198 research outputs found
Optimal Networks from Error Correcting Codes
To address growth challenges facing large Data Centers and supercomputing
clusters a new construction is presented for scalable, high throughput, low
latency networks. The resulting networks require 1.5-5 times fewer switches,
2-6 times fewer cables, have 1.2-2 times lower latency and correspondingly
lower congestion and packet losses than the best present or proposed networks
providing the same number of ports at the same total bisection. These advantage
ratios increase with network size. The key new ingredient is the exact
equivalence discovered between the problem of maximizing network bisection for
large classes of practically interesting Cayley graphs and the problem of
maximizing codeword distance for linear error correcting codes. Resulting
translation recipe converts existent optimal error correcting codes into
optimal throughput networks.Comment: 14 pages, accepted at ANCS 2013 conferenc
Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results
Fixed and mobile telecom operators, enterprise network operators and cloud
providers strive to face the challenging demands coming from the evolution of
IP networks (e.g. huge bandwidth requirements, integration of billions of
devices and millions of services in the cloud). Proposed in the early 2010s,
Segment Routing (SR) architecture helps face these challenging demands, and it
is currently being adopted and deployed. SR architecture is based on the
concept of source routing and has interesting scalability properties, as it
dramatically reduces the amount of state information to be configured in the
core nodes to support complex services. SR architecture was first implemented
with the MPLS dataplane and then, quite recently, with the IPv6 dataplane
(SRv6). IPv6 SR architecture (SRv6) has been extended from the simple steering
of packets across nodes to a general network programming approach, making it
very suitable for use cases such as Service Function Chaining and Network
Function Virtualization. In this paper we present a tutorial and a
comprehensive survey on SR technology, analyzing standardization efforts,
patents, research activities and implementation results. We start with an
introduction on the motivations for Segment Routing and an overview of its
evolution and standardization. Then, we provide a tutorial on Segment Routing
technology, with a focus on the novel SRv6 solution. We discuss the
standardization efforts and the patents providing details on the most important
documents and mentioning other ongoing activities. We then thoroughly analyze
research activities according to a taxonomy. We have identified 8 main
categories during our analysis of the current state of play: Monitoring,
Traffic Engineering, Failure Recovery, Centrally Controlled Architectures, Path
Encoding, Network Programming, Performance Evaluation and Miscellaneous...Comment: SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIAL
The Role of Inter-Controller Traffic for Placement of Distributed SDN Controllers
We consider a distributed Software Defined Networking (SDN) architecture
adopting a cluster of multiple controllers to improve network performance and
reliability. Besides the Openflow control traffic exchanged between controllers
and switches, we focus on the control traffic exchanged among the controllers
in the cluster, needed to run coordination and consensus algorithms to keep the
controllers synchronized. We estimate the effect of the inter-controller
communications on the reaction time perceived by the switches depending on the
data-ownership model adopted in the cluster. The model is accurately validated
in an operational Software Defined WAN (SDWAN). We advocate a careful placement
of the controllers, that should take into account both the above kinds of
control traffic. We evaluate, for some real ISP network topologies, the delay
tradeoffs for the controllers placement problem and we propose a novel
evolutionary algorithm to find the corresponding Pareto frontier. Our work
provides novel quantitative tools to optimize the planning and the design of
the network supporting the control plane of SDN networks, especially when the
network is very large and in-band control plane is adopted. We also show that
for operational distributed controllers (e.g. OpenDaylight and ONOS), the
location of the controller which acts as a leader in the consensus algorithm
has a strong impact on the reactivity perceived by switches.Comment: 14 page
A Cognitive Routing framework for Self-Organised Knowledge Defined Networks
This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one.
The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing
environment using Distributed Ledger Technology.
The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing
SNAP: Stateful Network-Wide Abstractions for Packet Processing
Early programming languages for software-defined networking (SDN) were built
on top of the simple match-action paradigm offered by OpenFlow 1.0. However,
emerging hardware and software switches offer much more sophisticated support
for persistent state in the data plane, without involving a central controller.
Nevertheless, managing stateful, distributed systems efficiently and correctly
is known to be one of the most challenging programming problems. To simplify
this new SDN problem, we introduce SNAP.
SNAP offers a simpler "centralized" stateful programming model, by allowing
programmers to develop programs on top of one big switch rather than many.
These programs may contain reads and writes to global, persistent arrays, and
as a result, programmers can implement a broad range of applications, from
stateful firewalls to fine-grained traffic monitoring. The SNAP compiler
relieves programmers of having to worry about how to distribute, place, and
optimize access to these stateful arrays by doing it all for them. More
specifically, the compiler discovers read/write dependencies between arrays and
translates one-big-switch programs into an efficient internal representation
based on a novel variant of binary decision diagrams. This internal
representation is used to construct a mixed-integer linear program, which
jointly optimizes the placement of state and the routing of traffic across the
underlying physical topology. We have implemented a prototype compiler and
applied it to about 20 SNAP programs over various topologies to demonstrate our
techniques' scalability
Optimizing Flow Rule Installations on SDN based Switches
Traditional network monitoring involving packet capturing or flow sampling has many challenges such as scalability, accuracy and availability of processing resource when networks become large-scale, high-speed and heterogeneous. SDN is a promising approach to address these challenges, in which highly granular flow rule installations can provide us with fine-grained flow based statistic. But each SDN switch has its own capacity limitation, such as its cache memory called TCAM, which can get exhausted with a large number of highly granular flow rule installations. Thus, network nodes need coordination of resources with other network nodes to monitor the network in a scalable manner. This thesis introduces an intelligent framework, called lite-flow, which divides flow rule installations into two parts, monitoring and forwarding flow rules. The proposed system distributes the load of monitoring flows among SDN switches, and makes the scalability and accuracy of network
monitoring manageable. Also, we introduce a forwarding mechanism which uses a more abundant L2 cache in SDN switches based on MAC labels
Enabling Scalable and Sustainable Softwarized 5G Environments
The fifth generation of telecommunication systems (5G) is foreseen to play a fundamental
role in our socio-economic growth by supporting various and radically new vertical
applications (such as Industry 4.0, eHealth, Smart Cities/Electrical Grids, to name
a few), as a one-fits-all technology that is enabled by emerging softwarization solutions
\u2013 specifically, the Fog, Multi-access Edge Computing (MEC), Network Functions Virtualization
(NFV) and Software-Defined Networking (SDN) paradigms. Notwithstanding
the notable potential of the aforementioned technologies, a number of open issues
still need to be addressed to ensure their complete rollout. This thesis is particularly developed
towards addressing the scalability and sustainability issues in softwarized 5G
environments through contributions in three research axes: a) Infrastructure Modeling
and Analytics, b) Network Slicing and Mobility Management, and c) Network/Services Management
and Control. The main contributions include a model-based analytics approach
for real-time workload profiling and estimation of network key performance indicators
(KPIs) in NFV infrastructures (NFVIs), as well as a SDN-based multi-clustering approach
to scale geo-distributed virtual tenant networks (VTNs) and to support seamless
user/service mobility; building on these, solutions to the problems of resource consolidation,
service migration, and load balancing are also developed in the context of 5G.
All in all, this generally entails the adoption of Stochastic Models, Mathematical Programming,
Queueing Theory, Graph Theory and Team Theory principles, in the context
of Green Networking, NFV and SDN
- …