버레이 멀티캐스트 트리 구성 알고리즘을 제안한다. 제안하는 알고리즘은 멀티캐스트 트리를 구성 할 때 링크의 지연뿐만 아니라 피어의 안정성 (Peer Stability)까지 고려한다. 실제로 피어는 매우 동적이고 불안정한 행동을 하기 때문에 안정적인 서비스를 제공하기 위해서 피어의 안정성은 필수적으로 고려해야한다. 그리고 제안하는 알고리즘에서는 멀티캐스트 트리의 상태에 따라서 링크의 지연과 피어의 안정성 사이의 가중치를 적응적으로 조절한다. 기본적으로 낮은 계산 복잡도로 근사해를 구하기 위해서 유전자 알고리즘 (Genetic Algorithm)을 이용한다. 마지막으로 실험 결과에서는 제안하는 알고리즘의 성능을 보인다. This paper presents a P2P (Peer-to-Peer) overlay multicast tree construction algorithm to support stable multimedia service over the Internet. While constructing a multicast tree, it takes into account not only the link delay, but also peer stability. Since peers actually show dynamic and unstable behavior over P2P-based network, it is essential to consider peer stability. Furthermore, the weighting factor between link delay and peer stability is adaptively controlled according to the characteristics of the multicast tree. Basically, Genetic algorithm is employed to obtain a near optimal solution with low computational complexity. Finally, simulation results are provided to show the performance of the proposed algorithm.

플러딩 라우팅 프로토콜과 양방향 LTS를 결합한 센서 노드의 시간 동기화 기법

일반적으로 센서 네트워크에서는 라우팅 트리를 구축한 후에 시간 동기화 작업을 따로 진행하였다. 그 때문에 패킷교환의 횟수가 늘어나고 전력의 소모를 유발한다. 본 논문에서는 라우팅 트리 구축과정에서 교환하는 정방향과 역방향의 패킷에 LTS(Lightweight Time Synchronization) 알고리즘 연산에 필요한 정보를 추가하여 플러딩 라우팅 트리 구축 알고리즘과 시간 동기화 과정을 결합한 알고리즘을 제안한다. 또한, 일정한 라운드 시간을 사용하여 클럭 휨으로 인한 시간 오류를 보정하였다. 제안하는 알고리즘이 TSRA(Time Synchronization Routing Algorithm) 방식보다 센서 노드들 간의 시간을 더욱 정교하게 동기화한다는 것을 NS2 시뮬레이터를 통해서 증명하였다. In wireless sensor networks Time synchronization used to be performed after routing tree is constructed. It results in increasing the number of packets and energy consumption. In this paper, we propose a time synchronization algorithm combined with flooding routing tree construction algorithm, which applies LTS (Lightweight Time Synchronization) information packed into the forwarding and backward routing packets. Furthermore, the proposed algorithm compensates the time error due to clock drift using the round time with fixed period. We prove that the proposed algorithm could synchronize the time of among sensor nodes more accurately compared to TSRA (Time Synchronization Routing Algorithm) using NS2 simulation tool.

A Depth-optimal Low-complexity Distributed Wireless Multicast Algorithm

This paper presents a wireless multicast tree construction algorithm, SWIM (Source-initiated WIreless Multicast). SWIM constructs a tree on which each multicast destination has the minimum possible depth (number of hops from the nearest source). It is proved that SWIM is fully distributed, with a worst case complexity upper-bounded by O(N3), and an empirically found average complexity of only O(N2). SWIM forms one shared tree from source(s) to the multicast destinations; yet, as a by-product, it creates a multicast mesh structure by maintaining alternative branches at every tree node, thus providing robustness to link failures. This makes it suitable for both ad hoc networks and access networks with multiple gateways. In terms of minimizing the number of forwarding nodes, SWIM is optimal for unicast and competitive with the state of the art for multicast, outperforming the best known distributed approaches from the literature except for the multicast ad hoc on demand distance vector (MAODV) algorithm. However, simulations of the MAODV algorithm alongside SWIM on a large set of network instances show that the depth minimality of SWIM leads to lower average delay per multicast destination. It is also shown that the delay performance of SWIM is virtually unaffected by the presence of low mobility in the network.

THE TRANSITIVE CLOSURE AND RELATED ALGORITHMS OF DIGRAPH ON THE RECONFIGURABLE ARCHITECTURE

The reconfigurable architecture is a parallel computation model that consists of many processor elements (PEs) and a reconfigurable bus system. There are many variant proposed reconfigurable architectures, for example, reconfigurable mesh (R-Mesh), directional reconfigurable mesh (DR-Mesh), processor arrays with reconfigurable bus systems (PARBS), complete directional processor arrays with reconfigurable bus systems (CD-PARBS), reconfigurable multiple bus machine (RMBM), directional reconfigurable multiple bus machine (directional RMBM), and etc. In this paper, a transitive closure (TC) algorithm of digraph is proposed on the models without the directional capability (non-directional). Some related digraph problems, such as strongly connected digraph, strongly connected component (SCC), cyclic checking, and tree construction, can also be resolved by modifying our transitive closure algorithm. All the proposed algorithms are designed on a three-dimensional (3-D) n×n×n non-directional reconfigurable mesh, n is the number of vertices in a digraph D, and can resolve the respective problems in O(log d(D)) time, d(D) is the diameter of the digraph D. The cyclic checking problem can be further reduced to O(log c(D)) time, c(D) is the minimum distance of cycles in the digraph D. There exist two different approaches: the matrix multiplication approach on the non-directional models for algebraic path problems (APP) and s-t connectivity approach on the directional models. In this paper, we will use the tree construction algorithm to prove those two approaches are insufficient to resolve all digraph problems and demonstrate why our approach is so important and innovative for digraph problems on the reconfigurable models.

단일 플러딩 라우팅 알고리즘을 활용한 센서 네트워크의 시간 동기화 기법

Usually time synchronization is performed after routing tree is constructed. This thesis proposes a time synchronization algorithm combined with single-flooding routing tree construction algorithm in a single path. TSRA (Time Synchronization Routing Algorithm) uses routing packets to construct a routing tree. Two types of time information are added to the routing packet: one is the packet receiving time, and the other is the packet sending time. Time offset and transmission time-delay between parent node and child node could be retrieved from the added time information using LTS (Lightweight Time Synchronization) algorithm. Then parent node sends the time offset and transmission time to children nodes and children nodes can synchronize their time to the parent node time along the routing tree. The performance of proposed algorithm is compared to the TPSN (Timing-sync Protocol for Sensor Networks) which is known to have high accuracy using NS2 simulation tool. The simulation result shows that the accuracy of time synchronization is comparable to TPSN, the synchronization time of all sensor nodes is faster than TPSN, and the energy consumption is less than TPSN.

A Dynamic Approach to Weighted Suffix Tree Construction Algorithm

time weighted suffix tree is consider as a one of the most important existing data structure used for analyzing molecular weighted sequence. Although a static partitioning based parallel algorithm existed for the construction of weighted suffix tree, but for very long weighted DNA sequences it takes significant amount of time. However, in our implementation of dynamic partition based parallel weighted suffix tree construction algorithm on cluster computing makes it possible to significantly accelerate the construction of weighted suffix tree.

Efficient routing and centralized scheduling algorithms for IEEE 802.16 Mesh Networks

An IEEE 802.16 wireless system can provide broadband wireless access to subscriber stations and operate in mesh mode. The communication between a subscriber station and a base station can pass through one or more intermediate subscriber stations. The IEEE 802.16 standard provides a centralized scheduling mechanism that supports contention-free and resource-guarantee transmission services in mesh mode. However, the corresponding algorithm to this schedule is quite primitive in the standard. In this paper, we propose a more efficient way to realize this schedule by maximizing channel utilization. Our designs are divided into two phases: routing and scheduling. First, a routing tree topology is constructed from a given mesh topology by our proposed tree construction algorithm. Secondly, we allocate channel resources to the edges in the routing tree by our proposed scheduling algorithm. To further support the quality-of-service schedule, we extend our designs by addressing some issues such as service class, admission control and fairness. Simulation results show the superiority of our proposed algorithms over others. Copyright © 2011 John Wiley & Sons, Ltd.