24,631 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
Distributed Collaborative Monitoring in Software Defined Networks
We propose a Distributed and Collaborative Monitoring system, DCM, with the
following properties. First, DCM allow switches to collaboratively achieve flow
monitoring tasks and balance measurement load. Second, DCM is able to perform
per-flow monitoring, by which different groups of flows are monitored using
different actions. Third, DCM is a memory-efficient solution for switch data
plane and guarantees system scalability. DCM uses a novel two-stage Bloom
filters to represent monitoring rules using small memory space. It utilizes the
centralized SDN control to install, update, and reconstruct the two-stage Bloom
filters in the switch data plane. We study how DCM performs two representative
monitoring tasks, namely flow size counting and packet sampling, and evaluate
its performance. Experiments using real data center and ISP traffic data on
real network topologies show that DCM achieves highest measurement accuracy
among existing solutions given the same memory budget of switches
A network processor for a learning based routing protocol
Recently, Cognitive Packet Networks (CPN) is proposed as an alternative to the IP based network architectures and shows similarity with the discrete active networks. In CPN, there is no routing table, instead reinforcement learning (Random Neural Networks) is used to route packets. CPN routes packets based on QoS, using measurements that are constantly collected by packets and deposited in mailboxes at routers. The applicability of the CPN concept has been demonstrated through several software implementations. However, higher data traffic and increasing packet processing demands require the implementation of this new network architecture in hardware. In this paper, we present a network processor architecture which supports this learning based protocol. ©2004 IEEE
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Security analysis of the micro transport protocol with a misbehaving receiver
BitTorrent is the most widely used Peer-to-Peer (P2P) protocol and it comprises the largest share of traffic in Europe. To make BitTorrent more Internet Service Provider (ISP) friendly, BitTorrent Inc. invented the Micro Transport Protocol (uTP). It is based on UDP with a novel congestion control called Low Extra Delay Background Transport (LEDBAT). This protocol assumes that the receiver always gives correct feedback, since otherwise this deteriorates throughput or yields to corrupted data. We show through experimental investigation that a misbehaving uTP receiver, which is not interested in data integrity, can increase the bandwidth of the sender by up to five times. This can cause a congestion collapse and steal large share of a victim’s bandwidth. We present three attacks, which increase the bandwidth usage significantly. We have tested these attacks in a real world environment and show its severity both in terms of number of packets and total traffic generated. We also present a countermeasure for protecting against the attacks and evaluate the performance of that defence strategy
Measurement Based Reconfigurations in Optical Ring Metro Networks
Single-hop wavelength division multiplexing (WDM) optical ring networks operating in packet mode are one of themost promising architectures for the design of innovative metropolitan network (metro) architectures. They permit a cost-effective design, with a good combination of optical and electronic technologies, while supporting features like restoration and reconfiguration that are essential in any metro scenario. In this article, we address the tunability requirements that lead to an effective resource usage and permit reconfiguration in optical WDM metros.We introduce reconfiguration algorithms that, on the basis of traffic measurements, adapt the network configuration to traffic demands to optimize performance. Using a specific network architecture as a reference case, the paper aims at the broader goal of showing which are the advantages fostered by innovative network designs exploiting the features of optical technologies
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