Guppie: A Coordination Framework for Parallel Processing Using Shared Memory Featuring A Master-Worker Relationship

Most programs can be parallelized to some extent. The processing power available in computers today makes parallel computing more desirable and attainable than ever before. Many machines today have multiple processors or multiple processing cores making parallel computing more available locally, as well as over a network. In order for parallel applications to be written, they require a computing language, such as C++, and a coordination language (or library), such as Linda. This research involves the creation and implementation of a coordination framework, Guppie, which is easy to use, similar to Linda, but provides more efficiency when dealing with large amounts of messages and data. Greater efficiency can be achieved in coarse-grained parallel computing through the use of shared memory managed through a master-worker relationship

Tuple Space Middleware for Wireless Networks

Wireless networks define a very challenging scenario for the application programmer. Indeed, the fluidity inherent in the wireless media cannot be entirely masked at the communication layer: issues such as disconnection and a continuously changing execution context most often must be dealt with according to the application logic. Appropriate abstractions, usually provided as part of a middleware, are therefore required to support and simplify the programming task

Tuple space middleware for wireless networks

This chapter addresses tuple spaces, a programming abstraction for data sharing and coordination among distributed processes. The shared memory is called a tuple space, a multiset of elementary data structures. Each tuple is a sequence of typed fields and coordination among processes occurs through the writing and reading of tuples. Originally introduced in the context of parallel computing, it has recently enjoyed wide popularity to develop wireless applications. This chapter concisely describes some of the most representative systems implementing this abstraction and analyzes them along some fundamental dimensions of comparison

Tuple Space Middleware for Wireless Networks

Wireless networks define a very challenging scenario for the application programmer. Indeed, the fluidity inherent in the wireless media cannot be entirely masked at the communication layer: issues such as disconnection and a continuously changing execution context most often must be dealt with according to the application logic. Appropriate abstractions, usually provided as part of a middleware, are therefore required to support and simplify the programming task