scholarly journals CLOUD STORAGE DENGAN TEKNOLOGI KUBERNETES UNTUK PLATFORM COLLABORATIVE RESEARCH

2021 ◽  
Vol 6 (1) ◽  
pp. 74-81
Author(s):  
Muhammad A. Nugroho ◽  
Rikie Kartadie
Keyword(s):  
Load Balancing ◽  
Collaborative Research ◽  
Cloud Storage ◽  
User Request ◽  
Load Peak

Memberikan model alternatif untuk penerapan penelitian kolaboratif melalui layanan teknologi komputasi awan yang diim- plementasikan di lingkungan komputer lokal atau untuk menampung penyimpanan file di luar lokasi, penggunaan berbagi file  cloud sangat bermanfaat dan mudah. Penggunaan teknologi ini harus diimplementasikan dan diuji keandalannya dalam skala    yang baik sehingga jika akan dikembangkan lebih lanjut dapat segera diimplementasikan dan sesuai dengan lingkungan dan  sumber daya jaringan yang ada. Penelitian ini berfokus pada implementasi dan pengujian performa kecepatan dan user request  yang menghasilkan nilai A pada uji kecepatan pada GTMetrix dan load peak tertinggi connection time 0-5ms. Solusi terhadap penurunan performa dapat disolusikan dengan menggunakan model scaling dikombinasikan dengan proxy, dan load balancing.

Research of Cloud Storage and Improved Distributed Strategy of Data Storage

2014 ◽  
Vol 496-500 ◽  
pp. 1812-1816 ◽  
Author(s):  
Hong Xia Mao
Keyword(s):  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Utilization Rate ◽  
Consistent Hashing ◽  
Storage Node ◽  
Load Rate ◽  
Hashing Algorithm ◽  
System Prototype

In this paper, an extensible system prototype of cloud storage is designed. Considering the load balance of cloud storage system, an improved data storage strategy based on consistent hashing algorithm is proposed in this paper. The strategy adopts virtual nodes to storage data and real–time monitoring of load rate of each storage node to adjust load balancing of the whole storage system. In the improved strategy, the priority is introduced into the storage system to rapidly improve the utilization rate of the new storage nodes. The strategy can effectively optimize the performance of the whole storage system, and improve the overall effect of the load balancing.

scholarly journals A Dynamical Load Balancing Method for Data Streaming and User Request in WebRTC Environment

2016 ◽  
Vol 17 (6) ◽  
pp. 581-592
Author(s):  
Linh Van Ma ◽  
Sanghyun Park ◽  
Jong-hyun Jang ◽  
Jaehyung Park ◽  
Jinsul Kim
Keyword(s):  
Load Balancing ◽  
Data Streaming ◽  
User Request

scholarly journals Improving the Reliability of Web Based Result Query Systems during High Traffic Periods

2019 ◽  
Vol 8 (2S5) ◽  
pp. 174-180
Keyword(s):  
Load Balancing ◽  
Autonomous Agents ◽  
Fast Response ◽  
Volunteer Work ◽  
Web Based ◽  
Computing Power ◽  
User Request ◽  
Query Systems ◽  
Incoming Request

Displaying of examination results by a single central entity, for lakhs of students becomes a tedious task, and sometimes may also result in server crashing. These servers typically rely on heavy and often unrestricted threads spawned to handle each incoming request which is the reason why the server resources are used up quickly. We propose a solution that is three fold: First, multiple Volunteer entities are brought in to hold the data and donate a portion of their computing power to offload the enormous work placed on the central entity. Second, the central entity is changed to play the role of dispatcher that generates monitors and assigns extremely lightweight, independent processes (called agents) to each user request without requiring any additional hardware upgrade. Each agent will be responsible to satisfy their assigned user requests. Third, we introduce a load balancing technique derived from the ideas of autonomous agents load balancing techniques in cloud to provide load balancing among the Volunteer entities and the central entity such that the Volunteer entities can continue with its own tasks and not be overwhelmed by its Volunteer work while ensuring fast response time and better reliability and response to the user.

scholarly journals Analysis of Load Balancing Techniques in Cloud Computing

2005 ◽  
Vol 4 (2) ◽  
pp. 737-741 ◽  
Author(s):  
Amandeep Sidhu ◽  
Supriya Kinger
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Job Scheduling ◽  
Single Node ◽  
Computing Paradigm ◽  
System A ◽  
Share Data ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. So, the amount of data storage increases quickly. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is necessary to utilize resources efficiently. This paper discusses some of the existing load balancing algorithms in cloud computing and also their challenges.

Sign in / Sign up

Export Citation Format

Share Document