Systems, Man & Cybernetics - October 2017 - 39
infrastructure monitoring data, which is the status of the
resources currently available or provisioned, including
uptime and resource use statistics. This data is provided
graphically or via an API to be directly used by control
mechanisms for routing decisions based on traffic measurements or link status.
Use Cases
The architecture and implementation provided by FELIX
was validated with two types of common scenarios in
modern data centers, i.e., the transmission of a large number of data flows, which can be very demanding on the
infrastructure (data domain), and the transmission, migration, and delocalization of the infrastructure or services
themselves (infrastructure domain). All use cases build on
the concept of automated flow switching within a data
center or between them across the transport layer. Data
domain use cases were achieved using OpenFlow-enabled
equipment to define paths within the data centers, and the
infrastructure domain use cases connected the endpoints
in each data center using NSI circuits over research and
education networks or common GRE tunnels, with network paths defined on-the-fly. The complete transcontinental FELIX infrastructure for these use cases can be
seen in Figure 5. We have previously reported some of the
use cases [11], [12] and will only focus on one data
domain and one infrastructure domain use case in the following sections.
Data Domain-Large-Scale Flows
for Data -Processing On-Demand
This use case focused on substantial data transmission
resulting from the sequential analysis of large sets of scientific raw data, such as that acquired from Earth
i2CAT FI Facility
(Spain)
6× OpenFlow Switches
3× Virtualization Servers
GÉANT
Plus
observation satellites and stored in data centers located in
close physical proximity to the acquisition point. In addition to demonstrating the functions of the FELIX SDI, this
use case also validated the integration of an enhanced
SDN-based controller, RYU [13], in support of on-demand
network path reconfigurations and showcased the transfer
of terabytes of data across the FELIX SDI.
The experimenter can choose a number of data centers
from which to obtain information, then define the slice on
top of them by requesting the required computing nodes
for the data postprocessing and the pool of network links
for the transmission. Once this is defined, it is possible to
request, enable, or disable paths communicating with the
FELIX SDI framework. An OpenFlow controller communicates with the equipment in the data center to define internal flows or routes between the hosts. The APIs exposed
by the RO to the experimenter provide a means to request,
start, or stop interdata center links at each moment. The
interdomain connectivity is defined by the experimenter
with varying degrees of detail, as illustrated in Figure 6.
Therefore, it was required to specify generic identifiers for
origin and destination domains or even to pinpoint specific endpoints, if detailed control was necessary. Altogether,
this defines dynamic connections in a matter of seconds to
a few minutes, depending on the type of connection and
the network segments to be traversed between infrastructures. Every specific portion of data can be transmitted
from the data center to the local working environment
individually and then postprocessed by algorithms developed by the experimenter.
This use case successfully demonstrated the dynamic
orchestration of heterogeneous federated infrastructures
while hiding the complexity of interdomain and transit do--
main network connections. Data was transferred on-demand
iMinds VirtualWall
(Belgium)
100+ Virtualization Servers
(+Open vSwitch Instances)
GÉANT BoD
(NSI)
GLIF
AutoGOLE
(NSI)
Internet
(GRE)
EICT FI Facility
(Germany)
1× OpenFlow Switches
1× Virtualization Servers
AIST FI Facility
(Japan)
2× OpenFlow Switches
5× Virtualization Servers
PSNC FI Facility
(Poland)
2× OpenFlow Switches
6× Virtualization Servers
KDDI FI Facility
(Japan)
2× OpenFlow Switches
Figure 5. The network connections between FELIX domains. BoD: bandwidth-on-demand; GLIF: Global Lambda
Integrated Facility; EICT: European Center for Information and Communication Technologies.
O c tob e r 2017
IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE
39
Table of Contents for the Digital Edition of Systems, Man & Cybernetics - October 2017
Systems, Man & Cybernetics - October 2017 - Cover1
Systems, Man & Cybernetics - October 2017 - Cover2
Systems, Man & Cybernetics - October 2017 - 1
Systems, Man & Cybernetics - October 2017 - 2
Systems, Man & Cybernetics - October 2017 - 3
Systems, Man & Cybernetics - October 2017 - 4
Systems, Man & Cybernetics - October 2017 - 5
Systems, Man & Cybernetics - October 2017 - 6
Systems, Man & Cybernetics - October 2017 - 7
Systems, Man & Cybernetics - October 2017 - 8
Systems, Man & Cybernetics - October 2017 - 9
Systems, Man & Cybernetics - October 2017 - 10
Systems, Man & Cybernetics - October 2017 - 11
Systems, Man & Cybernetics - October 2017 - 12
Systems, Man & Cybernetics - October 2017 - 13
Systems, Man & Cybernetics - October 2017 - 14
Systems, Man & Cybernetics - October 2017 - 15
Systems, Man & Cybernetics - October 2017 - 16
Systems, Man & Cybernetics - October 2017 - 17
Systems, Man & Cybernetics - October 2017 - 18
Systems, Man & Cybernetics - October 2017 - 19
Systems, Man & Cybernetics - October 2017 - 20
Systems, Man & Cybernetics - October 2017 - 21
Systems, Man & Cybernetics - October 2017 - 22
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Systems, Man & Cybernetics - October 2017 - 30
Systems, Man & Cybernetics - October 2017 - 31
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Systems, Man & Cybernetics - October 2017 - 35
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Systems, Man & Cybernetics - October 2017 - 37
Systems, Man & Cybernetics - October 2017 - 38
Systems, Man & Cybernetics - October 2017 - 39
Systems, Man & Cybernetics - October 2017 - 40
Systems, Man & Cybernetics - October 2017 - 41
Systems, Man & Cybernetics - October 2017 - 42
Systems, Man & Cybernetics - October 2017 - 43
Systems, Man & Cybernetics - October 2017 - 44
Systems, Man & Cybernetics - October 2017 - Cover3
Systems, Man & Cybernetics - October 2017 - Cover4
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