Systematic Review:Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.

Hierarchical Bayesian Calibration and On-line Updating Method for Influence Coefficient of Automatic Dynamic Balancing Machine

Measurement error of unbalance＇s vibration response plays a crucial role in calibration and on-line updating of influence coefficient（IC）. Focusing on the two problems that the moment estimator of data used in calibration process cannot fulfill the accuracy requirement under small sample and the disturbance of measurement error cannot be effectively suppressed in updating process, an IC calibration and on-line updating method based on hierarchical Bayesian method for automatic dynamic balancing machine was proposed. During calibration process, for the repeatedly-measured data obtained from experiments with different trial weights, according to the fact that measurement error of each sensor had the same statistical characteristics, the joint posterior distribution model for the true values of the vibration response under all trial weights and measurement error was established. During the updating process, information obtained from calibration was regarded as prior information, which was utilized to update the posterior distribution of IC combined with the real-time reference information to implement online updating. Moreover, Gibbs sampling method of Markov Chain Monte Carlo（MCMC） was adopted to obtain the maximum posterior estimation of parameters to be estimated. On the independent developed dynamic balancing testbed, prediction was carried out for multiple groups of data through the proposed method and the traditional method respectively, the result indicated that estimator of influence coefficient obtained through the proposed method had higher accuracy; the proposed updating method more effectively guaranteed the measurement accuracy during the whole producing process, and meantime more reasonably compromised between the sensitivity of IC change and suppression of randomness of vibration response.

Multi-head neural networks for simulating particle breakage dynamics

The breakage of brittle particulate materials into smaller particles under compressive or impact loads can be modelled as an instantiation of the population balance integro-differential equation.In this paper,the emerging computational science paradigm of physics-informed neural networks is studied for the first time for solving both linear and nonlinear variants of the governing dynamics.Unlike conventional methods,the proposed neural network provides rapid simulations of arbitrarily high resolution in particle size,predicting values on arbitrarily fine grids without the need for model retraining.The network is assigned a simple multi-head architecture tailored to uphold monotonicity of the modelled cumulative distribution function over particle sizes.The method is theoretically analyzed and validated against analytical results before being applied to real-world data of a batch grinding mill.The agreement between laboratory data and numerical simulation encourages the use of physics-informed neural nets for optimal planning and control of industrial comminution processes.

DYNAMICAL BALANCE STUDY OF RING REDUCER

The basic structure of epicyclical gear transmission with inner teeth ofsingle-ring, double-ring, three-ring and four-ring reducer are analyzed. The force analysis model ofring reducer is built. Following this, it is concluded that the present ring reducer~ have theproblem that the inertia force or the inertia moment is lopsided. On the base of analysis andcalculation the balanced ring reducer which can realize the balance of inertia force and inertiamoment is brought forward, and so is its concrete realizing step. The specimen of the balanced ringreducer is designed and manufactured; the experiment is carried out on the gear transmission testbench. Compared with other ring reducer of the same power, the balanced ring reducer has manyadvantages, such as low vibration noise, low cost and less production difficulty and less heat. Itis the substitute of other ring reducer of the same kind. Therefore, it has important theoreticsignificance and highly practical engineering value.

Soil phosphorus dynamic, balance and critical P values in longterm fertilization experiment in Taihu Lake region, China

Phosphorus（P） is an important macronutrient for plant but can also cause potential environmental risk. In this paper, we studied the long-term fertilizer experiment（started 1980） to assess the soil P dynamic, balance, critical P value and the crop yield response in Taihu Lake region, China. To avoid the effect of nitrogen（N） and potassium（K）, only the following treatments were chosen for subsequent discussion, including： C0（control treatment without any fertilizer or organic manure）, CNK treatment（mineral N and K only）, CNPK（balanced fertilization with mineral N, P and K）, MNK（integrated organic manure and mineral N and K）, and MNPK（organic manure plus balanced fertilization）. The results revealed that the response of wheat yield was more sensitive than rice, and no significant differences of crop yield had been detected among MNK, CNPK and MNPK until 2013. Dynamic and balance of soil total P（TP） and Olsen-P showed soil TP pool was enlarged significantly over consistent fertilization. However, the diminishing marginal utility of soil Olsen-P was also found, indicating that high-level P application in the present condition could not increase soil Olsen-P contents anymore. Linear-linear and Mitscherlich models were used to estimate the critical value of Olsen-P for crops. The average critical P value for rice and wheat was 3.40 and 4.08 mg kg^（–1）, respectively. The smaller critical P value than in uplands indicated a stronger ability of P supply for crops in this paddy soil. We concluded that no more mineral P should be applied in rice-wheat system in Taihu Lake region if soil Olsen-P is higher than the critical P value. The agricultural technique and management referring to activate the plant-available P pool are also considerable, such as integrated use of low-P organic manure with mineral N and K.

NUMERICAL EXPERIMENTS ON MULTI-LEVEL STATISTICAL ESTIMATION OF DYNAMIC BALANCE CONSTRAINTS IN GRAPES-3DVAR

This paper further explores the estimating and expressing of dynamic balance constraints using statistical methods in GRAPES-3DVAR(Version GM). Unlike the single-level scheme which only considers the coupling between mass and wind at one level, the multi-level scheme considers the coupling between their vertical profiles and calculates the balanced mass field at each layer using the rotational wind at all model levels. A reformed ridge regression method is used in the new scheme to avoid the multicollinearity problem and reduce the noises caused by unbalanced mesoscale disturbances. The results of numerical experiments show that the new scheme can get more reasonable vertical mass field, reduce the magnitude of the adjustment by the initialization, and improve the potential temperature analysis performance. Furthermore, the results of forecast verification in January(winter) and July(summer) both confirm that the new scheme can significantly improve the temperature forecast accuracy and bring slight positive effects to the pressure and wind forecast.

A New Material Balance Equation Model for Analyzing Dynamic Performance of C_2 Flooding

Implementing a CO2 flooding scheme successfully requires the capacity to get accurate information of reservoir dynamic performance and fluids injected. Despite some numerical simulation studies, the complicated drive mechanisms and actual reservoir performance have not been fully understood. There is a strong need to develop models from different perspectives to complement current simulators and provide valuable insights into the reservoir performance during CO2 flooding. The aim of this study is to develop a model by using an improved material balance equation （MBE） to analyze quickly the performance of CO2 flooding. After matching the historical field data the proposed model can be used to evaluate, monitor and predict the overall reservoir dynamic performance during CO2 flooding. In order to account accurately for the complex displacement process involving compositional effect and multiphase flow, the PVT properties and flowability of reservoir fluids are incorporated in the model. This study investigates the effects of a number of factors, such as reservoir pressure, the amount of CO2 injected, the CO2 partition ratios in reservoir fluids, the possibility of the existence of a free CO2 gas cap, the proportion of reservoir fluids contacted with CO2, the starting time of CO2 flooding, oil swelling, and oil flowability improvement by mixing with CO2. The model was used to analyze the CO2 flooding project in Weyburn oil field, Saskatchewan, Canada. This study shows that the proposed model is an effective complementary tool to analyze and monitor the overall reservoir performance during CO2 flooding.

Salt-Water Dynamics in Soils: V. Salt Balance in Soil Profiles

Salt balance in simulated soil columns was calculated on the basis of a large amount of long termobservation data. The results showed that under the climate conditions of senii-arid region of the Hnaiig-Huai-Hai Plain, the soils in the columns were under salt accumulation conditions when the groundwater depthwas controlled at less than 2.0 m, and under desalinization conditions when at larger than 2.5 m. In the soilcolnmns with clay soil and silty loam soil intercalated with a clay layer, the aniount of salt accumulated wasfar less than that in the soil column with silty loain soil throughout the whole profile. Under no irrigationconditions crop planting niay increase groundwater evaporation and hence salt accumulation in soil, mforingthe soil colnmns under desalinization be under salt accumulation conditions.

ANALYSIS OF METHOD FOR DETERMINING AZIMUTH OF PRINCIPAL AXIS OF INERTIA BASED ON DYNAMIC BALANCE MEASUREMENT

The dynamic balance quality of a rotating object is an important factor to maintain the stability and accuracy for motion. The azimuth of the principal axis of inertia is a major sign of dynamic balance. A usual method is measuring moment of inertia matrix relative to some base coordinates on a rotary inertia machine so as to calculate the azimuth of principal axis of inertia, By using the measured unbalance results on the two trimmed planes on a vertical hard bearing double-plane dynamic balancing machine, the dimension and direction of couple unbalance can be found. An azimuth angle formula for the principal axis of inertia is derived and is solved by using unbalance quantities. The experiments indicate that method based on dynamic balancing measurement is proved rational and effective and has a fine precision.

On-line real-time path planning of mobile robots in dynamic uncertain environment

A new path planning method for mobile robots in globally unknown environment with moving obstacles is pre- sented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predicted position taken as the next position of moving obstacles, a motion path in dynamic uncertain environment is planned by means of an on-line real-time path planning technique based on polar coordinates in which the desirable direction angle is taken into consideration as an optimization index. The effectiveness, feasibility, high stability, perfect performance of obstacle avoidance, real-time and optimization capability are demonstrated by simulation examples.

Local dynamic balance theory and technology of flow field in multilayer gob area

Flow field in multilayer gob area, which formed in small hiden-depth, multi-coal layer groups, close distance, hard coal layer, and hard roof, possesses characteristics such as complex, changeable and unstable. Dynamic balance theory of local flow field in multilayer gob area was built based on the realistic requirement that the serious threat on current mining coal layer by large-scale spontaneous combustion fire on close spontaneous combustion coal layer group of Datong Coal mining area at the ＇di-hard＇ conditions was caused by small coal pit mining. The kernel was in dynamic balance between flow field pressures of working face and local flow field in multilayer gob area was kept by transformation. Corresponding technology and set of devices were developed.

Equivalence of Dynamicity and Balance of Category in “INCEPTION”

"INCEPTION" has become a blockbuster recently and this word reflects the phenomenon:meaning expanding in a specific context,which,as a matter of fact,lives in many fields such as literature,films and speeches.Such words or phrases have both surface and deep meanings whose translation research is mainly placed on literal or literary transfer,leaving out their dynamicity and balance in meaning category.This paper aims to give a brief analysis on such phenomenon and puts forward to a new translation principle:category equivalence in dynamicity and balance.

A RESEARCH ON THE DYNAMIC MONITORING SYSTEM FOR FORAGE-LIVESTOCK BALANCE IN THE TEMPERATE CRASSLAND OF CHINA

Some principles and methods for the dynamic monitoring of forage-livestock bal-ance in the grazing system on the temperate grassland of China were discussed in thispaper. To prepare a dynamic monitoring system or the forage livestock balance of grazingrangeland system, the following theoretical bases will be observed in this work.

Yang’s Dynamic Vertical Balance Process for the Content of Cd in a Marine Bay

This study analyzes the horizontal and vertical migration processes of Cd contents based on the investigations conducted during May and August 1990. It reveals the dynamic balance process of Cd substance in a marine bay and shows that in the waters close to the source input, the content of Cd in the surface waters is the highest, and also the vertical dilution amount is the highest. This is the beginning of the dynamic vertical balance process. Along with distance from the source input, the sedimentation is an ongoing process, which results in a decrease in the content of Cd in the surface waters, and a reduction in the vertical dilution amount. This process continues to the balance point. In waters far away from the source input, the content of Cd is homogeneous in the waters, and the vertical dilution amount decreases to the lowest value, i.e., the balance point. Furthermore, a block diagram has been provided to demonstrate the dynamic vertical balance process.

Dynamic Balance in Children With Trisomy 21:A Pilot Study

At age 5,children with trisomy 21 have roughly 2 years of delayed motor development.We aimed to verify if children with trisomy 21(AD)(N=6,7.67±1.51 years)had a similar performance to children with a typical development(TD)(N=37,5.19±0.40 years old),in a playful motor action(to spin on herself until she cannot get more).On average,ADs gave less laps,for less time,spending more time per rotation,but without significant difference.Of the AD,one-third fell and rose to continue to spin;one-third stopped and resumed spinning(with intervals of 2.05±0.86s).Three ADs performed the action counterclockwise and the other three in clockwise direction.The results support the hypothesis that AD can perform the activity of spinning,with DT(significantly)younger,allowing to AD momentary pauses and conditions for their physical security.

Dynamic load balancing based on restricted multicast tree in triplet-based hierarchical interconnection network

To solve the load balancing problem in a triplet-based hierarchical interconnection network（THIN） system, a dynamic load balancing （DLB）algorithm--THINDLBA, which adopts multicast tree （MT）technology to improve the efficiency of interchanging load information, is presented. To support the algorithm, a complete set of DLB messages and a schema of maintaining DLB information in each processing node are designed. The load migration request messages from the heavily loaded node （HLN）are spread along an MT whose root is the HLN. And the lightly loaded nodes（LLNs） covered by the MT are the candidate destinations of load migration; the load information interchanged between the LLNs and the HLN can be transmitted along the MT. So the HLN can migrate excess loads out as many as possible during a one time execution of the THINDLBA, and its load state can be improved as quickly as possible. To avoid wrongly transmitted or redundant DLB messages due to MT overlapping, the MT construction is restricted in the design of the THINDLBA. Through experiments, the effectiveness of four DLB algorithms are compared, and the results show that the THINDLBA can effectively decrease the time costs of THIN systems in dealing with large scale computeintensive tasks more than others.

Adaptive delay-energy balanced partial offloading strategy in Mobile Edge Computing networks

Mobile Edge Computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy requirements.In this paper,we propose a flexible MECbased requirement-adaptive partial offloading model to accommodate each user's specific preference regarding delay and energy consumption.To address the dimensional differences between time and energy,we introduce two normalized parameters and then derive the computational overhead of processing tasks.Different from existing works,this paper considers practical variations in the user request patterns,and exploits a flexible partial offloading mode to minimize computation overheads subject to tolerable delay,task workload and power constraints.Since the resulting problem is non-convex,we decouple it into two convex subproblems and present an iterative algorithm to obtain a feasible offloading solution.Numerical experiments show that our proposed scheme achieves a significant improvement in computation overheads compared with existing schemes.

Learning-Based Dynamic Connectivity Maintenance for UAV-Assisted D2D Multicast Communication

Unmanned aerial vehicles(UAVs) enable flexible networking functions in emergency scenarios.However,due to the movement characteristic of ground users(GUs),it is challenging to capture the interactions among GUs.Thus,we propose a learningbased dynamic connectivity maintenance architecture to reduce the delay for the UAV-assisted device-todevice(D2D) multicast communication.In this paper,each UAV transmits information to a selected GU,and then other GUs receive the information in a multi-hop manner.To minimize the total delay while ensuring that all GUs receive the information,we decouple it into three subproblems according to the time division on the topology:For the cluster-head selection,we adopt the Whale Optimization Algorithm(WOA) to imitate the hunting behavior of whales by abstracting the UAVs and cluster-heads into whales and preys,respectively;For the D2D multi-hop link establishment,we make the best of social relationships between GUs,and propose a node mapping algorithm based on the balanced spanning tree(BST) with reconfiguration to minimize the number of hops;For the dynamic connectivity maintenance,Restricted Q-learning(RQL) is utilized to learn the optimal multicast timeslot.Finally,the simulation results show that our proposed algorithms perfor better than other benchmark algorithms in the dynamic scenario.

Dynamic and Integrated Load-Balancing Scheduling Algorithm for Cloud Data Centers

One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.

A Dynamic Load Balancing Method of Cloud-Center Based on SDN

In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What＇s more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput.