1,641 research outputs found
Why (and How) Networks Should Run Themselves
The proliferation of networked devices, systems, and applications that we
depend on every day makes managing networks more important than ever. The
increasing security, availability, and performance demands of these
applications suggest that these increasingly difficult network management
problems be solved in real time, across a complex web of interacting protocols
and systems. Alas, just as the importance of network management has increased,
the network has grown so complex that it is seemingly unmanageable. In this new
era, network management requires a fundamentally new approach. Instead of
optimizations based on closed-form analysis of individual protocols, network
operators need data-driven, machine-learning-based models of end-to-end and
application performance based on high-level policy goals and a holistic view of
the underlying components. Instead of anomaly detection algorithms that operate
on offline analysis of network traces, operators need classification and
detection algorithms that can make real-time, closed-loop decisions. Networks
should learn to drive themselves. This paper explores this concept, discussing
how we might attain this ambitious goal by more closely coupling measurement
with real-time control and by relying on learning for inference and prediction
about a networked application or system, as opposed to closed-form analysis of
individual protocols
BPFabric: Data Plane Programmability for Software Defined Networks
In its current form, OpenFlow, the de facto implementation
of SDN, separates the network’s control and data
planes allowing a central controller to alter the matchaction
pipeline using a limited set of fields and actions.
To support new protocols, forwarding logic, telemetry,
monitoring or even middlebox-like functions the currently
available programmability in SDN is insufficient.
In this paper, we introduce BPFabric, a platform, protocol,
and language-independent architecture to centrally
program and monitor the data plane. BPFabric leverages
eBPF, a platform and protocol independent instruction
set to define the packet processing and forwarding functionality
of the data plane. We introduce a control plane
API that allows data plane functions to be deployed onthe-fly,
reporting events of interest and exposing network
internal state.
We present a raw socket and DPDK implementation
of the design, the former for large-scale experimentation
using environment such as Mininet and the latter for
high-performance low-latency deployments. We show
through examples that functions unrealisable in OpenFlow
can leverage this flexibility while achieving similar
or better performance to today’s static design
Will SDN be part of 5G?
For many, this is no longer a valid question and the case is considered
settled with SDN/NFV (Software Defined Networking/Network Function
Virtualization) providing the inevitable innovation enablers solving many
outstanding management issues regarding 5G. However, given the monumental task
of softwarization of radio access network (RAN) while 5G is just around the
corner and some companies have started unveiling their 5G equipment already,
the concern is very realistic that we may only see some point solutions
involving SDN technology instead of a fully SDN-enabled RAN. This survey paper
identifies all important obstacles in the way and looks at the state of the art
of the relevant solutions. This survey is different from the previous surveys
on SDN-based RAN as it focuses on the salient problems and discusses solutions
proposed within and outside SDN literature. Our main focus is on fronthaul,
backward compatibility, supposedly disruptive nature of SDN deployment,
business cases and monetization of SDN related upgrades, latency of general
purpose processors (GPP), and additional security vulnerabilities,
softwarization brings along to the RAN. We have also provided a summary of the
architectural developments in SDN-based RAN landscape as not all work can be
covered under the focused issues. This paper provides a comprehensive survey on
the state of the art of SDN-based RAN and clearly points out the gaps in the
technology.Comment: 33 pages, 10 figure
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