Computing Programs

Grid computing, a subset of distributed computing, harnesses the power of many loosely coupled computers to perform sizable tasks.

Characteristics:
- Resource Pooling: Often described as "virtual supercomputing," grid computing pools resources, sometimes from globally scattered computers.
- Voluntary Participation: Projects like SETI@home exemplify this, where unused computing resources are tapped into.
- Heterogeneity: Grids can consist of varied machines, possibly with different operating systems and hardware configurations.
- Middleware Requirement: Essential for managing diverse resources, handling security, and orchestrating tasks.
Comparison:
- SETI Project: Fits the grid computing model where global volunteers contribute idle computer time.
- Blockchain: A form of distributed computing due to its decentralized nature but deviates from the traditional grid model. Its focus isn't pooling computational resources for large tasks but ensuring secure transaction data and consensus.

Key concerns with Grid computing includes protecting the grid controller from takeover or influence from bad actors.

Edge Computing

Overview: Edge computing moves certain processing tasks closer to the location where they are needed, rather than relying solely on a central cloud-based system.
Internet-of-Things (IoT) example: Situations where real-time or near-real-time processing is vital.
- Agriculture: Optimizing irrigation based on sensor data.
- Science/Space: Immediate data processing from space instruments.
- Military: Real-time strategies or drone controls based on immediate data.

Definition: An extension of edge computing, fog computing utilizes gateway devices in the field to gather, process, and send data more efficiently.
How It Works: Rather than sending all data directly to the cloud, fog computing aggregates and processes data at the edge first, then sends only the most relevant or processed data to the central system.
Purpose: By collecting and correlating data centrally at the edge, fog computing minimizes latency and enhances efficiency, especially when bandwidth is a concern.

Challenges: With numerous network-connected devices dispersed in various locations, ensuring security becomes paramount.
Key Solutions:
- Data Encryption: Protecting data in transit and at rest.
- Spoofing Protection: Ensuring data integrity and verifying the sources.
- Authentication: Confirming the legitimacy of devices and users accessing the network.

Internet of Things (IoT) represents a vast network of interconnected devices, each tapping into the internet to drive automation, remote management, or AI-powered functions. This category can encompass a variety of tools and machines, from a surveillance camera to sophisticated vehicles.
Smart devices subset of IoT devices characterized by their ability to offer customization options, typically through the installation of apps. These mobile devices, such as smartphones or tablets, can use on-device or in-the-cloud artificial intelligence (AI) processing to deliver personalized and intelligent services.