• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4950-4966
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• 2015

Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.219-226
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• 2005

This paper describes the open API with integration of semantic web service with PARLAY X based open API in 4G mobile network. It can be expected that the intelligence such as the context-awareness, adaptation and personalization in 4G mobile network will be deployed. But the existing PARLAY based network lacks in considering context-awareness, adaptation and personalization. Therefore, the object of this paper is to support the architecture and the Application Programming Interface (API) of the network service for the context-awareness, adaptation and Personalization in 4G mobile network The open API is to provide users with the adaptive network service to the changing context constraints as well as detecting the changing context and user's Preference. For instance, the open API can Provide users with QoS in network according to the detected context and user's preference, after detecting the context such as location and speed and user's preference.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.632-650
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• 2013

The paper considers a spectrum sharing cognitive radio (CR) network coexisting with a primary network under the average interference power constraint. In particular, the secondary user (SU) is assumed to carry delay-sensitive services and thus shall satisfy a given delay quality-of-service (QoS) constraint. The secondary receiver is also assumed to be equipped with multiple antennas to perform maximal ratio combining (MRC) to enhance SU performance. We investigate the effective capacity of the SU with MRC diversity under aforementioned constraints in Nakagami fading environments. Particularly, we derive the optimal power allocation to achieve the maximum effective capacity of the SU, and further derive the effective capacity in closed-form. In addition, we further obtain the closed-form expressions for the effective capacities under three widely used power and rate adaptive transmission schemes, namely, optimal simultaneous power and rate adaptation (opra), truncated channel inversion with fixed rate (tifr) and channel inversion with fixed rate without truncation (cifr). Numerical results supported by simulations are presented to consolidate our studies. The impacts on the effective capacity of various system parameters such as the number of antennas, the average interference power constraint and the delay QoS constraint are investigated in detail. It is shown that MRC diversity can significantly improve the effective capacity of the SU especially for cifr transmission scheme.

• Smart Media Journal
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• v.12 no.4
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• pp.19-26
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• 2023

IoT edge services utilizing neuromorphic hardware architectures are suitable for autonomous IoT applications as they perform intelligent processing on the device itself. However, spiking neural networks applied to neuromorphic hardware are difficult for IoT developers to comprehend due to their complex structures and various hyper-parameters. In this paper, we propose a method for generating spiking neural network (SNN) models that satisfy user performance requirements while considering the constraints of neuromorphic hardware. Our proposed method utilizes previously trained models from pre-processed data to find optimal SNN model parameters from profiling data. Comparing our method to a naive search method, both methods satisfy user requirements, but our proposed method shows better performance in terms of runtime. Additionally, even if the constraints of new hardware are not clearly known, the proposed method can provide high scalability by utilizing the profiled data of the hardware.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.334-345
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• 2010

In this paper, we study optimal tradeoffs of achievable throughput versus consumed power in wireless ad-hoc networks formed by a collection of multiple antenna nodes. Relying on adaptive modulation and/or dynamic channel coding rate allocation techniques for multiple antenna systems, we examine the maximization of throughput under power constraints as well as the minimization of transmission power under throughput constraints. In our examination, we also consider the impacts of enforcing quality of service requirements expressed in the form of channel coding block loss constraints. In order to properly model temporally correlated loss observed in fading wireless channels, we propose the use of finite-state Markov chains. Details of fading statistics of signal-to-interference-noise ratio, an important indicator of transmission quality, are presented. Further, we objectively inspect complexity versus accuracy tradeoff of solving our proposed optimization problems at a global as oppose to a local topology level. Our numerical simulations profile and compare the performance of a variety of scenarios for a number of sample network topologies.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.49-56
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• 2010

Severe energy constraints and the low power consumption require the significance of the energy efficient error control mechanisms in wireless sensor network (WSN). In this paper, an automatic repeat request (ARQ) methodology for the analysis of error control schemes in WSN is presented such that the effects of packet length, the modulation scheme and the interference effect of the wireless channel are investigated. Moreover, an analyis of ARQ error control is provided by considering two major architectures for wireless sensor network, i.e., Mica2 and MicaZ sensor nodes. And the throughput performance of WSN with asynchronous FSK signal and DSSS-OQPSK signal with selective repeat ARQ scheme are analyzed in multiple interference environment, and the probability of receiving a correct bit and packet from target node to sink node is evaluated as a function of the channel parameter, the number of wireless sensor node, and the spreading factor.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1251-1260
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• 2002

Real-time application programs have synchronization constraints which need to be met between media-data. Synchronization method represents feedback method including virtual client-side buffer. This buffer is used in buffer level method. It is client-leading synchronization that is absorbing variable transmission delay time and that is synchronizing by feedback control. It is the important factor for playback rate and QoS if the buffer level is normal or not. To solve the problems, we can control the start of transmission in multimedia server by appling filtering, control and network evaluation function. Synchronization method is processing for smooth presentation without cut-off while media is playing out. When audio frame which is master media is in high threshold buffer level we decrease play out time gradually, otherwise we increase it slowly.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.266-274
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• 2010

The efficient network resource management is one of the important topics in a real-time system. In this paper, we present a practical network resource management framework, control-theoretic packet scheduler (CPS) system. Using our framework, an operating system can schedule both input and output streams accurately and efficiently. Our framework adopts very portable feedback control theory for efficiency and accuracy. The CPS system is able to operate independent of the internal network protocol state, and it is designed to schedule packet streams in fine-grained time intervals to meet the resource requirement. This approach simplifies the design of the CPS system, and leads us to obtain the intended output bandwidth. We implemented our prototype system in Linux, and measured the performance of the network resource management system under various network QoS constraints. The distinctive features of our principles are as follows: It is robust and accurate, and its operation is independent of internal network protocols.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.121-136
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• 2023

Wireless Sensor Networks (WSNs) have many potential applications and unique challenges. Some problems of WSNs are: severe resources' constraints, low reliability and fault tolerant, low throughput, low scalability, low Quality of Service (QoS) and insecure operational environments. One significant solution against mentioned problems is hierarchical and clustering-based multipath routing. But, existent algorithms have many weaknesses such as: high overhead, security vulnerabilities, address-centric, low-scalability, permanent usage of optimal paths and severe resources' consumption. As a result, this paper is proposed an energy-aware, congestion-aware, location-based, data-centric, scalable, hierarchical and clustering-based multipath routing algorithm based on Numerical Taxonomy technique for homogenous WSNs. Finally, performance of the proposed algorithm has been compared with performance of LEACH routing algorithm; results of simulations and statistical-mathematical analysis are showing the proposed algorithm has been improved in terms of parameters like balanced resources' consumption such as energy and bandwidth, throughput, reliability and fault tolerant, accuracy, QoS such as average rate of packet delivery and WSNs' lifetime.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.455-461
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• 2008

Enhanced Distributed Channel Access (EDCA) is a channel access scheme adopted by the IEEE 802.11e draft standard for QoS-enabled wireless local area networks. It classifies traffic into separate Access Categories (ACs) and achieves service differentiation by allowing each AC to have its own values of channel access parameters. This paper proposes a scheme to dynamically adapt the EDCA parameters to traffic environment so that they both maximize the throughput of non real-time traffics and meet the delay and throughput constraints of real-time traffics. For this purpose, we develop a design algorithm for efficient exploration of the EDCA parameter space. Using the algorithm, we derive a Pareto curve fur delay-throughput trade-off in each anticipated traffic environment. The Pareto database can then be used to optimally adjust the parameter according to the traffic environment and administrative policies. Simulation results show that compared with the default parameter configuration, the proposed scheme is better for delay, throughput guarantee and can improve the throughput of non real-time traffics by 12% on average.