Redundant Links Research Articles

STRUCTURAL ANALYSIS AND RATIONAL DESIGN OF MECHANISMS OF CROSS-ROLL TUBE STRAIGHTENING MACHINES

Purpose. The article is aimed to perform a structural analysis of the main and auxiliary mechanisms of tube straightening machines, to identify structural and local redundant links in the mechanism schemes, and to offer recommendations on their rational design. Methodology. The solution is realized by means of the theory of mechanisms and machines using structural analysis of the mechanisms of tube straightening machines based on the universal structural theory of O.G. Ozol. Findings. The extended principle of the machine’s mechanism formation, which provides inclusion to the mechanism not only невільних solid bodies, but also the deformed bodies, allows us to consider the structure of machines for pressure processing of metals, taking into account the plastically deformed workpiece. Therefore, such machines include in their composition a deformed workpiece as an integral part of the machine mechanism, whose deformation and addition of certain geometric parameters to it is the reason the tube straightener was created for. Defects in the machine structure are determined by the local and structural redundant links included in the kinematic chains of the mechanisms, which transform the mechanism into a statically undetermined system. Movement of the mechanism with defects in the structure is possible in the presence of gaps or due to deformation of the links. The main mechanism of the tube straightening machine is a mechanism of variable structure, therefore, an analysis for its two states is carried out: before the tube is caught by the rollers and during its straightening. For calculation of the number of mobilities of the outer «roll – tube» pair, it was taken into consideration that most of the coordinates are overlaid with non-retentive links, which contain a fractional number of constraints. Fifteen redundant links were identified in the main mechanism and their amount in the auxiliary mechanisms of the tube straightening machine was established. Originality. The structural analysis of tube straightening machines with the search for redundant links was never performed. A structural analysis of the mechanisms of cross roll tube straightening machine was performed for the first time, taking into account the presence of external fractional links that are superimposed in the «roll-tube» pairs. Practical value. The practical recommendations for eliminating the harmful redundant links that were found in the structural analysis of the main and auxiliary mechanisms of the tube straightening machine were developed.

A compact 3-DOF shoulder mechanism constructed with scissors linkages for exoskeleton applications

A novel 3-degrees-of-freedom (DOF) spherical mechanism, singularity-free in the anatomical shoulder joint workspace, is described. The use of curved scissors linkages interconnected by revolute joints, whose axes share the same remote centre-of-motion, achieves the most compact design of its kind. The kinematics of this scissors shoulder mechanism (SSM) are derived and presented. A design equation restricting the linkage's curvature by the central/pitch angle of the fully stretched scissors is obtained. Motion-captured data are used for validating the reachable 3-d workspace while a test-subject is wearing a null protraction/retraction constrained exoskeleton. The embodiment of the SSM as a shoulder joint for an exoskeleton device does not compromise the upper extremity function within the anatomical reachable 3-d workspace. It operates within a volume of 0.236 m3, corresponding to 68.09% and 94.97% of the volumes of the full active (0.350 m3) and null protraction/retraction constrained active (0.223 m3) reachable workspaces of the test-subject, respectively. Thus, the SSM represents a simplification of a spatial spherical mechanism design and overcomes the need for the use of redundant links and optimization routines.

Control-Theoretical and Topological Analysis of Covariance Intersection Based Distributed Kalman Filter

Covariance intersection (CI) extends Kalman filter (KF) in distributed estimation, since it can fuse Gaussian estimates in the absence of the estimates' correlations. However, even with the preliminary success on the integration of CI and KF, existing discussion limited in global behavior is unable to directly deal with a system with a mixture of unbounded-covariance and bounded-covariance agents. In other words, until this letter there has been no explicit investigation on the analytic relationship between effective observability in each agent and system topology, to the best of our knowledge. To formalize these problems, we establish CI-based KF with explicit CI topology, on top of the conventional KF with observation exchanges. Consequently, the effect of CI on KF can be characterized by the impact of individual CI links on each agents. In particular, we systematically show that CI links can diminish the effective unobservable space, which relaxes the boundedness criterion. In addition, as a conservative fusion scheme, there may exist CI links that provide no improvement on estimation performance but generate additional uncertainty. A method is proposed to identify and then to suppress such redundant CI links for enhanced estimation performance. Finally, the pros and cons of CI on distributed estimation algorithms are comprehensively characterized and substantiated by a numerical example.

Modeling and Applications of a Family of Five-Degree-of-Freedom Parallel Mechanisms With Kinematic and Actuation Redundancy

This paper introduces a family of statically balanced five-degree-of-freedom (5DOF) parallel mechanisms (PMs) with kinematic and actuation redundancy. Moving platforms of this family of PMs can provide 4DOF Schönflies motion. Three applications are considered in this work. The first and second applications use kinematic redundancy to avoid parallel singularities and perform an auxiliary grasping task in sequence. The third application incorporates actuation redundancy into a kinematically redundant manipulator to increase the load-carrying capacity. Screw theory was used to derive the Jacobian of the 5DOF PM with kinematic and actuation redundancy. Parallel singularities can be completely alleviated by controlling the orientation of the redundant link, thereby obtaining a large rotational workspace, and actuation redundancy increases the load-carrying capacity. Using a commercially available multibody dynamic simulator, an example of trajectory was performed to illustrate the large rotational workspace of the first and second applications and compare the Euclidean norm of the vector of actuation torque of nonredundant and redundant PMs. Three prototypes were also developed to demonstrate the output motion and static balancing property.

A Modified Bayesian Network Model to Predict Reorder Level of Printed Circuit Board

Identifying the printed circuit board (PCB) orders with high reorder frequency for batch production can facilitate production capacity balance and reduce cost. In this paper, the repeated orders identification problem is transformed to a reorder level prediction problem. A prediction model based on a modified Bayesian network (BN) with Monte Carlo simulations is presented to identify related variables and evaluate their effects on the reorder level. From the historically accumulated data, different characteristic variables are extracted and specified for the model. Normalization and principal component analysis (PCA) are employed to reduce differences and the redundancy of the datasets, respectively. Entropy minimization based binning is presented to discretize model variables and, therefore, reduce input type and capture better prediction performance. Subsequently, conditional mutual information and link strength percentage are combined for the establishment of BN structure to avoid the defect of tree augmented naïve BN that easily misses strong links between nodes and generates redundant weak links. Monte Carlo simulation is conducted to weaken the influence of uncertainty factors. The model’s performance is compared to three advanced approaches by using the data from a PCB manufacturer and results demonstrate that the proposed method has high prediction accuracy.

Improving Effectiveness of Seamless Redundancy in Real Industrial Wi-Fi Networks

Reliability and determinism of Wi-Fi can be tangibly improved by means of seamless redundancy, to the point of making this technology suitable for industrial environments. As pointed out in recent papers, the most benefits can be achieved when no phenomena can simultaneously affect transmissions on all channels of a redundant link. In this paper, several aspects are analyzed which, if not properly counteracted, may worsen seamless redundancy effectiveness. Effects they cause on communication have been experimentally evaluated in real testbeds, which rely on commercial Wi-Fi devices. Then, practical guidelines are provided, which aim at preventing joint interference through a careful system design. Results show that measured communication quality can be made as good as expected in theory.

Identification and classification of best spreader in the domain of interest over the social networks

The emerging social networks promptly create greater opportunities for fast-developing viral marketing. The online social networks (OSNs) play an essential role in the information diffusion among the social users within the community. The social network being large-scale, it leads to the inconvenience in identifying the influential spreaders in a specific domain, as every social user receives the information from different sources through multiple connections over the network. Although, analyzing the complex social network is indispensable to determine the influence spreaders with the knowledge of understanding the dynamics of information evolution. The existing solutions of the influential measurement techniques lack in neglecting the redundant links and quantifying the temporal information among the social users while estimating the diffusion importance of a social user. Moreover, these techniques fail in analyzing the structural relationships in the domain. To overcome these obstacles, this paper presents a de-duplicated k-shell influence estimation (DKIE) model in the social network by classifying the influential spreaders based on the domain of interest using k-shell decomposition and N-gram similarity. The DKIE model incorporates two major phases such as generic influential spreader identification and domain-specific influential spreader identification. The first phase measures the diffusion importance of each active social user based on the structural relationships of the social network using k-shell decomposition method. It separates the core-like groups and true core and identifies the best spreaders regardless of the redundant links. The second phase exploits the topic of the discussion of the best spreaders and consequently, measures the topic-wise influence to categorize the domain-specific best spreaders using N-gram similarity measurement. The experimental results illustrate the effectiveness of DKIE approach.

Energy-Efficient Ant Colony-Based k-Hop Clustering and Transmission Range Assignment Protocol for Connectivity Construction in Dense Wireless Sensor Networks

Connectivity construction is the main phase of a communication-oriented topology control process. It consists of improving the current network physical topology while preserving important properties such as connectivity and symmetry. In this paper, we address the problem of combining two of the techniques commonly used for this purpose in networks composed of a large number of energy constrained wireless sensor-nodes namely, clustering and power control. We propose an ant colony-based asynchronous and localized protocol that helps to significantly reduce energy losses by simultaneously eliminating redundant and poor quality links, always keeping the Cluster Head-to-member distance up to k-hops (k≥1) and minimizing signalization. Simulation results show that our protocol outperforms some state-of-the-art solutions in terms of Quality of the Topology (QoT) and network lifetime prolongation.

Comparative Analysis of Control Plane Security of SDN and Conventional Networks

Software defined networking implements the network control plane in an external entity, rather than in each individual device as in conventional networks. This architectural difference implies a different design for control functions necessary for essential network properties, e.g., loop prevention and link redundancy. We explore how such differences redefine the security weaknesses in the SDN control plane and provide a framework for comparative analysis which focuses on essential network properties required by typical production networks. This enables analysis of how these properties are delivered by the control planes of SDN and conventional networks, and to compare security threats and mitigations. Despite the architectural difference, we find similar, but not identical, exposures in control plane security if both network paradigms provide the same network properties and are analyzed under the same threat model. However, defenses vary; SDN cannot depend on edge based filtering to protect its control plane, while this is arguably the primary defense in conventional networks. Our concrete security analysis suggests that a distributed SDN architecture that supports fault tolerance and consistency checks is important for SDN control plane security. Our analysis methodology may be of independent interest for future security analysis of SDN and conventional networks.

A Novel Algorithm for Loop Prevention and Fast Recovery (LPFR) in Ethernet Rings.

Traditional Ethernet networks use the rapid spanning tree protocol (RSTP) or the enhanced RSTP (eRSTP) to ensure a loop-free topology and provide redundant links as backup paths in case an active link has failed. However, when a failure occurs, the RSTP/eRSTP require a significant amount of reconfiguration time in order to find an alternative path. The RSTP/eRSTP are also limited by the number of nodes in a ring network, and their performance degrade when the number of nodes increases; the media redundancy protocol (MRP), which is used in industrial networks, has the same issues. In this paper, we introduce a new algorithm, called loop prevention and fast recovery (LPFR), which can be applied to Ethernet ring networks to provide a loop-free topology. When a failure occurs, LPFR requires only a very short amount of time to switch to an alternative path. LPFR needs a maximum of 6.1 ms for recovery time, versus ＜ 100 ms for the RSTP/eRSTP in a ring size of 20 nodes and ＜ 200 ms for the MRP in a ring size of 50 nodes. The LPFR offers a reduction in recovery time of up to 93.9 % compared to the RSTP/eRSTP, and 96.9 % compared to the MRP. However, in most cases, LPFR requires zero recovery time for such switching. In addition, in most situations, no frames are lost when a node switches to an alternative path. Unlike the RSTP/eRSTP and MRP, LPFR provides a better way for distributing the sent traffic among network links, which in turn improves network performance, reduces the probability of bottleneck occurrences, and reduces the frame latency between the source and the destination. This is because LPFR always sends the frame through the fastest path. The LPFR algorithm can run on a wide variety of ring sizes, which is not the case for the RSTP/eRSTP and MRP. Finally, the LPFR will use the Ethernet standard frame layout without any modifications or changes. This will allow all of the standard Ethernet devices and networks to be directly integrated into the LPFR networks without any proxies.

Distributed Energy Consumption Management in Green Content-Centric Networks via Dual Decomposition

Due to the in-network caching capability, content-centric networking (CCN) has emerged as one of the most promising architectures for the diffusion of contents over the Internet. Most existing works on CCN focus on network resource utilization, and the energy efficiency aspect is largely ignored. In this paper, we study the tradeoff between energy consumption and quality of service in CCN by switching off the redundant network content routers and links. We formulate the energy consumption management problem as a mixed integer linear programming (MILP) model and propose a centralized solution via spanning tree heuristic. Then, a fully distributed energy optimization algorithm is proposed via dual decomposition (DD) to solve the MILP problem for green CCN. The DD method transforms the centralized energy consumption control problem into the router status, link status, and link flow subproblems. Through turning off the redundant network devices, the total energy consumption of the network can be minimized. Simulation results reveal that the proposed scheme exhibits a fast convergence speed and achieves superior energy efficiency compared with other widely used schemes in CCN.

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks.

Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods.

An efficient lossy link localization approach for wireless sensor networks

Network fault management is crucial for a wireless sensor network (WSN) to maintain a normal running state because faults (e.g., link failures) often occur. The existing lossy link localization (LLL) approach usually infers the most probable failed link set first, and then gives the fault hypothesis set. However, the inferred failed link set contains many possible failures that do not actually occur. That quantity of redundant information in the inferred set can pose a high computational burden on fault hy-pothesis inference, and consequently decreases the evaluation accuracy and increases the failure localization time. To address the issue, we propose the conditional information entropy based redundancy elimination (CIERE), a redundant lossy link elimination approach, which can eliminate most redundant information while reserving the important information. Specifically, we develop a probabilistically correlated failure model that can accurately reflect the correlation between link failures and model the nonde-terministic fault propagation. Through several rounds of mathematical derivations, the LLL problem is transformed to a set-covering problem. A heuristic algorithm is proposed to deduce the failure hypothesis set. We compare the performance of the proposed approach with those of existing LLL methods in simulation and on a real WSN, and validate the efficiency and effec-tiveness of the proposed approach.

Experimental Evaluation of Seamless Redundancy Applied to Industrial Wi-Fi Networks

Seamless redundancy can be profitably exploited to improve predictability of wireless networks in general and, in particular, IEEE 802.11. According to this approach, packets are transmitted by senders on two (or more) channels at the same time and duplicate copies are discarded by receivers. As long as the behavior of physical channels is uncorrelated, communication quality improves noticeably, in terms of both transmission latencies and percentage of dropped frames. In this paper, communication over redundant links has been analyzed by means of a thorough experimental campaign, based on measurements carried out on real devices. Results confirm that, under typical operating conditions, the assumption of independence among channels in properly designed systems is verified reasonably well. Indeed, in our experiments, measured link quality indices did not differ more than 10% from what we expected from theory. This grants for redundant solutions tangible advantages over conventional Wi-Fi networks.

Simulation method of spatial laser field for arbitrary distance optical transmission with carbon nanotube

In this paper, an arbitrary distance optical transmission simulation method for free-space optical communication system is presented. Based on this method, direct point-to-point performance tests between two optical terminals can be realized in the laboratory, and the test results are equivalent to those on-orbit. A theoretical analysis of this method is presented in this paper. Verification experiments showed that there is a good linearity between the incoming power density and output photocurrent of the carbon nanotube (CNT); the relative power difference between the CNT and the charge-coupled device (CCD) camera is 4.75%, which can be ignored compared with the link redundancy.

Reducing method of the redundant links in the kinematic pairs of batten lever mechanism of weaving looms

Reducing method of the redundant links in the kinematic pairs of batten lever mechanism of weaving looms

Energy Efficient Greedy Algorithm for Wireless Mesh Networks

Aim: Wireless Mesh Networks (WMN’s) are gaining recognition among users. But WMN resources are not always utilized up to their full capacity. Redundant links and nodes can be turned in low power state for energy savings. WMN’s build on IEEE 802.11s, supports link based power saving mode (PSM). But IEEE 802.11s standard does not specify switching among PSM. This research work provides a greedy approximation algorithm to allow redundant nodes and links in low power state to achieve minimum energy consumption. Methodology: Proposed algorithm is based on traffic consolidation over few nodes, subject to available link slots due to wireless interference. This will permit redundant nodes in deep sleep mode. Results: Analysis reveals that choosing power saving mode carefully of peer links can achieve great energy efficiency. Conclusion: Results signifies that energy saving comes with cost of delay. So traffic consolidation based approaches are more suitable for delay tolerant networks.

A ranking approach based on k-shell decomposition method by filtering out redundant link in weighted networks

The k-shell decomposition method of identifying the influential nodes which accelerate spread or hinder propagation, plays an important role in analyzing the spreading performance of complex network, but it is too coarse in terms of ranking granularity. Recent study shows that the accuracy of the k-shell decomposition method in determining node coreness is significantly affected by the mutually densely connected local structures. Existing approach tries to filter out the confusion of the classical k-shell decomposition method, caused by such densely local structures, through redefining a diffusion importance value which is the number of out-leaving links at/from the nodes connected by a link. This value is used to quantify the potential influence of a link in spreading process. However, the existing approach is not suitable for ubiquitously weighted networks. In this paper, we develop a new ranking approach (filter-core) to identify the node spreading influence in weighted network. Here, we concern that the redundant links, although they are less important in the spreading process, form mutually densely connected local structures, which lead to the classical k-shell decomposition method unable to accurately determine the coreness of node in network. By redefining a new diffusion importance value for each link based on the weights of its connected nodes and the weight distribution, we filter out the redundant links which have a relatively low diffusion importance in the spreading process. After filtering out all redundant links and applying the classical k-shell decomposition method to the residual network, we obtain a new coreness for each node, which is more accurate to indicate spreading influence of node in the original network. Our approach is applied to three real weighted networks, i.e., the international trading network, the neural network of C. elegans, and the coauthorship network of scientists. And the susceptible-infected-recovered epidemic spreading model is used to make a comparison of performance between our approach and other three k-shell methods (including the weighted degree decomposition method, the s-core decomposition method, and the weighted k-shell method) in terms of four quantitative indices, i.e., the imprecision function, the standard deviation of infected fraction of max coreness node, the spreading time, and the number of recovered nodes at the end of spreading process. The experimental results show that our proposed approach is more accurate to identify the influential spreaders than the weighted degree decomposition method, the s-core decomposition method, and the weighted k-shell method, and also helps to more accurately decompose the network core structure for an optimal analysis in weighted network.

Retrieval, crawling and fusion of entity-centric data on the web

While the Web of (entity-centric) data has seen tremendous growth over the past years, take-up and re-use is still limited. Data vary heavily with respect to their scale, quality, coverage or dynamics, what poses challenges for tasks such as entity retrieval or search. This chapter provides an overview of approaches to deal with the increasing heterogeneity of Web data. On the one hand, recommendation, linking, profiling and retrieval can provide efficient means to enable discovery and search of entity-centric data, specifically when dealing with traditional knowledge graphs and linked data. On the other hand, embedded markup such as Microdata and RDFa has emerged a novel, Web-scale source of entity-centric knowledge. While markup has seen increasing adoption over the last few years, driven by initiatives such as schema.org, it constitutes an increasingly important source of entity-centric data on the Web, being in the same order of magnitude as the Web itself with regards to dynamics and scale. To this end, markup data lends itself as a data source for aiding tasks such as knowledge base augmentation, where data fusion techniques are required to address the inherent characteristics of markup data, such as its redundancy, heterogeneity and lack of links. Future directions are concerned with the exploitation of the complementary nature of markup data and traditional knowledge graphs.

Consensus of Teleoperating Cyber-Physical System via Centralized and Decentralized Controllers

Teleoperating cyber-physical system (TCPS) has been considered as a promising technology to stretch artificial intelligences to remote locations. Many applications of TCPS demand operator and slaves to keep state consensus on the shared information. However, the cyber- and physical- constrained characteristics on TCPS make it difficult to realize such a consensus. This paper investigates the consensus problem for single-master-multi-slave TCPS with time-varying delay and actuator saturation. According to the communication structures of slaves, centralized and decentralized controllers are, respectively, designed to drive the consensus of master and slave robots. To simplify the information fusion in decentralized controller design, we use min-weighted rigid graph-based topology optimization algorithm to reduce the communication redundancy in slave site. Under time-varying delay and actuator saturation constraints, the sufficient stability conditions are presented to show that the centralized and decentralized controllers can stabilize the single-master-multi-slave TCPS. Moreover, the stability conditions are rearranged into a form of linear matrix inequalities, and then, the required initial stability conditions for master and slaves are developed. Finally, simulations and experiments are demonstrated to show the validity of the method. It is shown that the consensus controllers can guarantee the asymptotic stability of single-master-multi-slave TCPS, while the topology optimization can reduce the redundancy of communication links.