TY - GEN A1 - Sahlmann, Kristina A1 - Scheffler, Thomas A1 - Schnor, Bettina T1 - Ontology-driven Device Descriptions for IoT Network Management T2 - 2018 Global Internet of Things Summit (GIoTS) N2 - One particular challenge in the Internet of Things is the management of many heterogeneous things. The things are typically constrained devices with limited memory, power, network and processing capacity. Configuring every device manually is a tedious task. We propose an interoperable way to configure an IoT network automatically using existing standards. The proposed NETCONF-MQTT bridge intermediates between the constrained devices (speaking MQTT) and the network management standard NETCONF. The NETCONF-MQTT bridge generates dynamically YANG data models from the semantic description of the device capabilities based on the oneM2M ontology. We evaluate the approach for two use cases, i.e. describing an actuator and a sensor scenario. KW - Internet of Things KW - Interoperability KW - oneM2M KW - Ontology KW - Semantic Web KW - NETCONF KW - YANG KW - MQTT Y1 - 2018 SN - 978-1-5386-6451-3 U6 - https://doi.org/10.1109/GIOTS.2018.8534569 SP - 295 EP - 300 PB - IEEE CY - New York ER - TY - GEN A1 - Elsaid, Mohamed Esam A1 - Shawish, Ahmed A1 - Meinel, Christoph T1 - Enhanced cost analysis of multiple virtual machines live migration in VMware environments T2 - 2018 IEEE 8th International Symposium on Cloud and Service Computing (SC2) N2 - Live migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the live migration feature. Despite the importance of live migration, the cost of live migration cannot be ignored and may result in service availability degradation. Live migration cost includes the migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of live migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new migration algorithms that minimize the cost and also predicting the migration cost. For the best of our knowledge, most of the papers that discuss the migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed migration time, network overhead and power consumption modeling for single and multiple VMs live migration. In this paper, we propose empirical models for the live migration time, network overhead and power consumption for single and multiple VMs migration. The proposed models are obtained using a VMware based testbed. Y1 - 2018 SN - 978-1-7281-0236-8 U6 - https://doi.org/10.1109/SC2.2018.00010 SP - 16 EP - 23 PB - IEEE CY - New York ER - TY - GEN A1 - Kötzing, Timo A1 - Krejca, Martin Stefan T1 - First-Hitting times under additive drift T2 - Parallel Problem Solving from Nature – PPSN XV, PT II N2 - For the last ten years, almost every theoretical result concerning the expected run time of a randomized search heuristic used drift theory, making it the arguably most important tool in this domain. Its success is due to its ease of use and its powerful result: drift theory allows the user to derive bounds on the expected first-hitting time of a random process by bounding expected local changes of the process - the drift. This is usually far easier than bounding the expected first-hitting time directly. Due to the widespread use of drift theory, it is of utmost importance to have the best drift theorems possible. We improve the fundamental additive, multiplicative, and variable drift theorems by stating them in a form as general as possible and providing examples of why the restrictions we keep are still necessary. Our additive drift theorem for upper bounds only requires the process to be nonnegative, that is, we remove unnecessary restrictions like a finite, discrete, or bounded search space. As corollaries, the same is true for our upper bounds in the case of variable and multiplicative drift. Y1 - 2018 SN - 978-3-319-99259-4 SN - 978-3-319-99258-7 U6 - https://doi.org/10.1007/978-3-319-99259-4_8 SN - 0302-9743 SN - 1611-3349 VL - 11102 SP - 92 EP - 104 PB - Springer CY - Cham ER - TY - GEN A1 - Kötzing, Timo A1 - Krejca, Martin Stefan T1 - First-Hitting times for finite state spaces T2 - Parallel Problem Solving from Nature – PPSN XV, PT II N2 - One of the most important aspects of a randomized algorithm is bounding its expected run time on various problems. Formally speaking, this means bounding the expected first-hitting time of a random process. The two arguably most popular tools to do so are the fitness level method and drift theory. The fitness level method considers arbitrary transition probabilities but only allows the process to move toward the goal. On the other hand, drift theory allows the process to move into any direction as long as it move closer to the goal in expectation; however, this tendency has to be monotone and, thus, the transition probabilities cannot be arbitrary. We provide a result that combines the benefit of these two approaches: our result gives a lower and an upper bound for the expected first-hitting time of a random process over {0,..., n} that is allowed to move forward and backward by 1 and can use arbitrary transition probabilities. In case that the transition probabilities are known, our bounds coincide and yield the exact value of the expected first-hitting time. Further, we also state the stationary distribution as well as the mixing time of a special case of our scenario. Y1 - 2018 SN - 978-3-319-99259-4 SN - 978-3-319-99258-7 U6 - https://doi.org/10.1007/978-3-319-99259-4_7 SN - 0302-9743 SN - 1611-3349 VL - 11102 SP - 79 EP - 91 PB - Springer CY - Cham ER - TY - GEN A1 - Kötzing, Timo A1 - Lagodzinski, Gregor J. A. A1 - Lengler, Johannes A1 - Melnichenko, Anna T1 - Destructiveness of Lexicographic Parsimony Pressure and Alleviation by a Concatenation Crossover in Genetic Programming T2 - Parallel Problem Solving from Nature – PPSN XV N2 - For theoretical analyses there are two specifics distinguishing GP from many other areas of evolutionary computation. First, the variable size representations, in particular yielding a possible bloat (i.e. the growth of individuals with redundant parts). Second, the role and realization of crossover, which is particularly central in GP due to the tree-based representation. Whereas some theoretical work on GP has studied the effects of bloat, crossover had a surprisingly little share in this work. We analyze a simple crossover operator in combination with local search, where a preference for small solutions minimizes bloat (lexicographic parsimony pressure); the resulting algorithm is denoted Concatenation Crossover GP. For this purpose three variants of the wellstudied Majority test function with large plateaus are considered. We show that the Concatenation Crossover GP can efficiently optimize these test functions, while local search cannot be efficient for all three variants independent of employing bloat control. Y1 - 2018 SN - 978-3-319-99259-4 SN - 978-3-319-99258-7 U6 - https://doi.org/10.1007/978-3-319-99259-4_4 SN - 0302-9743 SN - 1611-3349 VL - 11102 SP - 42 EP - 54 PB - Springer CY - Cham ER - TY - GEN A1 - Perscheid, Cindy A1 - Faber, Lukas A1 - Kraus, Milena A1 - Arndt, Paul A1 - Janke, Michael A1 - Rehfeldt, Sebastian A1 - Schubotz, Antje A1 - Slosarek, Tamara A1 - Uflacker, Matthias T1 - A tissue-aware gene selection approach for analyzing multi-tissue gene expression data T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) N2 - High-throughput RNA sequencing (RNAseq) produces large data sets containing expression levels of thousands of genes. The analysis of RNAseq data leads to a better understanding of gene functions and interactions, which eventually helps to study diseases like cancer and develop effective treatments. Large-scale RNAseq expression studies on cancer comprise samples from multiple cancer types and aim to identify their distinct molecular characteristics. Analyzing samples from different cancer types implies analyzing samples from different tissue origin. Such multi-tissue RNAseq data sets require a meaningful analysis that accounts for the inherent tissue-related bias: The identified characteristics must not originate from the differences in tissue types, but from the actual differences in cancer types. However, current analysis procedures do not incorporate that aspect. As a result, we propose to integrate a tissue-awareness into the analysis of multi-tissue RNAseq data. We introduce an extension for gene selection that provides a tissue-wise context for every gene and can be flexibly combined with any existing gene selection approach. We suggest to expand conventional evaluation by additional metrics that are sensitive to the tissue-related bias. Evaluations show that especially low complexity gene selection approaches profit from introducing tissue-awareness. KW - RNAseq KW - gene selection KW - tissue-awareness KW - TCGA KW - GTEx Y1 - 2018 SN - 978-1-5386-5488-0 U6 - https://doi.org/10.1109/BIBM.2018.8621189 SN - 2156-1125 SN - 2156-1133 SP - 2159 EP - 2166 PB - IEEE CY - New York ER - TY - GEN A1 - Bin Tareaf, Raad A1 - Berger, Philipp A1 - Hennig, Patrick A1 - Meinel, Christoph T1 - Personality exploration system for online social networks BT - Facebook brands as a use case T2 - 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI) N2 - User-generated content on social media platforms is a rich source of latent information about individual variables. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. The proposed model reported significant accuracy in predicting specific personality traits form brands. For evaluating our prediction results on actual brands, we crawled the Facebook API for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions. KW - Big Five Model KW - Brand Personality KW - Personality Prediction KW - Machine Learning KW - Social Media Analysis Y1 - 2019 SN - 978-1-5386-7325-6 U6 - https://doi.org/10.1109/WI.2018.00-76 SP - 301 EP - 309 PB - IEEE CY - New York ER - TY - GEN A1 - Andjelkovic, Marko A1 - Babic, Milan A1 - Li, Yuanqing A1 - Schrape, Oliver A1 - Krstić, Miloš A1 - Kraemer, Rolf T1 - Use of decoupling cells for mitigation of SET effects in CMOS combinational gates T2 - 2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS) N2 - This paper investigates the applicability of CMOS decoupling cells for mitigating the Single Event Transient (SET) effects in standard combinational gates. The concept is based on the insertion of two decoupling cells between the gate's output and the power/ground terminals. To verify the proposed hardening approach, extensive SPICE simulations have been performed with standard combinational cells designed in IHP's 130 nm bulk CMOS technology. Obtained simulation results have shown that the insertion of decoupling cells results in the increase of the gate's critical charge, thus reducing the gate's soft error rate (SER). Moreover, the decoupling cells facilitate the suppression of SET pulses propagating through the gate. It has been shown that the decoupling cells may be a competitive alternative to gate upsizing and gate duplication for hardening the gates with lower critical charge and multiple (3 or 4) inputs, as well as for filtering the short SET pulses induced by low-LET particles. KW - decoupling cells KW - radiation hardening KW - SET effects KW - CMOS technology KW - combinational logic Y1 - 2019 SN - 978-1-5386-9562-3 U6 - https://doi.org/10.1109/ICECS.2018.8617996 SP - 361 EP - 364 PB - IEEE CY - New York ER - TY - GEN A1 - Kayem, Anne Voluntas dei Massah A1 - Meinel, Christoph A1 - Wolthusen, Stephen D. T1 - Smart micro-grid systems security and privacy preface T2 - Smart micro-grid systems security and privacy N2 - Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures , to highly automated management , with current energy provisioning systems being run as cyber-physical systems . Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability , but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour . Y1 - 2018 SN - 978-3-319-91427-5 SN - 978-3-319-91426-8 U6 - https://doi.org/10.1007/978-3-319-91427-5_1 VL - 71 SP - VII EP - VIII PB - Springer CY - Dordrecht ER - TY - GEN A1 - Brand, Thomas A1 - Giese, Holger Burkhard T1 - Towards Generic Adaptive Monitoring T2 - 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) N2 - Monitoring is a key prerequisite for self-adaptive software and many other forms of operating software. Monitoring relevant lower level phenomena like the occurrences of exceptions and diagnosis data requires to carefully examine which detailed information is really necessary and feasible to monitor. Adaptive monitoring permits observing a greater variety of details with less overhead, if most of the time the MAPE-K loop can operate using only a small subset of all those details. However, engineering such an adaptive monitoring is a major engineering effort on its own that further complicates the development of self-adaptive software. The proposed approach overcomes the outlined problems by providing generic adaptive monitoring via runtime models. It reduces the effort to introduce and apply adaptive monitoring by avoiding additional development effort for controlling the monitoring adaptation. Although the generic approach is independent from the monitoring purpose, it still allows for substantial savings regarding the monitoring resource consumption as demonstrated by an example. Y1 - 2019 SN - 978-1-5386-5172-8 U6 - https://doi.org/10.1109/SASO.2018.00027 SN - 1949-3673 SP - 156 EP - 161 PB - IEEE CY - New York ER -