R2: A Distributed Remote Function Execution Mechanism With Built-in Metadata

TL;DR

This paper introduces R2, a distributed mechanism for remote function execution in Named Data Networking, optimizing resource allocation and execution time through a two-phase process with metadata-driven node selection.

Contribution

The paper presents R2, a novel distributed remote function execution mechanism with a metadata-based name structure and a two-phase process, improving efficiency in NDN environments.

Findings

R2 outperforms existing solutions in resource allocation.

Speedup ratio of 4.61 for 100 KiB data and quadratic function complexity.

Effective reduction of processing time with stop condition and analysis.

Abstract

Named data networking (NDN) constructs a network by names, providing a flexible and decentralized way to manage resources within the edge computing continuum. This paper aims to solve the question, "Given a function with its parameters and metadata, how to select the executor in a distributed manner and obtain the result in NDN?" To answer it, we design R2 that involves the following stages. First, we design a name structure including data, function names, and other function parameters. Second, we develop a 2-phase mechanism, where in the first phase, the function request from a client-first reaches the data source and retrieves the metadata, then the best node is selected while the metadata is responding to the client. In the second phase, the chosen node directly retrieves the data, executes the function, and provides the result to the client. Furthermore, we propose a stop condition to intelligently reduce the processing time of the first phase and provide a simple proof and range analysis. Simulations confirm that R2 outperforms the current solutions in terms of resource allocation, especially when the data volume and the function complexity are high. In the experiments, when the data size is 100 KiB and the function complexity is $\mathcal{O}(n^2)$, the speedup ratio is 4.61. To further evaluate R2, we also implement a general intermediate data processing logic named ``Bolt'' implemented on an app-level in ndnSIM. We believe that R2 shall help the researchers and developers to verify their ideas smoothly.