An information centric network for computing the distribution of computations
An information centric network for computing the distribution of computations
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DOI：
10.1145/2660129.2660150
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
M. Sifalakis;B. Kohler;Christopher Scherb;C. Tschudin
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文献类型：
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作者：
M. Sifalakis;B. Kohler;Christopher Scherb;C. Tschudin
命名函数网络（NFN）扩展了经典的信息中心网络（ICN），除了通过名称解析数据访问外，它还支持函数定义的概念和在同一个通过名称解析过程中对数据（或其他函数）的应用。这使得网络能够选择内部（最佳）位置来满足潜在的复杂用户表达。转发优化和路由策略此后成为（重新）分配计算和检索结果的动态决策的基础。在本文中，我们描述了基于无类型Lambda表达式和Scala过程的NFN实例化的内在操作和机制。然后，我们通过一系列概念验证实验来演示它们如何扩展信息中心网络（CCN）的功能，用于编排和分发数据计算，并重新使用以前计算的缓存结果。最后，我们报告并讨论了来自这些实验的主要观察结果，并强调了可以影响专注于命名数据的ICN协议架构的重要见解。
Named Function Networking (NFN) extends classic Information Centric Networking (ICN), such that in addition to resolving data access by name, it also supports the concept of function definition and application to data (or other functions) in the same resolution-by-name process. This empowers the network to select internally (optimal) places for fulfilling a potentially complex user expression. Forwarding optimization and routing policies become thereafter a basis of dynamic decisions for (re)-distributing computations, and retrieving results. In this paper we describe the intrinsic operations and mechanisms of an instantiation of NFN based on untyped Lambda expressions and Scala procedures. Then, we demonstrate through a series of proof-of-concept experiments how they extend the capabilities of an information centric network (CCN), for orchestrating and distributing data computations, and re-using cached results from previous computations. In the end we report and discuss the main observations stemming from these experiments and highlight important insights that can impact the architecting of ICN protocols that focus on named-data.