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Distributed sensor networks are a developing technology that promises to revolutionize our ability to sense environments, natural and social, over unprecedented spatial and temporal scales.
Creating autonomous, collaborative, and robust computation across a large set of small computing devices.
Distributed Networks makes use of current models in the areas of:

1. artificial intelligence,
2. machine learning,
3. control theory,
4. decision theory, and
5. distributed computing.

It also brings to the forefront current topics of research that connect the form and function of complex networks.

A distributed network is a type of computer network that is spread over different networks and provides a single data communication network, which can be managed jointly or separately by each network. Besides shared communication within the network, a distributed network often also distributes processing.
Distributed networks are part of a distributed computing architecture in which enterprise IT infrastructure resources are divided over a number of networks, processors and intermediary devices. A distributed network is powered by network management software, which manages and monitors data routing, combining and allocating network bandwidth, access control and other core networking processes.
1) Distributed networks and 2) processing work together to deliver specialized applications to different remote users. This means that an application may be hosted and executed from a single machine but accessed by many others. A client/server computing architecture is an example of a distributed network where the server is the producer of a resource and many interconnected remote users are the consumers who access the application from different networks.

1. When a single database is lost, it does not affect all the data.
2. User interaction is done with a local database, which results in higher access speeds, faster reporting and queries.
3. Cheaper operation results from taking the advantage of off-peak rates of communications between Satellite and Master databases syncing on scheduled access.
4. The Satellite databases come with local changes until the Master database acknowledges that it has upgraded these changes. This results in preventing accidental loss of local data amid transmission.
5. A major improvement in Master database performance, since it does not need to deal with the Satellite database changes consistently. With this, you simply move your Satellite transactional load to a manageable schedule leave a lot of time for other operations.

Disadvantages of Distributed Network

1. The distributed database architecture is more demanding in the form of design, administration and analysis.
2. There are issues in accessing Satellite data from the Master database, which is often done according to the scheduled syncs. Indeed, there is often a manual override where syncing can be made to occur.
3. Many complex routines need to be developed to ensure that data synchronization is working perfectly.
4. Delays will exist between the satellite and master data footprints, where many reports generated by the satellite database are not current with the data of the master .

Conclusion: Understanding the advantages and disadvantages helps to have a clear idea about our needs and where and how to implement the thing. There are other applications using Distributed network, besides the master or Satellite databases.