A method to optimize the deployment of IoT services using Wall's algorithm in Fog and cloud computing environment and hxivybrid ABC colony ant colony in management data center consumption energy

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Gohari Sepideh

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Year:2025 | Issue:11

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Title

A method to optimize the deployment of IoT services using Wall's algorithm in Fog and cloud computing environment and hxivybrid ABC colony ant colony in management data center consumption energy

Author(s)

Gohari Sepideh

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Abstract

Cloud computing provides a new way to deliver information technology services using the Internet. One of the main elements of this processing model is virtualization. Virtualization is a technique that hides the complexities of a cloud computing system from the user and is able to separate the management of hardware and software. One of the important achievements of virtualization is migration. Migration serves various purposes, including load balancing and distribution, load balancing, online maintenance, fault tolerance, energy management, energy fault tolerance, reducing response time, and facilitating maintenance of servers in data centers and computing clusters. Cloud computing examines different methods of virtual machine migration. Increasing flexibility and scalability of cloud data centers. In recent years, different solutions have been proposed to minimize energy consumption in cloud data center buildings. Two very popular methods are dynamic server consolidation and virtual machine consolidation. The dynamic server consolidation method saves energy by reducing the amount of resources required to satisfy workloads. Dynamic consolidation of virtual machines is another effective method in improving resource consumption and energy efficiency, which improves the hardware virtualization method. In this Seminar The proposed method using bee and ant colonies reduces the workload of dynamic servers, which are the main energy consumers in cloud data centers, and a very weak cooling system will be required in cloud data centers. The proposed method of dynamic consolidation of virtual machines with bee and ant colonies is to drastically reduce energy in cloud data centers. With the emergence of the Internet of Things (IoT) as one of the essential components of our daily lives, understanding how to improve the quality of service (QOS) in IoT networks has become a challenging problem. Today, most interactions between IoT devices and support for end-servers are performed through large-scale cloud data centers. However, with the dramatic growth of IoT devices and the data they generate and transmit between objects and the cloud, it has become costly, inefficient, and in some cases unfeasible. Fog computing serves as a solution to this issue, providing networking, storage, and computing resources for IoT close to objects and users. One of the promising advantages of fog is the reduction of service latency for end-user applications, while cloud provides more extensive computing and stores this capacity with higher latency. Therefore, it is essential to understand the interaction between fog computing and cloud and evaluate the impact of fog computing on IoT system latency and QoS. In this paper, we introduce a general framework for fog-cloud IoT applications and propose a latency minimization policy for fog-enabled devices, which aims to reduce service latency in IoT applications. Then, we present an analytical model to evaluate our policy and show how the proposed framework can be used to reduce IoT service latency. With the rapid growth of the Internet of Things (IoT), the classical centralized cloud computing method has encountered multiple challenges, such as high latency, low capacity, and network failure. To address these challenges, fog computing (Fog) brings the cloud closer to IoT devices. Fog provides processing and storage of IoT data locally on IoT devices instead of sending it to the cloud. In contrast to the cloud, fog provides faster response and better quality of service, making fog computing the best choice for enabling IoT to provide efficient and secure services to many users.

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