Towards an approximate graph entropy measure for identifying incidents in network event data

A key objective of monitoring networks is to identify potential service threatening outages from events within the network before service is interrupted. Identifying causal events, Root Cause Analysis (RCA), is an active area of research, but current approaches are vulnerable to scaling issues with high event rates. Elimination of noisy events that are not causal is key to ensuring the scalability of RCA. In this paper, we introduce vertex-level measures inspired by Graph Entropy and propose their suitability as a categorization metric to identify nodes that are a priori of more interest as a source of events. We consider a class of measures based on Structural, Chromatic and Von Neumann Entropy. These measures require NP-Hard calculations over the whole graph, an approach which obviously does not scale for large dynamic graphs that characterise modern networks. In this work we identify and justify a local measure of vertex graph entropy, which behaves in a similar fashion to global measures of entropy when summed across the whole graph. We show that such measures are correlated with nodes that generate incidents across a network from a real data set

Short vs. long flows: a battle that both can win

In this paper, we introduce MMPTCP, a hybrid transport protocol which aims at unifying the way data is transported in data centres. MMPTCP runs in two phases; initially, it randomly scatters packets in the network under a single congestion window exploiting all available paths. This is beneficial to latency-sensitive flows. During the second phase, MMPTCP runs in Multi-Path TCP mode, which has been shown to be very efficient for long flows. Initial evaluation shows that our approach significantly improves short flow completion times while providing high throughput for long flows and high overall network utilisation

Evaluating modern data centre transport protocols in OMNeT++/INET

In this paper we present our work towards an evaluation platform for data centre transport protocols. We developed a simulation model for NDP1, a modern data transport protocol in data centres, a FatTree network topology and per-packet ECMP load balancing. We also developed a data centre environment that can be used to evaluate and compare data transport protocols, such as NDP and TCP. We describe how we integrated our model with the INET Framework and present example simulations to showcase the workings of the developed framework. For that, we ran a comprehensive set of experiments and studied different components and parameters of the developed models

Enhancing multi-source content delivery in content-centric networks with fountain coding

Fountain coding has been considered as especially suitable for lossy environments, such as wireless networks, as it provides redundancy while reducing coordination overheads between sender(s) and receiver(s). As such it presents beneficial properties for multi-source and/or multicast communication. In this paper we investigate enhancing/increasing multi-source content delivery efficiency in the context of Content-Centric Networking (CCN) with the usage of fountain codes. In particular, we examine whether the combination of fountain coding with the in-network caching capabilities of CCN can further improve performance. We also present an enhancement of CCN's Interest forwarding mechanism that aims at minimizing duplicate transmissions that may occur in a multi-source transmission scenario, where all available content providers and caches with matching (cached) content transmit data packets simultaneously. Our simulations indicate that the use of fountain coding in CCN is a valid approach that further increases network performance compared to traditional schemes

Poster: an in-vehicle software defined network architecture for connected and automated vehicles

Vehicular network architectures are being reviewed and re-designed to meet requirements for increasing data rates and flexibility driven in part by the adoption of Connected and Automated Vehicles (CAV) strategies. A progressive move from traditional bus based networks, such as CAN, to Ethernet-based network architectures is being considered across the automotive industry. In this paper we advocate for an in-vehicle Software-Defined Network architecture and discuss benefits that such a shift in the architectural paradigm will bring by strengthening cyber-security defences and enabling a fail-operational capability through network programmability and provably correct networks

Multipath TCP in ns-3

In this paper we present our work on designing and implementing an NS3 model for MultiPath TCP (MPTCP). Our MPTCP model closely follows MPTCP specifications, as described in RFC 6824, and supports TCP NewReno loss recovery on a per subflow basis. Subflow management is based on MPTCP's kernel implementation. We briefly describe how we integrate our MPTCP model with NS3 and present example simulation results to showcase its working state

Polyraptor: embracing path and data redundancy in data centres for efficient data transport

In this paper, we introduce Polyraptor, a novel data transport protocol that uses RaptorQ (RQ) codes and is tailored for one-to-many and many-to-one data transfer patterns, which are extremely common in modern data centres. Polyraptor builds on previous work on fountain coding-based transport and provides excellent performance, by exploiting native support for multicasting in data centres and data resilience provided by data replication

Towards model checking real-world software-defined networks

In software-defined networks (SDN), a controller program is in charge of deploying diverse network functionality across a large number of switches, but this comes at a great risk: deploying buggy controller code could result in network and service disruption and security loopholes. The automatic detection of bugs or, even better, verification of their absence is thus most desirable, yet the size of the network and the complexity of the controller makes this a challenging undertaking. In this paper, we propose MOCS, a highly expressive, optimised SDN model that allows capturing subtle real-world bugs, in a reasonable amount of time. This is achieved by (1) analysing the model for possible partial order reductions, (2) statically pre-computing packet equivalence classes and (3) indexing packets and rules that exist in the model. We demonstrate its superiority compared to the state of the art in terms of expressivity, by providing examples of realistic bugs that a prototype implementation of MOCS in Uppaal caught, and performance/scalability, by running examples on various sizes of network topologies, highlighting the importance of our abstractions and optimisations