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A noninvasive estimation of central blood-pressure is required by the researchers or the medical practitioners in the cardiovascular field. Up to now, a simulation based approach has been pursued by many researchers and the practical results are obtained. As the progresses in the electrical engineering, the possibility that a wearable central blood-pressure gauge can be realized is increased. This...
Today, X.509 certificates is largely adopted for the identity verification of an entity. Such organizations and people use it to confirm their identities in online transaction. Then, it is necessary to verify the certificate trustworthiness in order to accept or reject it for a particular transaction. Besides, certificates are issued by the certificate authority based on the procedures which are described...
In this paper, we investigate the problem of robust congestion control in infrastructure-based cognitive radio networks (CRN). We develop an active queue management (AQM) algorithm, termed MAQ, based on multiple model predictive control (MMPC). The goal is to stabilize the TCP queue at the base station (BS) under disturbances from the varying service capacity for secondary users (SU). The proposed...
Wireless content delivery networks (WCDNs) have received attention as a promising solution to reduce the network congestion caused by rapidly growing demands for mobile content. The amount of reduced congestion is intuitively proportional to the hit ratio in a WCDN. Cooperation among cache servers is strongly required to maximize the hit ratio in a WCDN where each cache server is equipped with a small-size...
Commercial large-scale VoD systems such as Netflix and Hulu rely on CDNs to deliver videos to users around the world. Various anomalies occur often and degrade users' Quality of Experience (QoE). Detecting and locating such anomalies are highly complex due to a large number of different entities involved in the end-to-end video delivery. These entities include VoD provider, CDN/Cloud providers, transit...
The modern semiconductor fabricator needs both accurate and fast cycle time (CT) forecasts. Due to complexity of development and computational intractability, simulation may be supplemented by queueing network methods. In this paper, we develop extensions to approximation methods for queueing networks that are suited for fab modeling using decomposition without aggregation. We conduct simulation experiments...
Deep learning with a large number of parametersrequires distributed training, where model accuracy and runtimeare two important factors to be considered. However, there hasbeen no systematic study of the tradeoff between these two factorsduring the model training process. This paper presents Rudra, aparameter server based distributed computing framework tunedfor training large-scale deep neural networks...
Resource and buffer allocation problems are well-known topics in manufacturing system research. A proper allocation of resource and space can significantly improve the system performance and reduce the investment cost. However, few works consider the joint problem because of its complexity. Recent research has shown that Discrete Event Optimization (DEO) framework, an integrated simulation-optimization...
One of the most critical and costly decisions made in emergency departments (EDs) is whether to admit a patient into the hospital. These decisions require investment in time for patient testing and treatment, delaying care to other patients. Short-stay units (SSUs) are an alternative to discharging or fully admitting ED patients, allowing extended patient observation. However, little is understood...
Transient queue-size distribution in a finite-buffer system with Poisson arrivals and generally distributed processing times is investigated. In the evolution of the system the server needs randomly distributed setup times preceding the service initialization in each new busy period. Applying the paradigm of embedded Markov chain and the formula of total probability, a Volterra-type system of integral...
This paper presents ESCAPE, an informed moving target defense mechanism for cloud containers. ESCAPE models the interaction between attackers and their target containers as a "predator searching for a prey" search game. Live migration of Linux-containers (prey) is used to avoid attacks (predator) and failures. The entire process is guided by a novel host-based behavior-monitoring system...
In data center, applications which are typically multi-server, high-parallel, long-running like web-related applications are really common. They always compute over large-scale dataset and consume plenty of energy. Up until now, most researches focuses on trading a loss of performance for energy saving. However, managing the power is more important compared with reducing it. In this paper, we add...
Big data is a main problem for data mining methods. Fortunately, the rapid advances in affordable high performance computing platforms such as the Graphics Processing Unit (GPU) have helped researchers in reducing the execution time of many algorithms including data mining algorithms. This paper discusses the utilization of the parallelism capabilities of the GPU to improve the the performance of...
A software for distributed neural network training is introduced here. The introduced software named NeuralGenesis implements a client — server model for parallel genetic algorithms with custom features such as: an enhanced stopping rule, an advanced mutation scheme and periodical application of a local search procedure. The software is coded in Qt5 for portability reasons and it is freely available...
We present a resilient task-based domain-decomposition preconditioner for partial differential equations (PDEs) built on top of User Level Fault Mitigation Message Passing Interface (ULFM-MPI). The algorithm reformulates the PDE as a sampling problem, followed by a robust regression-based solution update that is resilient to silent data corruptions (SDCs). We adopt a server-client model where all...
Virtual Content Delivery Network (vCDN) migration is necessary to optimize the use of resources and improve the performance of the overall SDN/NFV-based CDN function in terms of network operator cost reduction and high streaming quality. It requires intelligent and enticed joint SDN/NFV migration algorithms due to the evident huge amount of traffic to be delivered to end customers of the network....
An analysis of the familiarity between users in a group requires large amounts of information. We could determine the degree of familiarity by using personal information gleaned from a social networking service. For a realtime service, we usually use video data. Unfortunately, this data is closely related to a user's privacy, so the user may feel uncomfortable about its use. Therefore, in this study,...
This article describes experimental develop of control position without considerate trajectory that realize the quadricopter, realizing the essays in different highs about above sea level. Using parametric identification to obtain the model, it's designed a PID control with positions “x” and “y” by using Routh Hurwitz method to determinate the parameters. Finally it simulates the control in Matlab...
The significant continuous increase in the power consumption of data centers, brought about by the adoption of cloud computing, is a major social problem. Moreover, the demand for data centers is expected to grow owing to the increasing requirement for data processing related to Internet of Things (IoT) applications. Consequently, reducing the power consumption of data centers has become an urgent...
With the advent of network "softwarization", Network Functions Virtualization (NFV) is foreseen to provide flexibility and programmability levels that would essentially help in coping with tomorrow's demands. However, energy efficiency and the resulting complexity of network/service management pose serious sustainability and scalability issues that may hinder NFV's advantages. This paper...
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