DISTRIBUTED SYSTEMS

DISTRIBUTED SYSTEMS

1. What is a distributed system?

   • This definition involves two characteristics of distributed systems. The first is that a distributed system is a collection of computing elements and The second function is that users think they are dealing with a single system.
   • Characteristics
     • Collection of autonomous computing elements
       • Modern distributed systems can and usually will consist of various nodes, from very large high-performance computers to small plug-and-play computers and even smaller devices.
     • Single coherent system
       • A distributed system should appear as a single coherent system, researchers even say that there should be a single system view, which means that end users shouldn’t even notice the fact that they’re working on processes, with data and control scattered across the entire the computer network.
   • Middleware
     • Distributed systems are usually organized to have separate software layers logically placed on top of the various operating systems of the computers that are part of the system.
       • Function
         • To assist the development of distributed applications

2. Design Goals

   • A distributed system should make resources easily accessible; it should hide the fact that resources are distributed across a network; it should be open; and it should be scalable.
     • Supporting resource sharing
       • An important goal of a distributed system is to make it easy for users to access and share remote resources. Resources can be virtually anything, but typical examples include peripherals, storage facilities, data, files, services, and networks, to name just a few.
     • Making distribution transparent
       • An important goal of a distributed system is to hide the fact that its processes and resources are physically distributed across multiple computers possibly separated by large distances.
         • Types of distribution transparency
           • Access: Hide differences in data representation and how an object is accessed. Location: Hide where an object is located. Relocation: Hide that an object may be moved to another location while in use. Migration: Hide that an object may move to another location. Replication: Hide that an object is replicated. Concurrency: Hide that an object may be shared by several independent users. Failure: Hide the failure and recovery of an object.
         • Degree of distribution transparency
           • Although distribution transparency is generally considered preferable for any distributed system, there are situations in which attempting to blindly hide all distribution aspects from users is not a good idea.
     • Being open
       • An open distributed system is essentially a system that offers components that can easily be used by, or integrated into other systems.
       • Being scalable
         • worldwide connectivity through the Internet is as common as being able to send a postcard to anyone anywhere around the world. Moreover, where until recently we were used to having relatively powerful desktop computers for office applications and storage
           • Scalability dimensions
             • Size scalability
               • A system can be scalable with respect to its size, meaning that we can easily add more users and resources to the system without any noticeable loss of performance
             • Geographical scalability
               • A geographically scalable system is one in which the users and resources may lie far apart, but the fact that communication delays may be significant is hardly noticed.
             • Administrative scalability
               • An administratively scalable system is one that can still be easily managed even if it spans many independent administrative organizations.

3. Types of distributed systems

   • High performance distributed computing
     • An important class of distributed systems is the one used for high-performance computing tasks. Roughly speaking, one can make a distinction between two subgroups. In cluster computing the underlying hardware consists of a collection of similar workstations or PCs, closely connected by means of a high-speed local-area network. In addition, each node runs the same operating system.
   • Cluster computing
     • Cluster computing systems became popular when the price/performance ratio of personal computers and workstations improved. At a certain point, it became financially and technically attractive to build a supercomputer using off-the-shelf technology by simply hooking up a collection of relatively simple computers in a high-speed network.
   • Grid computing
     • A characteristic feature of traditional cluster computing is its homogeneity. In most cases, the computers in a cluster are largely the same, have the same operating system, and are all connected through the same network.
   • Cloud computing
     • Eventually, this led to the concept of utility computing by which a customer could upload tasks to a data center and be charged on a per-resource basis. Utility computing formed the basis for what is now called cloud computing.
       • Application
         • Actual applications run in this layer and are offered to users for further customization. Well-known examples include those found in office suites
       • Platform
         • One could argue that the platform layer provides to a cloudcomputing customer what an operating system provides to application developers, namely the means to easily develop and deploy applications that need to run in a cloud.
       • Infrastructure
         • This is an important layer forming the backbone for most cloud computing platforms.
       • Hardware
         • The lowest layer is formed by the means to manage the necessary hardware: processors, routers, but also power and cooling systems
   • Distributed information systems
     • Another important class of distributed systems is found in organizations that were confronted with a wealth of networked applications, but for which interoperability turned out to be a painful experience.
       • Distributed transaction processing
         • In practice, operations on a database are carried out in the form of transactions. Programming using transactions requires special primitives that must either be supplied by the underlying distributed system or by the language runtime system.
       • Enterprise application integration
         • The more applications became decoupled from the databases they were built upon, the more evident it became that facilities were needed to integrate applications independently from their databases
   • Pervasive systems
     • The distributed systems discussed so far are largely characterized by their stability: nodes are fixed and have a more or less permanent and high-quality connection to a network. To a certain extent, this stability is realized through the various techniques for achieving distribution transparency.
     • Ubiquitous computing systems
       • Distribution
         • Devices are networked, distributed, and accessible in a transparent manner
       • Interaction
         • Interaction between users and devices is highly unobtrusive
       • Context awareness
         • The system is aware of a user’s context in order to optimize interaction
       • Autonomy
         • Devices operate autonomously without human intervention, and are thus highly self-managed
       • Intelligence
         • The system as a whole can handle a wide range of dynamic actions and interactions
   • Mobile computing systems
     • mobility often forms an important component of pervasive systems, and many, if not all aspects that we have just discussed also apply to mobile computing. There are several issues that set mobile computing aside to pervasive systems in general
     • Sensor networks
       • A sensor network generally consists of tens to hundreds or thousands of relatively small nodes, each equipped with one or more sensing devices