Atharv Gyan

Edge computing represents a paradigm shift in the way computing resources are deployed and managed, particularly in relation to cloud architecture. Traditionally, cloud computing involves centralized data centers where processing, storage, and networking functions are concentrated. However, with the rise of edge computing, computing tasks are distributed closer to the data source or end-user devices, resulting in a more decentralized architecture. This shift has significant implications for cloud architecture, impacting aspects such as latency, scalability, security, and service delivery. One of the key impacts of edge computing on cloud architecture is the reduction of latency. By moving computing resources closer to the point of data generation or consumption, edge computing minimizes the distance that data must travel, resulting in lower latency and improved response times. This is particularly important for applications that require real-time or near-real-time processing, such as I...

Introduction to Edge Computing and IoT Edge computing refers to the practice of processing data near the edge of the network, where the data is generated, rather than relying solely on centralized data-processing warehouses or cloud-based systems. This approach contrasts with traditional cloud computing, where data is transmitted to centralized data centers for processing and analysis. The Internet of Things (IoT) consists of a network of interconnected devices, sensors, and systems that communicate and exchange data to perform various tasks and provide valuable insights. IoT devices are deployed across various sectors, including smart homes, industrial automation, healthcare, transportation, and more. Impact of Edge Computing on IoT Improved Response Times One of the primary benefits of edge computing in IoT is the significant improvement in response times. By processing data closer to the source, edge computing reduces latency, which is the time it takes for data to travel from the...