• Smart Media Journal
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• v.13 no.1
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• pp.45-51
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• 2024

Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery.

• Current Optics and Photonics
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• v.1 no.4
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• pp.315-324
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• 2017

In recent years, multicast services such as high-definition television (HDTV), video conferencing, interactive distance learning, and distributed games have increased exponentially, and wavelength-division multiplexing (WDM) networks are considered to be a promising technology due to their support for multicast applications. Multicast survivability in WDM networks has been the focus of extensive attention since a single-link failure in an optical network may result in a massive loss of data. But the improvement of network survivability increases energy consumption due to more resource allocation for protection. In this paper, an energy-efficient multicast algorithm (EEMA) is proposed to reduce energy consumption in WDM networks. Two cost functions are defined based on the link state to determine both working and protection paths for a multicast request in WDM networks. To increase the number of sleeping links, the link cost function of the working path aims to integrate new working path into the links with more working paths. Sleeping links indicate the links in sleep mode, which do not have any working path. To increase bandwidth utilization by sharing spare capacity, the cost function of the protection path is defined to use sleeping fibers for establishing new protection paths. Finally, the performance of the proposed algorithm is evaluated in terms of energy consumption, and also the blocking probability is evaluated under various traffic environments through OPNET. Simulation results show that our algorithm reduces energy consumption while maintaining the quality of service.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.171-174
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• 2013

Virtualization technology opened a new era in the field of Data intensive, Grid and Cloud Computing. Today's Data centers are smarter than ever leveraging the Virtualization technology. In response to that, Dynamic consolidations of Virtual Machines (VMs) allow efficient resource management by live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), leads to stipulation in dealing with energy-performance trade-off as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a Cloud Based CDN approach for allocation of VM that aims to maximize the client-level SLA. Our experiment result demonstrates significant enhancement of SLA at certain level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.397-406
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• 2014

Radio frequency (RF) jamming is a denial of service attack targeted at wireless networks. In resource-hungry scenarios with constant traffic demand, jamming can create connectivity problems and seriously affect communication. Therefore, the vulnerabilities of wireless networks must be studied. In this study, we investigate a particular type of RF jamming that exploits the semantics of physical (PHY) and medium access control (MAC) layer protocols. This can be extended to any wireless communication network whose protocol characteristics and operating frequencies are known to the attacker. We propose two efficient jamming techniques: A low-data-rate random jamming and a shot-noise based protocol-aware RF jamming. Both techniques use shot-noise pulses to disrupt ongoing transmission ensuring they are energy efficient, and they significantly reduce the detection probability of the jammer. Further, we derived the tight upper bound on the duration and the number of shot-noise pulses for Wi-Fi, GSM, and WiMax networks. The proposed model takes consider the channel access mechanism employed at the MAC layer, data transmission rate, PHY/MAC layer modulation and channel coding schemes. Moreover, we analyze the effect of different packet sizes on the proposed jamming methodologies. The proposed jamming attack models have been experimentally evaluated for 802.11b networks on an actual testbed environment by transmitting data packets of varying sizes. The achieved results clearly demonstrate a considerable increase in the overall jamming efficiency of the proposed protocol-aware jammer in terms of packet delivery ratio, energy expenditure and detection probabilities over contemporary jamming methods provided in the literature.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2422-2443
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• 2020

This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

• Smart Media Journal
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• v.13 no.6
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• pp.24-34
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• 2024

If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.

• Journal of Venture Innovation
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• v.3 no.1
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• pp.165-182
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• 2020

This research shows solutions for relieving the reversibility of the VAT system, and the solutions will be reviewed with current issues about supporting welfare. The Followings provide practical implementing solutions for each issue. Since the VAT is taxed for all goods and services as a general consumption tax, it is efficient tax policy for resource allocation comparing to income tax. On the other hand, because of the reversibility of the tax burden is also treated as a non-effective tax system for fair taxation. Even it is a non-effective tax system, the VAT system takes the most portion from the total national tax. In South Korea economic system, it is hard to raise the VAT rate because the economic effects are tremendous. For the long-term, the possibility of increasing the VAT rate is unavoidable, considering the economy, society, environment and energy, and aging. Therefore, a variety of substituted policies for the reversibility should be covered once there is a conference for the increase in the VAT rate. This research provides foundational solutions by acknowledging the reversibility of the tax burden in terms of the effective value-added tax rate. The followings are four solutions. First, it is required to adjust the duty-free system for relieving the reversibility and expand the tax-free system as well as individual consumption tax items. Second, The relief of reversibility should be worked by imposing higher the tax rate for high-income people' goods and services. Third, the adjustment of the duty-free system could be considered due to relieve the reversibility of the VAT. Last, it is considered to adjust of the simplified taxation system because the simplified taxation system is seriously against the tax-transfer principles.