Throughput Time Research Articles

Fuzzy based hybrid BAT and firefly algorithm for optimal path selection and security in wireless sensor network

Nodes are deployed randomly in the network area of the WSN. data transmission from source to destination via intermediate nodes should be done in a secure fashion. Due to the large size of packet loss and energy consumption of sensor nodes, a secure and energy-efficient path must be required. The main objective of this research is to provide secure data transmission among node-to-node for efficient delivery of data packets to the destination. The system uses a novel hybrid firefly and BAT algorithm for path selection, an innovative trust value generation, and optimal neighborhood selection using fuzzy logic. The research employs Elliptic Curve Cryptography (ECC) combined with Diffie-Hellman exchange for key generation and key exchange. Path selection is done by fuzzy logic and optimization of selection has been carried out by hybrid BAT and Firefly algorithms. Key generation includes a time-based randomness factor that increases the complexity of cryptanalysis, thereby providing the most security. The performance of the simulation is analyzed and depicted in terms of delay, throughput, energy, and processing time. The research has been carried out using a network simulator with nodes deployed randomly in the network area with mobility as the primary concern that requires dynamic path selection.

STREAMLINING THE SHIP STRUCTURAL OPTIMIZATION PROCESS BY USING AN EARLY 3D PRODUCT MODEL

Optimization of ship structure has been a target for ship designers ever since the beginning of modern shipbuilding. At the same time, class society rules and regulations have been continuously evolving and guiding shipbuilders in their use of more advanced methods and tools, which will further facilitate the optimization of structures against the latest knowledge. This paper presents the results of a project in which the whole rule-based structural optimization process is built inside one technology platform. This platform combines the necessary modelling work, prescriptive rule check, FEM-based rule check and further weight and other calculations in one automated and streamlined process. This will have a tremendous effect on the throughput time of iteration cycles. The paper will present the process and technologies used for integrating the different components into the common design platform. It will also show some results achieved in a commercial cargo ship design.

Research on Convergence Media Consensus Mechanism Based on Blockchain

In recent years, the media industry has achieved rapid development and experienced three development stages from traditional media to new media and then to the current convergence media. Convergence media has brought about great changes in content production, communication mechanism, operation and maintenance management, but also brought about problems such as declining credibility of the industry, difficulty in confirming content rights, difficulty in protecting user privacy, etc. Research on convergence media based on blockchain can make use of the characteristics of blockchain to design or optimize the media industry. In this paper, we introduced the development of convergence media, blockchain and consensus mechanism, then we described a sustainable convergence media ecology based on blockchain. Furthermore, we designed and implemented a consensus mechanism named proof of efficiency (PoE). After analysis, PoE can provide high security and resist 51% resource attack, sybil attack, etc. The experimental results show that PoE has the characteristics of decentralization, strong consistency, low energy consumption, short average block generation time, high throughput and short block confirmation time; the consensus results of PoE can reflect the node’s ecological characteristics in convergence media which can stimulate the activity of nodes and better solve the generation of the Matthew effect.

Packet Routing in Dynamic Multi-Hop UAV Relay Network: A Multi-Agent Learning Approach

The multi-hop unmanned aerial vehicle (UAV) network can serve as data relays where ground users (GUs) do not have reliable direct connections to the base station (BS). Existing works mainly focus on simple dual-hop system. In this paper, we investigate the packet routing problem in a multi-hop UAV relay network to minimize the data transmission time and enhance the network throughput. However, the dynamic network topology due to UAV mobility makes the packet routing challenging since the limited communication range of each UAV leads to volatile wireless connection. Moreover, the line-of-sight communication links may cause strong interference among UAVs. Towards this end, we propose a novel multi-agent deep reinforcement learning based algorithm, named as multi-agent QMIX (MAQMIX) to: 1) design proper UAVs’ trajectories to serve the moving GUs while maintaining the network connection; 2) allocate frequency resource properly among UAVs to alleviate the impact of interference; and 3) choose a proper next hop UAV for each data packet to reduce the transmission time and probability of network congestion. The proposed MAQMIX has two novel training mechanisms, i.e., intra-UAV and inter-UAV training mechanisms, which can tackle the large action space issue and coordinate the training among UAVs in the multi-hop UAV relay network. Simulation results demonstrate that the MAQMIX outperforms baseline schemes in terms of the network congestion avoidance, throughput, and transmission time.

LBSMT: Load Balancing Switch Migration Algorithm for Cooperative Communication Intelligent Transportation Systems

We entered an era when the automotive industry is undergoing a digital revolution. Automobiles evolving into automated movable objects are using artificial intelligence capabilities. In contrast, cellular communications networks incorporate emerging technologies, such as SDN (software-defined networking) and NFV (network functions virtualization). Sophisticated software-defined communications networks virtualizes network functions and paving the way for the new design, monitoring, and management strategies. SDN is rising towards the application of load balancing for real time applications due to the heavy load of data on servers. When there is intra-communication between the various switches and domains; migration of switches takes place and the load over servers is imbalanced. An imbalance of the load will increase the response time and decrease the throughput. In intelligent transportation systems (ITS) balance on the servers should be maintained for the network sustainability. To provide a solution for the requirement of ITS, a dynamic QoS-aware load balancing switch migration algorithm (LBSMT) is proposed in this paper. As per the results validated in Python, after the migration LBSWT has improved CPU utilization, memory utilization, throughput and response time over server load, round robin, weighted round robin, LBBSRT and dynamic server algorithms.

Effects of the COVID-19 Pandemic on Surgical Clinics

Objective: This study aimed to reveal how surgical clinics were affected by the COVID-19 pandemic based on concrete data.
 Method: In this study, the outpatient clinics of surgical branches were examined in terms of the number of presenting patients, number of visits, patient age, number of patient revisits, number of appointments made, patients’ time of arrival for their appointments, patient throughput times, number of patients that underwent surgery, and number of surgical operations performed during the COVID-19 pandemic. 
 Results: During the first year of the pandemic, concerning the number of presenting patients and number of visits, the most affected outpatient clinic was otorhinolaryngology and the least affected was gynecology and obstetrics. It was determined that the highest decrease in the mean age of patients presenting to outpatient clinics was in urology, and the lowest decrease in pediatric surgery. The patients who were the earliest to arrive for their appointments to undergo examinations were those that presented to the cardiovascular surgery clinic, while pediatric surgery patients arrived at the hospital closest to their appointment times. In the first year of the COVID-19 pandemic, the number of patients that underwent surgery decreased by 53% and the operations performed by 55% compared to the previous year.
 Conclusion: With the effect of the pandemic, there was a decrease in the number of patients that presented to the outpatient clinics of surgical branches, number of visits to these clinics, appointments made, repeated visits, patients that underwent surgery, number of operations performed, and mean age of patients.

An Adaptive Enhanced Technique for Locked Target Detection and Data Transmission over Internet of Healthcare Things

The incredible advancements in data transmission technology have opened up more potentials for data security than ever before. Numerous methods for data protection have been developed during the previous decades, including steganography and cryptography. The security and integrity of medical data have emerged as major barriers for healthcare service systems as the Internet of Things has evolved dramatically in the healthcare business. Communication between two devices securely is a difficult problem. Numerous cryptographic algorithms are already available, including data encryption standard (DES), Rivest–Shamir–Adleman (RSA), and advanced encryption standard (AES). In this paper, we present a hybrid security model for the protection of diagnostic text data contained in medical photographs. The proposed model is built by combining a proposed hybrid encryption system with either a 2D Discrete Wavelet Transform 1 Level (2D-DWT-1L) or a 2D Discrete Wavelet Transform 2 Level (2D-DWT-2L) steganography technique. The suggested model encrypts secret data and hides them using 2D-DWT-3L. As text covers, color and grayscale images are employed. The suggested system’s performance was tested using PSNR, SSIM, MSE, and Correlation. Associated to state-of-the-art approaches, the proposed model masked personal patient data with high capacity, imperceptibility and minimum deterioration in the received stego-image. We use MATLAB to build the proposed mechanism, and measures such as throughput and execution time are used to assess performance.

Assessing the Network-Wide Impacts of Dedicated Lanes for Connected Autonomous Vehicles

Dedicated lanes for autonomous vehicles (AV) are introduced as an effective strategy to improve mobility in mixed traffic of AVs and heterogeneous drivers. However, adding a new lane is costly, and dedicating an existing lane may increase traffic congestion in other lanes. Previous studies investigated the impacts of AV dedicated lanes on throughput at the segment level and/or assumed a fixed route choice. However, AV dedicated lanes change route choice behavior, which affects traffic distribution over the network. Therefore, this study explores the impacts of AV dedicated lanes on the traffic performance of large-scale networks by conducting a network-level cost–benefit analysis on the implementation of AV dedicated lanes under different demand and AV market penetration rate (MPR) scenarios. This study examines the impacts of implementing AV dedicated lanes to freeway links on traffic congestion at corridor and network levels. Various factors are explored: changes in aggregate flow–density relationships, throughput, and average travel times. To this end, DYNASMART-P software is updated to consider AV dedicated lanes and is used to simulate the mixed traffic. Traffic simulation analyses on the large-scale network of Chicago indicate that these impacts depend on the AV MPR, demand level, and AV dedicated lane implementation approach. Dedicated lanes for AVs are beneficial for a high demand level scenario at all AV MPRs. However, for the base demand scenario, (760,000 vehicles during a.m. peak), deploying such lanes is only justified for low AV MPRs. Furthermore, the impacts of AV dedicated lanes on traffic at the network level are different from those on single segments.

A Point-of-Care Digital Workflow for 3D Printed Passive Presurgical Orthopedic Plates in Cleft Care.

Cleft lip and palate are one of the most common congenital craniofacial malformations. As an initial treatment, presurgical orthopedics is considered standard treatment at many cleft centers. Digital impressions are becoming feasible in cleft care. Computer-aided design (CAD) and three-dimensional (3D) printing are manufacturing standards in dentistry. The assimilation of these technologies has the potential to alter the traditional workflow for the fabrication of customized presurgical orthopedic plates. We present a digital workflow comprising three steps: 3D digital image acquisition with an intraoral scanner, open-source CAD modeling, and point-of-care 3D printing for the fabrication of personalized passive presurgical plates for newborns with cleft lip and palate. The digital workflow resulted in patient-related benefits, such as no risk of airway obstruction with quicker data acquisition (range 1–2.5 min). Throughput time was higher in the digital workflow 260–350 min compared to 135 min in the conventional workflow. The manual and personal intervention time was reduced from 135 min to 60 min. We show a clinically useful digital workflow for presurgical plates in cleft treatment. Once care providers overcome procurement costs, digital impressions, and point-of-care 3D printing will simplify these workflows and have the potential to become standard for cleft care.

PEMBERLAKUAN BALANCE SCORECARD UNTUK MENGUKUR KINERJA PELAYANAN DI KEBUN BINATANG KOTA SURABAYA INDONESIA

Surabaya Zoo which was founded in 1916 experienced the effects of globalization in which the change occur very rapidly. Customer wants and needs (tourists) are constantly changing, science and technology that continues togrow and compatition among businesses pariwisaata an increasingly sharp, forcing the Surabaya Zoo to constantly improve its ability to provide travel services. The purposeof this study is to analyzee in depth how the implementation of the concept of balance scorecard to measure performance of the Surabaya Zoo. The concept of balance scorecard at the Surabaya Zoo includes four persepectives and the persepectives of four each-each have several strategic targets, performance measure and targets to be achieved. The four persepectives are : (1) Financial Persepective targeting strategy : increased surpluses, increased revenue, and cost reduction, performance measure used is the percentage increase in surplus, the precentage change in revenue and decrease costs. (2) Customer Persepective targeting strategies : the speed of service, quality relationship with the customer, the performance measure used is the throughput time, customer retention. (3) Internal Business Process Persepective with strategic objectives : incerased development and product marketing, performance measure used are service error rate, comparisons of the old infrastructure with new ones, the precentage of revenue from new products. (4) Learning and Growth Persepective with strategic objectives : increased employee productivity, increased commitment of personnal, the performance measure used is the percentage of employees who educated and trained, personnal satisfaction.

Energy Aware Stable Multipath Disjoint Routing Based on Accumulated Trust Value in MANETs

Conserving energy and finding the stable path are the two vital issues in Mobile Ad Hoc Networks (MANETs) as the prior increases the network lifetime and the later increases the network throughput. The nodes which are not legitimate in terms of residual energy and packet forwarding history might be a threat to the path thereby making the path unstable. Thus, it results in frequent link failure, reduced throughput, reduced network and path life time. In order to reduce these hazards, authors have proposed an energy efficient, reliable path selecting protocol referred to as Trust Based Energy Aware Multipath Disjoint Routing Protocol (TEA-MDRP) for MANETS in this article. TEA-MDRP finds the optimum route between the source and the destination nodes using two parameters namely, the Accumulated Trust Value (ATV) and the node’s residual energy (N_res). ATV is calculated based on the packet forwarding status of the node which shows how good the node is in terms of packet forwarding point of view. TEA-MDRP allows only the nodes which have a good ATV and sufficient residual energy. A good ATV shows loyalty in forwarding the packets while a sufficiently large residual energy node avoids frequent path breakups and packet drops. Thus, the TEA-MDRP not only increases the network and path lifetime but also increases the throughput of the communication. Further, with the legitimate nodes in the paths, the TEA-MDRP considerably reduces the control packet overhead which might occur because of the frequent route re-discovery process. An extensive simulation is carried out using Network Simulator-2.35 for the quantitative and qualitative analysis of TEA-MDRP. The results obtained are compared with classical AOMDV and the results are satisfactory.

PEMBERLAKUAN BALANCE SCORECARD UNTUK MENGUKUR KINERJA PELAYANAN DI KEBUN BINATANG KOTA SURABAYA INDONESIA

Surabaya Zoo which was founded in 1916 experienced the effects of globalization in which the change occur very rapidly. Customer wants and needs (tourists) are constantly changing, science and technology that continues togrow and compatition among businesses pariwisaata an increasingly sharp, forcing the Surabaya Zoo to constantly improve its ability to provide travel services. The purposeof this study is to analyzee in depth how the implementation of the concept of balance scorecard to measure performance of the Surabaya Zoo. The concept of balance scorecard at the Surabaya Zoo includes four persepectives and the persepectives of four each-each have several strategic targets, performance measure and targets to be achieved. The four persepectives are : (1) Financial Persepective targeting strategy : increased surpluses, increased revenue, and cost reduction, performance measure used is the percentage increase in surplus, the precentage change in revenue and decrease costs. (2) Customer Persepective targeting strategies : the speed of service, quality relationship with the customer, the performance measure used is the throughput time, customer retention. (3) Internal Business Process Persepective with strategic objectives : incerased development and product marketing, performance measure used are service error rate, comparisons of the old infrastructure with new ones, the precentage of revenue from new products. (4) Learning and Growth Persepective with strategic objectives : increased employee productivity, increased commitment of personnal, the performance measure used is the percentage of employees who educated and trained, personnal satisfaction.

Streamlining Semiconductor Manufacturing of 200 mm and 300 mm Wafers: A Longitudinal Case Study on the Lot-to-Order-Matching Process

Lot-to-order matching (LTOM) is a crucial process in semiconductor manufacturing since inefficient allocation and order release have strong adverse effects on factory performance. Although prior research proposes several heuristics for the mathematical optimization of the LTOM process, successful real-world implementations following practical and comprehensive approaches are scarce. Our longitudinal case study addresses that issue by summarizing the results of an extensive research project on the automation and optimization of the LTOM process for 200 mm and 300 mm wafers at Infineon Technologies Dresden. Grounded in Action Design Research, we integrated different research methods to provide meaningful insights into the benefits, challenges, and best practices of our approach. Thereby, we also compare the results for 200 mm and 300 mm wafers. The project had positive impacts on multiple quantitative and qualitative key performance indicators, e.g., throughput, on-time delivery, tool utilization, cycle and working time savings, collaboration, and employee satisfaction. Finally, we provide managerial guidance for similar projects and implications for future research.

Privacy preserving monitoring protocol for Cyber–Physical System

Cyber–Physical Systems integrate computational and physical systems that can interact with humans in various ways. Due to less research on location privacy, building a monitoring protocol for the CPS system is challenging. Location privacy is becoming a major issue in the CPS, where the actual source and its messages are kept avoided by an attacker. The attacker follows the incoming message’s route to reach the source’s location. To hide the location of the source from attackers and increase their safety period, this research proposes a Multi-Ring protocol. A complete theoretical and mathematical analysis is discussed to check the model’s complexity and performance. The message delivery delay, throughput, energy consumption, and safety time ratio metrics are used for performance comparison. The simulation results confirmed that the proposed protocol increases the source safety period and network lifetime compared to the existing protocols.

Intelligent Process of Spectrum Handoff in Cognitive Radio Network

Spectrum handoff is a crucial function of Cognitive Radio (CR) which is the change of operating frequency. The main problem in spectrum handoff is the time taken in the searching, selection, and switching to a new available channel which can cause a significant amount of delay during spectrum handoff. This research aims to minimize the delay that occurs during spectrum handoff. A Proactive Fuzzy-Based Backup Channel Selection Scheme (PFBBCSS) was proposed where the Secondary User (SU) gathers backup channels in advance before the return of the Primary User (PU), then fuzzy logic would be used for the selection of the best channel out of the available backup channels. The proposed scheme was simulated and evaluated using the MATLAB Simulation tool and the result was compared with a Pure Proactive Spectrum Handoff Scheme. Results showed, in terms of throughput and efficient time utilization under a varying number of licensed channels, that the proposed scheme performed better, making it a good mechanism to be used for handoff decisions by the Secondary User (SU).

Energy efficiency in cognitive radio network using cooperative spectrum sensing based on hybrid spectrum handoff

Rapid spectrum usage in wireless networks may reduce energy efficiency, requiring cognitive radio networks to be more efficient than conventional ones. Due to increased data transmission demand, cognitive radio networks arose from a lack of spectrum bandwidth. Spectrum sensing and handoff decision are two cognitive radio network strategies that help avoid interference, channel access, and cohabitation between primary and secondary users. Current research focuses on handoff decision and cooperative spectrum sensing to improve sensing efficiency and system throughput while neglecting energy efficiency and handoff latency. Spectrum mobility and sensing are essential for energy-efficient cognitive radio networks. This study provides a second priority user transmission system using cooperative spectrum sensing to sense available channels. An energy detection technique optimizes the sensing process's energy usage, leading to energy efficiency. A primary user traffic pattern-based threshold approach is presented for spectrum mobility management. A threshold approach is utilized to calculate probabilistic stay-and-wait and QoS handoff values. The transmission channel is selected using a hybrid handoff strategy based on dynamic spectrum aggregation. Moreover, a cooperative spectrum sensing algorithm is described and simulated to identify the optimum channel with the greatest throughput and minimum energy consumption. The proposed approach increases energy efficiency and throughput while maintaining handoff delay and avoids miss-detection and false alarm. This technique improves energy efficiency, sensing performance, throughput, and handoff time. miss-detection.

A state lossless scheduling strategy in distributed stream computing systems

Stateful scheduling is of critical importance for the performance of a distributed stream computing system. In such a system, inappropriate task deployment lowers the resource utilization of cluster and introduces more communication between compute nodes. Also an online adjustment to task deployment scheme suffers slow state recovery during task restart. To address these issues, we propose a state lossless scheduling strategy (Sl-Stream) to optimize the task deployment and state recovery process. This paper discusses this strategy from the following aspects: (1) A stream application model and a resource model are constructed, together with the formalization of problems including subgraph partitioning, task deployment and stateful scheduling. (2) A multi-factor topology partitioning method is proposed using a quantum particle swarm algorithm. The assignment between tasks and nodes is optimized using a bipartite graph minimum matching algorithm. (3) A hierarchical local topology migration is performed when an online scheduling is triggered, which ensures the processing sustainability of data streams. (4) A fragment loss-tolerant jerasure tool is used to divide the state data into fragments and periodically save them in upstream vertex instances, which ensures the available fragments be able to reconstruct the whole state in parallel. (5) Metrics including latency, throughput and state recovery time are evaluated in a real distributed stream computing environment. With a comprehensive evaluation of variable-rate input scenarios, the proposed Sl-Stream system provides promising improvements on throughput, latency and state recovery time compared to the existing Storm’s scheduling strategies.

Multicriteria Deming Regressive African Buffalo Optimized Mapping for 3D NoC Architecture Design

Purpose. Networks-on-Chip (NoC) is a network-based communication between operating cores and intellectual property (IP) cores integrated on the same chip. An efficient design of NoC ensures high-speed data transfer and minimum essential connections in large-scale multicore, low power applications. Design/methodology/approach. A unique technique called Multicriteria Deming Regressive African Buffalo Optimized Mapping Weighted Directive Graph Theory (MDRABOMWDGT) is introduced for an efficient Network-on-Chip architecture design. The main aim of the proposed technique is to find efficient operating cores integrated on the chip with minimum time. Initially, a set of IP cores are listed with their connections from the benchmark dataset. Then Multicriteria Deming Regressive African Buffalo Optimization is applied to the topology for mapping strategy on 3D NoC, with communication metrics such as throughput, latency, and computation time. The optimization technique initializes the population of cores in search space. For each core in the network, communication metrics are measured; then Deming regression is applied to analyze multicriteria functions for minimizing computation time. Further, fitness is measured to get an optimal IP core for improving the performance of mapping in 3D NoC. Findings. Comprehensive experimental evaluation is conducted using a benchmark dataset, communication metrics are measured, and results show significant improvement in performance with respect to energy parameters compared to state-of-the-art works. Originality/value. The mapping strategy for 3D NOC is developed and the results are compared with the state-of-the-art techniques.

Assignment of parcels to loading stations in robotic sorting systems

Autonomous robots are increasingly used in warehouses in the recent decade, due to their flexible throughput capacity and low operating cost. Sorting may be the newest warehouse scene where autonomous robots are adopted. We consider a robotic sorting system with a two-tier layout where robots drive on the top mezzanine and sort parcels from loading stations (inputs) to drop-off points (outputs) via spiral conveyors connected to roll containers at the lower tier. We investigate the assignment optimization of arrival parcels to loading stations, to minimize the system throughput time. We first build an open queueing network to estimate the system performance and validate its accuracy by simulation. Then, we formulate an integer-programming model that takes the minimization of throughput time as the objective. We prove the computational complexity of the model by transferring it into an order batching problem, and design a Tabu search algorithm for solution. We evaluate the efficiency of the algorithm by both numerical experiments that take the Gurobi solver, the random and closest assignment rules as the comparison target, and a real case study. The results show that our algorithm can reduce the system throughput time by 7.09% and 8.76% and lower the manual cost by 11.99% and 17.50% over the random and the closest assignment rule, respectively. Moreover, it outperforms the Gurobi solver in large instances in terms of throughput time. The real case study shows that the system throughput time and the manual cost can be reduced by about 25% and 16%, compared with the assignment rule used in practice.

PROPIEDADES DE RENDIMIENTO Y ANÁLISIS DE AGRUPACIÓN DE LOS PUERTOS COSTEROS DE CHINA CONTINENTAL: UN MÉTODO DE ANÁLISIS MEDIANTE UNA RED COMPLEJA DE SERIES TEMPORALES

Explicit development orientations of ports are critical to promoting port clusters from chaotic competitions to a hierarchical collaborative development. To investigate the development orientation and hierarchies of coastal ports in Mainland China, a visibility graph network was constructed in this study for a time series analysis of China's port throughputs from 2000 to 2020. In this model, the four throughput indexes of cargo, domestic trade cargo, foreign trade cargo, and container were used to measure the scale of ports. The topological structural features of the throughput network of ports, including its average degree, diameter, and average clustering coefficient, were calculated. The ports were then divided into four types based on their network characteristics. Results show that the throughput time series network of coastal ports in Mainland China has an obvious hierarchical structure and generally has the characteristics of small-world networks. These ports are closely connected and have a strong transshipment capacity. However, an "absolute center" does not exist in this network, and these ports are in a state of disorderly and chaotic competition with serious homogenization. The proposed model provides an appropriate method for the future planning and design of port clusters. Keywords: Port throughput, Throughput characteristics, Visibility graph, Time series complex networks, Clustering analysis