199,734 research outputs found
Impaired awareness of hypoglycemia in type 1 diabetes. The role of lactate
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196836.pdf (Publisher’s version ) (Open Access)Radboud University, 22 november 2018Promotores : Tack, C.J.J., Heerschap, A. Co-promotores : Galan, B.E. de, Graaf, M. van de
Cerebral adaptations in type 1 diabetes and impaired awareness of hypoglycemia. A magnetic resonance study
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191599.pdf (Publisher’s version ) (Open Access)Radboud University, 28 juni 2018Promotores : Heerschap, A., Tack, C.J.J. Co-promotores : Graaf, M. van der, Galan, B.E. d
A scalable and error-tolerant solution for traffic matrix assessment in hybrid IP/SDN networks
No full textThe advent of the Software Defined Networking (SDN) paradigm represents a great opportunity for the definition of new network management solutions. In this work, we focus on the definition and implementation of a novel technique to solve the Traffic Matrix Assessment (TMA) problem from the perspective of an Internet Service Provider. Since the migration from legacy IP networks to fully-deployed SDN ones needs to be incremental due to budget and technical constraints, this paper proposes a mixed measurement and estimation scalable solution for hybrid IP/SDN networks to accurately solve the TMA problem by exploiting the availability of flow rule counters in SDN switches. The performance evaluation shows that our error-Tolerant solution is able to assess the TM with a negligible estimation error by only measuring a small percentage of traffic flows, overcoming other state-of-The-Art algorithms proposed in the literature. Moreover, the performance analysis of the proposed implementation using the OpenDaylight controller over an emulated network environment, shows that a trade-off between the quality of the assessed TM and its impact on the network in terms of control messages can be found by properly tuning the number of measured flows
Reducing the reconfiguration cost of flow tables in energy-efficient Software-Defined Networks
No full textSoftware-Defined Networking (SDN) is a new networking paradigm that is attracting the attention of the research community due to the flexibility provided by the separation between data and control planes. In particular, the SDN scenario introduces new aspects to be considered when formulating the energy-aware routing problem, such as the reconfiguration cost of flow tables. In this paper we introduce and investigate the problem of minimizing the power consumption of an SDN network while also reducing the number of rules that have to be modified in the flow tables of SDN nodes. An optimization problem formulation and a GA (Genetic Algorithm) based heuristic are presented to tackle this two-fold problem. The performance analysis, carried out over different realistic network topologies, highlights that GA is able to increase the power saving opportunities up to the 20% more than other energy-aware routing solutions proposed in the literature, while reducing the number of rules that have to be modified up to 100 times
A Machine Learning-Based Framework to Estimate the Lifetime of Network Line Cards
No full textWith the increasing tendency on data rates in forthcoming communication networks, availability is a crucial aspect to guarantee Quality of Service (QoS) requirements. The possibility of predicting the lifetime of networking hardware can be a key to improve the overall network QoS. This paper proposes a generic Machine Learning (ML) based framework that learns how to mimic the mathematical model behind the lifetime of network line cards. Results show that a good precision (85%) and recall (close to 100%) on the estimation can be achieved regardless the type of line cards the network is composed of
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
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