Ibrahim Mekawy; Alhanouf Alburaikan; Iman Atighi
Abstract
The current landscape of Cloud Computing predominantly relies on closed data centers, housing a multitude of dedicated servers that cater to cloud services. However, an immense number of underutilized Personal Computers (PCs) are owned by individuals and organizations globally. These dormant resources ...
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The current landscape of Cloud Computing predominantly relies on closed data centers, housing a multitude of dedicated servers that cater to cloud services. However, an immense number of underutilized Personal Computers (PCs) are owned by individuals and organizations globally. These dormant resources can be harnessed to form an alternative cloud infrastructure, offering a wide array of cloud services, particularly focusing on infrastructure as a service. This innovative strategy, the "no data center" approach, complements the conventional data center-centric cloud provisioning model. In a research paper, the authors introduce their opportunistic Cloud Computing framework called cuCloud, which effectively utilizes the idle resources of underutilized PCs within a given organization or community. The success of their system serves as tangible evidence that the "no data center" concept is indeed feasible. Beyond conceptualization and philosophy, the authors' experimental findings strongly validate their approach.
Mingyue Wang
Abstract
The goal of research in the intriguing area of cloud computing is to discover the most effective solution and method for sharing and protecting data. Load Balancing (LB) on public infrastructure using cloud computing's ideal geographic location. In cloudy environments, LB is widely used as a visitor ...
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The goal of research in the intriguing area of cloud computing is to discover the most effective solution and method for sharing and protecting data. Load Balancing (LB) on public infrastructure using cloud computing's ideal geographic location. In cloudy environments, LB is widely used as a visitor control approach. Cloud requests look for resources to support performance. The resources are frequently things like bandwidth, processing power, and storage. LB is the process of effectively allocating these resources to each competing job. This study will offer a thorough analysis of cloud load-balancing methods.
Aziza Algarni
Abstract
Cloud computing is an essential tool for sharing resources across virtual machines, and it relies on scheduling and load balancing to ensure that tasks are assigned to the most appropriate resources. Multiple independent tasks need to be handled by cloud computing, and static and dynamic scheduling plays ...
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Cloud computing is an essential tool for sharing resources across virtual machines, and it relies on scheduling and load balancing to ensure that tasks are assigned to the most appropriate resources. Multiple independent tasks need to be handled by cloud computing, and static and dynamic scheduling plays a crucial role in allocating tasks to the right resources. This is especially important in heterogeneous environments, where algorithms can improve load balancing and enhance cloud computing's efficiency. This paper aims to evaluate and discuss algorithms that can improve load balancing in cloud systems.
