• Journal of Communications and Networks
• /
• v.17 no.1
• /
• pp.58-66
• /
• 2015

Aeronautical communication networks (ACN) is an emerging concept in which aeronautical stations (AS) are considered as a part of multi-tier network for the future wireless communication system. An AS could be a commercial plane, helicopter, or any other low orbit station, i.e., Unmanned air vehicle, high altitude platform. The goal of ACN is to provide high throughput and cost effective communication network for aeronautical applications (i.e., Air traffic control (ATC), air traffic management (ATM) communications, and commercial in-flight Internet activities), and terrestrial networks by using aeronautical platforms as a backbone. In this paper, we investigate the issues about connectivity, throughput, and delay in ACN. First, topology of ACN is presented as a simple mobile ad hoc network and connectivity analysis is provided. Then, by using information obtained from connectivity analysis, we investigate two communication models, i.e., single-hop and two-hop, in which each source AS is communicating with its destination AS with or without the help of intermediate relay AS, respectively. In our throughput analysis, we use the method of finding the maximum number of concurrent successful transmissions to derive ACN throughput upper bounds for the two communication models. We conclude that the two-hop model achieves greater throughput scaling than the single-hop model for ACN and multi-hop models cannot achieve better throughput scaling than two-hop model. Furthermore, since delay issue is more salient in two-hop communication, we characterize the delay performance and derive the closed-form average end-to-end delay for the two-hop model. Finally, computer simulations are performed and it is shown that ACN is robust in terms of throughput and delay performances.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.3
• /
• pp.321-331
• /
• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1479-1501
• /
• 2020

Dependable functioning of dynamic networks is essential for delivering ubiquitous services. Faults are the root causes of network outages. The comparison diagnosis model, which automates fault's identification, is one of the leading approaches to attain network dependability. Most of the existing research has focused on stationary networks. Nonetheless, the time-free comparison model imposes no time constraints on the system under considerations, and it suits most of the diagnosis requirements of dynamic networks. This paper presents a novel protocol that diagnoses faulty nodes in diagnosable dynamic networks. The proposed protocol comprises two stages, a testing stage, which uses the time-free comparison model to diagnose faulty neighbour nodes, and a disseminating stage, which leverages a Random Linear Network Coding (RLNC) technique to disseminate the partial view of nodes. We analysed and evaluated the performance of the proposed protocol under various scenarios, considering two metrics: communication overhead and diagnosis time. The simulation results revealed that the proposed protocol diagnoses different types of faults in dynamic networks. Compared with most related protocols, our proposed protocol has very low communication overhead and diagnosis time. These results demonstrated that the proposed protocol is energy-efficient, scalable, and robust.

• Journal of Communications and Networks
• /
• v.10 no.3
• /
• pp.268-286
• /
• 2008

In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.6
• /
• pp.1070-1079
• /
• 2016

In this paper, the design of recursive radial basis function neural networks based on incremental fuzzy c-means is introduced for processing the big data. Radial basis function neural networks consist of condition, conclusion and inference phase. Gaussian function is generally used as the activation function of the condition phase, but in this study, incremental fuzzy clustering is considered for the activation function of radial basis function neural networks, which could effectively do big data processing. In the conclusion phase, the connection weights of networks are given as the linear function. And then the connection weights are calculated by recursive least square estimation. In the inference phase, a final output is obtained by fuzzy inference method. Machine Learning datasets are employed to demonstrate the superiority of the proposed classifier, and their results are described from the viewpoint of the algorithm complexity and performance index.

• Journal of Communications and Networks
• /
• v.7 no.2
• /
• pp.178-191
• /
• 2005

Fourth-generation (4G) wireless networks will be the IP-based cellular networks integrating Internet with the existing cellular networks. Two important issues should be concerned in the IP-based cellular networks, IP mobility, and quality-of-service (QoS) guarantees. In this paper, we proposed two mechanisms to solve the problems with IP mobility and RSVP-based QoS provisioning. First, virtual-IP (VIP) allocation scheme in areas with a large rate of handoff can minimize the wireless signaling overhead due to IP mobility. The access routers (ARs) create dynamically the VIP zone by using the measured handoff rate derived from the history of the handoff into neighboring ARs. We show that VIP allocation scheme reduces the binding update messages in the wireless link than hierarchical mobile IPv6. Second, the new advance resource reservation protocol called proportional aggregate RSVP (PA-RSVP) can minimize waste of bandwidth and soft state refresh overhead due to IP mobility. It allocates the bandwidth in advance between the mobility anchor point and neighboring ARs using proportional aggregate reservation. We also show that PA-RSVP provides an improved performance over existing protocols.

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

• Journal of Communications and Networks
• /
• v.13 no.1
• /
• pp.43-49
• /
• 2011

In this paper, a new medium access control (MAC) protocol entitled three-phase multiple access with continual contention resolution (TPMA-CCR) is proposed for wireless multi-hop ad hoc networks. This work is motivated by the previously known three-phase multiple access (TPMA) scheme of Hou and Tsai [2] which is the suitable MAC protocol for clustering multi-hop ad hoc networks owing to its beneficial attributes such as easy collision detectible, anonymous acknowledgment (ACK), and simple signaling format for the broadcast-natured networks. The new TPMA-CCR is designed to let all contending nodes participate in contentions for a medium access more aggressively than the original TPMA and with continual resolving procedures as well. Through the systematical performance analysis of the suggested protocol, it is also shown that the maximum throughput of the new protocol is not only superior to the original TPMA, but also improves on the conventional slotted carrier sense multiple access (CSMA) under certain circumstances. Thus, in terms of performance, TPMA-CCR can provide an attractive alternative to other contention-based MAC protocols for multi-hop ad hoc networks.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.3
• /
• pp.145-156
• /
• 2000

In this paper, we propose a new methodology which includes the optimal design procedure of Polynomial Neural Networks(PNN) structure for model identification of complex and nonlinear system. The proposed PNN algorithm is based on GMDA(Group Method of Data handling) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. In other words, the PNN uses high-order polynomial as extended type besides quadratic polynomial used in GMDH, and the number of input of its node in each layer depends on that of variables used in the polynomial. The design procedure to obtain an optimal model structure utilizing PNN algorithm is shown in each stage. The study is illustrated with the aid of pH neutralization process data besides representative time series data for gas furnace process used widely for performance comparison, and shows that the proposed PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and prediction capabilities of model is evaluated and also discussed.

• Communications of the Korean Mathematical Society
• /
• v.24 no.3
• /
• pp.467-479
• /
• 2009

This paper ultimately aims to develop noninvasive techniques to identify the inside of a given electrical network. Based on the theory of the partial differentiation equations and mathematical modeling, this paper devises the algorithms to find the locations of possible abnormalities. To ensure the certainty of the algorithms, this study restricted the forms of the network and the number of abnormalities, rendering it easy to prove the uniqueness of the position of the abnormalities.