34,170 research outputs found
Computing Persistent Homology of Directed Flag Complexes
This work was funded in part by an EPSRC grant EP/P025072/—“Topological Analysis of Neural Systems”.Peer reviewedPublisher PD
Consistent SDNs through Network State Fuzzing
The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Nevertheless, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part. Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to continuously test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly
A comparison of three heuristics to choose the variable ordering for CAD
Cylindrical algebraic decomposition (CAD) is a key tool for problems in real
algebraic geometry and beyond. When using CAD there is often a choice over the
variable ordering to use, with some problems infeasible in one ordering but
simple in another. Here we discuss a recent experiment comparing three
heuristics for making this choice on thousands of examples
HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges
High Performance Computing (HPC) clouds are becoming an alternative to
on-premise clusters for executing scientific applications and business
analytics services. Most research efforts in HPC cloud aim to understand the
cost-benefit of moving resource-intensive applications from on-premise
environments to public cloud platforms. Industry trends show hybrid
environments are the natural path to get the best of the on-premise and cloud
resources---steady (and sensitive) workloads can run on on-premise resources
and peak demand can leverage remote resources in a pay-as-you-go manner.
Nevertheless, there are plenty of questions to be answered in HPC cloud, which
range from how to extract the best performance of an unknown underlying
platform to what services are essential to make its usage easier. Moreover, the
discussion on the right pricing and contractual models to fit small and large
users is relevant for the sustainability of HPC clouds. This paper brings a
survey and taxonomy of efforts in HPC cloud and a vision on what we believe is
ahead of us, including a set of research challenges that, once tackled, can
help advance businesses and scientific discoveries. This becomes particularly
relevant due to the fast increasing wave of new HPC applications coming from
big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR
Road to the Restoration of the Ohrid Archbishopric
The restoration of the abolished Ohrid Archbishopric did not begin with the processes at the end of the World War II, but immediately after its abolition in the eighteenth century. The restoration of the Ohrid Archbishopric as the Macedonian Orthodox Church is in full accordance with the church tradition and practices established by the other local Orthodox churches in the process of obtaining their autocephaly during the nineteenth and twentieth centuries
Consistent SDNs through Network State Fuzzing
The conventional wisdom is that a software-defined network (SDN) operates
under the premise that the logically centralized control plane has an accurate
representation of the actual data plane state. Unfortunately, bugs,
misconfigurations, faults or attacks can introduce inconsistencies that
undermine correct operation. Previous work in this area, however, lacks a
holistic methodology to tackle this problem and thus, addresses only certain
parts of the problem. Yet, the consistency of the overall system is only as
good as its least consistent part. Motivated by an analogy of network
consistency checking with program testing, we propose to add active probe-based
network state fuzzing to our consistency check repertoire. Hereby, our system,
PAZZ, combines production traffic with active probes to periodically test if
the actual forwarding path and decision elements (on the data plane) correspond
to the expected ones (on the control plane). Our insight is that active traffic
covers the inconsistency cases beyond the ones identified by passive traffic.
PAZZ prototype was built and evaluated on topologies of varying scale and
complexity. Our results show that PAZZ requires minimal network resources to
detect persistent data plane faults through fuzzing and localize them quickly
while outperforming baseline approaches.Comment: Added three extra relevant references, the arXiv later was accepted
in IEEE Transactions of Network and Service Management (TNSM), 2019 with the
title "Towards Consistent SDNs: A Case for Network State Fuzzing
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