iccide.com

3rd International Conference on Computational Intelligence and Data Engineering (ICCIDE-25)

Menu

CLOUD COMPUTING

Big Data Analytics and Cloud Computing

Big Data Analytics involves analyzing large and complex datasets to uncover patterns, trends, and insights, driving decision-making and innovation. Cloud Computing provides scalable, on-demand computing resources and storage over the internet, enabling efficient data processing and analysis. Together, they allow businesses to process massive datasets in real time, improve performance, reduce costs, and enable data-driven decision-making.

Fog Computing is a decentralized computing infrastructure that extends cloud computing to the edge of networks, closer to data sources. It processes data locally on devices or intermediate nodes, reducing latency and bandwidth use. Fog computing is ideal for IoT applications, enabling faster real-time analytics and decision-making. It enhances efficiency and reliability in environments requiring quick responses and low latency.

Edge Computing is a distributed computing model where data processing occurs closer to the data source, such as IoT devices or local servers, instead of relying on centralized cloud servers. This reduces latency, conserves bandwidth, and improves real-time decision-making. Edge computing is vital for applications requiring quick responses, such as autonomous vehicles, smart cities, and industrial automation.

Cognitive Computing refers to systems that simulate human thought processes in analyzing complex data. Using AI, machine learning, and natural language processing, these systems learn, reason, and interact with users in a human-like manner. Cognitive computing is applied in decision support, customer service, and problem-solving, enabling machines to understand, interpret, and respond to unstructured data, enhancing human-computer interaction.

 

Quantum Computing uses principles of quantum mechanics to perform calculations much faster than classical computers. It leverages quantum bits (qubits), which can exist in multiple states simultaneously, allowing for parallel processing. This enables quantum computers to solve complex problems in fields like cryptography, optimization, and drug discovery that would be infeasible for traditional computers, offering exponential computational power.

Soft Computing involves computational techniques like fuzzy logic, genetic algorithms, and neural networks, designed to handle imprecision and uncertainty in complex problems. It seeks approximate solutions rather than exact ones. Machine Learning is a subset of AI that uses algorithms to enable systems to learn from data and improve over time. Both fields often overlap in solving real-world problems with uncertainty.

Distributed Computing is a model where multiple interconnected computers work together to perform tasks, share resources, and solve problems. It divides large computations into smaller tasks, which are processed concurrently across different machines, improving efficiency, scalability, and fault tolerance. This model is widely used in cloud computing, parallel processing, and big data applications, enabling faster and more reliable operations.

Mobile Computing refers to the use of portable devices, such as smartphones and tablets, to access and process data while on the move. It involves wireless communication technologies like Wi-Fi, Bluetooth, and cellular networks, enabling users to perform tasks such as browsing, email, and navigation remotely. Mobile computing enhances convenience, connectivity, and productivity in various personal and business applications.

Agent-Based Computing involves using autonomous, self-directed software agents that interact with their environment and other agents to solve complex problems. These agents can perceive their surroundings, make decisions, and perform actions based on predefined rules or learned behavior. Commonly used in simulations, multi-agent systems, and artificial intelligence, agent-based computing is applied in fields like robotics, finance, and traffic management.