Redundant Lines Research Articles

ENSURING THE THREAD CAPACITY OF ELECTRICAL TRANSMISSION LINES UNDER THE CONDITIONS OF THEIR RESERVATION

A method of increasing the power transmission capacity in the post-emergency mode is considered, when a redundant line is connected to one of the working power transmission lines (LEP) with a voltage of 10 kV using the point of automatic switching on of the reserve (AVR). The effectiveness of such redundancy in most cases turns out to be low due to the limited capacity of trunk sections of mutually reserved lines with smaller cross-sections of wires at the end sections of these lines, which were built as radial lines. This leads to increased losses of active power and voltage, and, as a result, unacceptable deviation of voltage in remote load nodes of the redundant power transmission line. In order to improve the parameters of the operation mode of power transmission, it is proposed to use devices of longitudinal capacitive compensation and reactive power compensation in the scheme of the AVR point. An assessment of the effectiveness of the proposed measure was made.

ТОЧНІСТЬ КООРДИНАТ ВИЗНАЧЕННЯ МІСЦЯ СУДНА, РОЗРАХОВАНИХ МЕТОДОМ НАЙМЕНШИХ КВАДРАТІВ, ПРИ НАЯВНОСТІ НАДЛИШКОВИХ ЛІНІЙ ПОЛОЖЕННЯ

This article discusses the accuracy of the vessel’s position coordinates, calculated using the least squares method, in the presence of redundant line positions (LP) over time, assuming the LP error is normally distributed. It is stated that for a normal error distribution, the least squares method is the maximum likelihood method, thus the norm of the positional error covariance matrix is minimized, ensuring the highest accuracy of the vessel’s position coordinates. Field observation results are presented, where experimental data were obtained, demonstrating the possibility of altering navigational parameters. Following the adjustment of navigational parameters, a series of tests were conducted, exceeding 100 in total. The analysis of these results indicates that deviations in navigational parameterization, achieved over a limited time interval, conform to the normal law of variability distribution. Adjustments to the parameters over a larger interval are subject to changes in the laws of change, with the degree of power of some of the normal law proportional to the interval of the series value of the navigational parameter. It is demonstrated that the efficiency of observing the vessel’s coordinates, calculated by the least squares method during times of redundant LP, the errors of which can be calculated according to different laws, is less than one. To evaluate the efficiency of coordinate observation derived from overly large LP and gaps using the least squares method, a computer simulation was performed. During this simulation, efficiency values were compared with the highest theoretically achievable efficiency values, as outlined in the article, and the difference between them in the case of high-technological parameters was less than 22.0%. The simulations conducted showed good agreement between the efficiency assessments derived from analytical expressions and those obtained from the simulations, thereby confirming the validity of the analytical method for evaluating the efficiency of observed coordinates, calculated by the least squares method. Keywords: navigational safety, accuracy of coordinates assignment, change of law and subdivision, simulation modelling.

DIG-SLAM: an accurate RGB-D SLAM based on instance segmentation and geometric clustering for dynamic indoor scenes

Simultaneous localization and mapping (SLAM) has emerged as a critical technology enabling robots to navigate in unknown environments, drawing extensive attention within the robotics research community. However, traditional visual SLAM ignores the presence of dynamic objects in indoor scenes, and dynamic point features of dynamic objects can lead to incorrect data correlation, making the traditional visual SLAM is difficult to accurately estimate the camera’s pose when the objects in the scenes are moving. Using only point features cannot fully extract geometric information in dynamic indoor scenes, reducing the system’s robustness. To solve this problem, we develop a RGB-D SLAM system called DIG-SLAM. Firstly, the objects’ contour regions are extracted using the YOLOv7 instance segmentation method, serving as a prerequisite for determining dynamic objects and constructing a semantic information map. Meanwhile, the line features are extracted using the line segment detector algorithm, and the redundant line features are optimized via K-means clustering. Secondly, moving consistency checks combined with instance partitioning determine dynamic regions, and the point and line features of the dynamic regions are removed. Finally, the combination of static line features and point features optimizes the camera pose. Meanwhile, a static semantic octree map is created to provide richer and higher-level scene understanding and perception capabilities for robots or autonomous systems. The experimental results on the Technische Universität München dataset show that the average absolute trajectory error of the developed DIG-SLAM is reduced by 28.68% compared with the dynamic semantic SLAM. Compared with other dynamic SLAM methods, the proposed system shows better camera pose estimation accuracy and system’s robustness in dynamic indoor environments and better map building in real indoor scenes.

Genetic erosion within the Fabada dry bean market class revealed by high-throughput genotyping.

The Fabada market class within the dry beans has a well-differentiated seed phenotype with very large white seeds. This work investigated the genetic diversity maintained in the seed collections within this market class and possible genetic erosion over the last 30 years. A panel with 100 accessions was maintained in seed collections for 30 years, 57 accessions collected from farmers in 2021, six cultivars developed in SERIDA, and 16 reference cultivars were gathered and genotyped with 108,585 SNPs using the genotyping-by-sequencing method. Filtering based on genotypic and phenotypic data was carried out in a staggered way to investigate the genetic diversity among populations. The dendrogram generated from genotyping revealed 90 lines forming 16 groups with identical SNP profiles (redundant lines) from 159 lines classified as market-class Fabada according to their passport data. Seed phenotyping indicated that 19 lines were mistakenly classified as Fabada (homonymies), which was confirmed in the dendrogram built without redundant lines. Moreover, this study provides evidence of genetic erosion between the population preserved for 30 years and the currently cultivated population. The conserved population contains 54.6% segregation sites and 41 different SNP profiles, whereas the cultivated population has 19.6% segregation sites and 26 SNP profiles. The loss of genetic variability cannot be attributed to the diffusion of modern cultivars, which increase genetic diversity (six new SNP profiles). The results allow for the more efficient preservation of plant genetic resources in genebanks, minimizing redundant accessions and incorporating new variations based on genotypic and phenotypic data.

Identification and location method of strip ingot for autonomous robot system using kmeans clustering and color segmentation

AbstractIn order to improve the efficiency of autonomous robot sorting steel ingots, this paper proposes a two‐dimensional weighted equivalent clustering‐based progressive probabilistic hough transform (2D‐WEC‐PPHT) algorithm for the problem of identifying and locating strip ingots in automatic picking strip ingot palletizing. First, the steel ingot image is preprocessed and the PPHT linear detection method is used to extract the edge linear information of the steel ingot. Second, the angle and position information are normalized and weighted, and a two‐dimensional clustering distance calculation method is proposed for two‐dimensional clustering of the extracted line information. Besides, the clustering line clusters with close angles were processed into equivalent lines by mean fitting. Then, the average threshold method was used to segment the ingot between each two fitting lines, and the minimum rectangle was used to box the segmentation part. The centroid of the box‐selected rectangle is the positioning center of the ingot, and the long side angle of the box‐selected rectangle is the deviation angle information of the ingot. Finally, the experimental results show that the number of redundant lines detected by the 2D‐WEC‐PPHT is significantly less than that of traditional methods such as HT and PPHT. The positioning speed of ingot is faster than that of HT and PPHT, and the processing time is reduced from 20 s to 10 s. In the case of large proportion of old ingots with weak reflection, the recognition accuracy reached 93.5%, and the angular and position positioning accuracy were 2.270° and 11.675 mm, respectively. The recognition accuracy of new ingots with strong reflection reached 99.574%, which met the requirements of picking positioning accuracy.

Efficient reconstruction of cell lineage trees for cell ancestry and cancer.

Mosaic mutations can be used to track cell ancestries and reconstruct high-resolution lineage trees during cancer progression and during development, starting from the first cell divisions of the zygote. However, this approach requires sampling and analyzing the genomes of multiple cells, which can be redundant in lineage representation, limiting the scalability of the approach. We describe a strategy for cost- and time-efficient lineage reconstruction using clonal induced pluripotent stem cell lines from human skin fibroblasts. The approach leverages shallow sequencing coverage to assess the clonality of the lines, clusters redundant lines and sums their coverage to accurately discover mutations in the corresponding lineages. Only a fraction of lines needs to be sequenced to high coverage. We demonstrate the effectiveness of this approach for reconstructing lineage trees during development and in hematologic malignancies. We discuss and propose an optimal experimental design for reconstructing lineage trees.

Distribution network planning with DG units considering the network reconfiguration and reliability

The failure statistics of most utilities show that distribution networks (DN) make the most considerable individual contribution to the lack of supply to consumers. There are several advantages to optimizing distributed generation (DG) allocation in DNs, including loss reduction, voltage profile improvements, and reliability. A traditional objective function of optimal DG allocation is to minimize the total power loss and improve the voltage profile. Due to their ability to supply loads locally, DG units enhance the load-carrying capability of lines and, therefore, serve the same purpose as redundant lines. A DN’s reliability indices can also be improved by optimal DG allocation. As such, it is interesting to investigate how network reconfiguration (NR) may be further enhanced to improve the achievement of these critical objectives and ensure the system’s efficient operation in this context. The purpose of this paper is to present an intensive investigation of the reliability and performance improvement that NR can achieve when using DG units in modern DNs. An efficient metaheuristic rider optimizer algorithm (ROA) is applied to the complex combinatorial NR and DG allocation problem with stringent constraints. Analyses are conducted on benchmark IEEE 33-bus test DNs with explicit presentation of results.

Topologi Redundansi Link Untuk Keamanan Serta Mitigasi Ketersediaan Jaringan Komputer Menggunakan Rapid Spanning Tree Protocol

The frequent occurrence of natural disasters requires telecommunications companies to require a backup internet backbone line if the telecommunications infrastructure is damaged/disconnected due to natural disasters. Reporting from inet.detik.com APJII revealed that the Jakarta-Singapore fiber optic network had broken, which had an impact on internet services in Indonesia. Fiber optic repair can take up to 2-3 weeks requiring network backup, the main solution for network backup with satellite, but problems will arise when configuration for satellite lines takes 1-2 days. Problems arise again when combined between fiber optic internet lines and satellite internet lines which cause the looping network to create network disturbances, to maintain interference, a spanning tree protocol method is needed to backup lines automatically and create link redundancy if one of the lines is problematic or disconnected. The purpose of this study is to design a link redundancy topology for security and mitigation of network availability using the rapid spanning tree protocol (RSTP) with router rb750gr3, switch rb260gs and switch dgs-108. In the RSTP network topology, it is designed with 3 redundant lines connected between the rb260gs switch and the dgs-108 switch, with an on-stick router rb750gr3 and is designed with 6 access mode vlan lines. In testing the inter-vlan network, RSTP terminates the redundancy link and then uses the ping command at the command prompt to determine how many minutes to backup the link. The NDLC method is used in determining how many seconds to backup this redundancy link using. The results of testing the link termination ether2-switch-mikrotik and ether1-switch-dlink using the "ping" command for 20 seconds in determining how many seconds to backup the link get the result that Request Time Out does not occur and the average time for each pc in determining the backup path for the pc-vlan20 22.9ms, pc-vlan30 35ms, pc-vlan70 23.5ms. The results of link termination testing ether3-switch-mikrotik and ether2-switch-dlink using the "ping" command for 20 seconds in determining how many seconds to backup the link get the result that there is no Request Time Out and the average time for each pc in determining the backup path for the pc-vlan20 23ms, pc-vlan30 24ms, pc-vlan70 43.7ms.

Design and Simulation of Content-Aware Hybrid DRAM-PCM Memory System

Phase Change Memory (PCM) can directly connect persistent memory to main memory bus, while it achieves high read throughput and low standby power, the critical concerns are its poor write performance and limited durability. A naturally in-spired design is the hybrid memory architecture that fuses DRAM and PCM, so as to exploit the positive aspects of both types of memory. Unfortunately, existing solutions are seriously challenged by the limited main memory size, which is the primary bottleneck of in-memory computing. In this paper, we introduce a novel Content Aware Hybrid DRAM-PCM memory system framework—CAHRAM, which exploits deduplication to improve line sharing with high memory efficiency. It reduces write traffic to hybrid memory by removing unnecessary duplicate line writes, thereby further enhancing the write endurance of PCM. And it also substantially extends available free memory space by coalescing redundant lines in hybrid memory. We also design a reference-based page migration technique to minimize the access overheads caused by the performance gap between DRAM and PCM. Compared with the state-of-the-art in a hybrid memory simulator, our experiment results show that CAHRAM can achieve the highest I/O performance and the longest PCM lifetime with the competitive efficiencies in space and energy.

Degradation Detection in a Redundant Sensor Architecture.

Safety-critical automation often requires redundancy to enable reliable system operation. In the context of integrating sensors into such systems, the one-out-of-two (1oo2) sensor architecture is one of the common used methods used to ensure the reliability and traceability of sensor readings. In taking such an approach, readings from two redundant sensors are continuously checked and compared. As soon as the discrepancy between two redundant lines deviates by a certain threshold, the 1oo2 voter (comparator) assumes that there is a fault in the system and immediately activates the safe state. In this work, we propose a novel fault prognosis algorithm based on the discrepancy signal. We analyzed the discrepancy changes in the 1oo2 sensor configuration caused by degradation processes. Several publicly available databases were checked, and the discrepancy between redundant sensors was analyzed. An initial analysis showed that the discrepancy between sensor values changes (increases or decreases) over time. To detect an increase or decrease in discrepancy data, two trend detection methods are suggested, and the evaluation of their performance is presented. Moreover, several models were trained on the discrepancy data. The models were then compared to determine which of the models can be best used to describe the dynamics of the discrepancy changes. In addition, the best-fitting models were used to predict the future behavior of the discrepancy and to detect if, and when, the discrepancy in sensor readings will reach a critical point. Based on the prediction of the failure date, the customer can schedule the maintenance system accordingly and prevent its entry into the safe state—or being shut down.

Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments

Given that the rapidly exploring random tree algorithm (RRT) and its variants cannot efficiently solve problems of path planning of autonomous vehicles, this paper proposes a new, adaptive improved RRT algorithm. Firstly, an adaptive directional sampling strategy is introduced to avoid excessive search by reducing the randomness of sampling points. Secondly, a reasonable node selection strategy is used to improve the smoothness of the path by utilizing a comprehensive criterion that combines angle and distance. Thirdly, an adaptive node expansion strategy is utilized to avoid invalid expansion and make the generated path more reasonable. Finally, the expanded ellipse is used to realize vehicle obstacle avoidance in advance, and the post-processing strategy removes redundant line segments of the initial path to improve its quality. The simulation results show that the quality of the planned path is significantly improved. This path followed successfully has good trajectory stability, which shows the proposed algorithm’s effectiveness and practicability in autonomous vehicles’ local path planning.

Generic microgrid controller with self-healing capabilities

Generic Microgrid Controller (GMC) specifications, developed at the University of California, Irvine (UCI) to support the standardization of microgrid controllers and guide IEEE standards were applied to the UCI Microgrid (UCIMG) for testing and deployment. While transition and dispatch capabilities of GMC were simulated and demonstrated, response of the controller to internal faults while islanded or to inadvertent trip of generation were not addressed previously. The present study adds self-healing capabilities to the GMC for islanded microgrid operations with the goal to enhance reliability of serving critical loads, and resiliency of the system. To verify and assess self-healing attributes as well as impacts on reliability and resiliency while islanded, the self-healing capability was simulated on the UCIMG model developed on MATLAB Simulink. The model was enhanced with recently deployed redundancies including two new switchyards and redundant lines, and was then divided into sections to (1) focus on critical and high priority loads, and (2) reduce the number of nodes and computational requirements. Our study explores the resiliency of a real system microgrid platform using the FLISR (fault location, isolation and service restoration) approach as the self-healing capability as part of the microgrid controller. This expert systems approach with precalculated and predetermined sequence makes it a practical and simple solution which can be implemented without having to deal with computational limits of the controller and time constraints. Results show that, even with a fault-induced circuit outage during islanded operation, critical loads can be served by interconnected circuits and rapidly dispatched switching, thereby minimizing the loss of critical and noncritical loads, and increasing reliability and resiliency.

A New Method for Type Synthesis of 2R1T and 2T1R 3-DOF Redundant Actuated Parallel Mechanisms with Closed Loop Units

The current type synthesis of the redundant actuated parallel mechanisms is adding active-actuated kinematic branches on the basis of the traditional parallel mechanisms, or using screw theory to perform multiple getting intersection and union to complete type synthesis. The number of redundant parallel mechanisms obtained by these two methods is limited. In this paper, based on Grassmann line geometry and Atlas method, a novel and effective method for type synthesis of redundant actuated parallel mechanisms (PMs) with closed-loop units is proposed. Firstly, the degree of freedom (DOF) and constraint line graph of the moving platform are determined successively, and redundant lines are added in constraint line graph to obtain the redundant constraint line graph and their equivalent line graph, and a branch constraint allocation scheme is formulated based on the allocation criteria. Secondly, a scheme is selected and redundant lines are added in the branch chains DOF graph to construct the redundant actuated branch chains with closed-loop units. Finally, the branch chains that meet the requirements of branch chains configuration criteria and F&C (degree of freedom & constraint) line graph are assembled. In this paper, two types of 2 rotational and 1 translational (2R1T) redundant actuated parallel mechanisms and one type of 2 translational and 1 rotational (2T1R) redundant actuated parallel mechanisms with few branches and closed-loop units were taken as examples, and 238, 92 and 15 new configurations were synthesized. All the mechanisms contain closed-loop units, and the mechanisms and the actuators both have good symmetry. Therefore, all the mechanisms have excellent comprehensive performance, in which the two rotational DOFs of the moving platform of 2R1T redundant actuated parallel mechanism can be independently controlled. The instantaneous analysis shows that all mechanisms are not instantaneous, which proves the feasibility and practicability of the method.

CAE-RLSM: Consistent and Efficient Redundant Line Segment Merging for Online Feature Map Building

In order to obtain a compact line segment-based map representation for localization and planning of mobile robots, it is necessary to merge redundant line segments which physically represent the same part of the environment in different scans. In this paper, a consistent and efficient redundant line segment merging approach (CAE-RLSM) is proposed for online feature map building. The proposed CAE-RLSM is composed of two newly proposed modules: one-to-many incremental line segment merging (OTM-ILSM) and multi-processing global map adjustment (MP-GMA). Different from state-of-the-art offline merging approaches, the proposed CAE-RLSM can achieve real-time mapping performance, which not only reduces the redundancy of incremental merging with high efficiency, but also solves the problem of global map adjustment after loop closing to guarantee global consistency. Furthermore, a new correlation-based evaluation metric is proposed for the quality evaluation of line segment maps. This evaluation metric does not require manual measurement of the environmental metric information, instead it makes full use of globally consistent laser scans obtained by simultaneous localization and mapping (SLAM) systems to compare the performance of different line segment-based mapping approaches in an objective and fair manner. Comparative experimental results with respect to a mean shift-based offline redundant line segment merging approach (MS-RLSM) and an offline version of one-to-one incremental line segment merging approach (O$^2$TO-ILSM) on both public data sets and self-recorded data set are presented to show the superior performance of CAE-RLSM in terms of efficiency and map quality in different scenarios.

Innovation, insight and trust: Customer experience excellence delivered responsibly in a digital world

Financial institutions are investing in innovative solutions that help restore customer trust — an imperative focus amid high-profile data breaches and postfinancial crisis apprehension. Many have made data privacy central to their day-today operations, recognising its importance as a competitive differentiator. Financial institutions, however, face the added challenge of dedicating the necessary attention to improving the customer experience, achieving regulatory compliance and maintaining robust security. This paper covers the capabilities and benefits of a low-code automation platform, a scalable solution that supports financial institutions in putting the customer first. Low-code dramatically simplifies the process of building and deploying applications while reducing the time it takes to do so. It empowers citizen developers with the ability to bring their ideas to life with intuitive point-and-click methods, replacing manual and redundant lines of code. Finally, low-code applications have the ability to store data on one interface, promising a single source of truth and providing employees with the right information at the right time. Supported by rigorous security standards and compliance, low-code delivers the security customers demand of financial institutions, ensuring that personal and financial data is safe. Essentially, low-code allows business and IT to work together, aligning their priorities towards one goal: making the customer successful.

Generating straight skeleton-based navigation networks with Industry Foundation Classes for indoor way-finding

Indoor navigation networks are the foundation of indoor localization-based services. To build navigation graph networks of buildings, the medial axis is an effective way to represent the paths of indoor spaces, as medial axis-based navigation networks are consistent with common human cognition of paths and satisfy the requirements of spatial queries in most indoor map-matching algorithms. The existing methods for generating medial axis-based indoor navigation networks compute the modified medial axis of indoor spaces to represent indoor paths. However, these methods cannot deal with rooms with irregular shapes or generate detours. Especially, these methods fail to generate path lines to represent floor-to-floor paths accurately. To address these issues, this study develops a novel approach called an improved generation of straight skeletons-based navigation networks (I-GSSNN) to produce straight skeletons based indoor navigation graph networks. The straight skeleton is adopted in I-GSSNN to catch the medial axis of indoor spaces. The Industry Foundation Classes (IFC) model, a widely-used format of Building Information Modeling (BIM), is used as input in the I-GSSNN. The I-GSSNN is a workflow that includes constructing path lines of corridors, connecting doors to corridors, generating floor-to-floor path lines, and removing redundant lines. Compared with existing methods, the I-GSSNN can handle rooms with any polygon shape and produces fewer detours. Novel algorithms are developed in the I-GSSNN to generate path lines for accurately representing stairs and elevators. An educational building is used as a case study to validate the result of I-GSSNN. The case study indicates that the I-GSSNN can generate a complete three-dimensional (3D) navigation network of the educational building. In addition, the accuracy test shows that the route length based on the generated navigation networks is very close to the real length. Significantly, the results show that the I-GSSNN can accurately generate full 3D navigation graph networks of buildings that can serve as indoor maps for indoor route planning and navigation and can also be used in code checking and pedestrian circulation analysis during building design.

Robust Line Detection of Synthetic Aperture Radar Images Based on Vector Radon Transformation

Line detection on synthetic aperture radar (SAR) images is still challenging due to the existence of strong speckles. This article proposes a novel line detection method for SAR images based on vector Radon transform (VRT). First, the ratio of exponentially weighted averages operator is determined to calculate the edge map. Then, the VRT is proposed to transform the edge map into the parameter map and decompose the parameter map along the angle of projection into two mutually perpendicular components, i.e., parallel component and vertical component, which strips off part of the random edge information and ensures the sharpness of the peaks (local extremum). Peaks are detected in the parallel component. Finally, the intersection analysis technique is adopted to remove the redundant lines. Experiments are carried out with six amplitude-format SAR images of various bands, resolutions, and polarizations from Chinese airborne SAR systems, GaoFen-3 (GF-3) satellite, and TerraSAR-X satellite. The results demonstrate the outperformance of the proposed method. Furthermore, a road edge detection scheme is designed based on the proposed line detection method. The experimental results of the road edge detection further confirm the effectiveness of the proposed method and show its potential for practical use.

A Decentralized Processing Schema for Efficient and Robust Real-time Multi-GNSS Satellite Clock Estimation

Real-time multi-GNSS precise point positioning (PPP) requires the support of high-rate satellite clock corrections. Due to the large number of ambiguity parameters, it is difficult to update clocks at high frequency in real-time for a large reference network. With the increasing number of satellites of multi-GNSS constellations and the number of stations, real-time high-rate clock estimation becomes a big challenge. In this contribution, we propose a decentralized clock estimation (DECE) strategy, in which both undifferenced (UD) and epoch-differenced (ED) mode are implemented but run separately in different computers, and their output clocks are combined in another process to generate a unique product. While redundant UD and/or ED processing lines can be run in offsite computers to improve the robustness, processing lines for different networks can also be included to improve the clock quality. The new strategy is realized based on the Position and Navigation Data Analyst (PANDA) software package and is experimentally validated with about 110 real-time stations for clock estimation by comparison of the estimated clocks and the PPP performance applying estimated clocks. The results of the real-time PPP experiment using 12 global stations show that with the greatly improved computational efficiency, 3.14 cm in horizontal and 5.51 cm in vertical can be achieved using the estimated DECE clock.

Coding-Based Low-Power Through-Silicon-Via Redundancy Schemes for Heterogeneous 3-D SoCs

Three-dimensional integration, employing through-silicon vias (TSVs), improves the system-on-chip (SoC) performance. However, redundancy schemes are required to cope with the relatively poor TSV manufacturing yield. Existing redundancy schemes do not exploit technological heterogeneity between the dies. Hardware costs can differ for the individual dies. This demands asymmetrical schemes with low complexity in costly mixed signal or RF dies. Furthermore, redundant TSVs are only used in the case of a defect. In the most probable case of correct manufacturing, they are unused. Another emerging technique using redundant lines is low-power coding (LPC). This paper presents a hybrid TSV redundancy technique based on coding, which can be used for LPC and for yield enhancement. Furthermore, the approach is strongly asymmetric. In case of a fault, a configuration is only required for the encoder or decoder located in the cheaper die, while in the costly die, a minimal set of XOR gates is sufficient. A case study for an existing heterogeneous SoC shows that the proposed technique decreases area overhead and power consumption compared to the best previous technique by over 69 % and 33%, respectively.

Evalusi Kinerja Hot Standby Router Protocol (HSRP) dan Gateway Load Balancing Protocol (GLBP) untuk Layanan Video Streaming

Realtime (streaming) data communication has become a major requirement for companies and government institutions. Communication that occurs is not only limited to one particular local area but covers other areas so as to form a broad network (WAN). In building network infrastructure, one of the most important things is how networks can deal with failure (failure) on a computer network consists of failure of devices (devices) that affect Quality of Services (QoS). In every internet network design process, a redundant line is always added to complete the main line. So that if the main line is disrupted, data traffic can be transferred to the backup path, this process is called network redundancy. So that if one gateway dies, another gateway will immediately replace the dead gateway. There are two protocols included in the FHRP, namely Hot Standby Routing Protocol (HSRP), and Gateway Load Balancing Protocol (GLBP), these two protocols that can overcome this problem. So from that this study will discuss which protocol between the two protocols has the best performance in overcoming the problem. Methods of data collection with literature studies and literature studies, simulations carried out with 8 stages (problem formulation, conceptual models, input & output data, modeling, simulation, verification & validation, experimentation, and output analysis). The results of this study provide the best QoS value for the delay value is the HSRP ROUTER protocol, and for the value of packet loss is HSRP, and for throughput value is HSRP and the routing protocol that is appropriate for the network for video streaming services is HSRP