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Cloud computing and fog computing are both integral to modern network architectures, enabling data processing and storage across various devices. However, they serve different purposes and are optimized for different use cases. While cloud computing has become widely recognized and adopted for large-scale storage and processing, fog computing emerges as an extension of cloud computing, designed to handle the challenges posed by the Internet of Things (IoT), real-time data processing, and the need for low latency. Cloud computing refers to the practice of using remote servers hosted on the internet to store, manage, and process data, instead of using local servers or personal computers. It provides high scalability, flexibility, and on-demand resources, which makes it ideal for enterprise applications that require vast amounts of storage and computing power. Users and organizations can access applications and data over the internet without the need for maintaining physical infrastructure. Examples of cloud computing providers include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Fog computing, on the other hand, is a decentralized computing infrastructure that extends the capabilities of cloud computing closer to the edge of the network. In fog computing, data processing is done at or near the source of the data, often on local devices, gateways, or edge servers. This approach reduces the amount of data sent to the cloud for processing, thereby minimizing latency, conserving bandwidth, and improving response times. Fog computing is designed to cater to IoT ________ _______ ___ ______ __________.
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