Enhancing Multicriteria-Based Recommendations by Alleviating Scalability and Sparsity Issues Using Collaborative Denoising Autoencoder

A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.

Advanced DAG-Based Ranking(ADR)Protocol for Blockchain Scalability

In the past decade,blockchain has evolved as a promising solution to develop secure distributed ledgers and has gained massive attention.However,current blockchain systems face the problems of limited throughput,poor scalability,and high latency.Due to the failure of consensus algorithms in managing nodes’identities,blockchain technology is considered inappropriate for many applications,e.g.,in IoT environments,because of poor scalability.This paper proposes a blockchain consensus mechanism called the Advanced DAG-based Ranking(ADR)protocol to improve blockchain scalability and throughput.The ADR protocol uses the directed acyclic graph ledger,where nodes are placed according to their ranking positions in the graph.It allows honest nodes to use theDirect Acyclic Graph(DAG)topology to write blocks and verify transactions instead of a chain of blocks.By using a three-step strategy,this protocol ensures that the system is secured against doublespending attacks and allows for higher throughput and scalability.The first step involves the safe entry of nodes into the system by verifying their private and public keys.The next step involves developing an advanced DAG ledger so nodes can start block production and verify transactions.In the third step,a ranking algorithm is developed to separate the nodes created by attackers.After eliminating attacker nodes,the nodes are ranked according to their performance in the system,and true nodes are arranged in blocks in topological order.As a result,the ADR protocol is suitable for applications in the Internet of Things(IoT).We evaluated ADR on EC2 clusters with more than 100 nodes and achieved better transaction throughput and liveness of the network while adding malicious nodes.Based on the simulation results,this research determined that the transaction’s performance was significantly improved over blockchains like Internet of Things Applications(IOTA)and ByteBall.

The scalability of the tunnel-regenerated multi-active-region light-emitting diode structure

The scalability of the tunnel-regenerated multi-active-region （TRMAR） structure has been investigated for the application in light-emitting diodes （LEDs）. The use of the TRMAR structure was proved theoretically to have unique advantages over conventional slngle-active-layer structures in virtually every aspect, such as high quantum efficiency, high power and low leakage. Our study showed that the TRMAR LED structure could obtain high output power under low current injection and high wall-plug efficiency compared with the conventional single-active-layer LED structure.

Scalability Technologies for Wireless Mesh Networks

The continuous increase of data transmission density in wireless mobile communications has posed a challenge to the system performance of Wireless Mesh Networks (WMNs ). There is a rule for wireless Ad hoc networks that the average node capacity decreases while the number of nodes increases , so it is hard to establish a large - scale wireless Mesh network. Network scalability is very important for enhancing the adaptive networking capability of the wireless Mesh network. This article discusses key scalability technologies for Mesh Base Stations (BSs ) and Mesh Mobile Stations (MSs ), such as channel allocation, intelligent routing , multi- antenna , node classification, Quality of Service (QoS) differentiation and cooperative transmission.

Improving the stability and scalability of all-inorganic inverted CsPbI_(2)Br perovskite solar cell

All-inorganic perovskite solar cells(PSCs) have potential to pass the stability international standard of IEC61215:2016 but cannot deliver high performance and stability due to the poor interface contact. In this paper, Sn-doped TiO_(2)(Ti_(1-x)Sn_(x)O_(2)) ultrathin nanoparticles are prepared for electron transport layer(ETL) by solution process. The ultrathin Ti_(1-x)Sn_(x)O_(2) nanocrystals have greatly improved interface contact due to the facile film formation, good conductivity and high work function. The all-inorganic inverted NiOx/CsPbI_(2)Br/Ti_(1-x)Sn_(x)O_(2)p-i-n device shows a power conversion efficiency(PCE) of 14.0%. We tested the heat stability, light stability and light-heat stability. After stored in 85℃ for 65 days, the inverted PSCs still retains 98% of initial efficiency. Under continuous standard one-sun illumination for 600 h,there is no efficiency decay, and under continuous illumination at 85℃ for 200 h, the device still retains 85% of initial efficiency. The 1.0 cm^(2) device of inverted structure shows a PCE of up to 11.2%. The ultrathin Ti_(1-x)Sn_(x)O_(2)is promising to improve the scalability and stability and thus increase the commercial prospect.

Enhancing Cloud-Based IoT/M2M System Scalability by Dynamic Network Slicing

With ever-increasing applications of IoT, and due to the heterogeneous and bursty nature of these applications, scalability has become an important research issue in building cloud-based IoT/M2M systems. This research proposes a dynamic SDN-based network slicing mechanism to tackle the scalability problems caused by such heterogeneity and fluctuation of IoT application requirements. The proposed method can automatically create a network slice on-the-fly for each new type of IoT application and adjust the QoS characteristics of the slice dynamically according to the changing requirements of an IoT application. Validated with extensive experiments, the proposed mechanism demonstrates better platform scalability when compared to a static slicing system.

Tackling IoT Scalability with 5G NFV-Enabled Network Slicing

With emerging large volume and diverse heterogeneity of Internet of Things (IoT) applications, the one-size-fits-all design of the current 4G networks is no longer adequate to serve various types of IoT applications. Consequently, the concepts of network slicing enabled by Network Function Virtualization (NFV) have been proposed in the upcoming 5G networks. 5G network slicing allows IoT applications of different QoS requirements to be served by different virtual networks. Moreover, these network slices are equipped with scalability that allows them to grow or shrink their instances of Virtual Network Functions (VNFs) when needed. However, all current research only focuses on scalability on a single network slice, which is the scalability at the VNF level only. Such a design will eventually reach the capacity limit of a single slice under stressful incoming traffic, and cause the breakdown of an IoT system. Therefore, we propose a new IoT scalability architecture in this research to provide scalability at the NS level and design a testbed to implement the proposed architecture in order to verify its effectiveness. For evaluation, three systems are compared for their throughput, response time, and CPU utilization under three different types of IoT traffic, including the single slice scaling system, the multiple slices scaling system and the hybrid scaling system where both single slicing and multiple slicing can be simultaneously applied. Due to the balanced tradeoff between slice scalability and resource availability, the hybrid scaling system turns out to perform the best in terms of throughput and response time with medium CPU utilization.

Analysis and case study on multi-dimensional scalability of the Internet architecture

This paper presents the definition of multi-dimensional scalability of the Internet architecture, and puts forward a mathematical method to evaluate Internet scalability based on a variety of constraints. Then, the method is employed to study the Internet scalability problem in performance, scale and service scalability. Based on the examples, theoretical analysis and experimental simulation are conducted to address the scalability issue. The results show that the proposed definition and evaluation method of multi-dimensional Internet scalability can effectively evaluate the scalability of the Internet in every aspect, thus providing rational suggestions and methods for evaluation of the next generation Internet architecture.

FPSblo:A Blockchain Network Transmission Model Utilizing Farthest Point Sampling

Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.

Scalability Analysis of Request Scheduling in Cloud Computing

Rapid advancement of distributed computing systems enables complex services in remote computing clusters. Massive applications with large-scale and disparate characteristics also create high requirements for computing systems. Cloud computing provides a series of novel approaches to meet new trends and demands.However, some scalability issues have to be addressed in the request scheduling process and few studies have been conducted to solve these problems. Thus, this study investigates the scalability of the request scheduling process in cloud computing. We provide a theoretical definition of the scalability of this process. By modeling the scheduling server as a stochastic preemptive priority queue, we conduct a comprehensive theoretical and numerical analysis of the scalability metric under different structures and various environment configurations. The comparison and conclusion are expected to shed light on the future design and deployment of the request scheduling process in cloud computing.

Rational design of vitamin C/defective carbon van der Waals heterostructure for enhanced activity,durability and storage stability toward oxygen reduction reaction

Metal-free defective carbon materials with abundant active sites have been widely studied as low-cost and efficient oxygen reduction reaction(ORR)electrocatalysts in metal-air batteries.However,the active sites in defective carbon are easily subjected to serious oxidation or hydroxylation during ORR or storage,leading to rapid degradation of activity.Herein,we design a van der Waals heterostructure comprised of vitamin C(VC)and defective carbon(DC)to not only boost the activity but also enhance the durability and storage stability of the DC-VC electrocatalyst.The formation of VC van der Waals between DC and VC is demonstrated to be an effective strategy to protect the defect active sites from oxidation and hydroxylation degradation,thus significantly enhancing the electrochemical durability and storage anti-aging performance.Moreover,the DC-VC van der Waals can reduce the reaction energy barrier to facilitate the ORR.These findings are also confirmed by operando Fourier transform infrared spectroscopy and density functional theory calculations.It is necessary to mention that the preparation of this DC-VC electrocatalyst can be scaled up,and the ORR performance of the largely produced electrocatalyst is demonstrated to be very consistent.Furthermore,the DC-VC-based aluminum-air batteries display very competitive power density with good performance maintenance.

Multi-disciplinary Pathways to Computing:A Scalable and Col aborative Approach to Capitalize on the Demand for Computer Science Education

The number of students demanding computer science(CS)education is rapidly rising,and while faculty sizes are also growing,the traditional pipeline consisting of a CS major,a CS master’s,and then a move to industry or a Ph.D.program is simply not scalable.To address this problem,the Department of Computing at the University of Illinois has introduced a multidisciplinary approach to computing,which is a scalable and collaborative approach to capitalize on the tremendous demand for computer science education.The key component of the approach is the blended major,also referred to as“CS+X”,where CS denotes computer science and X denotes a non-computing field.These CS+X blended degrees enable win-win partnerships among multiple subject areas,distributing the educational responsibilities while growing the entire university.To meet the demand from non-CS majors,another pathway that is offered is a graduate certificate program in addition to the traditional minor program.To accommodate the large number of students,scalable teaching tools,such as automatic graders,have also been developed.

Construction of a High‑Performance Composite Solid Electrolyte Through In‑Situ Polymerization within a Self‑Supported Porous Garnet Framework

Composite solid electrolytes(CSEs)have emerged as promising candidates for safe and high-energy–density solid-state lithium metal batteries(SSLMBs).However,concurrently achieving exceptional ionic conductivity and interface compatibility between the electrolyte and electrode presents a significant challenge in the development of high-performance CSEs for SSLMBs.To overcome these challenges,we present a method involving the in-situ polymerization of a monomer within a self-supported porous Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12)(LLZT)to produce the CSE.The synergy of the continuous conductive LLZT network,well-organized polymer,and their interface can enhance the ionic conductivity of the CSE at room temperature.Furthermore,the in-situ polymerization process can also con-struct the integration and compatibility of the solid electrolyte–solid electrode interface.The synthesized CSE exhibited a high ionic conductivity of 1.117 mS cm^(-1),a significant lithium transference number of 0.627,and exhibited electrochemical stability up to 5.06 V vs.Li/Li+at 30℃.Moreover,the Li|CSE|LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) cell delivered a discharge capacity of 105.1 mAh g^(-1) after 400 cycles at 0.5 C and 30℃,corresponding to a capacity retention of 61%.This methodology could be extended to a variety of ceramic,polymer electrolytes,or battery systems,thereby offering a viable strategy to improve the electrochemical properties of CSEs for high-energy–density SSLMBs.

A programmable MDAC with power scalability

A programmable high precision multiplying DAC （MDAC） is proposed. The MDAC incorporates a frequency-current converter （FCC） to adjust the power versus sampling rate and a programmable operational am- plifier （POTA） to achieve the tradeoff between resolution and power of the MDAC, which makes the MDAC suitable for a 12 bit SHA-less pipelined ADC. The prototype of the proposed pipelined ADC is implemented in an SMIC CMOS 0.18 μm 1P6M process. Experimental results demonstrate that power of the proposed ADC varies from 15.4 mW （10 MHz） to 63 mW （100 MHz） while maintaining an SNDR of 60.5 to 63 dB at all sampling rates. The differential nonlinearity and integral nonlinearity without any calibration are no more than 2.2/-1 LSB and 1.6/-1.9 LSB, respectively.

Research of Scalability of the Belt-Type Sensor Networks

For the large-scale application requirements of the belt-type networks,the mathematical modeling as well as quantitative analysis for the scalability of the network based on average path length is completed in this paper,and the theorem for the scale scalability of the belt-type networks is derived.The theorem provides a calculation formula for the upper limit of node scale theory of the belt-type networks and a calculation formula for the upper limit of single node load theory.

High efficiency modeling of broadband millimeter-wave CMOS FETs with gate width scalability by using pre-modeled cells

Thisworkpresentsahighlyefficientapproachforbroadbandmodelingofmillimeter-waveCMOSFETs with gate width scalability by using pre-modeled cells. Only a few devices with varied gate width are required to be measured and modeled with fixed models, and later used as pre-modeled cells. Then a target device with the desired gate width is constructed by choosing appropriate cells and connecting them with a wiring network. The corresponding scalable model is constructed by incorporating the fixed models of the cells used in the target device and the scalable model of the connection wires. The proposed approach is validated by experiments on 65-nm CMOS process up to 40 GHz and across a wide range of gate widths.

Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

Recently,vehicular ad hoc networks(VANETs)finds applicability in different domains such as security,rescue operations,intelligent transportation systems(ITS),etc.VANET has unique features like high mobility,limited mobility patterns,adequate topologymodifications,and wireless communication.Despite the benefits of VANET,scalability is a challenging issue which could be addressed by the use of cluster-based routing techniques.It enables the vehicles to perform intercluster communication via chosen CHs and optimal routes.The main drawback of VANET network is the network unsteadiness that results in minimum lifetime.In order to avoid reduced network lifetime in VANET,this paper presents an enhanced metaheuristics based clustering with multihop routing technique for lifetime maximization(EMCMHR-LM)in VANET.The presented EMCMHR-LM model involves the procedure of arranging clusters,cluster head(CH)selection,and route selection appropriate for VANETs.The presentedEMCMHR-LMmodel uses slime mold optimization based clustering(SMO-C)technique to group the vehicles into clusters.Besides,an enhanced wild horse optimization based multihop routing(EWHO-MHR)protocol by the optimization of network parameters.The presented EMCMHR-LMmodel is simulated usingNetwork Simulator(NS3)tool and the simulation outcomes reported the enhanced performance of the proposed EMCMHR-LM technique over the other models.

Fast and scalable routing protocols for data center networks

Data center networks may comprise tens or hundreds of thousands of nodes,and,naturally,suffer from frequent software and hardware failures as well as link congestions.Packets are routed along the shortest paths with sufficient resources to facilitate efficient network utilization and minimize delays.In such dynamic networks,links frequently fail or get congested,making the recalculation of the shortest paths a computationally intensive problem.Various routing protocols were proposed to overcome this problem by focusing on network utilization rather than speed.Surprisingly,the design of fast shortest-path algorithms for data centers was largely neglected,though they are universal components of routing protocols.Moreover,parallelization techniques were mostly deployed for random network topologies,and not for regular topologies that are often found in data centers.The aim of this paper is to improve scalability and reduce the time required for the shortest-path calculation in data center networks by parallelization on general-purpose hardware.We propose a novel algorithm that parallelizes edge relaxations as a faster and more scalable solution for popular data center topologies.

An Interoperability Cross-Block Chain Framework for Secure Transactions in IoT

The purpose of this research is to deal with effective block chain framework for secure transactions.The rate of effective data transactions and the interoperability of the ledger are the two major obstacles involved in Blockchain and to tackle this issue,Cross-Chain based Transaction(CCT)is introduced.Traditional industries have been restructured by the introduction of Internet of Things(IoT)to become smart industries through the feature of data-driven decision-making.Still,there are a few limitations,like decentralization,security vulnerabilities,poor interoperability,as well as privacy concerns in IoTs.To overcome this limitation,Blockchain has been employed to assure a safer transaction process,especially in asset exchanges.In recent decades,scalable local ledgers implement Blockchains,simultaneously sustaining peer validations of transactions which can be at local or global levels.From the single Hyperledger-based blockchains system,the CCT takes the transaction amid various chains.In addition,the most significant factor for this registration processing strategy is the Signature to ensure security.The application of the Quantum cryptographic algorithm amplifies the proposed Hyperledger-based blockchains,to strengthen the safety of the process.The key has been determined by restricting the number of transactions that reach the global Blockchain using the quantum-based hash function and accomplished by scalable local ledgers,and peer validations of transactions at local and global levels without any issues.The rate of transaction processing for entire peers has enhanced with the ancillary aid of the proposed solution,as it includes the procedure of load distribution.Without any boosted enhancement,the recommended solution utilizes the current transaction strategy,and also,it’s aimed at scalability,resource conservation,and interoperability.The experimental results of the system have been evaluated using the metrics like block weight,ledger memory,the usage of the central processing unit,and the communication overhead.

Hybrid Graph Partitioning with OLB Approach in Distributed Transactions

Online Transaction Processing(OLTP)gets support from data partitioning to achieve better performance and scalability.The primary objective of database and application developers is to provide scalable and reliable database systems.This research presents a novel method for data partitioning and load balancing for scalable transactions.Data is efficiently partitioned using the hybrid graph partitioning method.Optimized load balancing(OLB)approach is applied to calculate the weight factor,average workload,and partition efficiency.The presented approach is appropriate for various online data transaction applications.The quality of the proposed approach is examined using OLTP database benchmark.The performance of the proposed methodology significantly outperformed with respect to metrics like throughput,response time,and CPU utilization.