Experimental Software Systems: Linear Naming: Experimental Software for Optimizing Communication Protocols

EIA-9806718 Mairson，Harry G. 艾伦布兰代斯大学鲍登分校 ESS：线性优化：用于优化通信协议的实验软件 我们的研究项目的目标是设计和实施显着 用于本地和分布式的过程调用协议的新形式 通信该项目结合了应用技术的发展 从事编程语言设计的基础研究。研究 重点介绍了一种新的过程调用协议的实现， 结合了按值调用的理想语义， 按名字呼叫。实现依赖于共享技术 值以及计算线程的共享。与此密切相关的是 处理值和控制的语言原语的开发 结构以对称的方式。 分享的语用学与 分布式网络计算中的“线性命名”，特别是在命名时， 计算是移动的。过程调用协议及其交互 命名形式是将复杂计算结合在一起的粘合剂。中 在分布式环境中，不断发展的计算的一部分可以成为 彼此分离一个基本的问题是把这些部件 在适当的时候再聚在一起-这就是命名 是为了在命名中适当注意线性可以使跨网络 引用便宜，可以支持高度移动的数据结构，并且可以 方便物流人员按需有效地迁移任务， 明确的指导。

EIA-9806718 Mairson, Harry G. Bawden, Alan Brandeis University ESS: Linear Naming: Experimental Software for Optimizing Communication Protocols The goal of our research project is to design and implement significantly new forms of procedure calling protocols for local and distributed communication. This project combines development of applications technology with foundational research on programming language design. The research focuses on the implementation of a new procedure-calling protocol that incorporates the desirable semantics of call-by-value with the efficiency of call-by-name. The implementation depends on the technology of sharing values as well as the sharing of computation threads. Closely linked is the development of language primitives for handling values and control structures in a symmetric manner. The pragmatics of sharing is intimately connected to the crucial role of "linear naming" in distributed network computation, especially when named computations are mobile. Procedure-calling protocols and their interaction with naming form the glue that holds complex computations together. In a distributed environment, parts of an evolving computation can become separated from each other. A fundamental problem is bringing these parts back together again when the appropriate time arrives---this is what naming is for. Proper attention to linearity in naming can make cross-network references cheap, can support highly mobile data structures, and can facilitate heuristics to effectively migrate tasks on demand without explicit guidance.