Load Balancing System Research Articles

A scheduling algorithm based on critical factors for heterogeneous multicore processors

SummaryAs the development of chip manufacturing technology slows down, high‐performance processors often have high energy consumption and high heat generation. Therefore, heterogeneous multi‐core processors become more and more popular, and the heterogeneous multi‐core processors is adopted to execute programs. At present, the general program consists of multiple threads. To reach goals of accelerating program execution and reducing energy consumption and heat generation of system, a suitable thread scheduling algorithm for heterogeneous multi‐core processors is needed. In this article, a thread scheduling algorithm based on multiple critical scheduling factors is proposed. First, a prediction model of thread performance and energy consumption is used to predict the core sensitivity of threads. Then, critical threads are judged and accelerated by collecting the synchronization information between threads. Finally, the load balancing method based on the computing power of cores and the core sensitivity of threads is employed to perform system load balancing, which ensures the fairness of the scheduling. Several experiments are provided, and the results show that the proposed algorithm can obtain better performance of thread schedule.

Balancing of four wire loads using linearized H-bridge static synchronous compensators

<p>In this paper, a load balancing system is designed to balance the secondary phase currents of 11 kV/380 V, 50 Hz, 100 kVA power transformer in a three phase 4-wire, distribution network. The load balancing system is built of six identical modified static synchronous compensators (M-STATCOMs). Each M-STATCOM is constructed of a voltage source converter-based H-bridge controlled in capacitive and inductive modes as a linear compensating susceptance. The M-STATCOM current is controlled by varying its angle such that it exchanges pure reactive current with the utility grid. Three identical M-STATCOMs are connected in delta-form to balance the active phase currents of the power transformer, whereas the other three identical M-STATCOMs are connected in star-form to compensate for reactive currents. The M-STATCOMs in the delta-connected compensator are driven by 380 V line-to-line voltages, whilst, those connected in star-form are driven by 220 V phase voltages. The results of the 220 V and 380 V M-STATCOMs have exhibited linear and continuous control in capacitive and inductive regions of operation without steady-state harmonics. The proposed load balancing system has offered high flexibility during treating moderate and severe load unbalance conditions. It can involve any load unbalance within the power transformer current rating and even unbalance cases beyond the power transformer current rating.<strong></strong></p>

Load balancing policies without feedback using timed replicas

Dispatching policies such as join the shortest queue (JSQ), join the queue with smallest workload (JSW), and their power of two variants are used in load balancing systems where the instantaneous queue length or workload information at all queues or a subset of them can be queried. In situations where the dispatcher has an associated memory, one can minimize this query overhead by maintaining a list of idle servers to which jobs can be dispatched. Recent alternative approaches that do not require querying such information include the cancel-on-start and cancel-on-complete replication policies. The downside of such policies however is that the servers must communicate either the start or the completion time instant of each service to the dispatcher and must allow the coordinated and instantaneous cancellation of all redundant replicas. In practice, the requirements of query messaging, memory, and replica cancellation pose challenges in their implementation and their advantages are not clear. In this work, we consider load-balancing policies that do not need to query load information, do not need memory, and do not need to cancel replicas. Our policies allow the dispatcher to append a timer to each job or its replica. A job or a replica is discarded if its timer expires before it starts receiving service. We analyze several variants of this policy which are novel and simple to implement. We numerically observe that the variants of the proposed policy outperform popular feedback-based policies for low arrival rates, despite no feedback from servers to the dispatcher.

Exponential Tail Bounds on Queues

A popular approach to computing performance measures of queueing systems (such as delay and queue length) is studying the system in an asymptotic regime. However, these results are only valid in the limit and often provide bounds for the pre-limit systems that are not optimized and, hence, give loose bounds for the tail probabilities. In this paper, we provide optimized bounds for the tail probabilities of the scaled total queue length in a load-balancing system under Join the Shortest Queue (JSQ). Our bounds characterize the rate of convergence of the tail probabilities to the corresponding heavy traffic values. For the tail probability of the JSQ system, our bounds yield a multiplicative error that arises from three factors: pre-limit tail, pre-exponent error, and State-Space Collapse (SSC). As an immediate corollary of our main theorem, we provide a bound to the tail probabilities of a single-server queue. In this case, the multiplicative error only consists of pre-limit tail and pre-exponent error, since there is no state-space collapse.

NETWORK ANALYSIS AND OPTIMIZATION USING LOAD BALANCING TECHNIQUES

The Internet is currently growing rapidly. The needs and rapid developments in the use of the Internet network require a balance in the provision of Internet facilities. Internet standard service is the continuation of the connectivity of the Internet. Connection from the Internet is required to always be maintained under any circumstances, but connectivity will not always run smoothly, many obstacles or disturbances are encountered so that the connection does not run smoothly. Then backup management is needed from the continuity of the connection from the Internet so that if one connection is interrupted, there will be a backup. One thing that can be done is to use a load-balancing system. The subjects taken in this study focus on implementing backups from Internet network sources or backups from dependency on one Internet service provider. The method used in this study uses literature study and observation, namely direct observation of the network at the Benteng Village Village Office. the design starts with selecting the right ISP source to be used as a backup. The design is continued with the Mikrotik installation and the application of load balancing in Mikrotik. testing of the load balancing system is carried out by technical testing of the implementation that has been carried out. by testing the speed, load balancing function, and testing optimization of the load balancing. Based on the tests carried out in this study, it resulted in the optimal application of load balancing. The application of load balancing can run without changing the existing network and makes the connection run more optimally if there is an increase in network traffic due to the distribution of balanced connection lanes

Load Balancing and Fail Over MikroTik Implementation Using Per Connection Classifier (PCC) on Two Internet Providers Interconnection

Load balancing is tasked with dividing and balancing the traffic load on two or more ISPs in a balanced way so that the output obtained when using this technique is to maximize throughput, minimize response time and avoid overload on one ISP line when one of the ISPs experiences a disconnection. This can be seen from the automatic connection switching to an active ISP gateway, so that network performance continues to run normally. Throughput testing in the morning, afternoon, and evening showed very good value changes after load balancing was applied. Delay and Packet Loss tests also show a change in value from bad to very good after the implementation of the Load balancing system. The results of this study indicate that in measuring network performance for conditions of delay, packet loss, jitter and throughput before and after system implementation using load balancing and failover with the Per Connection Classifier (PCC) method, different results were found

Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data

With the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-field data for real-time interactive visualization, this paper proposes novel strategies for data partitioning and communication management. Firstly, we propose a data-partitioning strategy based on grid segmentation. This approach constructs metadata to create file viewports for each process and performs grid partitioning. Subsequently, it reconstructs sub-grids within each process and utilizes a coordinate-mapping algorithm to map global coordinates to local process coordinates, facilitating access to attribute variables through a lookup table. Secondly, we introduce a real-time interactive method for large-scale flow fields. This method leverages the system architecture of high-speed interconnection among compute nodes in a cluster environment and low-speed interconnection between service nodes and rendering nodes. It enables coordinated management of parallel rendering and synchronized rendering methods. The experimental results on typical flow-field data demonstrate that the proposed data-partitioning strategy improves the loading speed of millions of grid-level data by a factor of 7, surpassing ParaView’s performance by 1.5 times. Furthermore, it achieves system load balancing. Real-time interaction experiments with datasets containing 500 million and 800 million grid cells exhibit millisecond-level latencies, demonstrating the effectiveness of the proposed communication management method in meeting the real-time interactive visualization demands of large-scale flow-field data.

Energy saving through load balancing of 3-wire loads

<span lang="EN-US">In this paper, static var compensators (SVCs) and many load compensation techniques are reviewed. A continuously and linearly controlled compensating susceptance is devised from a switched capacitor bank and a switched reactor bank. The switched capacitor bank is built of four binary weighted thyristor switched capacitors, while the switched reactor bank is built of three binary weighted thyristor switched reactors. Although few switched capacitors and reactor are used, their binary weighted values beside their control scheme make them respond as a continuously and linearly controlled reactive device in capacitive and inductive modes of operation. A load balancing system is constructed of three identical devised compensating susceptances connected in delta-form. It is designed for balancing an 11 kV 50 Hz distribution station. The proposed system is designed and tested on PSpice which is a computer program equivalent in performance to real hardware design. The simulation results of the proposed system have showed significant treatment of severe imbalance conditions.</span>

A Q-Learning-Based Load Balancing Method for Real-Time Task Processing in Edge-Cloud Networks

Edge computing has emerged as a promising solution to reduce communication delays and enhance the performance of real-time applications. However, due to the limited processing power of edge servers, it is challenging to achieve efficient task processing. In this paper, we propose a Q-learning-based load-balancing method that optimizes the distribution of real-time tasks between edge servers and cloud servers to reduce processing time. The proposed method is dynamic and adaptive, taking into account the constantly changing network status and server usage. To evaluate the effectiveness of the proposed load-balancing method, extensive simulations are conducted in an Edge-Cloud network environment. The simulation results demonstrate that the proposed method significantly reduces processing time compared to traditional static load-balancing methods. The Q-learning algorithm enables the load-balancing system to dynamically learn the optimal decision-making strategy to allocate tasks to the most appropriate server. Overall, the proposed Q-learning-based load-balancing method provides a dynamic and efficient solution to balance the workload between edge servers and cloud servers. The proposed method effectively achieves real-time task processing in edge computing environments and can contribute to the development of high-performance edge computing systems.

Load balancing for multi-beam additive manufacturing systems

Load balancing for multi-beam additive manufacturing systems

HARMONIC: Shapley values in market games for resource allocation in vehicular clouds

Real-time allocation of resources to fulfill service requests from road vehicles is becoming increasingly complex, for two main reasons: the continuous increase in the number of Internet-connected vehicles on roads all over the world, and the emergence of complex and resource-greedy applications that require fast execution, often under limited availability of computational resources. While many resource allocation solutions to this problem have been proposed recently, these solutions rely on unrealistic scenarios and constraints that limit their practical use.This paper presents HARMONIC, a Game Theory-based coalition game that aims to maximize resource utilization and dynamically balance resource usage across multiple Vehicular Clouds (VCs). HARMONIC employs a Shapley value-based strategy to determine the order of task allocation to available resources. It is built upon our proposed Market Game model, specifically designed to address resource allocation challenges in dynamic VCs. We conduct a comparative analysis with existing literature solutions under various scenarios and resource constraints to evaluate HARMONIC’s performance. Our simulation results demonstrate that HARMONIC achieves resource allocation in fewer rounds and with fewer failures. Furthermore, it effectively distributes tasks to more VCs, improving load balancing and overall system efficiency.

Network Design Using Load Balancing Equal Cost Multi Path (ECMP) Method At Lexima Consultant Office

The development of technological advances also contributed to the advancement of Internet technology. Where the Internet is one of the needs that is considered important in all fields, this is evidenced by the number of Internet users from 2020 to 2023 having a significant increase. Lexima Consultant as one of the institutions engaged in information system creation services, of course, requires an internet connection. However, there are several obstacles faced, one of which is the absence of a load balancing and failover network system which sometimes makes the need for internet access with large bandwidth allocations to be disrupted and even cut off. Implementing the right technique at the Lexima Consultant office for sending data packets as the main factor supporting activities is certainly very much needed. In the research conducted, a load balancing technique was used using the ECMP method to optimize network performance and avoid internet network disturbances. From the research conducted, it can be concluded that the implementation of the load balancing method using the ECMP method has been able to divide connection paths and failover can run properly, so the possibility of disruption in the form of a network connection loss will be very small

A real-time and ACO-based offloading algorithm in edge computing

With the increasingly widespread use of networks and end devices, more and more data and computations must be processed. With processing constrained by the limited resources of the end device, edge computing plays an important role. Edge computing offloads computation to surrounding edge nodes with corresponding computing capabilities so that the end device can get a response within a reasonable latency to meet the user's needs. Since these edge nodes are composed of multiple heterogeneous computing units, any system's task-offloading strategy must necessarily affect the system's load balance and execution time. This study proposes a real-time, two-stage ant colony algorithm (RTACO) with the following goals: 1) the algorithm requires low latency; 2) the algorithm minimizes the makespan of all tasks; 3) the algorithm optimizes the system load and reduces the burden of the task-offloading algorithm, thereby providing a stable and high-performance edge computing system. Experiments show that RTACO requires low execution time, and can still effectively achieve good results even when the system has limited resources.

A hybrid GA-PSO strategy for computing task offloading towards MES scenarios.

As a new type of computing paradigm closer to service terminals, mobile edge computing (MEC), can meet the requirements of computing-intensive and delay-sensitive applications. In addition, it can also reduce the burden on mobile terminals by offloading computing. Due to cost issues, results in the deployment density of mobile edge servers (MES) is restricted in real scenario, whereas the suitable MES should be chosen for better performance. Therefore, this article proposes a task offloading strategy under the sparse MES density deployment scenario. Commonly, mobile terminals may reach MES through varied access points (AP) based on multi-hop transmitting mode. The transmission delay and processing delay caused by the selection of AP and MES will affect the performance of MEC. For the purpose of reducing the transmission delay due to system load balancing and superfluous multi-hop, we formulated the multi-objective optimization problem. The optimization goals are the workload balancing of edge servers and the completion delay of all task offloading. We express the formulated system as an undirected and unweighted graph, and we propose a hybrid genetic particle swarm algorithm based on two-dimensional genes (GA-PSO). Simulation results show that the hybrid GA-PSO algorithm does not outperform state-of-the-art GA and NSA algorithms in obtaining all task offloading delays. However, the workload by standard deviation approach is about 90% lower than that of the GA and NSA algorithms, which effectively optimizes the performance of load balancing and verifies the effectiveness of the proposed algorithm.

A Distributed Approach for Time-Dependent Observation Scheduling Problem in the Agile Earth Observation Satellite Constellation

The increasing number of agile earth observation satellites (AEOSs) in orbit have advanced maneuverable capabilities, enabling the AEOS constellation to provide richer observation services. Therefore, observation scheduling in the AEOS constellation is crucial for improving the performance of satellite remote sensing systems. This paper focuses on the problem of distributed observation scheduling in the AEOS constellation, where a period of transition time is required between two consecutive observations, and this constraint depends on the start time of observations. We define a new fitness function that not only maximizes the profit sum but also considers system load balancing. Based on the fundamental idea of a distributed performance impact (PI) algorithm, we develop a PI-based distributed scheduling method (PIDSM) that runs concurrently on all AEOSs via local inter-satellite link (ISL)-based communications. The PIDSM iterates between two phases: target inclusion and consensus and target removal. The first phase aims to select the optimal task for each AEOS, while the second phase reaches a consensus over all AEOSs and removes targets that may decrease overall fitness. Experimental results demonstrate that the PIDSM can schedule more targets, reduce communication overhead, and achieve higher fitness values than existing algorithms. Sensitivity analyses further validate the effectiveness of the PIDSM.

Research on Electric Boiler Auxiliary Thermal Power Unit Operation in Isolated Grid

An electric boiler is widely used in the research and application of thermal power flexibility transformation because of its fast regulation and strong energy storage capacity. However, as an electrical load with high flexibility, the value of isolated operation of auxiliary units in case of grid line failures has not been fully recognized. This paper studies the unit load balance system, unit isolated network operation decision-making, unit load switching, steam turbine control, and boiler control of live boiler operation, so as to realize the control function of an electric boiler assisting the isolated network operation of the thermal power unit, ensure that the unit can stably turn into the isolated network operation state in case of grid failure, and effectively ensure the heating of residents and the rapid restoration of grid power supply.

A near-optimal & load balanced resilient system design for high-performance computing platform

A near-optimal & load balanced resilient system design for high-performance computing platform

The Statewide Patient Load Balancing Work of Washington State's Medical Operations Coordination Center.

Load balancing of constrained healthcare resources has become a critical aspect of assuring access to care during periods of pandemic related surge. These impacts include patient surges, staffing shortages, and limited access to specialty resources. This research focuses on the creation and work of a novel statewide coordination center, the Washington Medical Coordination Center (WMCC), whose primary goal is the load balancing of patients across the healthcare continuum of Washington State. This article discusses the origins, development, and operations of the WMCC including key partners, cooperative agreements, and structure necessary to create a patient load balancing system on a statewide level. As of April 21, 2022, the WMCC received 3821 requests from Washington State hospitals. Nearly 90% were received during the pandemic surge. Nearly 75% originated from rural hospitals that are most often limited in their ability to transfer patients when referral centers are also overwhelmed. The WMCC served as an effective tool to carry out patient load balancing activities during the COVID-19 pandemic surge in Washington State. It (the WMCC) has been shown to be an equity enhancing, cost effective means of managing healthcare surge events across a broad geographic region.

Improved round-robin rule learning for optimal load balancing in distributed cloud systems

A newly emerging technology that distributes virtualised computer resources across the internet is referred to as 'cloud computing' and is gaining popularity. These clouds' ability to evenly distribute the load is vital. Load balancing in cloud computing distributes dynamic workloads so no database server is overcrowded or underloaded (LB). As a result, a dynamic load balancing technique in the cloud may contribute to improved service stability and resource utilisation. In this study, we model a load balancing system that balances the cloud's available resources using a rule-based round-robin method. Cloud parameters are used to calculate and allocate resources using a rule-based round-robin technique. The study analyses cloud metrics to determine cloud loads and resources. The cloud sim tool is used to allocate resources, and its effectiveness is tested against a variety of performance measures such as overhead, migration time, and throughput rate. Simulation results show that rule-based round-robin improves cloud performance. When compared to existing algorithms, the proposed methodology improves task performance by about 4%.

ACO-Inspired Load Balancing Strategy for Cloud-Based Data Centre with燩redictive Machine Learning Approach

Virtual Machines are the core of cloud computing and are utilized to get the benefits of cloud computing. Other essential features include portability, recovery after failure, and, most importantly, creating the core mechanism for load balancing. Several study results have been reported in enhancing load-balancing systems employing stochastic or biogenetic optimization methods. It examines the underlying issues with load balancing and the limitations of present load balance genetic optimization approaches. They are criticized for using higher-order probability distributions, more complicated solution search spaces, and adding factors to improve decision-making skills. Thus, this paper explores the possibility of summarizing load characteristics. Second, this study offers an improved prediction technique for pheromone level prediction over other typical genetic optimization methods during load balancing. It also uses web-based third-party cloud service providers to test and validate the principles provided in this study. It also reduces VM migrations, time complexity, and service level agreements compared to other parallel standard approaches.