We describe a peer-to-peer self-organizing overlay network for our global computing system. The preliminary simulation results show that the network has some small-world characteristics such as higher clustering coeff...
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ISBN:
(纸本)9780769533285
We describe a peer-to-peer self-organizing overlay network for our global computing system. The preliminary simulation results show that the network has some small-world characteristics such as higher clustering coefficient and short path length, which leads to an efficient heuristic task scheduling algorithm on which any volunteer peer with limited knowledge about its neighbors can dispatch its excrescent computation tasks to the more powerful nodes globally, in a way contrary to the current global computing system in which a global broker is responsible for the task scheduling. We argue that our approach is a start point to eliminate the broker component which makes these systems unscalable.
Regrouping of China operators gives the light of FMC services. Owing to the technology advantages and competition compelling, all services from mobile and fixed networks together will give new operator competition pow...
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ISBN:
(纸本)9780769535012
Regrouping of China operators gives the light of FMC services. Owing to the technology advantages and competition compelling, all services from mobile and fixed networks together will give new operator competition power growing chance. In this paper, we will give some reasons and analyses.
Unplugged activity becomes popular in ICT (Information and Communication technology) education and other information-related courses as an alternative for computer science theory education. However, there is no evalua...
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ISBN:
(纸本)9781538650417
Unplugged activity becomes popular in ICT (Information and Communication technology) education and other information-related courses as an alternative for computer science theory education. However, there is no evaluation standards for unplugged activity in the literature. In this work, an evaluation standard for unplugged activity is developed and proposed.
Blind quantum computation provides protocols which enable users to get access to quantum computing resources without leaking information about the algorithms to be performed. This paper suggests a possible attack on b...
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ISBN:
(纸本)9781665423830
Blind quantum computation provides protocols which enable users to get access to quantum computing resources without leaking information about the algorithms to be performed. This paper suggests a possible attack on blind quantum computation, which can corrupt the quantum operations and their expected outputs.
Cloud computing (CC) have been widely adopted in the educational institutions during the past decade, as the virtual infrastructures and shared architectures offer various work groups and parties to benefit from the s...
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ISBN:
(纸本)9781728108933
Cloud computing (CC) have been widely adopted in the educational institutions during the past decade, as the virtual infrastructures and shared architectures offer various work groups and parties to benefit from the solutions. With the emergence of cloud centric applications, various technologies have allowed institutions to gain a wide range of applications and services that are beneficial for both the educators and students. Furthermore, CC have allowed institutions to reduce storage costs and up-front commitment for computing infrastructure implementations. This study quantifies the components and parameters when deploying a HPC center and adopting a CC based facility. We investigate and identify the CAPital Expenses (CAPEX) and OPerating Expenses (OPEX) for the Total Cost of Ownership (TCO) of a HPC center within a higher educational environment. Furthermore, we discuss the software licensing models for CC which can be classified into the perpetual and subscription-based licensing model. In this study, we discuss the financial benefits and opportunities for utilizing a CC based computing infrastructure and HPC center. We propose a cost benefit framework for the in-house compute facility and CC that can help institutions and educational stakeholders when deploying a HPC facility or CC model.
This paper investigates a requirement and an performance of virtualization solutions for a naval combat systems. A Total ship computing environment (TSCE) for distributed naval combat systems needs a seamless operatio...
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ISBN:
(纸本)9781728108933
This paper investigates a requirement and an performance of virtualization solutions for a naval combat systems. A Total ship computing environment (TSCE) for distributed naval combat systems needs a seamless operation environments. In such a case, hardware resource is constructed considering overload when naval combat systems is constituted. Virtualization environments construction is tried for solving problems such as assets overinvestments, etc. However, previous researches focus on virtualization structure research, without what is a suitable virtualization scheme for naval combat systems. Therefore, this paper evaluates available functions and performance of each virtualization solution. Experimental results show that comparative performance of each virtualization solution. The analyzed results can be used for enhancing design approach and verification for a naval combat systems using virtualization.
Edge computing is one of the recent computing architectures which utilizes computing resources near the data source or service endpoint to provide a service with better Quality of Service, and recently applying Deep N...
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ISBN:
(纸本)9781728108933
Edge computing is one of the recent computing architectures which utilizes computing resources near the data source or service endpoint to provide a service with better Quality of Service, and recently applying Deep Neural Network (DNN) on the edge is gaining focus from Artificial Intelligence (AI) service area. To place an AI application on an edge needs to be optimized before being deployed since usually edge device has limited computing resources comparing to those on the clouds. However, this optimization process usually degrades the accuracy on the AI since the precision on AI model parameters becomes lower during this optimization phase. In this paper, a novel method on DNN deployment has been proposed. Instead of optimizing parameter of an AI model, the proposed methods divide AI model into more than two parts and place each one on the edge and the cloud. Only partial part of AI model will be placed on the edge, and since there is no parameter optimization, there is no loss of accuracy. To easily maintain and access the deployed AI, a container structure to turn an AI into a microservice has been proposed as well. Test was processed with two AI microservice that contain partial AI models in each, and the result shows increase in end-to-end service delay with no loss of accuracy.
With the development of electronic engineering technology, diversifications of devices are being created. Moreover, computing machines are more accessible and with the development of communication technology, entrance...
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ISBN:
(纸本)9780769534077
With the development of electronic engineering technology, diversifications of devices are being created. Moreover, computing machines are more accessible and with the development of communication technology, entrance of new products related with ubiquitous paradigm are appearing. Ubiquitous computing device are connected within it, and they are convergence. Consequently, there is need of new methodology of device evaluation. In this paper, by collecting and integrating the current usability factor and ubiquitous characteristic factors, Ubiquitous Evaluation Factors are derived. Usability evaluation of each part of the Ubiquitous device, decomposition is performed. It is able to obtain the evaluation score of the device components from usability evaluation and score of the evaluation done in each usability factor. This framework is developed by web-based system allowing real product evaluation, and making comparison of the usability evaluation score obtained. Though this framework, usability test on ubiquitous device is simplified and systematized.
Many application developers are now choosing to install their Web applications on cloud data centers because of the attractiveness of cloud computing environment. Predicting future resource workload is critical since ...
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ISBN:
(纸本)9781665423830
Many application developers are now choosing to install their Web applications on cloud data centers because of the attractiveness of cloud computing environment. Predicting future resource workload is critical since it allows cloud service providers to automatically modify resources online in order to meet service level agreements (SLA). This paper proposes a multivariate deep learning prediction model to predict future resource workload for cloud computing environment. The prediction model uses a special type of recurrent neural network (RNN) called Bidirectional long short-term memory (Bi-LSTM). This work also explains and shows the advantage by using multivariate data compared to univariate data in time series forecasting. The experiments, using real world workload dataset, show that the proposed multivariate Bi-LSTM model outperforms the univariate Bi-LSTM model in prediction accuracy.
In vehicular edge computing (VEC), resource-intensive tasks are offloaded to computing nodes at the network edge. Owing to high mobility and distributed nature, optimal task offloading in vehicular environments is sti...
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ISBN:
(纸本)9781538650417
In vehicular edge computing (VEC), resource-intensive tasks are offloaded to computing nodes at the network edge. Owing to high mobility and distributed nature, optimal task offloading in vehicular environments is still a challenging problem. In this paper, we first introduce a software-defined vehicular edge computing (SD-VEC) architecture where a controller not only guides the vehicles' task offloading strategy but also determines the edge cloud resource allocation strategy. To obtain the optimal strategies, we formulate a problem on the edge cloud selection and resource allocation to maximize the probability that a task is successfully completed within a pre-specified time limit. Since the formulated problem is a well-known NP-hard problem, we devise a mobility-aware greedy algorithm (MGA) that determines the amount of edge cloud resources allocated to each vehicle. Trace-driven simulation results demonstrate that MGA provides near-optimal performance and improves the successful task execution probability compared with conventional algorithms.
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