• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.45-56
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• 2010

Sensor Networks are composed of many sensor nodes, which are capable of sensing, computing, and communicating with each other, and one or more sink node(s). Sensor networks collect information of various objects' identification and surrounding environment. Due to the limited resources of sensor nodes, use of wireless channel, and the lack of infrastructure, sensor networks are vulnerable to security threats. Most research of sensor networks have focused on how to detect and counter one type of attack. However, in real sensor networks, it is impractical to predict the attack to occur. Additionally, it is possible for multiple attacks to occur in sensor networks. In this paper, we propose the Secure Routing Mechanism to Defend Multiple Attacks in Sensor Networks. The proposed mechanism improves and combines existing security mechanisms, and achieves higher detection rates for single and multiple attacks.

• Journal of IKEEE
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• v.23 no.4
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• pp.1203-1207
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• 2019

As the number of IP cores has been increasing in a System-on-Chip (SoC), multiple routers are included in on-chip-networks. Each router has its own arbitration policy and it is difficult to obtain a desired arbitration result by combining multiple routers. Allocating desired bandwidths to the ports across the routers is more difficult. In this paper, a guaranteed bandwidth allocation scheme using an IP-level QoS control is proposed to overcome the limitations of existing local arbitration policies. Each IP can control the priority of a packet depending on the data communication requirement within the allocated bandwidth. The experimental results show that the proposed mechanism guarantees for IPs to utilize the allocated bandwidth in multiple router on-chip-networks. The maximum error rate of bandwidth allocation of the proposed scheme is only 1.9%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1642-1661
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• 2015

Wireless mesh networks are a special type of broadcast networks which cover the qualifications of both ad-hoc as well as infrastructure mode networks. These networks offer connectivity to the last mile through hop to hop communication and by comparatively reducing the cost of infrastructure in terms of wire and hardware. Channel assignment has always been the focused area for such networks specifically when using non-overlapping channels and sharing radio frequency spectrum while using multiple radios. It has always been a challenge for mesh network on impartial utilization of the resources (channels), with the increase in users. The rational utilization of multiple channels and multiple radios, not only increases the overall throughput, capacity and scalability, but also creates significant complexities for channel assignment methods. For a better understanding of research challenges, this paper discusses heuristic methods, measurements and channel utilization applications and also examines various researches that yield to overcome this problem. Finally, we highlight prospective directions of research.

• Korean Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.77-84
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• 1997

This paper is concerning the development of multiple neural networks system of problem domains where the complete input space can be decomposed into several different regions, and these are known prior to training neural networks. We will adopt oblique decision tree to represent the divided input space and sel ect an appropriate subnetworks, each of which is trained over a different region of input space. The overall architecture of multiple neural networks system, called the federated architecture, consists of a facilitator, normal subnetworks, and tile networks. The role of a facilitator is to choose the subnetwork that is suitable for the given input data using information obtained from decision tree. However, if input data is close enough to the boundaries of regions, there is a large possibility of selecting the invalid subnetwork due to the incorrect prediction of decision tree. When such a situation is encountered, the facilitator selects a tile network that is trained closely to the boundaries of partitioned input space, instead of a normal subnetwork. In this way, it is possible to reduce the large error of neural networks at zones close to borders of regions. The validation of our approach is examined and verified by applying the federated neural networks system to the configuration design of a midship structure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.993-1003
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• 2012

In this paper, we propose a method that wireless mobile nodes can obtain high throughput in heterogeneous wireless networks using multiple connections and it has low packet loses under handover situation. Currently, a mobile node exchanges data with server for one network connection. The proposed method can use high throughput because it doesn't only use one network(WLAN, 3G, etc.) but also use multiple wireless networks. When mobile nodes move to area to use multiple connection, mobile nodes request heterogeneous wireless networks using multiple connections message from the server and the server transmit packets using multiple connections. Also, this method doesn't disconnect previous networks, so packets losses are decreased. Using the NS-2 simulation, we verify that the propose method enhances throughput.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.85-94
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• 2008

As a variety of wireless network services, such as WLAN, WiBro, cdma2000, and HSDPA, are provided and the range of users' choices for the wireless services are broaden, MCoA (Multiple Car-of Address) concepts that enable users to use wireless interfaces simultaneously have been presented in IETF MONAMI6 WG. Through this scheme, users can access several networks simultaneously by using multiple wireless interfaces. Such various wireless connection technologies continue to advance as they are connected and integrated to All-IP-based core network, and at the same time, heterogeneous networks are being managed overlaid according to the coverage of the wireless connection technologies. Under such circumstances, needs for an integrated architecture have arisen, and thus Wireless service framework is required that effectively manages heterogeneous networks which coexist with next generation's networks for 4G. In this paper, a wireless service framework is suggested in the consideration of current wireless service environment, and the framework covers the schemes to minimize the packet loss caused by handover, and also modified Multiple Care-of Address that helps to select most effective network by considering characteristics of various interfaces as well as users' preferences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2546-2566
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• 2016

This paper investigates an efficient transmission scheme for the remote wireless sensors to receive information which is rarely discussed in the integrated remote wireless sensor and multibeam satellite networks (IWSMSNs). The networks can be employed to exchange sensing information for emergency scenario, ocean scenario, and so on, which are isolated from available terrestrial networks. As the efficient transmission link is important to the IWSMSNs, we propose a hybrid full frequency (HFF) precoding by taking advantage of frequency reuse and multiple-input multiple-output (MIMO) precoding. Considering energy efficiency and sinks fairness are crucial to transmission link, thus the HFF precoding problems are formulated as transmit power minimization (TPM) and max-min fair (MMF) received signal to interference plus noise ratio (SINR) problems, which can be transformed to indefinite quadratic optimization programs. Then this paper presents a semi-definite programming (SDP) algorithm to solve the problems for the IWSMSNs. The promising potential of HFF for the real IWSMSNs is demonstrated through simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.473-481
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• 2007

Energy efficiency is one of the most critical concerns for wireless sensor networks. By allowing sensor nodes in close proximity to cooperate in transmission to form a virtual multiple-input multiple-output(MIMO) system, recent progress in wireless MIMO communications can be exploited to boost the system throughput, or equivalently reduce the energy consumption for the same throughput and BER target. However, these cooperative transmission strategies may incur additional energy cost and system overhead. In this paper, assuming that data collectors are equipped with antenna arrays and superior processing capability, energy efficiency of relevant traditional and cooperative transmission strategies: Single-input-multiple-output(SIMO), space-time block coding(STBC), and spatial multiplexing(SM) are studied. Analysis in the wideband regime reveals that, while receive diversity introduces significant improvement in both energy efficiency and spectral efficiency, further improvement due to the transmit diversity of STBC is limited, as opposed to the superiority of the SM scheme especially for non-trivial spectral efficiency. These observations are further confirmed in our analysis of more realistic systems with limited bandwidth, finite constellation sizes, and a target error rate. Based on this analysis, general guidelines are presented for optimal transmission strategy selection in system level and link level, aiming at minimum energy consumption while meeting different requirements. The proposed selection rules, especially those based on system-level metrics, are easy to implement for sensor applications. The framework provided here may also be readily extended to other scenarios or applications.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.283-291
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• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.