Evaluating load balancing policies for performance and energy-efficiency

Nowadays, more and more increasingly hard computations are performed in challenging fields like weather forecasting, oil and gas exploration, and cryptanalysis. Many of such computations can be implemented using a computer cluster with a large number of servers. Incoming computation requests are then, via a so-called load balancing policy, distributed over the servers to ensure optimal performance. Additionally, being able to switch-off some servers during low period of workload, gives potential to reduced energy consumption. Therefore, load balancing forms, albeit indirectly, a trade-off between performance and energy consumption. In this paper, we introduce a syntax for load-balancing policies to dynamically select a server for each request based on relevant criteria, including the number of jobs queued in servers, power states of servers, and transition delays between power states of servers. To evaluate many policies, we implement two load balancers in: (i) iDSL, a language and tool-chain for evaluating service-oriented systems, and (ii) a simulation framework in AnyLogic. Both implementations are successfully validated by comparison of the results.Comment: In Proceedings QAPL'16, arXiv:1610.0769

Windowed Factorization and Merging

In this work, an online 3D reconstruction algorithm is proposed which attempts to solve the structure from motion problem for occluded and degenerate data. To deal with occlusion the temporal consistency of data within a limited window is used to compute local reconstructions. These local reconstructions are transformed and merged to obtain an estimation of the 3D object shape. The algorithm is shown to accurately reconstruct a rotating and translating artificial sphere and a rotating toy dinosaur from a video. The proposed algorithm (WIFAME) provides a versatile framework to deal with missing data in the structure from motion problem

A domain specific language for performance evaluation of medical imaging systems

We propose iDSL, a domain specific language and toolbox for performance evaluation of Medical Imaging Systems. iDSL provides transformations to MoDeST models, which are in turn converted into UPPAAL and discrete-event MODES models. This enables automated performance evaluation by means of model checking and simulations. iDSL presents its results visually. We have tested iDSL on two example image processing systems. iDSL has successfully returned differentiated delays, resource utilizations and delay bounds. Hence, iDSL helps in evaluating and choosing between design alternatives, such as the effects of merging subsystems onto one platform or moving functionality from one platform to another

Identification of Diabetic Small-Fiber Neuropathy Based on Electrophysiological and Psychophysical Responses to Intra-Epidermal Electric Stimulation using a Naïve Bayes Classifier

Diagnosis and stratification of small-fiber neuropathy patients is difficult due to a lack of methods that are both sensitive and specific. Our lab recently developed a method to accurately measure psychophysical and electrophysiological responses to intra-epidermal electric stimulation, specifically targeting small nerve fibers in the skin. In this work, we study whether using one or a combination of psychophysical and electrophysiological outcome measures can be used to identify diabetic small-fiber neuropathy. It was found that classification of small-fiber neuropathy based on psychophysical and electrophysiological responses to intra-epidermal electric stimulation could match or even outperform current state-of-the-art methods for the diagnosis of small-fiber neuropathy.Clinical Relevance - Neuropathy is damage or dysfunction of nerves in the skin, often leading to the development of chronic pain. Small-fiber neuropathy is the most prevalent type of neuropathy and occurs frequently in patients with diabetes mellitus, but can also occur in other diseases or in response to chemotherapy. Early detection of neuropathy could help diabetic patients to adapt glucose management, and doctors to adjust treatment strategies to prevent nerve loss and chronic pain, but is impeded by a lack of clinical tools to monitor small nerve fiber function.</p