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In the analysis of distributed algorithms, more attention is usually paid on communication operations than computational steps. Perhaps the simplest model of distributed computing is a synchronous system where all nodes operate in a lockstep fashion. This model is commonly known as the LOCAL model.
If, however, data is lost in a distributed system, retrieving it would be very easy, because there is always a copy of the data in a different location of the database. Designing a centralized database is generally much less complex than designing a distributed database, as distributed database systems are based on a hierarchical structure.
Some researchers have made a functional and experimental analysis of several distributed file systems including HDFS, Ceph, Gluster, Lustre and old (1.6.x) version of MooseFS, although this document is from 2013 and a lot of information are outdated (e.g. MooseFS had no HA for Metadata Server at that time). [50]
A relatively new method of centralized computing, hosted computing, solves many of the problems associated with traditional distributed computing systems. By centralizing processing and storage on powerful server hardware located in a data center, rather than in a local office, it relieves organizations of the many responsibilities in owning ...
The duplication process is normally done at a set time after hours. This is to ensure that each distributed location has the same data. In the duplication process, users may change only the master database. This ensures that local data will not be overwritten. Both replication and duplication can keep the data current in all distributive ...
A distributed algorithm is an algorithm designed to run on computer hardware constructed from interconnected processors.Distributed algorithms are used in different application areas of distributed computing, such as telecommunications, scientific computing, distributed information processing, and real-time process control.
Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...
“Distributed” or “grid” computing in general is a special type of parallel computing that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a network (private, public or the Internet) by a conventional network interface producing commodity hardware, compared to the lower efficiency of designing and constructing a small ...