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Hidden Markov Model-based load balancing in Data Center Networks

COMPUTER JOURNAL 2020年第10期63卷 1449-1462页

作者： He, Binjie Zhang, Dong Zhao, Chang Fuzhou Univ Coll Math & Comp Sci Fuzhou Fujian Peoples R China

Modern data centers provide multiple parallel paths for end-to-end communications. Recent studies have been done on how to allocate rational paths for data flows to increase the throughput of data center networks. A centralized load balancing algorithm can improve the rationality of the path selection by using path bandwidth information. However, to ensure the accuracy of the information, current centralized load balancing algorithms monitor all the link bandwidth information in the path to determine the path bandwidth. Due to the excessive link bandwidth information monitored by the controller, however, much time is consumed, which is unacceptable for modern data centers. This paper proposes an algorithm called hidden Markov Model-based load balancing (HMMLB). HMMLB utilizes the hidden Markov Model (HMM) to select paths for data flows with fewer monitored links, less time cost, and approximate the same network throughput rate as a traditional centralized load balancing algorithm. To generate HMMLB, this research first turns the problem of path selection into an HMM problem. Secondly, deploying traditional centralized load balancing algorithms in the data center topology to collect training data. Finally, training the HMM with the collected data. Through simulation experiments, this paper verifies HMMLB's effectiveness.

关键词： hidden Markov Model (HMM) load balancing algorithm data center

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Best effort strategy and virtual load for asynchronous iterative load balancing

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JOURNAL OF COMPUTATIONAL SCIENCE 2018年 26卷 118-127页

作者： Couturier, Raphael Giersch, Arnaud Hakem, Mourad Univ Bourgogne Franche Comte FEMTO ST Inst Belfort France

Most of the time, asynchronous load balancing algorithms are extensively studied from a theoretical point of view. The Bertsekas and Tsitsiklis' algorithm [1] is undeniably the best known algorithm for which the asymptotic convergence proof is given. From a practical point of view, when a node needs to balance a part of its load to some of its neighbors, the algorithm's description is unfortunately too succinct, and no details are given on what is really sent and how the load balancing decisions are made. In this paper, we propose a new strategy called best effort which aims at balancing the load of a node to all its less loaded neighbors while ensuring that all involved nodes by the load balancing phase have the same amount of load. Moreover, since asynchronous iterative algorithms are less sensitive to communication delays and their variations [2], both load transfer and load information messages are dissociated. To speedup the convergence time of the load balancing process, we propose a clairvoyant virtual load heuristic. This heuristic allows a node receiving a load information message to integrate the future virtual load (if any) in its load's list, even if the load has not been received yet. This leads to have predictive snapshots of nodes' loads at each iteration of the load balancing process. Consequently, the notified node sends a real part of its load to some of its neighbors, taking into account the virtual load it will receive in the subsequent time-steps. Based on the SimGrid simulator, some series of test-bed scenarios are considered and several QoS metrics are evaluated to show the usefulness of the proposed algorithm. (C) 2018 Elsevier B.V. All rights reserved.

关键词： load balancing algorithm Virtual load Simulation with SimGrid

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load balancing Based on Multi-Agent Framework to Enhance Cloud Environment

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Computers, Materials & Continua 2023年第2期74卷 3015-3028页

作者： Shrouk H.Hessen Hatem M.Abdul-kader Ayman E.Khedr Rashed K.Salem Information Systems Department Faculty of Computers and InformationMenoufia UniversityShebin ElkomEgypt Information Systems Department Faculty of Computers and Artificial IntelligenceSouth Valley UniversityHurghadaEgypt Information Systems Department Faculty of Computers and Information TechnologyFuture University in Egypt(FUE)CairoEgypt

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 ***,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 *** 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 *** agents are integrated based on relevant features of behavioral interaction using classification techniques to balance the *** balancing algorithm is developed to serve users’requests to improve the solution of workload problems with an efficient *** activity task from IoT devices has been classified by feature selection methods in the preparatory phase to optimize the scalability ***,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 ***-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.

关键词： Cloud computing IoT multi-agent system load balancing algorithm server utilities

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Critical analysis of load balancing strategies for cloud environment

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INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND DISTRIBUTED SYSTEMS 2017年第3-4期18卷 213-234页

作者： Jain, Anurag Kumar, Rajneesh Chandigarh Engn Coll Dept Comp Sci & Engn Mohali Punjab India Maharishi Markandeshwar Univ Maharishi Markandeshwar Engn Coll Dept Comp Sci & Engn Mullana Ambala India

Future of cloud computing depends on effective installation of infrastructure, efficient utilisation of resources and dynamic transformation of load. Due to inundation of tasks at the data centre there is a need for load balancing strategy. This will help in achieving better fault tolerance ratio and higher customer satisfaction. load balancing strategy plays an important role in the distribution of the workload dynamically across multiple nodes so that no server is either underutilised or overwhelmed. Also, due to data proliferation nature of data sources such as social media sites, geographical information systems and the weather forecasting system, there is an exponential growth of structured and unstructured data which is called big data. The present data models are not capable enough to handle big data. To process the data efficiently, there is also a need of load balancing strategy at the data centre level. In this paper, the authors experimentally analyse some popular approaches for load balancing of tasks in a cloud environment using the cloud analyst simulator.

关键词： cloud computing cloud analyst load balancing task scheduling load balancing algorithm big data

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An Efficient load balancing Approach for N-Hierarchical Web Server Cluster

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Wuhan University Journal of Natural Sciences 2015年第6期20卷 537-542页

作者： PAK Ilchol QIAO Baiyou SHEN Muchuan ZHU Junhai CHEN Donghai College of Information Science and Engineering Northeastern University College of Information Science and Technology Kim Chaek University of Technology

Aiming at the load imbalance and poor scalability in single-tier Web server clusters, an efficient load balancing ap- proach is proposed for constructing an N-hierarchical （multi-tier） Web server cluster. In each layer, multiple load balancers are set to receive the user requests simultaneously, and different load bal- ancing algorithms are used to construct the high-scalable Web cluster system. At the same time, an improved load balancing al- gorithm is proposed, which can dynamically calculate weights according to the utilization of the server resources, and reasonably distribute the loads for each server according to the load status of the servers. The experimental results show that the proposed ap- proach can greatly decrease the load imbalance among the Web servers and reduce the response time of the entire Web cluster system.

关键词： Web server cluster load balancing algorithm scalability availability

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Efficient WMaxMin Static algorithm For load balancing In Cloud Computation

Efficient WMaxMin Static Algorithm For Load Balancing In Clo...

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International Conference on Innovations in Power and Advanced Computing Technologies

作者： Bharat Khatavkar Prabadevi Boopathy Mtech IT Networking VIT University (SITE) Vellore India-632014 Assistant Professor VIT University (SITE) Vellore India-632014

ISBN: (纸本)9781509056835

Cloud Computing is the new emerging area which provides variety of deployment as well as service model such as SAAS, PAAS and IAAS and it is in rapid adoption by many vendors and companies which are growing in the fast rate. Most critical functionality in Cloud Computation is load balancing because the data centers have n number of hosts and these host comprises of n number of virtual machines, so when tasks (cloudlets) comes it must be assigned to the virtual machines without overloaded and under loaded any of the VMs. There are many algorithms for load balancing in cloud but still the problem persists. Here the idea is to combine the Weighted Round Robin and Max Min algorithm to implement an efficient load balancing algorithm which is WeightedMaxMin by taking two consideration factors viz., waiting time and Response time. The simulation and implementation is through CloudSim.

关键词： Cloud Computation Cloudlets Virtual Machine load balancing algorithm data centres Host CloudSim WMaxMin

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Distribution System Loss Reduction by Automatic Transformer load balancing 20

Distribution System Loss Reduction by Automatic Transformer ...

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20th International Multi-Topic Conference (INMIC)

作者： Ali, Basit Siddique, Imran Bahria Univ Karachi Karachi Pakistan Islamabad Elect Supply Co Islamabad Pakistan

ISBN: (纸本)9781538623039

This paper presents the innovative solution of the unbalanced phases in the LV (low voltage) networks. A realistic data of eight transformers with different power rating has been taken. The data has been gathered from the area where unbalance phase problem is relatively frequent. An automatic phase load balancing methodology is proposed which can balance the load on three phases of transformers using a monitoring system. This system continuously checks the load on phases and gives feedback to the main control center. It gives command to each Slave unit through which switching device is connected. Furthermore power loss comparison and their economic effects before and after implementing the proposed technique have been discussed.

关键词： Distribution system main control center load balancing algorithm

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The Internet-based Electrical Engineering Virtual Lab: Using load-balancing Cluster System

The Internet-based Electrical Engineering Virtual Lab: Using...

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International Conference on Manufacturing Engineering and Automation (ICMEA 2012)

作者： Chen, Jianfeng Zhang, Shouheng Zhu, Shan'an Zhejiang Univ Coll Elect Engn Hangzhou 310003 Zhejiang Peoples R China

ISBN: (纸本)9783037855300

In order to promote the development of Chinese modem education and relative technologies, this paper proposes the Internet-based Electrical Engineering Virtual Lab (iEEVL). iEEVL is a type of distant education. It virtualizes the electric and electronic experiments, and makes it possible to do online experiments by students. Besides, iEEVL uses the load-balancing cluster system to help it work well. The cluster is mainly based on the technologies of two-tier load-balancing algorithm, Twisted server framework, server virtualization and Modelica technology, and acts an important role in iEEVL. It not only realizes the computing function of the virtual experiments, meets the requirements of balanced distribution and high concurrency, but also improves the stability and scalability of iEEVL.

关键词： Internet-based Electrical Engineering Virtual Lab (iEEVL) Cluster Twisted load balancing algorithm Server Virtualization Modelica Distant Education

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A Data Collection Technology of Virtual Reality Simulation System Based on load balancing 11

A Data Collection Technology of Virtual Reality Simulation S...

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11th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

作者： Ma, Denghui Zuo, Xin Yue, Yuanlong Qian, Kewei China Univ Petr Coll Informat Sci & Engn Beijing Peoples R China

ISBN: (纸本)9781728118598

Aiming at the problem of high load on data collection site caused by a large amount of real-time data are stored in the database in a large-scale virtual reality simulation system. A distributed data collection scheme was proposed. Firstly, this paper introduced the overall architecture of the virtual reality simulation system for subsea production process of oil and gas and analyzed the data flow of the system. Secondly, based on this virtual reality simulation system, a distributed data collection module was designed. The whole data collection module took the distributed database as the core, and adopted an algorithm combining static load distribution and dynamic collection task scheduling to distribute data collection tasks to each site according to the performance of each index of its server. Then, in the process of data collection, the collection task part of the site with larger load was automatically distributed to the site with smaller load in real time, so that the load of each site was balanced.

关键词： component virtual reality simulation system distributed data collection load balancing algorithm

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An improved load balanced metaheuristic scheduling in cloud

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第5-Sup期22卷 10873-10881页

作者： Aruna, M. Bhanu, D. Karthik, S. Surya Engn Coll Dept Comp Sci & Engn Erode India Karpagam Inst Technol Dept Comp Sci & Engn Coimbatore Tamil Nadu India SNS Coll Technol Dept Comp Sci & Engn Coimbatore Tamil Nadu India

Cloud computing refers to on-demand delivery of service over internet and has application in various domains like media, research, business, bigdata analysis etc. Task scheduling is one of the prime issues in this type of environment. Various metaheuristic algorithms and hard optimization problems have been proposed for solving cloud task scheduling which is a non-deterministic polynomial or an NP. Adaptation of the scheduling strategy to the changes taking place in the environment has to be done by a good scheduler. A proposal for cloud scheduling by means of a balanced load using both firefly algorithm (FA) and particle swarm optimization (PSO) heuristics has been made. The aim is to balance the load of the entire system while at the same time bring down the makespan of a set of tasks. This new strategy for scheduling has been simulated with CloudSim tool kit package. The results of this experiment proved that the proposed FA performed better than min-min scheduling, PSO, and also the first come first serve methods.

关键词： Cloud computing Scheduling load balancing algorithm Firefly algorithm (FA)

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