Introduction to Distributed Systems

A system composed of independent computers networked together to appear as a single system to users.

In a distributed system, components located on networked computers communicate and coordinate actions by exchanging messages.

A centralized server provides resources and services to multiple clients. Think of a server catering to a large number of users.

Each node acts as both a client and a server, sharing resources directly with each other. Think of a network where everyone shares files.

A system organized into layers, with each layer offering specific services. Think of a layered cake where each layer has a unique role.

A system where distributed resources are provided as services over the internet (IaaS, PaaS, SaaS). Think of cloud providers like AWS.

A distributed system that links heterogeneous computing resources to tackle complex problems. Think of SETI@home, a project that uses home computers to analyze data.

A processor executes a single instruction on a single piece of data at a time. Think of your desktop before dual-core CPUs.

Processors execute the same instruction on multiple pieces of data simultaneously. Think of GPUs handling graphics processing in parallel.

Multiple instructions are executed on a single data stream. Think of a pipeline architecture where stages process the same data consecutively.

Multiple instructions are executed on multiple data streams simultaneously. Think of a complex system with many processors doing different tasks.

In shared memory MIMD, processors share a common memory space. Think of a workplace where everyone has access to a shared whiteboard.

In distributed memory MIMD, each processor has its own individual memory. Think of a team where each member has their own separate notebook.

The ability of a system to handle a wide variety of machines and devices. Think of a system that works with different brands of computers.

The ability of a system to withstand failures and network problems. Think of a system that keeps running even if some computers crash.

The ability of a system to handle growth in nodes or workload without performance degradation. Think of a system that can handle more users or traffic smoothly.

The ability of a system to hide its internal workings from users. Think of a system that works seamlessly from the user's perspective.

The ability of a system to handle multiple clients concurrently. Think of a restaurant that can serve many customers at the same time.

The efficiency of a system in terms of resource utilization and performance. Think of a system that uses all available resources effectively.

The availability of data and services to clients at all times. Think of a system that is always online and accessible.

The ability of a system to protect itself against security threats and attacks. Think of a system with strong security measures.

The ability of a system to be extended with new features or functionalities. Think of a system that can be adapted and updated.

The challenges of coordinating and synchronizing multiple processors in a distributed system.

The issue of managing memory and data in a distributed system.

The ability to detect and utilize parallelism in a distributed system.

The process of scheduling tasks and processes across different processors in a distributed system.

The hardware challenges of providing sufficient memory and bandwidth in a distributed system.

The challenge of designing and managing software that operates in a distributed environment.

The need for high-performance computing arises from complex problems requiring significant computing power, such as large-scale simulations, design optimization, and data analysis in diverse fields.

Mainframe systems are centralized, with a single powerful computer handling all tasks. In contrast, multiprocessor systems distribute tasks across multiple processors, offering potential for higher performance and scalability.

Transparency in distributed systems aims to hide internal workings from users, allowing them to interact with the system as if it were a single, unified entity, regardless of its distributed nature.

Efficiency in distributed systems refers to how effectively the system utilizes its resources (processors, memory, network bandwidth) to achieve optimal performance, minimizing waste and maximizing throughput.

Robustness in distributed systems refers to the system's ability to withstand failures, such as computer crashes or network interruptions, and continue functioning without interruption or data loss.

Concurrency in distributed systems allows the system to handle multiple requests or tasks simultaneously, improving responsiveness and throughput, especially when dealing with a high volume of user interactions.

Scalability in distributed systems refers to the system's capacity to handle an increasing workload or a growing number of users or devices without compromising performance or stability.

Heterogeneity in distributed systems refers to the capability of handling a range of diverse computer types and network technologies, enabling flexibility and adaptation to different environments.

Robustness in distributed systems means the system can withstand failures (like computer crashes, network outages) and continue functioning without disruption or data loss, ensuring reliability.

Scalability in distributed systems refers to the ability to handle increasing workloads (more users, data, tasks) without significant performance degradation or instability. Think of a system that can grow smoothly as demands expand.

Transparency in distributed systems aims to hide the internal complexities from users, presenting the system as a single cohesive entity, making it easier to use and manage. Think of a system that hides its intricate inner workings.

Concurrency in distributed systems refers to the ability to handle multiple requests or tasks simultaneously without affecting performance. Think of a system that can juggle multiple tasks without getting overwhelmed.

Efficiency in distributed systems is about utilizing resources (processors, memory, network bandwidth) effectively to maximize performance, minimizing wasted resources and maximizing throughput. Think of a system that makes the best use of its resources.

Availability in distributed systems refers to the continuous accessibility of data and services to users. Think of a system that is always online and readily available.

Security in distributed systems involves protecting against unauthorized access, data breaches, and other malicious activities by implementing safeguards and security measures. Think of a system that is well-protected from attacks.

Openness in distributed systems refers to the system's ability to be extended with new features, functionalities, or integrations. Think of a system that can be customized and adapted for future needs.

A distributed system's challenges include coordinating multiple processors, managing memory and data across various locations, detecting parallelism, and efficiently scheduling processes across different nodes.

Managing memory and data in a distributed system involves allocating and accessing resources across different nodes, ensuring consistency and reliability.

Parallelism detection in a distributed system involves identifying tasks that can be executed concurrently on different processors, maximizing computational power and speeding up execution.

Process scheduling in a distributed system involves efficiently assigning tasks to different processors, considering workloads, resource availability, and dependencies, to optimize performance.

Hardware challenges in a distributed system include providing sufficient memory capacity, network bandwidth, and processing power to accommodate the demands of the system.

Software challenges in a distributed system involve designing and managing software that can operate effectively across multiple systems and handle communication, coordination, and data management.