Distributed communication in ML

Distributed communication in ML

We present our experience in implementing a group communication toolkit in Objective Caml, a dialect of the ML family of programming languages. We compare the toolkit both quantitatively and qualitatively to a predecessor toolkit which was implemented in C. Our experience shows that using the high-level abstraction features of ML gives substantial advantages. Some of these features, such as aut...

Shared Environments for Distributed ML

Implementing distributed Linda in Standard ML

We have implemented the Linda model of shared distributed tuple space in a functional programming language, Standard ML. We use ML’s flexible type system and pattern matching facilities to provide ML programmers with the basic Linda operations on tuples. No preprocessor is used, and no compiler changes are required. We use separate ML modules to implement the Linda interface, operations on tupl...

Communication Primitives for Minimally Synchronous Parallel ML

Minimally Synchronous Parallel ML is a functional parallel language whose execution time can then be estimated and dead-locks and indeterminism are avoided. Programs are written as usual ML programs but using a small set of additional functions. Provided functions are used to access the parameters of the parallel machine and to create and operate on a parallel data structure. It follows the cos...

Data Recovery Using ML Equalizer in NLOS Communication Environment

Wireless communication has become very important in this world due to easy handling of equipments and installation of operating software’s. The capacity and gain of these equipments depend on the channel conditions therefore we have to take care of channel noise, delay, gain, signal propagation and processing equipments. At the receiving end, receiver is responsible in inverting the effect of c...