@inproceedings {INPROC-2017-51,
author = {Thomas Bach and Muhammad Adnan Tariq and Ruben Mayer and Kurt Rothermel},
title = {{Knowledge is at the Edge! How to Search in Distributed Machine Learning Models}},
booktitle = {OTM 2017 Conferences},
publisher = {Springer International Publishing},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {1--19},
type = {Konferenz-Beitrag},
month = {Oktober},
year = {2017},
doi = {10.1007/978-3-319-69462-7_27},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2017-51/INPROC-2017-51.pdf},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Verteilte Systeme},
abstract = {},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-51&engl=0}
}
@inproceedings {INPROC-2015-42,
author = {Thomas Bach and Muhammad Adnan Tariq and Christian Mayer and Kurt Rothermel},
title = {{Utilizing the Hive Mind - How to Manage Knowledge in Fully Distributed Environments}},
booktitle = {OTM 2015 Conferences},
address = {Rhodos},
publisher = {Springer Verlag},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {1--18},
type = {Konferenz-Beitrag},
month = {Oktober},
year = {2015},
keywords = {Knowledge retrieval; Distributed knowledge; Confidence-based indexing; Indexing; Query routing; Knowledge},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2015-42/INPROC-2015-42.pdf},
contact = {thomas.bach@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Verteilte Systeme},
abstract = {By 2020, the Internet of Things will consist of 26 Billion connected devices.
All these devices will be collecting an innumerable amount of raw observations,
for example, GPS positions or communication patterns. In order to benefit from
this enormous amount of information, machine learning algorithms are used to
derive knowledge from the gathered observations. This benefit can be increased
further, if the devices are enabled to collaborate by sharing gathered
knowledge. In a massively distributed environment, this is not an easy task, as
the knowledge on each device can be very heterogeneous and based on a different
amount of observations in diverse contexts. In this paper, we propose two
strategies to route a query for specific knowledge to a device that can answer
it with high confidence. To that end, we developed a confidence metric that
takes the number and variance of the observations of a device into account. Our
routing strategies are based on local routing tables that can either be learned
from previous queries over time or actively maintained by interchanging
knowledge models. We evaluated both routing strategies on real world and
synthetic data. Our evaluations show that the knowledge retrieved by the
presented approaches is up to 96.7 \% as accurate as the global optimum.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2015-42&engl=0}
}
@inproceedings {INPROC-2015-05,
author = {Thomas Bach and Muhammad Adnan Tariq and Boris Koldehofe and Kurt Rothermel},
title = {{A Cost Efficient Scheduling Strategy to Guarantee Probabilistic Workflow Deadlines}},
booktitle = {Proceedings of the International Conference on Networked Systems},
address = {Cottbus, Germany},
publisher = {IEEE Computer Society},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {1--8},
type = {Konferenz-Beitrag},
month = {M{\"a}rz},
year = {2015},
keywords = {robust workflow execution; parallel service execution; service execution},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2015-05/INPROC-2015-05.pdf},
contact = {thomas.bach@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Verteilte Systeme},
abstract = {Today, workflows are widely used to model business processes. A recent trend is
to use them to model applications in heterogeneous, large-scale distributed
systems. In such systems, many, possibly mobile, providers offer independent
and interchangeable services that can be used to satisfy the different
activities of a workflow. Due to varying server loads, failures, and changing
network characteristics, the response time of these services is highly
volatile. Thus, it is hard to ensure the timely and reliable execution of
workflows depending on such services. A common approach is to invoke several
services in parallel to increase the probability of success. This, however, can
easily lead to overprovisioning and high cost when needlessly invoked services
have to be compensated. In this paper, we investigate the search space between
parallel and sequential invocation of services. We propose to invoke
independent services staggered over time to ensure timely workflow execution at
minimal cost. Evaluations show that our approach reduces the execution cost by
up to 85 \% while it guarantees to fulfill activity deadlines with 99.9 \%
probability.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2015-05&engl=0}
}
@inproceedings {INPROC-2014-57,
author = {David Richard Sch{\"a}fer and Santiago G{\'o}mez S{\'a}ez and Thomas Bach and Vasilios Andrikopoulos and Muhammad Adnan Tariq},
title = {{Towards Ensuring High Availability in Collective Adaptive Systems}},
booktitle = {Proceedings of the First International Workshop of Business Processes in Collective Adaptive Systems: BPCAS'14; Eindhoven, Netherlands, September 8, 2014},
publisher = {Springer},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
type = {Workshop-Beitrag},
month = {September},
year = {2014},
keywords = {workflows; high availability; service discovery; process fragment injection},
language = {Englisch},
cr-category = {D.2.0 Software Engineering General,
D.2.11 Software Engineering Software Architectures,
D.2.12 Software Engineering Interoperability,
C.2.4 Distributed Systems,
C.4 Performance of Systems},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2014-57/INPROC-2014-57.pdf},
contact = {david.schaefer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen;
Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Verteilte Systeme},
abstract = {Collective Adaptive Systems support the interaction and adaptation of virtual
and physical entities towards achieving common objectives. For these systems,
several challenges at the modeling, provisioning, and execution phases arise.
In this position paper, we define the necessary underpinning concepts and
identify requirements towards ensuring high availability in such systems. More
specifically, based on a scenario from the EU Project ALLOW Ensembles, we
identify the necessary requirements and derive an architectural approach that
aims at ensuring high availability by combining active workflow replication,
service selection, and dynamic compensation techniques.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2014-57&engl=0}
}
@inproceedings {INPROC-2014-29,
author = {David Richard Sch{\"a}fer and Thomas Bach and Muhammad Adnan Tariq and Kurt Rothermel},
title = {{Increasing Availability of Workflows Executing in a Pervasive Environment}},
booktitle = {Proceedings of the 2014 IEEE International Conference on Services Computing},
address = {Anchorage, AK, USA},
publisher = {IEEE Computer Society},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {717--724},
type = {Konferenz-Beitrag},
month = {Juni},
year = {2014},
doi = {10.1109/SCC.2014.98},
isbn = {978-1-4799-5066-9/14},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems,
C.4 Performance of Systems},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2014-29/INPROC-2014-29.pdf,
http://dx.doi.org/10.1109/SCC.2014.98},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Verteilte Systeme},
abstract = {Workflows have gained enormous importance to organize and manage business
processes. With the recent advent of smartphones and mobile applications,
traditional business process management is shifting. Now, long-running business
processes (workflows) have to be executed in large-scale distributed and
pervasive environments. Due to the heterogeneity and high dynamicity of such
environments, they are vulnerable to frequent communication and device failures
and, thus, impose new requirements on the execution of workflows. To increase
the availability, we concurrently executed restructured replicas of workflows
on multiple nodes. We developed techniques to generate differently structured
replicas and propose a metric that identifies the set of replicas that ensures
the highest availability during execution. Finally, we presented a distributed
algorithm to coordinate and synchronize the concurrent execution of the
identified replicas while maintaining the original workflow semantics. Our
methods approximately double the availability during execution, while our
generation techniques produce almost optimal replicas over a hundred times
faster.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2014-29&engl=0}
}