Edge Cloud (EC) is poised to brace massive
machine type communication (mMTC) for 5G and IoT by
providing compute and network resources at the edge. Yet,
the EC being regionally domestic with a smaller scale, faces
the challenges of bandwidth and computational throughput.
Resource management techniques are considered necessary
to achieve efficient resource allocation objectives. Software
Defined Network (SDN) enabled EC architecture is emerging as
a potential solution that enables dynamic bandwidth allocation
and task scheduling for latency sensitive and diverse mobile
applications in the EC environment. This study proposes a
novel Heuristic Reinforcement Learning (HRL) based flowlevel
dynamic bandwidth allocation framework and validates
it through end-to-end implementation using OpenFlow meter
feature. OpenFlow meter provides granular control and allows
demand-based flow management to meet the diverse QoS requirements
germane to IoT traffics. The proposed framework is
then evaluated by emulating an EC scenario based on real NSF
COSMOS testbed topology at The City College of New York. A
specific heuristic reinforcement learning with linear-annealing
technique and a pruning principle are proposed and compared
with the baseline approach. Our proposed strategy performs
consistently in both Mininet and hardware OpenFlow switches
based environments. The performance evaluation considers
key metrics associated with real-time applications: throughput,
end-to-end delay, packet loss rate, and overall system cost
for bandwidth allocation. Furthermore, our proposed linear
annealing method achieves faster convergence rate and better
reward in terms of system cost, and the proposed pruning
principle remarkably reduces control traffic in the network.
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A Formal Model for Resiliency-Aware Deployment of SDN: A SCADA-Based Case Study
The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller. Introducing SDN into a SCADA network helps in deploying novel grid control operations, as well as, their management. As the overall network cannot be transformed to have only SDN-enabled devices overnight because of budget constraints, a systematic deployment methodology is needed. In this work, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are specified with respect to a set of identified threat vectors. The deployment plan primarily includes the best placements of the SDN-enabled switches. The plan may include one or more links to be installed newly. We model and implement the SDNSynth framework that includes the satisfaction of several requirements and constraints involved in the resilient operation of the SCADA. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study and evaluate its performance on different synthetic SCADA systems.
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- Award ID(s):
- 1929183
- NSF-PAR ID:
- 10145189
- Date Published:
- Journal Name:
- 15th International Conference on Network and Service Management (CNSM)
- Page Range / eLocation ID:
- 1 to 5
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The emergency of machine type and ultra-reliable low latency communication is imposing stringent constraints for service provisioning. Addressing such constraints is challenging for network and cloud service providers. As a trending paradigm, software-defined networking (SDN) plays a significant role in future networks and services. However, the classical implementation of the SDN controller has limitations in-terms-of latency and reliability since the controller is decoupled from the forwarding device. Several research works have tried to tackle these challenges by proposing solutions such as Devoflow, DIFANE, and hierarchical and distributed controller deployment. Nonetheless, these approaches are not fully addressing these challenges. This paper tries to address the problem of latency and reliability by proposing a dynamic controller role delegation architecture for forwarding devices. To align with the microservice or multi-agent-based service-based architecture, the role delegation function as a service is proposed. The dynamic role delegation enables to predict and (pre-)installed flow rules in the forwarding devices based on various considerations such as network state, packet type, and service's stringent requirements. The proposed architecture is implemented and evaluated for latency and resiliency performance in comparison to the centralized and distributed deployment of the SDN controller. We used ComNetsEmu, a softwarized network emulation tool, to emulate SDN and NFV (Network Function Virtualization). The result indicated a significant decrease in latency and improved resilience in case of failure, yielding better network performance.more » « less
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Summary The Pacific Rim Application and Grid Middleware Assembly (PRAGMA) is an international community of researchers that actively collaborate to address problems and challenges of common interest in eScience. The PRAGMA Experimental Network Testbed (PRAGMA‐ENT) was established with the goal of constructing an international software‐defined network (SDN) testbed to offer the necessary networking support to the PRAGMA cyberinfrastructure. PRAGMA‐ENT is isolated, and PRAGMA researchers have complete freedom to access network resources to develop, experiment, and evaluate new ideas without the concerns of interfering with production networks.
In the first phase, PRAGMA‐ENT focused on establishing an international L2 backbone. With support from the Florida Lambda Rail, Internet2, PacificWave, Japan Gigabit Network, and TaiWan Advanced Research and Education Network, PRAGMA‐ENT backbone connects openflow‐enabled switches at University of Florida, University of California, San Diego, Nara Institute of Science and Technology (Japan), Osaka University (Japan), National Institute of Advanced Industrial Science and Technology (Japan), and National Applied Research Laboratories (Taiwan).
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.23919/CNSM46954.2019.9012715
