An Improvement on the Weighted Least-Connection Scheduling Algorithm for Load Balancing in Web Cluster Systems

Choi, DongJun; Chung, Kwang Sik; Shon, Jin Gon

doi:10.1007/978-3-642-17625-8_13

Cited by 16 publications

(9 citation statements)

References 1 publication

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“…Metode test diambil berdasarkan metode tes pada penelitian sebelumnya, yaitu menggunakan algoritme WLC untuk melakukan load balancing pada sepuluh server virtual dengan resources server yang sama. Jumlah request yang digunakan pada pengujian adalah 800 request [16]. Algoritme WLC ini merupakan gabungan antara algoritme weight dan least connection.…”

Section: F Metode Testunclassified

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Sistem Load Balancing Menggunakan Least Time First Byte dan Multi Agent System

Afriansyah¹,

Somantri²,

Riyadi³

2017

Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

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Abstract-Network activity has increased in every year due to rapid growth of internet users. This phenomenon eventually increases the load server. The high load on server makes server down. The proposed system to handle the issue is using Least Time First-Byte algorithm and multi-agent system in distributed load balancing. The agent collects information resources on the backend servers and communicates with the agents. The Least Time First-Byte algorithm is then combined with the information resources from the agent, called as Least Time First Byte with Multi Agent System (LFB-MAS). The simulation results show that LFB-MAS performs load balance efficiently to all server and provides better performance. The LFB-MAS can process 100% from the 1,800 requests, whereas WLC algorithm is only capable of processing 74.50% from 1,800 requests and LFB without agent is only capable of processing 75.61% from 1,800 requests. The results prove that LFB-MAS can handle high tasks or requests and is reliable.Intisari-Lalu lintas jaringan meningkat setiap tahunnya dikarenakan cepatnya peningkatan pengguna internet. Hal ini dapat meningkatkan beban kerja server. Beban yang tinggi pada server akan menyebabkan server menjadi down. Metode yang diajukan untuk menangani masalah tersebut adalah dengan load balancing terdistribusi menggunakan algoritme least time firstbyte dan multi agent system. Agent akan mengumpulkan informasi dan dapat berkomunikasi antar agent sesuai tugas yang diberikan. Metode load balancing yang diajukan dapat disebut dengan Least Time First Byte with Multi Agent System (LFB-MAS). Berdasarkan data yang diperoleh pada hasil pengujian, metode WLC hanya mampu memproses sekitar 74,50% dari 1.800 request dan LFB tanpa menggunakan agent hanya mampu memproses 75,61% dari 1.800 request. Metode LFB-MAS dapat memproses 100% dari semua request atau 1.800 request yang diberikan. Hal ini menunjukkan bahwa LFB-MAS dapat melakukan sistem load balancing dengan efisien ke seluruh server backend yang tersedia dengan hasil yang lebih baik, tidak ada bottleneck, low risk server overload, dan andal.Kata Kunci--Andal, server, JADE, multi agent system, load balancing. I. PENDAHULUANServer menjadi hal yang sangat penting dan diperlukan pada era teknologi saat ini. Server menjadi pusat pelayanan dari seluruh pengguna. Server itu sendiri merupakan sebuah sistem komputer dengan spesifikasi sumber daya yang sangat tinggi daripada komputer umumnya dan bertugas menyediakan jenis layanan tertentu serta pengolah data yang sangat kompleks dan besar. Semakin banyak pengguna, maka semakin kompleks juga infrastruktur server yang dibangun. Infrastruktur server yang dibangun harus dapat menampung sejumlah request yang datang dari para penggunanya. Load server akan tinggi seiring dengan banyaknya penggunaan layanan yang disediakan oleh server. Beban server yang tinggi mengakibatkan kecepatan proses menurun dan bisa membuat server berhenti bekerja. Berdasarkan masalah tersebut, diperlukan teknologi yang sesuai untuk dapat mengatasi permasalahan ini. Sis...

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Section: F Metode Testunclassified

“…Sistem cluster merupakan sistem yang memberikan skalabilitas kepada setiap server baru yang akan ditambahkan [16]. Sistem cluster dibagi menjadi beberapa bagian, yaitu komputasi cluster dengan kinerja komputasi yang tinggi, komputasi cluster dengan ketersediaan yang tinggi, dan komputasi cluster dengan distribusi beban sesuai dengan tujuan dari sistem komputasi.…”

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Sistem Load Balancing Menggunakan Least Time First Byte dan Multi Agent System

Afriansyah¹,

Somantri²,

Riyadi³

2017

Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

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“…The work in [42] presents a highly efficient and controllable virtual machine online migration scheduling algorithm to tackle the visiting block problem caused by unreasonable application for core network and unbalanced workload at the virtual data center. The proposed WRR (Weighted Round-Robin) algorithm in [43] is a weighted scheduling algorithm based on polling, and it distributes the service requests between servers in the form of polling. In the aforementioned studies, Kafka is an access mechanism organizing messages in the form of “topics“.…”

Section: Related Workmentioning

confidence: 99%

“…When dealing with the DAPVDC, Kafka consumes a large cost to frequently create the topic and maintain the original order of the service request, limited by its own access schema features though it is widely applied in streaming data processing. WRR in [43] handles a large number of service requests by the means of polling. Although it satisfies the processing fairness of the server requests, it does not make full use of the access ability of new servers, which affects the capacity of the access cluster’s load balancing when processing requests for a longer time.…”

Section: Related Workmentioning

confidence: 99%

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

Meng

Chen

Xiong

2016

Sensors

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This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

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“…Load balancing strategy [8] mainly includes RoundRobin Scheduling (RR), Weighted Round-Robin Scheduling (WRR) [9], Least-Connection Scheduling(LC) [10], Weighted Least-Connection Scheduling(WLC) [11], Locality-Based Least-Connection Scheduling(LBLC) [12], Locality-Based Least-Connection with Replication Schedul-ing(LBLCR), Destination Hashing Scheduling(DH), Source Hashing Scheduling and so on. Aiming at practical situation or experimental questions, algorithms can be restructured to optimize job assignment, such as appending dynamic detection based on the state of node, or adding algorithms based on some effective math conclusion into load balancing strategy.…”

Section: Related Workmentioning

confidence: 99%

A New MapReduce Framework Based on Virtual IP Mechanism and Load Balancing Strategy

Song¹,

Hao²,

Hu³

et al. 2015

TOCSJ

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Abstract:MapReduce is an important method for large-scale data processing on parallel architecture. In Hadoop ecosystem, MapReduce runs on the application-level, thus it provides system with flexibility. MapReduce is good at offline batch processing and it could accelerate the whole execution time. The deficiency of the MapReduce architecture is a lack in balancing and scalability, thus leads to low efficiency when dealing with large-scale data. In this paper, we propose a new MapReduce framework that is more suitable for Hadoop ecosystem. The framework is based on the virtual IP mechanism and load balancing strategy. Comparative experiments indicate that the new framework achieve twice the performance compared to the original MapReduce. Besides, the framework fully meets the environment of Hadoop ecosystem, and provides a stable and efficient data processing.

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An Improvement on the Weighted Least-Connection Scheduling Algorithm for Load Balancing in Web Cluster Systems

Cited by 16 publications

References 1 publication

Sistem Load Balancing Menggunakan Least Time First Byte dan Multi Agent System

Sistem Load Balancing Menggunakan Least Time First Byte dan Multi Agent System

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

A New MapReduce Framework Based on Virtual IP Mechanism and Load Balancing Strategy

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