339 research outputs found
Evolving SDN for Low-Power IoT Networks
Software Defined Networking (SDN) offers a flexible and scalable architecture
that abstracts decision making away from individual devices and provides a
programmable network platform. However, implementing a centralized SDN
architecture within the constraints of a low-power wireless network faces
considerable challenges. Not only is controller traffic subject to jitter due
to unreliable links and network contention, but the overhead generated by SDN
can severely affect the performance of other traffic. This paper addresses the
challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks.
We explore how traditional SDN needs to evolve in order to overcome the
constraints of low-power wireless networks, and discuss protocol and
architectural optimizations necessary to reduce SDN control overhead - the main
barrier to successful implementation. We argue that interoperability with the
existing protocol stack is necessary to provide a platform for controller
discovery and coexistence with legacy networks. We consequently introduce
{\mu}SDN, a lightweight SDN framework for Contiki, with both IPv6 and
underlying routing protocol interoperability, as well as optimizing a number of
elements within the SDN architecture to reduce control overhead to practical
levels. We evaluate {\mu}SDN in terms of latency, energy, and packet delivery.
Through this evaluation we show how the cost of SDN control overhead (both
bootstrapping and management) can be reduced to a point where comparable
performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based
network. Additionally, we demonstrate {\mu}SDN through simulation: providing a
use-case where the SDN configurability can be used to provide Quality of
Service (QoS) for critical network flows experiencing interference, and we
achieve considerable reductions in delay and jitter in comparison to a scenario
without SDN
Seer: Empowering Software Defined Networking with Data Analytics
Network complexity is increasing, making network control and orchestration a
challenging task. The proliferation of network information and tools for data
analytics can provide an important insight into resource provisioning and
optimisation. The network knowledge incorporated in software defined networking
can facilitate the knowledge driven control, leveraging the network
programmability. We present Seer: a flexible, highly configurable data
analytics platform for network intelligence based on software defined
networking and big data principles. Seer combines a computational engine with a
distributed messaging system to provide a scalable, fault tolerant and
real-time platform for knowledge extraction. Our first prototype uses Apache
Spark for streaming analytics and open network operating system (ONOS)
controller to program a network in real-time. The first application we
developed aims to predict the mobility pattern of mobile devices inside a smart
city environment.Comment: 8 pages, 6 figures, Big data, data analytics, data mining, knowledge
centric networking (KCN), software defined networking (SDN), Seer, 2016 15th
International Conference on Ubiquitous Computing and Communications and 2016
International Symposium on Cyberspace and Security (IUCC-CSS 2016
Optical Network Virtualisation using Multi-technology Monitoring and SDN-enabled Optical Transceiver
We introduce the real-time multi-technology transport layer monitoring to
facilitate the coordinated virtualisation of optical and Ethernet networks
supported by optical virtualise-able transceivers (V-BVT). A monitoring and
network resource configuration scheme is proposed to include the hardware
monitoring in both Ethernet and Optical layers. The scheme depicts the data and
control interactions among multiple network layers under the software defined
network (SDN) background, as well as the application that analyses the
monitored data obtained from the database. We also present a re-configuration
algorithm to adaptively modify the composition of virtual optical networks
based on two criteria. The proposed monitoring scheme is experimentally
demonstrated with OpenFlow (OF) extensions for a holistic (re-)configuration
across both layers in Ethernet switches and V-BVTs
Isolating SDN Control Traffic with Layer-2 Slicing in 6TiSCH Industrial IoT Networks
Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel
Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide
deterministic communications and efficient allocation of resources across
constrained Internet of Things (IoT) networks, particularly in Industrial IoT
(IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been
identified as means of providing centralized control in a number of key
situations. However, implementing a centralized SDN architecture in a Low Power
and Lossy Network (LLN) faces considerable challenges: not only is controller
traffic subject to jitter due to unreliable links and network contention, but
the overhead generated by SDN can severely affect the performance of other
traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism
for creating dedicated forwarding paths across TSCH networks, in order to
isolate the SDN control overhead. Not only does this prevent control traffic
from affecting the performance of other data flows, but the properties of
6TiSCH tracks allows deterministic, low-latency SDN controller communication.
Using our own lightweight SDN implementation for Contiki OS, we firstly
demonstrate the effect of SDN control traffic on application data flows across
a 6TiSCH network. We then show that by slicing the network through the
allocation of dedicated resources along a SDN control path, tracks provide an
effective means of mitigating the cost of SDN control overhead in IEEE
802.15.4-2015 TSCH networks
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