With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The...With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.展开更多
This article lists all possible conversion equations of influence coefficients(ICs)with different formats when some of these are known to handle two-plane balancing tasks with no or less trial weight runs.There are tw...This article lists all possible conversion equations of influence coefficients(ICs)with different formats when some of these are known to handle two-plane balancing tasks with no or less trial weight runs.There are two approaches for two-plane balancing.One can treat it as a multi-plane balance problem involving a 2×2 matrix of complex ICs where two direct ICs along with two cross-effect ICs are generated so that correction weights at one or two balance planes can be determined.One can also apply a static pare(in-phase)and/or couple pair(180 degrees out-of-phase)weights for balancing.The latter approach has been used quite often in the field,especially on steam turbine and generator rotors.Dependent on vibration mode shapes and combinations as well as balance plane accessibility,sometimes applying static or couple pair weights can be a wise choice;other times weights at one or two end planes are needed.There are totally 4 possible sets of IC data due to weights at plane 1,plane 2,static pair,and couple pair.IC data would typically be obtained by applying trial weights followed by trial weight runs.It is found,however,that all these IC data can be converted easily without trial weight runs once any two of 4 sets are known.The above findings and conversion equations have been obtained analytically and verified by experimental results.Real cases are given to demonstratetheirapplications.展开更多
Basic helix–loop–helix(bHLH)proteins play pivotal roles in plant growth,development,and stress responses.However,the molecular and functional properties of bHLHs have not been fully characterized.In this study,a nov...Basic helix–loop–helix(bHLH)proteins play pivotal roles in plant growth,development,and stress responses.However,the molecular and functional properties of bHLHs have not been fully characterized.In this study,a novel XI subgroup of the bHLH protein gene RcbHLH59 was isolated and identified in rose(Rosa sp.).This gene was induced by salinity stress in both rose leaves and roots,and functioned as a transactivator.Accordingly,silencing RcbHLH59 affected the antioxidant system,^(Na+/K+)balance,and photosynthetic system,thereby reducing salt tolerance,while the transient overexpression of RcbHLH59 improved salinity stress tolerance.Additionally,RcbLHLH59 was found to regulate the expression of sets of pathogenesis-related(PR)genes in RcbHLH59-silenced(TRV-RcbHLH59)and RcbHLH59-overexpressing(RcbHLH59-OE)rose plants.The RcPR4/1 and RcPR5/1 transcript levels showed opposite changes in the TRVRcbHLH59 and RcbHLH59-OE lines,suggesting that these two genes are regulated by RcbHLH59.Further analysis revealed that RcbHLH59 binds to the promoters of RcPR4/1 and RcPR5/1,and that the silencing of RcPR4/1 or RcPR5/1 led to decreased tolerance to salinity stress.Moreover,callose degradation-and deposition-related genes were impaired in RcPR4/1-or RcPR5/1-silenced plants,which displayed a salt tolerance phenotype by balancing the ^(Na+/K+)ratio through callose deposition.Collectively,our data highlight a new RcbLHLH59-RcPRs module that positively regulates salinity stress tolerance by balancing Na^(+)/K^(+)and through callose deposition in rose plants.展开更多
Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure ...Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure reward mechanism that can facilitate load balancing among MECS.In addition,intelligent management of service caching and load balancing can improve the network utility in MEC blockchain networks with multiple types of workloads.In this paper,we investigate a learningbased joint service caching and load balancing policy for optimizing the communication and computation resources allocation,so as to improve the resource utilization of MEC blockchain networks.We formulate the problem as a challenging long-term network revenue maximization Markov decision process(MDP)problem.To address the highly dynamic and high dimension of system states,we design a joint service caching and load balancing algorithm based on the double-dueling Deep Q network(DQN)approach.The simulation results validate the feasibility and superior performance of our proposed algorithm over several baseline schemes.展开更多
This paper presents a novel fuzzy firefly-based intelligent algorithm for load balancing in mobile cloud computing while reducing makespan.The proposed technique implicitly acts intelligently by using inherent traits ...This paper presents a novel fuzzy firefly-based intelligent algorithm for load balancing in mobile cloud computing while reducing makespan.The proposed technique implicitly acts intelligently by using inherent traits of fuzzy and firefly.It automatically adjusts its behavior or converges depending on the information gathered during the search process and objective function.It works for 3-tier architecture,including cloudlet and public cloud.As cloudlets have limited resources,fuzzy logic is used for cloudlet selection using capacity and waiting time as input.Fuzzy provides human-like decisions without using any mathematical model.Firefly is a powerful meta-heuristic optimization technique to balance diversification and solution speed.It balances the load on cloud and cloudlet while minimizing makespan and execution time.However,it may trap in local optimum;levy flight can handle it.Hybridization of fuzzy fireflywith levy flight is a novel technique that provides reduced makespan,execution time,and Degree of imbalance while balancing the load.Simulation has been carried out on the Cloud Analyst platform with National Aeronautics and Space Administration(NASA)and Clarknet datasets.Results show that the proposed algorithm outperforms Ant Colony Optimization Queue Decision Maker(ACOQDM),Distributed Scheduling Optimization Algorithm(DSOA),andUtility-based Firefly Algorithm(UFA)when compared in terms of makespan,Degree of imbalance,and Figure of Merit.展开更多
According to the advances in users’service requirements,physical hardware accessibility,and speed of resource delivery,Cloud Computing(CC)is an essential technology to be used in many fields.Moreover,the Internet of ...According to the advances in users’service requirements,physical hardware accessibility,and speed of resource delivery,Cloud Computing(CC)is an essential technology to be used in many fields.Moreover,the Internet of Things(IoT)is employed for more communication flexibility and richness that are required to obtain fruitful services.A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents.This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various utilities and a significant number of IoT devices with low resources.Different agents are integrated based on relevant features of behavioral interaction using classification techniques to balance the workload.Aload balancing algorithm is developed to serve users’requests to improve the solution of workload problems with an efficient distribution.The activity task from IoT devices has been classified by feature selection methods in the preparatory phase to optimize the scalability ofCC.Then,the server’s availability is checked and the classified task is assigned to its suitable server in the main phase to enhance the cloud environment performance.Multi-agent load balancing framework is succeeded to cope with the importance of using large-scale requirements of CC and(low resources and large number)of IoT.展开更多
A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network...A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.展开更多
Healthcare is a fundamental part of every individual’s life.The healthcare industry is developing very rapidly with the help of advanced technologies.Many researchers are trying to build cloud-based healthcare applic...Healthcare is a fundamental part of every individual’s life.The healthcare industry is developing very rapidly with the help of advanced technologies.Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises,as well as by patients from their mobile devices through communication interfaces.These systems promote reliable and remote interactions between patients and healthcare professionals.However,there are several limitations to these innovative cloud computing-based systems,namely network availability,latency,battery life and resource availability.We propose a hybrid mobile cloud computing(HMCC)architecture to address these challenges.Furthermore,we also evaluate the performance of heuristic and dynamic machine learning based task scheduling and load balancing algorithms on our proposed architecture.We compare them,to identify the strengths and weaknesses of each algorithm;and provide their comparative results,to show latency and energy consumption performance.Challenging issues for cloudbased healthcare systems are discussed in detail.展开更多
Every day,more and more data is being produced by the Internet of Things(IoT)applications.IoT data differ in amount,diversity,veracity,and velocity.Because of latency,various types of data handling in cloud computing ...Every day,more and more data is being produced by the Internet of Things(IoT)applications.IoT data differ in amount,diversity,veracity,and velocity.Because of latency,various types of data handling in cloud computing are not suitable for many time-sensitive applications.When users move from one site to another,mobility also adds to the latency.By placing computing close to IoT devices with mobility support,fog computing addresses these problems.An efficient Load Balancing Algorithm(LBA)improves user experience and Quality of Service(QoS).Classification of Request(CoR)based Resource Adaptive LBA is suggested in this research.This technique clusters fog nodes using an efficient K-means clustering algorithm and then uses a Decision Tree approach to categorize the request.The decision-making process for time-sensitive and delay-tolerable requests is facilitated by the classification of requests.LBA does the operation based on these classifications.The MobFogSim simulation program is utilized to assess how well the algorithm with mobility features performs.The outcome demonstrates that the LBA algorithm’s performance enhances the total system performance,which was attained by(90.8%).Using LBA,several metrics may be examined,including Response Time(RT),delay(d),Energy Consumption(EC),and latency.Through the on-demand provisioning of necessary resources to IoT users,our suggested LBA assures effective resource usage.展开更多
Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex systems.Microservices Architecture is one of th...Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex systems.Microservices Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed independently.This methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,etc.and the advantages;Microservices bring some challenges too.Multiple microservices need to be invoked one by one as a chain.In most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s request.It results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of requests.The communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting time.Experiments were done for both interactive as well as non interactive workloads to test the effectiveness of the solution.The approach has been proved to be very effective in reducing latency in the case of long service chains.展开更多
Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system resources.It is also referred to as a system that will let the consumers utilize...Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system resources.It is also referred to as a system that will let the consumers utilize computational resources like databases,servers,storage,and intelligence over the Internet.In a cloud network,load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency.It is also known as a server pool or server farm.When a single node is overwhelmed,balancing the workload is needed to manage unpredictable workflows.The load balancer sends the load to another free node in this case.We focus on the Balancing of workflows with the proposed approach,and we present a novel method to balance the load that manages the dynamic scheduling process.One of the preexisting load balancing techniques is considered,however it is somewhat modified to fit the scenario at hand.Depending on the experimentation’s findings,it is concluded that this suggested approach improves load balancing consistency,response time,and throughput by 6%.展开更多
Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of th...Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of the network results in packet loss and Delay(DL).For optimal performance,it is important to load balance between different gateways.As a result,a stable load balancing procedure is implemented,which selects gateways based on Fuzzy Logic(FL)and increases the efficiency of the network.In this case,since gate-ways are selected based on the number of nodes,the Energy Consumption(EC)was high.This paper presents a novel Node Quality-based Clustering Algo-rithm(NQCA)based on Fuzzy-Genetic for Cluster Head and Gateway Selection(FGCHGS).This algorithm combines NQCA with the Improved Weighted Clus-tering Algorithm(IWCA).The NQCA algorithm divides the network into clusters based upon node priority,transmission range,and neighbourfidelity.In addition,the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC,packet loss rate(PLR),etc.展开更多
In wireless sensor network(WSN),the gateways which are placed far away from the base station(BS)forward the collected data to the BS through the gateways which are nearer to the BS.This leads to more energy consumptio...In wireless sensor network(WSN),the gateways which are placed far away from the base station(BS)forward the collected data to the BS through the gateways which are nearer to the BS.This leads to more energy consumption because the gateways nearer to the BS manages heavy traffic load.So,to over-come this issue,loads around the gateways are to be balanced by presenting energy efficient clustering approach.Besides,to enhance the lifetime of the net-work,optimal routing path is to be established between the source node and BS.For energy efficient load balancing and routing,multi objective based beetle swarm optimization(BSO)algorithm is presented in this paper.Using this algo-rithm,optimal clustering and routing are performed depend on the objective func-tions routingfitness and clusteringfitness.This approach leads to decrease the power consumption.Simulation results show that the performance of the pro-posed BSO based clustering and routing scheme attains better results than that of the existing algorithms in terms of energy consumption,delivery ratio,through-put and network lifetime.Namely,the proposed scheme increases throughput to 72%and network lifetime to 37%as well as it reduces delay to 37%than the existing optimization algorithms based clustering and routing schemes.展开更多
Electrocatalytic urea synthesis via coupling of nitrate with CO_(2)is considered as a promising alternative to the industrial urea synthetic process.However,the requirement of sub-reaction(NO_(3)RR and CO_(2)RR)activi...Electrocatalytic urea synthesis via coupling of nitrate with CO_(2)is considered as a promising alternative to the industrial urea synthetic process.However,the requirement of sub-reaction(NO_(3)RR and CO_(2)RR)activities for efficient urea synthesis is not clear and the related reaction mechanisms remain obscure.Here,the construction,breaking,and rebuilding of the sub-reaction activity balance would be accompanied by the corresponding regulation in urea synthesis,and the balance of sub-reaction activities was proven to play a vital role in efficient urea synthesis.With rational design,a urea yield rate of 610.6 mg h−1 gcat.−1 was realized on the N-doped carbon electrocatalyst,superior to that of noble-metal electrocatalysts.Based on the operando SRFTIR measurements,we proposed that urea synthesis arises from the coupling of^(*)NO and^(*)CO to generate the key intermediate of^(*)OCNO.This work provides new insights and guidelines into urea synthesis from the aspect of activity balance.展开更多
At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,wh...At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.展开更多
Based on imbibition replacement of shut-in well in tight oil reservoirs, this paper expounds the principle of saturation rebalancing during the shut-in process after fracturing, establishes an optimization method for ...Based on imbibition replacement of shut-in well in tight oil reservoirs, this paper expounds the principle of saturation rebalancing during the shut-in process after fracturing, establishes an optimization method for shut-in time after horizontal well volume fracturing with the goal of shortening oil breakthrough time and achieving rapid oil breakthrough, and analyzes the influences of permeability, porosity, fracture half-length and fracturing fluid volume on the shut-in time. The oil and water imbibition displacement in the matrix and fractures occurs during the shut-in process of wells after fracturing. If the shut-in time is too short, the oil-water displacement is not sufficient, and the oil breakthrough time is long after the well is put into production. If the shut-in time is too long, the oil and water displacement is sufficient, but the energy dissipation in the formation near the bottom of the well is severe, and the flowing period is short and the production is low after the well is put into production. A rational shut-in time can help shorten the oil breakthrough time, extend the flowing period and increase the production of the well. The rational shut-in time is influenced by factors such as permeability, porosity, fracture half-length and fracturing fluid volume. The shortest and longest shut-in times are negatively correlated with porosity, permeability, and fracture half-length, and positively correlated with fracturing fluid volume. The pilot test in tight oil horizontal wells in the Songliao Basin, NE China, has confirmed that the proposed optimization method can effectively improve the development effect of horizontal well volume fracturing.展开更多
Aiming at the characteristics of obvious block division and strong discreteness in the assembly production mode of electronic products,this paper proposes a composite U-shaped flexible assembly line model,and establis...Aiming at the characteristics of obvious block division and strong discreteness in the assembly production mode of electronic products,this paper proposes a composite U-shaped flexible assembly line model,and establishes a multi-objective optimization mathematical model on this basis.According to the characteristics of the model,the improved ranked positional weight(RPW)method is used to adjust the generation process of the initial solution of the genetic algorithm,so that the genetic algorithm can be applied to the block task model.At the same time,the adaptive cross mutation factor is used on the premise that tasks between different blocks are not crossed during cross mutation,which effectively improves the probability of excellent individuals retaining.After that,the algorithm is used to iterate to obtain the optimal solution task assignment.Finally,the algorithm results are compared with actual production data,which verifies the validity and feasibility of the assembly line model for discrete production mode proposed in this paper.展开更多
Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during...Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the operational process,different types of active balancing actuators have been designed and widely applied in actual production.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance parameters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving efficiency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5%.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electromagnetic efficiency and a more stable and compact structure.展开更多
Typical rotors such as those on steam turbine or generator are often supported by two bearings with two balance planes at both ends.Vibrations are monitored by a pair of proximity probes at each bearing.There are two ...Typical rotors such as those on steam turbine or generator are often supported by two bearings with two balance planes at both ends.Vibrations are monitored by a pair of proximity probes at each bearing.There are two approaches to reduce 1X vibration due to unbalance at both ends via balancing with influence coefficient method.The first approach is to treat it as a multiple-plane balancing problem involving 2x2 matrix of complex influence coefficients.The second approach is to treat it as two single-plane balance problems using static(in-phase)and couple(180 degree out-of-phase)components,respectively.Conversion equations of influence coefficients between these two approaches have been found previously by the author.The corresponding spreadsheets that convert influence coefficients between these two formats are presented in the current paper.The paper shows effectiveness of these conversion equations in dealing with real balancing problems in the field.A detailed balance case is presented to demonstrate how the conversion equations are used to reduce vibration effectively.展开更多
High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation ba...High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.展开更多
文摘With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.
文摘This article lists all possible conversion equations of influence coefficients(ICs)with different formats when some of these are known to handle two-plane balancing tasks with no or less trial weight runs.There are two approaches for two-plane balancing.One can treat it as a multi-plane balance problem involving a 2×2 matrix of complex ICs where two direct ICs along with two cross-effect ICs are generated so that correction weights at one or two balance planes can be determined.One can also apply a static pare(in-phase)and/or couple pair(180 degrees out-of-phase)weights for balancing.The latter approach has been used quite often in the field,especially on steam turbine and generator rotors.Dependent on vibration mode shapes and combinations as well as balance plane accessibility,sometimes applying static or couple pair weights can be a wise choice;other times weights at one or two end planes are needed.There are totally 4 possible sets of IC data due to weights at plane 1,plane 2,static pair,and couple pair.IC data would typically be obtained by applying trial weights followed by trial weight runs.It is found,however,that all these IC data can be converted easily without trial weight runs once any two of 4 sets are known.The above findings and conversion equations have been obtained analytically and verified by experimental results.Real cases are given to demonstratetheirapplications.
基金supported by the National Key Research and Development Program(2018YFD1000400)National Natural Science Foundation of China(Grant No.32002084).
文摘Basic helix–loop–helix(bHLH)proteins play pivotal roles in plant growth,development,and stress responses.However,the molecular and functional properties of bHLHs have not been fully characterized.In this study,a novel XI subgroup of the bHLH protein gene RcbHLH59 was isolated and identified in rose(Rosa sp.).This gene was induced by salinity stress in both rose leaves and roots,and functioned as a transactivator.Accordingly,silencing RcbHLH59 affected the antioxidant system,^(Na+/K+)balance,and photosynthetic system,thereby reducing salt tolerance,while the transient overexpression of RcbHLH59 improved salinity stress tolerance.Additionally,RcbLHLH59 was found to regulate the expression of sets of pathogenesis-related(PR)genes in RcbHLH59-silenced(TRV-RcbHLH59)and RcbHLH59-overexpressing(RcbHLH59-OE)rose plants.The RcPR4/1 and RcPR5/1 transcript levels showed opposite changes in the TRVRcbHLH59 and RcbHLH59-OE lines,suggesting that these two genes are regulated by RcbHLH59.Further analysis revealed that RcbHLH59 binds to the promoters of RcPR4/1 and RcPR5/1,and that the silencing of RcPR4/1 or RcPR5/1 led to decreased tolerance to salinity stress.Moreover,callose degradation-and deposition-related genes were impaired in RcPR4/1-or RcPR5/1-silenced plants,which displayed a salt tolerance phenotype by balancing the ^(Na+/K+)ratio through callose deposition.Collectively,our data highlight a new RcbLHLH59-RcPRs module that positively regulates salinity stress tolerance by balancing Na^(+)/K^(+)and through callose deposition in rose plants.
基金supported in part by the National Natural Science Foundation of China 62072096the Fundamental Research Funds for the Central Universities under Grant 2232020A-12+4 种基金the International S&T Cooperation Program of Shanghai Science and Technology Commission under Grant 20220713000the Young Top-notch Talent Program in Shanghaithe"Shuguang Program"of Shanghai Education Development Foundation and Shanghai Municipal Education Commissionthe Fundamental Research Funds for the Central Universities and Graduate Student Innovation Fund of Donghua University CUSF-DH-D-2019093supported in part by the NSF under grants CNS-2107190 and ECCS-1923717。
文摘Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure reward mechanism that can facilitate load balancing among MECS.In addition,intelligent management of service caching and load balancing can improve the network utility in MEC blockchain networks with multiple types of workloads.In this paper,we investigate a learningbased joint service caching and load balancing policy for optimizing the communication and computation resources allocation,so as to improve the resource utilization of MEC blockchain networks.We formulate the problem as a challenging long-term network revenue maximization Markov decision process(MDP)problem.To address the highly dynamic and high dimension of system states,we design a joint service caching and load balancing algorithm based on the double-dueling Deep Q network(DQN)approach.The simulation results validate the feasibility and superior performance of our proposed algorithm over several baseline schemes.
基金funded by University Grant Commission with UGC-Ref.No.:3364/(NET-JUNE 2015).
文摘This paper presents a novel fuzzy firefly-based intelligent algorithm for load balancing in mobile cloud computing while reducing makespan.The proposed technique implicitly acts intelligently by using inherent traits of fuzzy and firefly.It automatically adjusts its behavior or converges depending on the information gathered during the search process and objective function.It works for 3-tier architecture,including cloudlet and public cloud.As cloudlets have limited resources,fuzzy logic is used for cloudlet selection using capacity and waiting time as input.Fuzzy provides human-like decisions without using any mathematical model.Firefly is a powerful meta-heuristic optimization technique to balance diversification and solution speed.It balances the load on cloud and cloudlet while minimizing makespan and execution time.However,it may trap in local optimum;levy flight can handle it.Hybridization of fuzzy fireflywith levy flight is a novel technique that provides reduced makespan,execution time,and Degree of imbalance while balancing the load.Simulation has been carried out on the Cloud Analyst platform with National Aeronautics and Space Administration(NASA)and Clarknet datasets.Results show that the proposed algorithm outperforms Ant Colony Optimization Queue Decision Maker(ACOQDM),Distributed Scheduling Optimization Algorithm(DSOA),andUtility-based Firefly Algorithm(UFA)when compared in terms of makespan,Degree of imbalance,and Figure of Merit.
文摘According to the advances in users’service requirements,physical hardware accessibility,and speed of resource delivery,Cloud Computing(CC)is an essential technology to be used in many fields.Moreover,the Internet of Things(IoT)is employed for more communication flexibility and richness that are required to obtain fruitful services.A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents.This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various utilities and a significant number of IoT devices with low resources.Different agents are integrated based on relevant features of behavioral interaction using classification techniques to balance the workload.Aload balancing algorithm is developed to serve users’requests to improve the solution of workload problems with an efficient distribution.The activity task from IoT devices has been classified by feature selection methods in the preparatory phase to optimize the scalability ofCC.Then,the server’s availability is checked and the classified task is assigned to its suitable server in the main phase to enhance the cloud environment performance.Multi-agent load balancing framework is succeeded to cope with the importance of using large-scale requirements of CC and(low resources and large number)of IoT.
基金supported in part by the Guangdong Basic and Applied Basic Research Foundation under grant 2020A1515110269.
文摘A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.
基金supported by the Bio and Medical Technology Development Program of the National Research Foundation(NRF)funded by the Korean government(MSIT)(No.NRF-2019M3E5D1A02069073)supported by the Soonchunhyang University Research Fund.
文摘Healthcare is a fundamental part of every individual’s life.The healthcare industry is developing very rapidly with the help of advanced technologies.Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises,as well as by patients from their mobile devices through communication interfaces.These systems promote reliable and remote interactions between patients and healthcare professionals.However,there are several limitations to these innovative cloud computing-based systems,namely network availability,latency,battery life and resource availability.We propose a hybrid mobile cloud computing(HMCC)architecture to address these challenges.Furthermore,we also evaluate the performance of heuristic and dynamic machine learning based task scheduling and load balancing algorithms on our proposed architecture.We compare them,to identify the strengths and weaknesses of each algorithm;and provide their comparative results,to show latency and energy consumption performance.Challenging issues for cloudbased healthcare systems are discussed in detail.
文摘Every day,more and more data is being produced by the Internet of Things(IoT)applications.IoT data differ in amount,diversity,veracity,and velocity.Because of latency,various types of data handling in cloud computing are not suitable for many time-sensitive applications.When users move from one site to another,mobility also adds to the latency.By placing computing close to IoT devices with mobility support,fog computing addresses these problems.An efficient Load Balancing Algorithm(LBA)improves user experience and Quality of Service(QoS).Classification of Request(CoR)based Resource Adaptive LBA is suggested in this research.This technique clusters fog nodes using an efficient K-means clustering algorithm and then uses a Decision Tree approach to categorize the request.The decision-making process for time-sensitive and delay-tolerable requests is facilitated by the classification of requests.LBA does the operation based on these classifications.The MobFogSim simulation program is utilized to assess how well the algorithm with mobility features performs.The outcome demonstrates that the LBA algorithm’s performance enhances the total system performance,which was attained by(90.8%).Using LBA,several metrics may be examined,including Response Time(RT),delay(d),Energy Consumption(EC),and latency.Through the on-demand provisioning of necessary resources to IoT users,our suggested LBA assures effective resource usage.
文摘Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex systems.Microservices Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed independently.This methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,etc.and the advantages;Microservices bring some challenges too.Multiple microservices need to be invoked one by one as a chain.In most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s request.It results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of requests.The communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting time.Experiments were done for both interactive as well as non interactive workloads to test the effectiveness of the solution.The approach has been proved to be very effective in reducing latency in the case of long service chains.
基金supported by the project:“Research and Implementation of Innovative Solutions for Monitoring Consumption in Technical Installations Using Artificial Intelligence”,beneficiary S.C.REMONI TECHNOLOGIES RO S.R.L in partnership with“Gheorghe Asachi”Technical University of Iasi,Financing Contract No.400/390076/26.11.2021,SMIS Code 121866,financed by POC/163/1/3.
文摘Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system resources.It is also referred to as a system that will let the consumers utilize computational resources like databases,servers,storage,and intelligence over the Internet.In a cloud network,load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency.It is also known as a server pool or server farm.When a single node is overwhelmed,balancing the workload is needed to manage unpredictable workflows.The load balancer sends the load to another free node in this case.We focus on the Balancing of workflows with the proposed approach,and we present a novel method to balance the load that manages the dynamic scheduling process.One of the preexisting load balancing techniques is considered,however it is somewhat modified to fit the scenario at hand.Depending on the experimentation’s findings,it is concluded that this suggested approach improves load balancing consistency,response time,and throughput by 6%.
文摘Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of the network results in packet loss and Delay(DL).For optimal performance,it is important to load balance between different gateways.As a result,a stable load balancing procedure is implemented,which selects gateways based on Fuzzy Logic(FL)and increases the efficiency of the network.In this case,since gate-ways are selected based on the number of nodes,the Energy Consumption(EC)was high.This paper presents a novel Node Quality-based Clustering Algo-rithm(NQCA)based on Fuzzy-Genetic for Cluster Head and Gateway Selection(FGCHGS).This algorithm combines NQCA with the Improved Weighted Clus-tering Algorithm(IWCA).The NQCA algorithm divides the network into clusters based upon node priority,transmission range,and neighbourfidelity.In addition,the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC,packet loss rate(PLR),etc.
文摘In wireless sensor network(WSN),the gateways which are placed far away from the base station(BS)forward the collected data to the BS through the gateways which are nearer to the BS.This leads to more energy consumption because the gateways nearer to the BS manages heavy traffic load.So,to over-come this issue,loads around the gateways are to be balanced by presenting energy efficient clustering approach.Besides,to enhance the lifetime of the net-work,optimal routing path is to be established between the source node and BS.For energy efficient load balancing and routing,multi objective based beetle swarm optimization(BSO)algorithm is presented in this paper.Using this algo-rithm,optimal clustering and routing are performed depend on the objective func-tions routingfitness and clusteringfitness.This approach leads to decrease the power consumption.Simulation results show that the performance of the pro-posed BSO based clustering and routing scheme attains better results than that of the existing algorithms in terms of energy consumption,delivery ratio,through-put and network lifetime.Namely,the proposed scheme increases throughput to 72%and network lifetime to 37%as well as it reduces delay to 37%than the existing optimization algorithms based clustering and routing schemes.
基金National Key R&D Program of China,Grant/Award Number:2020YFA0710000National Natural Science Foundation of China,Grant/Award Numbers:21573066,21902047,21825201,22075075,22173048,and U1932212China Postdoctoral Science Foundation,Grant/Award Numbers:2020M682540,BX20200116。
文摘Electrocatalytic urea synthesis via coupling of nitrate with CO_(2)is considered as a promising alternative to the industrial urea synthetic process.However,the requirement of sub-reaction(NO_(3)RR and CO_(2)RR)activities for efficient urea synthesis is not clear and the related reaction mechanisms remain obscure.Here,the construction,breaking,and rebuilding of the sub-reaction activity balance would be accompanied by the corresponding regulation in urea synthesis,and the balance of sub-reaction activities was proven to play a vital role in efficient urea synthesis.With rational design,a urea yield rate of 610.6 mg h−1 gcat.−1 was realized on the N-doped carbon electrocatalyst,superior to that of noble-metal electrocatalysts.Based on the operando SRFTIR measurements,we proposed that urea synthesis arises from the coupling of^(*)NO and^(*)CO to generate the key intermediate of^(*)OCNO.This work provides new insights and guidelines into urea synthesis from the aspect of activity balance.
基金supported supported by the National Key Research and Development Program of China(No.2020YFE0200500)CERNET Innovation Project(NGII20190806)。
文摘At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.
基金Supported by China National Major Project of Science and Technology(2016ZX05046-004)PetroChina Major Project of Science and Technology(2017B-4905)PetroChina Jilin Oilfield Company Major Project of Science and Technology(JY21A2-12).
文摘Based on imbibition replacement of shut-in well in tight oil reservoirs, this paper expounds the principle of saturation rebalancing during the shut-in process after fracturing, establishes an optimization method for shut-in time after horizontal well volume fracturing with the goal of shortening oil breakthrough time and achieving rapid oil breakthrough, and analyzes the influences of permeability, porosity, fracture half-length and fracturing fluid volume on the shut-in time. The oil and water imbibition displacement in the matrix and fractures occurs during the shut-in process of wells after fracturing. If the shut-in time is too short, the oil-water displacement is not sufficient, and the oil breakthrough time is long after the well is put into production. If the shut-in time is too long, the oil and water displacement is sufficient, but the energy dissipation in the formation near the bottom of the well is severe, and the flowing period is short and the production is low after the well is put into production. A rational shut-in time can help shorten the oil breakthrough time, extend the flowing period and increase the production of the well. The rational shut-in time is influenced by factors such as permeability, porosity, fracture half-length and fracturing fluid volume. The shortest and longest shut-in times are negatively correlated with porosity, permeability, and fracture half-length, and positively correlated with fracturing fluid volume. The pilot test in tight oil horizontal wells in the Songliao Basin, NE China, has confirmed that the proposed optimization method can effectively improve the development effect of horizontal well volume fracturing.
文摘Aiming at the characteristics of obvious block division and strong discreteness in the assembly production mode of electronic products,this paper proposes a composite U-shaped flexible assembly line model,and establishes a multi-objective optimization mathematical model on this basis.According to the characteristics of the model,the improved ranked positional weight(RPW)method is used to adjust the generation process of the initial solution of the genetic algorithm,so that the genetic algorithm can be applied to the block task model.At the same time,the adaptive cross mutation factor is used on the premise that tasks between different blocks are not crossed during cross mutation,which effectively improves the probability of excellent individuals retaining.After that,the algorithm is used to iterate to obtain the optimal solution task assignment.Finally,the algorithm results are compared with actual production data,which verifies the validity and feasibility of the assembly line model for discrete production mode proposed in this paper.
基金Supported by National Natural Scie nce Foun dation of China(Grant No.51875031)Youth Backb one Personal Project of Beijing(Grant No.2017000020124G018).
文摘Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the operational process,different types of active balancing actuators have been designed and widely applied in actual production.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance parameters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving efficiency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5%.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electromagnetic efficiency and a more stable and compact structure.
文摘Typical rotors such as those on steam turbine or generator are often supported by two bearings with two balance planes at both ends.Vibrations are monitored by a pair of proximity probes at each bearing.There are two approaches to reduce 1X vibration due to unbalance at both ends via balancing with influence coefficient method.The first approach is to treat it as a multiple-plane balancing problem involving 2x2 matrix of complex influence coefficients.The second approach is to treat it as two single-plane balance problems using static(in-phase)and couple(180 degree out-of-phase)components,respectively.Conversion equations of influence coefficients between these two approaches have been found previously by the author.The corresponding spreadsheets that convert influence coefficients between these two formats are presented in the current paper.The paper shows effectiveness of these conversion equations in dealing with real balancing problems in the field.A detailed balance case is presented to demonstrate how the conversion equations are used to reduce vibration effectively.
基金supported by National Science and Technology Support Program of China (Grant No. 2012BAF15G00)
文摘High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.
