The application successfully demonstrates the distributed database operations as it allows the user to not only view the records of both London and Scotland sites, but also to manipulate the data by inserting new or updating existing records. However, still there is a lot of…
Due to time limitation, this problem has not been resolved yet and therefore, the application still requires to be fine tuned to allow it to be run through IIS rather than involving Visual Studio’s internal ASP.NET Development Server.
Currently, this application’s backend, SQL Server 2005, does not store any data locally. It simply contains two linked servers which are called whenever the application requires carrying out some data operation – viewing, inserting and updating records. Excessive communication with linked servers may result in increase of network traffic, hence, minimizing the performance of only the application itself but of the entire corporate network as well.
Therefore, it is very important to maintain some part of the data locally in SQL Server 2005 in order to reduce the network load by minimizing the communication with remote servers. This can be achieved through re-designing the database involving three key aspects – data fragmentation, data replication and data allocation.
Data Fragmentation refers to the process of breaking up the database into logical units called fragments which can be stored at different sites. The simplest logical units are the table themselves (Padigela, n.d.).
Fragmented or Partitioned refers to partitioning of database into disjoint fragments, with each fragment assigned to one site (no replication). This is also called ‘non-redundant allocation’ (Padigela, n.d.).
Complete Replication involves maintenance of a complete copy of database at each site (no fragmentation) and therefore, storage costs and communication costs for updates are main drawbacks of this strategy. To overcome this, snapshots – a copy of the data at a given time – are used to update copies of database periodically (Padigela, n.d.).
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The paper will critically look at the factors motivating the adoption of distributed systems in order to evaluate the reality of a true distributed computing environment. Description of current research on the development of appropriate sub-components of distributed computer systems will then follow. This paper will present a critical evaluation on the reality of having a true distribute system.
Chief among those rules is this: Build applications that harness network effects to get better the more people use them” (Pang 2009). Unfortunately, there is still no exact definition available for this technology. In order to understand the concept of Web 2.0, one needs to be an information technology expert.
The other JVM can be on the same machine or any other machine on the network. However, the only thing it requires is for the JVM to be present at both sides. It implements remote interface developed by us and also language specifications, which is used by the server to provide the service as per the method call.
In most implementations of MPI, a fixed set of processes is created at program initialization, and one process is created per processor. However, these processes may execute different programs. Hence, the MPI programming model is also referred to as Multiple Program Multiple Data (MPMD) programming model to distinguish it from the Single Program Multiple Data (SPMD) model in which every processor executes the same program, but on different data.
The healthcare community is making increased use of electronic information systems to store and share the medical records of Patients. Community Doctors are therefore able to manage their patient's records more easily within each individual healthcare practice
It can produce enormous savings in terms of improved worker productivity and reduction of uncertainties, coupled with savings in time and effort as well.
Distributed connectivity can be utilized to good effect by engineers, especially at
that remain constant while being transmitted over a distance while in the case of analog signals, disturbances and noise in the environment will also carry over into the signal; hence digital signals are preferred in telecommunications (Ambardar, 1999:1-2). Telecommunications
22) points out that the design and implementation of distributed file systems faces many challenges such as caching techniques, naming service and transparency, file replication, access control and scalability considerations, and support for concurrency and
A good distributed file sharing system has designs considerations such as:
The system being a shared file distributed system data must be stored on the network for easier access by other clients on the network.
The purpose is to synchronize the data and ensure that actions like updates are in all other areas in case of multiple users. Decentralized database, on the other hand, is an example of a massive database being divided into smaller ones.
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