10 research outputs found

    Comparison of Similarity Measures for Trajectory Clustering - Aviation Use Case

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    Various distance-based clustering algorithms have been reported, but the core component of all of them is a similarity or distance measure for classification of data. Rather than setting the priority to comparison of the performance of different clustering algorithms, it may be worthy to analyze the influence of different similarity measures on the results of clustering algorithms. The main contribution of this work is a comparative study of the impact of 9 similarity measures on similarity-based trajectory clustering using DBSCAN algorithm for commercial flight dataset. The novelty in this comparison is exploring the robustness of the clustering algorithm with respect to algorithm parameter. We evaluate the accuracy of clustering, accuracy of anomaly detection, algorithmic efficiency, and we determine the behavior profile for each measure. We show that DTW and Frechet distance lead to the best clustering results, while LCSS and Hausdorff Cosine should be avoided for this task

    Cloud-inclusive Aerial Imagery based on Commercial Flights as Remote Sensing Platform

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    Earth observation (EO) significantly increased in the second half of the 20th century and continues to advance rapidly, with remote sensing being a key component for gathering Earth-related information. Nowadays, satellites, manned aircraft, helicopters, UAVs and drones are used to capture aerial imagery in a periodic or schedule-based manner. This paper examine the feasibility of creating a novel remote sensing system by mounting cameras on commercial flights. The study evaluates flight coverage, including spatial and temporal resolutions, and considers the impact of clouds on image usability. We have compared flight coverage with cloud-inclusive flight coverage, which represents reduced flight coverage based on cloud quantity. Results show that entire country of Croatia is covered between 95% and 100% during the day and night. However, when clouds are included in the calculation, it is important to consider different altitudes and periods of the year because their distribution is not the same. In a less cloudy month (August), the highest differences between flight coverage and cloud-inclusive flight coverage for high-altitude flights are 70% for the worst-case scenario and 25% for the best-case scenario. Results show it is feasible to use commercial flights as a new remote sensing system

    Cloud computing: survey on energy efficiency

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    International audienceCloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions

    TimeCap: Methodology for comparing IT infrastructures based on time and capacity metrics

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    Abstract—Scientific community is one of the major driving forces for developing and utilizing IT technologies such as Supercomputers and Grid. Although, the main race has always been for bigger and faster infrastructures, an easier access to such infrastructures in recent years created a demand for more customizable and scalable environments. However, introducing new technologies and paradigms such as Cloud computing requires a comprehensive analysis of its benefits before the actual implementation. In this paper we introduce the TimeCap, a methodology for comparing IT infrastructures based on time requirements and resource capacity wastage. We go beyond comparing just the execution time by introducing the Time Complexity as part of TimeCap, a methodology used for comparing arbitrary time related tasks required for completing a procedure, i.e., obtaining the scientific results. Moreover, a resource capacity wastage is compared using the Discrete Capacity, a second methodology as part of TimeCap used for analyzing resource assignment and utilization. We evaluate our methodology by comparing a traditional physical infrastructure and a Cloud infrastructure using our local IT resources. We use a real world scientific application for calculating plasma instabilities for analyzing time and capacity required for computation. I

    Aerial Imagery Based on Commercial Flights as Remote Sensing Platform

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    Remote sensing is commonly performed via airborne platforms such as satellites, specialized aircraft, and unmanned aerial systems (UASs), which perform airborne photography using mounted cameras. However, they are limited by their coverage (UASs), irregular flyover frequency (aircraft), and/or low spatial resolution (satellites) due to their high altitude. In this paper, we examine the utilization of commercial flights as an airborne platform for remote sensing. Namely, we simulate a situation where all aircraft on commercial flights are equipped with a mounted camera used for airborne photography. The simulation is used to estimate coverage, the temporal and spatial resolution of aerial imagery acquired this way, as well as the storage capacity required for storing all imagery data. The results show that Europe is 83.28 percent covered with an average of one aerial photography every half an hour and a ground sampling distance of 0.96 meters per pixel. Capturing such imagery results in 20 million images or four petabytes of image data per day. More detailed results are given in the paper for separate countries/territories in Europe, individual commercial airlines and alliances, as well as three different cameras

    Defining the cloud battlefield - supporting security assessments by cloud customers

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    Cloud computing is becoming more and more popular, but security concerns overshadow its technical and economic benefits. In particular, insider attacks and malicious insiders are considered as one of the major threats and risks in cloud computing. As physical boundaries disappear and a variety of parties are involved in cloud services, it is becoming harder to define a security perimeter that divides insiders from outsiders, therefore making security assessments by cloud customers more difficult. In this paper, we propose a model that combines a comprehensive system model of infrastructure clouds with a security model that captures security requirements of cloud customers as well as characteristics of attackers. This combination provides a powerful tool for systematically analyzing attacks in cloud environments, supporting cloud customers in their security assessment by providing a better understanding of existing attacks and threats. Furthermore, we use the model to construct "what-if" scenarios that could possible lead to new attacks and to raise concerns about unknown threats among cloud customers

    Energy Efficiency for Ultrascale Systems: Challenges and Trends from Nesus Project

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    International audienceEnergy consumption is one of the main limiting factors for designing and deploying ultrascale systems. Therefore, this paper presents challenges and trends associated with energy efficiency for ultrascale systems based on current activities of the working group on "Energy Efficiency" in the European COST Action Nesus IC1305. The analysis contains major areas that are related to studies of energy efficiency in ultrascale systems: heterogeneous and low power hardware architectures, power monitoring at large scale, modeling and simulation of ultrascale systems, energy-aware scheduling and resource management, and energy-efficient application design
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