journal article·2022Open access

Load Balancing Framework for Cross-Region Tasks in Cloud Computing

Jaleel Nazir, Muhammad Waseem Iqbal, Tahir Alyas, Muhammad Hamid, Muhammad Saleem, Saadia Malik, Nadia Tabassum

Computers, Materials & Continua· Volume 70· Issue 1

Abstract

Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them. To maximize various performance parameters in cloud computing, researchers suggested various load balancing approaches. To store and access data and services provided by the different service providers through the network over different regions, cloud computing is one of the latest technology systems for both end-users and service providers. The volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been experienced. Users of the cloud are looking for services that are intelligent, and, can balance the traffic load by service providers, resulting in seamless and uninterrupted services. Different types of algorithms and techniques are available that can manage the load balancing in the cloud services. In this paper, a newly proposed method for load balancing in cloud computing at the database level is introduced. The database cloud services are frequently employed by companies of all sizes, for application development and business process. Load balancing for distributed applications can be used to maintain an efficient task scheduling process that also meets the user requirements and improves resource utilization. Load balancing is the process of distributing the load on various nodes to ensure that no single node is overloaded. To avoid the nodes from being overloaded, the load balancer divides an equal amount of computing time to all nodes. The results of two different scenarios showed the cross-region traffic management and significant growth in revenue of restaurants by using load balancer decisions on application traffic gateways.
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Research context

OpenAlex topics: Cloud Computing and Resource Management · IoT and Edge/Fog Computing · Data Stream Mining Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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