2021
1.
Alhowaidi, Mohammad; Nadig, Deepak; Hu, Boyang; Ramamurthy, Byrav; Bockelman, Brian
Cache management for large data transfers and multipath forwarding strategies in Named Data Networking Journal Article
In: Computer Networks, vol. 199, pp. 108437, 2021, ISSN: 1389-1286.
Abstract | BibTeX | Tags: Cache management, Compact Muon Solenoid, Forwarding strategy, NDN, SDN | Links:
@article{ALHOWAIDI2021108437,
title = {Cache management for large data transfers and multipath forwarding strategies in Named Data Networking},
author = {Mohammad Alhowaidi and Deepak Nadig and Boyang Hu and Byrav Ramamurthy and Brian Bockelman},
url = {https://www.sciencedirect.com/science/article/pii/S1389128621003972},
doi = {10.1016/j.comnet.2021.108437},
issn = {1389-1286},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
journal = {Computer Networks},
volume = {199},
pages = {108437},
abstract = {Named Data Networking (NDN) is a promising approach to provide fast in-network access to compact muon solenoid (CMS) datasets. It proposes a content-centric rather than a host-centric approach to data retrieval. Data packets with unique and immutable names are retrieved from a content store (CS) using Interest packets. The current NDN architecture relies on forwarding strategies that are only dependent upon on-path caching. Such a design does not take advantage of the cached content available on the adjacent off-path routers in the network, thus reducing data transfer efficiency. In this work, we propose a software-defined, storage-aware routing mechanism that leverages NDN router cache-states, software defined networking (SDN) and multipath forwarding strategies to improve the efficiency of very large data transfers. First, we propose a novel distributed multipath (D-MP) forwarding strategy and enhancements to the NDN Interest forwarding pipeline. In addition, we develop a centralized SDN-enabled control for the multipath forwarding strategy (S-MP), which leverages the global knowledge of NDN network states that distributes Interests efficiently. We perform extensive evaluations of our proposed methods on an at-scale wide area network (WAN) testbed spanning six geographically separated sites. Our proposed solutions easily outperform the existing NDN forwarding strategies. The D-MP strategy results in performance gains ranging between 10.4x to 12.5x over the default NDN implementation without in-network caching, and 12.2x to 18.4x with in-network caching enabled. For S-MP strategy, we demonstrate a performance improvement of 10.6x to 12.6x, and 12.9x to 18.5x, with in-network caching disabled and enabled, respectively. Further, we also present a comprehensive analysis of NDN cache management for large data transfers and propose a novel prefetching mechanism to improve data transfer performance. Due to the inherent capacity limitations of the NDN router caches, we use SDN to provide an intelligent and efficient solution for data distribution and routing across multiple NDN router caches. We demonstrate how software-defined control can be used to partition and distribute large CMS files based on NDN router cache-state knowledge. Further, SDN control will also configure the router forwarding strategy to retrieve CMS data from the network. Our proposed solution demonstrates that the CMS datasets can be retrieved 28%–38% faster from the NDN routers’ caches than existing NDN approaches. Lastly, we develop a prefetching mechanism to improve the transfer performance of files that are not available in the router’s cache.},
keywords = {Cache management, Compact Muon Solenoid, Forwarding strategy, NDN, SDN},
pubstate = {published},
tppubtype = {article}
}
Named Data Networking (NDN) is a promising approach to provide fast in-network access to compact muon solenoid (CMS) datasets. It proposes a content-centric rather than a host-centric approach to data retrieval. Data packets with unique and immutable names are retrieved from a content store (CS) using Interest packets. The current NDN architecture relies on forwarding strategies that are only dependent upon on-path caching. Such a design does not take advantage of the cached content available on the adjacent off-path routers in the network, thus reducing data transfer efficiency. In this work, we propose a software-defined, storage-aware routing mechanism that leverages NDN router cache-states, software defined networking (SDN) and multipath forwarding strategies to improve the efficiency of very large data transfers. First, we propose a novel distributed multipath (D-MP) forwarding strategy and enhancements to the NDN Interest forwarding pipeline. In addition, we develop a centralized SDN-enabled control for the multipath forwarding strategy (S-MP), which leverages the global knowledge of NDN network states that distributes Interests efficiently. We perform extensive evaluations of our proposed methods on an at-scale wide area network (WAN) testbed spanning six geographically separated sites. Our proposed solutions easily outperform the existing NDN forwarding strategies. The D-MP strategy results in performance gains ranging between 10.4x to 12.5x over the default NDN implementation without in-network caching, and 12.2x to 18.4x with in-network caching enabled. For S-MP strategy, we demonstrate a performance improvement of 10.6x to 12.6x, and 12.9x to 18.5x, with in-network caching disabled and enabled, respectively. Further, we also present a comprehensive analysis of NDN cache management for large data transfers and propose a novel prefetching mechanism to improve data transfer performance. Due to the inherent capacity limitations of the NDN router caches, we use SDN to provide an intelligent and efficient solution for data distribution and routing across multiple NDN router caches. We demonstrate how software-defined control can be used to partition and distribute large CMS files based on NDN router cache-state knowledge. Further, SDN control will also configure the router forwarding strategy to retrieve CMS data from the network. Our proposed solution demonstrates that the CMS datasets can be retrieved 28%–38% faster from the NDN routers’ caches than existing NDN approaches. Lastly, we develop a prefetching mechanism to improve the transfer performance of files that are not available in the router’s cache.