• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.5
• /
• pp.753-775
• /
• 2010

Greedy forwarding is a key mechanism of geographic routing using distance as a metric. As greedy forwarding only uses 1-hop neighbor node information, it minimizes routing overhead and is highly scalable. In existing greedy forwarding schemes, a node selects a next forwarding node based only on the distance. However, the signal strength in a realistic environment reduces exponentially depending on the distance, so that by considering only the distance, it may cause a large number of data packet retransmissions. To solve this problem, many greedy forwarding schemes have been proposed. However, they do not consider the unreliable and asymmetric characteristics of wireless links and thus cause the waste of limited battery resources due to the data packet retransmissions. In this paper, we propose a reliable and energy-efficient opportunistic greedy forwarding scheme for unreliable and asymmetric links (GF-UAL). In order to further improve the energy efficiency, GF-UAL opportunistically uses the path that is expected to have the minimum energy consumption among the 1-hop and 2-hop forwarding paths within the radio range. Comprehensive simulation results show that the packet delivery rate and energy efficiency increase up to about 17% and 18%, respectively, compared with the ones in PRR${\times}$Distance greedy forwarding.

• Journal of Digital Convergence
• /
• v.19 no.3
• /
• pp.211-216
• /
• 2021

Information from various heterogeneous devices is steadily increasing in distributed cloud environments. This is because high-speed network speeds and high-capacity multimedia data are being used. However, research is still underway on how to minimize information errors in big data sent and received by heterogeneous devices. In this paper, we propose a deep learning-based asymmetric storage management technique for minimizing bandwidth and data errors in networks generated by information sent and received in cloud environments. The proposed technique applies deep learning techniques to optimize the load balance after asymmetric hash of the big data information generated by each device. The proposed technique is characterized by allowing errors in big data collected from each device, while also ensuring the connectivity of big data by grouping big data into groups of clusters of dogs. In particular, the proposed technique minimizes information errors when storing and managing big data asymmetrically because it used a loss function that extracted similar values between big data as seeds.

• Journal of KIISE:Information Networking
• /
• v.30 no.5
• /
• pp.668-675
• /
• 2003

In this paper, we propose an enhanced p-cycle (preconfigured protection cycle) scheme for WDM mesh networks with QoS constraints. In the previous researches on p-cycle, it is assumed that user's connection has a hi-directional connectivity and the same bandwidth on both direction. Therefore it is difficult to apply p-cycle based link protection to uni-directional connections for multicasting or asymmetric broadband multimedia communications with hi-directional connectivity. And it didn't consider QoS of backup path. We enhanced the p-cycles to accomodate uni-directional connections for multicasting or asymmetric bandwidth communications with hi-directional connectivity. And we propose a selection procedure of p-cycle to assure QoS of backup path. We were able to reduce a required backup bandwidth by applying a uni-directional p-cycle concept to asymmetric broadband multimedia communication environment. The proposed p-cycle selection procedure is applied to the U.S. sample network to evaluate whether the configured p-cycles can support QoS constraint of working path and backup path.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.3
• /
• pp.17-25
• /
• 2004

Internet Service Subscribers Network has a new role of providing various multimedia services to the home. However, there exist several types of distributed subscriber networks using Asymmetric Digital Subscriber Line (ADSL), Very high-bit rate Digital Subscriber Line (VDSL), and Data Over Cable Service Interface Specifications (DOCSIS). The efficient and concentrated network management of those several distributed subscribers networks with resources requires the general network information model, which has and conceptional managed objects independent of type of network and its equipment to manage the integrated subscriber network. This paper presents the general Internet subscribers network model of the managed object to manage that network in the form of integrated hierarchy. This paper adopts the object-oriented development methodology with UML and designs and implements the integrated subscribers NMS of cable data network and VDSL network as examples of the subscriber networks.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.3
• /
• pp.297-308
• /
• 2001

We propose an algorithm which can reconstruct the 3D information from geographical information. The conventional techniques, the triangular patches and the Random Fractal Midpoint Displacement (RFMD) method, etc., have often been used to reconstruct natural images. While the RFMD method using Gaussian distribution obtains good results for the symmetric images, it is not reliable on asymmetric images immanent in the nature. Our proposed algorithm employs neural networks for the RFMD method to present the asymmetrical images. By using a neural network for reconstructing the 3D images, we can utilize statistical characteristics of irregular data. We show that our algorithm has a better performance than others by the point of view on the similarity evaluation. And, it seems that our method is more efficient for the mountainous topography which is more rough and irregular.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.3
• /
• pp.65-72
• /
• 2010

We propose the asymmetric 2.5Gbps/622Mbps PON(Passive Optical Network) in order to reduce the bandwith of filter at receiver with inverse RZ(Return to Zero) code coded downstream and NRZ(Non Return to Zero) upstream re-modulation. I theoretically analyze BER(Bit Error Rate) performance and the power sensitivity with the optimal threshold level by performing simulation with MATLAB according to the types of downstream data. The results have shown that the optimal threshold level at the optical receiver could be saturated at 0.33 as the optical received power increase more than -26dBm to keep $10^{-12}$ of BER to a minimum. Also the power sensitivity is more improved by about 3dB by fixing the threshold level at 0.33 than the conventional receiver. The proposed system can be a useful technology for optical access networks with asymmetric upstream and downstream data rates because the optical receiver can be used without controlling threshold levels and that does not require a light source in optical network unit (ONU) and its control circuits in the optical line termination (OLT).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.1B
• /
• pp.1-10
• /
• 2007

We propose a new approach to accommodate bidirectional asymmetric traffic demands as well as unexpected dynamic internet traffic variation in the WDM mesh network by using optical networking technologies. In the proposed scheme, an intermediate node determines the optical path based on the switching statistics of IP router of the node which characterizes the Internet traffic variation, which in effect provides a dynamic and distributed traffic control over the network. It is expected to reduce the efficiency deterioration of RWA(Routing and Wavelength Assignment) due to the real-time variation of Internet traffic so that expandability and flexibility of the network can be enhanced. In this paper, we describe a methodology for traffic behavior analysis at a node, and the decision policy of the establishment/release of optical path. In addition, we evaluate the performance of the proposed scheme through the computer simulations.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.5
• /
• pp.76-85
• /
• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the cyclic connection neural network, in which each neuron is connected only to its nearest neurons with binary synaptic weights of $\pm$ 1, has been investigated. Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of $n$-neuron network to produce a limit cycle of $n$- or 2$n$-period are also given. The results show that the estimated number of limit cycles is an exponential function of $n$. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.

• Convergence Security Journal
• /
• v.16 no.5
• /
• pp.3-9
• /
• 2016

The wireless sensor networks have become an economically viable monitoring solution for a wide variety of civilian and military applications. The main challenge in wireless sensor networks is the secure transmission of information through the network, which ensures that the network is secure, energy-efficient and able to identify and prevent intrusions in a hostile or unattended environment. In that correspondence, this paper proposes a distributed clustering process that integrates the necessary measures for secure wireless sensors to ensure integrity, authenticity and confidentiality of the aggregated data. We use the notion of pre-distribution of symmetric and asymmetric keys for a secured key management scheme, and then describe the detailed scheme which each sensor node within its cluster makes use of the pre-distribution of cryptographic parameters before deployment. Finally, we present simulation results for the proposed scheme in wireless sensor network.

• Journal of Korea Society of Industrial Information Systems
• /
• v.4 no.1
• /
• pp.68-76
• /
• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the ring connection neural network in which each neuron is only to its nearest neurons with binary synaptic weights of ±1, has been inconnected vestigated Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of n-neuron network to produce a limit cycle of n- or 2n-period are also given The results show that the estimated number of limit cycle is an exponential function of n. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.