Finding event correlations in federated wireless sensor networks

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Event correlation engines help us find events of interest inside raw sensor data streams and help reduce the data volume, simultaneously. This paper discusses some of the challenges faced in finding event correlations over federated wireless sensor networks (WSNs) including high data volumes, uncertain or missing data, application-specific dependencies and widely varying data ranges and sampling frequencies. Analysisover real geo-tracking data of moving objects confirms some of these challenges. Federation at the data layer above the WSNs is presented as a feasible alternative.TÜBİTAK ; IBM Shared University Research program ; European Commissio

Mining typical load profiles in buildings to support energy management in the smart city context

Mining typical load profiles in buildings to drive energy management strategies is a fundamental task to be addressed in a smart city environment. In this work, a general framework on load profiles characterisation in buildings based on the recent scientific literature is proposed . The process relies on the combination of different pattern recognition and classification algorithms in order to provide a robust insight of the energy usage patterns at different level s and at different scales (from single building to stock of buildings). Several im plications related to energy profiling in buildings, including tariff design, demand side management and advanced energy diagnos is are discussed. Moreover, a robust methodology to mine typical energy patterns to support advanced energy diagnosis in buildin gs is introduced by analysing the monitored energy consumption of a cooling/heating mechanical room

MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted

Experimental and Analytical Investigation of the Transient Thermal Response of Air Cooled Data Centers

This work investigates the transient response of the thermal environment in air cooled data centers through experiments, analytical and computational tools. The key thermal characteristics of the various data center components were extracted from a set of experiments. This includes the development of practical experimental procedures for the thermal characterization of servers solely based on air temperature measurements and the transient response of the computer room air handlers. The knowledge of thermal characteristics paves the way for the physics-based lumped-capacitance models. A CFD-based transient simulation of the air temperature field, in which the transient thermal response of the servers was included via user-defined functions failed to predict the time-dependent server inlet temperature with acceptable accuracy and highlighted the need for including the thermal capacitance and heat transfer characteristics of the entire room, not just the servers. Hence, a practical faster-executing hybrid lumped capacitance-CFD/Experimental model was developed to investigate the thermal response of data centers under certain scenarios of cooling interruption, server shutdown and cooling air flow changes. Beyond the servers, the model takes into account the effect of the air volume, the building materials of the room and plenum and the CRAH units. The model is capable of predicting server inlet temperatures to within the experimental uncertainty (±1°C) with inputs that are relatively easy to obtain in a production data center

Modelling the assimilation and value of sensor information systems in data centres

Sensor Information Systems (SIS) refer to any IS that utilises sensor(s) that are directly or indirectly connected to other sensors or sensor networks in order to automate, inform and/or transform a given task or process or appliance. SIS are promoted as one of the best practices to overcome critical data centres issues such as inefficiency of Information Technology (IT) infrastructure usage, rising cost of operations, and the consumption and efficiency of energy. A review of the sensor, IS, and data centre literature shows that there is a dearth of theory driven empirical research on the utilisation of SIS in data centres, the factors that explain variations in applying SIS in data centres and the value of SIS use to data centres. The aim of this study is therefore to address the gap in the current literature and answer research questions. The research was conducted through a mixed method approach consisting of a literature review, exploratory case studies (pilot study) and large scale survey. Drawing from several theories of innovation adoption and value, and the five exploratory case studies, an integrative theoretical framework, which we call as TOIN (Technology, Organisation, Institutional and Natural Environment), was proposed to investigate the factors that explain the variation in the assimilation of SIS and the impact of SIS use on data centre’s operational and environmental performance. A series of hypotheses are developed by linking the TOIN factors to SIS assimilation and value in a two order-based model. The TOIN framework is tested using Partial Least Squares (PLS) path modelling and data collected from a global survey of 205 data centres. The findings indicate that SIS compatibility, perceived SIS risk, green IT orientation, and normative pressure directly influence the level of SIS usage among data centres. In addition, normative pressure, energy pressure, and natural environmental pressure indirectly affect the assimilation of SIS through influencing the organizational conditions for SIS use. These results are mostly sensitive to differences in data centre characteristics including age and type of data centre. Further, the test of the second order model show that the level of actual usage as well as the level of SIS mangers’ knowledge affect the operational and environmental performance of data centre operations including the facility, cooling and power, and computing platforms. The research represents one of the first studies on the use and value of SIS in general and in the context of data centre environment in particular. It makes an original contribution by proposing and validating the TOIN framework which can be used as a theoretical foundation for future and related studies. It also contributes original knowledge regarding how data centres are using SIS to tackle some of the operational, economic and environmental challenges. Thus, the research adds to the body of knowledge on intelligent systems, infrastructure management, green IS and energy informatics. Furthermore, the research extends the current innovation theories by incorporating the natural environment to study the technology use and value and shows the significance of natural environment considerations on organizations’ activities