2021
2.
Nadig, Deepak; Alaoui, Sara El; Ramamurthy, Byrav; Pitla, Santosh
ERGO: A Scalable Edge Computing Architecture for Infrastructureless Agricultural Internet of Things Proceedings Article
In: 2021 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), pp. 1–2, 2021, (ISSN: 1944-0375).
Abstract | BibTeX | Tags: Ag-IoT, cloud computing, Computer architecture, Edge Computing, Infrastructureless, Instruments, machine learning, Metropolitan area networks, Performance evaluation, Throughput | Links:
@inproceedings{nadig_ergo_2021,
title = {ERGO: A Scalable Edge Computing Architecture for Infrastructureless Agricultural Internet of Things},
author = {Deepak Nadig and Sara El Alaoui and Byrav Ramamurthy and Santosh Pitla},
url = {https://deepaknadig.com/wp-content/uploads/2021/09/Nadig-et-al.-2021-ERGO-A-Scalable-Edge-Computing-Architecture-for-I.pdf},
doi = {10.1109/LANMAN52105.2021.9478811},
year = {2021},
date = {2021-07-01},
urldate = {2021-07-01},
booktitle = {2021 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN)},
pages = {1--2},
abstract = {In this paper, we propose ERGO (edge architecture for Ag-IoT), an edge-computing architecture for infrastructureless smart agriculture environments. We also develop Ag-IoT application APIs and the associated microservice infrastructure. Our implementation and evaluations show that ERGO can operate independently of cloud-backed assistance, is highly scalable, modular, and affords composability benefits to Ag-IoT systems. We also demonstrate that ERGO outperforms traditional infrastructure in response latencies and transactional throughput, on average, by over 54% and 77%, respectively.},
note = {ISSN: 1944-0375},
keywords = {Ag-IoT, cloud computing, Computer architecture, Edge Computing, Infrastructureless, Instruments, machine learning, Metropolitan area networks, Performance evaluation, Throughput},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we propose ERGO (edge architecture for Ag-IoT), an edge-computing architecture for infrastructureless smart agriculture environments. We also develop Ag-IoT application APIs and the associated microservice infrastructure. Our implementation and evaluations show that ERGO can operate independently of cloud-backed assistance, is highly scalable, modular, and affords composability benefits to Ag-IoT systems. We also demonstrate that ERGO outperforms traditional infrastructure in response latencies and transactional throughput, on average, by over 54% and 77%, respectively.
2018
1.
Alhowaidi, M.; Nadig, D.; Ramamurthy, B.; Bockelman, B.; Swanson, D.
Multipath Forwarding Strategies and SDN Control for Named Data Networking Proceedings Article
In: 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1–6, 2018.
Abstract | BibTeX | Tags: Computer architecture, Data transfer, IP networks, Pipeline processing, Pipelines, Routing, Routing protocols | Links:
@inproceedings{alhowaidi_multipath_2018,
title = {Multipath Forwarding Strategies and SDN Control for Named Data Networking},
author = {M. Alhowaidi and D. Nadig and B. Ramamurthy and B. Bockelman and D. Swanson},
url = {https://deepaknadig.com/wp-content/uploads/2021/09/Alhowaidi-et-al.-2018-Multipath-Forwarding-Strategies-and-SDN-Control-fo.pdf},
doi = {10.1109/ANTS.2018.8710068},
year = {2018},
date = {2018-12-01},
urldate = {2018-12-01},
booktitle = {2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)},
pages = {1--6},
abstract = {Named Data Networking (NDN) proposes a contentcentric 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 dependent upon on-path caching and is therefore inefficient. This approach reduces data transfer efficiency by ignoring the cached content available on the adjacent off-path routers in the network. In this paper, we propose a novel distributed multipath (D-MP) forwarding strategy and enhancements to the NDN Interest forwarding pipeline. Furthermore, we develop a centralized SDNenabled control for the multipath forwarding strategy (S-MP) that distributes Interests efficiently by using the global knowledge of the NDN network states. We perform extensive evaluations of our proposed methods on an at-scale WAN testbed spanning six geographically separated sites. Our solutions outperform the existing NDN forwarding strategies by a significant margin. We show that 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 gains of 12.2x to 18.4x with in-network caching. In addition, for the S-MP case, we demonstrate a performance improvement of 10.6x to 12.6x, and 12.9x to 18.5x, for with- and without in-network caching respectively.},
keywords = {Computer architecture, Data transfer, IP networks, Pipeline processing, Pipelines, Routing, Routing protocols},
pubstate = {published},
tppubtype = {inproceedings}
}
Named Data Networking (NDN) proposes a contentcentric 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 dependent upon on-path caching and is therefore inefficient. This approach reduces data transfer efficiency by ignoring the cached content available on the adjacent off-path routers in the network. In this paper, we propose a novel distributed multipath (D-MP) forwarding strategy and enhancements to the NDN Interest forwarding pipeline. Furthermore, we develop a centralized SDNenabled control for the multipath forwarding strategy (S-MP) that distributes Interests efficiently by using the global knowledge of the NDN network states. We perform extensive evaluations of our proposed methods on an at-scale WAN testbed spanning six geographically separated sites. Our solutions outperform the existing NDN forwarding strategies by a significant margin. We show that 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 gains of 12.2x to 18.4x with in-network caching. In addition, for the S-MP case, we demonstrate a performance improvement of 10.6x to 12.6x, and 12.9x to 18.5x, for with- and without in-network caching respectively.