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As system of systems (SoS) models become increasingly complex and interconnected a new approach is needed to capture the effects of humans within the SoS. Many real-life events have shown the detrimental outcomes of failing to account for humans in the loop. This research introduces a novel and cross-disciplinary methodology for modeling humans interacting with technologies to perform tasks within...
Because of the popularity of cloud computing, Cloud Service Providers (CSPs) can rent virtual machines (VMs) from Cloud Providers (CPs) conveniently. In our previous work, we proposed an autonomic and elastic resource scheduling framework, named AERS, which made full use of both proactive and reactive controllers in the field of dynamic resource provision and was integrated with an availability-aware...
Apache Spark provides numerous configuration settings that can be tuned to improve the performance of specific applications running on the platform. However, due to its multi-stage execution model and high interactive complexity across nodes, it is nontrivial to understand how/why a specific setting influences the execution flow and performance. To address this challenge, we develop an execution model-driven...
Today's advanced driver assistance systems (ADAS) are increasingly becoming more complex. The next step in this direction is the development of automated driving systems. However, along with the complexity, the effort required for development and validation of these systems is increasing as well. In order to be able to master this complexity in terms of cost and time, simulations are being used more...
Detecting anomalous behaviors of cloud platforms is one of critical tasks for cloud providers. Every anomalous behavior potentially causes incidents, especially some unaware and/or unknown issues, which severely harm their SLA (Service Level Agreement). Existing solutions generally monitor cloud platform at different layers and then detect anomalies based on rules or learning algorithms on monitoring...
Providers of computing services such as data science clouds need to maintain large hardware infrastructures often with thousands of nodes. Using commodity hardware leads to heter-ogeneous setups that differ significantly in individual nodes' performance, which must be understood to allow for account-ing, strategic planning, and to identify problems and bottle-necks. Today's method of choice are active...
In current applications Analog/Mixed-Signal (AMS) circuits gets increasingly demanding. To speed up the design process parts of the design were implemented in hardware description languages. Besides positive aspects like simulation processing times these models need to be checked in terms of verification run set completeness, i.e. input stimuli, parameter setting, and test bench circuitry. For this...
Small-scale clouds (SCs) often suffer from resource under-provisioning during peak demand, leading to inability to satisfy service level agreements (SLAs) and consequent loss of customers. One approach to address this problem is for a set of autonomous SCs to share resources among themselves in a cost-induced cooperative fashion, thereby increasing their individual capacities (when needed) without...
In this paper we examine the use of trust metrics for punishing dishonest (cheating) and malicious (griefing) behavior in peer-to-peer massively multiplayer online games (MMOG’s). In particular, we first replicate the work of Goodman and Verbrugge and then propose a metric of our own. Our approach uses a reinforcement learning trust metric that can more rapidly and accurately detect dishonest and...
Computer simulation model is designed to conduct virtual testing of electro-optical systems for angles measuring, which incorporates multi-element photo-detectors arrays. The model allows to determine the measurement error. The main method of research is the method of multiple statistical tests. The conditions of the models formalization are considered. The model provides calculation of the dependence...
Saliency detection is an important problem in many computer vision applications. As a kind of popular method, graph based manifold ranking (GMR) has been successfully used in saliency detection problem. In traditional GMR saliency detection, it involves two main stages, i.e., ranking with background queries and ranking with foreground queries. However, in GMR method, these two stages are conducted...
Anomaly detection involves way towards finding the example in the information that violates ordinary conduct. The choice of anomaly detection algorithm can to a great extent affect the undertaking of anomaly identification. The decision of abnormality revelation calculation can influence complexity and correctness of the process. The choice of anomaly recognition calculations may increase the occurrence...
The robustness is one of the primary characteristics of a real system, which impacts the function and performance of the system. Many real systems in our real world can be formulated as complex networks. It is a feasible method to estimate the robustness of real systems from the perspective of complex networks. The robustness evaluation is one of the basic and hot research topics in the field of complex...
To ensure the scalability of big data analytics, approximate MapReduce platforms emerge to explicitly trade off accuracy for latency. A key step to determine optimal approximation levels is to capture the latency of big data jobs, which is long deemed challenging due to the complex dependency among data inputs and map/reduce tasks. In this paper, we use matrix analytic methods to derive stochastic...
Understanding the mobile user flow flux patterns is important for numerous applications. Much of the mobility modeling studies have focused on a user-centric approach for outdoors movement. In this study, we take a location-centric approach for indoor mobility to analyze and characterize region relationships as pertains to user flow. Our study is trace-driven, as we use extensive measurements from...
The problem of estimating the accuracy of signal reconstruction from threshold-based sampling, by only taking the sampling output into account, is addressed. The approach is based on re-sampling the reconstructed signal and the application of a distance measure in the output space which satisfies the condition of quasi-isometry. The quasi-isometry property allows to estimate the reconstruction accuracy...
The paper presents a design of SRAM circuit using CNTFET transistors. The complete model describing CNTFET, developed in Stanford University is modified for the purpose of designing a 6T (2×2) SRAM memory cell. The simulation results of the CNTFET SRAM memory cell manifest usability and applicability of the modified CNTFET model in designing digital circuits. The simplified CNTFET model is coded in...
Auto-scaling, a key property of cloud computing, allows application owners to acquire and release resourceson demand. However, the shared environment, along with theexponentially large configuration space of available parameters, makes configuration of auto-scaling policies a challenging task. Inparticular, it is difficult to quantify, a priori, the impact of a policyon Quality of Service (QoS) provision...
Chapel is an emerging PGAS (Partitioned Global Address Space) language whose design goal is to make parallel programming more productive and generally accessible. To date, the implementation effort has focused primarily on correctness over performance. We present a performance measurement technique for Chapel and the idea is also applicable to other PGAS models. The unique feature of our tool is that...
In active learning for Automatic Speech Recognition (ASR), a portion of data is automatically selected for manual transcription. The objective is to improve ASR performance with retrained acoustic models. The standard approaches are based on confidence of individual sentences. In this study, we look into an alternative view on transcript label quality, in which Gaussian Supervector Distance (GSD)...
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