• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.1
• /
• pp.26-32
• /
• 2011

It is very important for more effective military operation to share information required in recognizing a situation by monitoring battlefield. The recognition of situations is offered visually though multi-media systems such as a COP(Common Operation Picture), UAV etc. The operating method has rapidly changed into Network-Centric Warfare (NCW). As a result, the data that these Multimedia systems should control is increasing. Improved performance of Multimedia systems is required to deal with them. In this paper, we propose Extended-Military Multimedia System(E-MMS) applying the most excellent scheduling method in terms of meet-ratio in real time when Multimedia systems carry out assigned information in real time for monitoring as the method of improved performance. As a result of utility about proposed system, it is verified that realtime EDF(Earliest Deadline First) scheduling method is more improved up to 20% compared to non-realtime FCFS(First Come First Service) in terms of the deadline meet ratio.

• KEPCO Journal on Electric Power and Energy
• /
• v.3 no.2
• /
• pp.73-78
• /
• 2017

Recently, a number of foreign electric power companies including domestic Korea Electric Power Corporation (KEPCO) have actively engaged in the construction of a power grid with the concept of a smart grid. The Smart grid is a technology that increases the efficiency of the power by converging the information network with the power grid. It can maximize the energy efficiency through the two-way communication between the utility and the consumer. However, as the power grid converges with the information and communication network, security threats are increasing more than existing power grids. Due to the nature of the power grid, the damage caused by security threats is not only personal privacy but also economic loss of society. So smart grid becomes the target of hackers. In this paper, we discuss security vulnerabilities of Advanced Metering Infrastructure (AMI), which is a core technology of smart grid construction, and the corresponding security technologies to prevent security damage of smart grid.

• Journal of Advanced Navigation Technology
• /
• v.15 no.4
• /
• pp.585-590
• /
• 2011

In the past few years, M2M (Machine-to-Machine) applications have become a hot topic in the wireless industry. While M2M applications can be used for many purposes (smart homes, smart metering/electricity meter reading, fleet management, mobile workforce, automobile insurance, vending machines, etc), and in many sectors (healthcare, agriculture, commercial, industrial, retail, utility, etc.), smart metering applications or smart grids present the biggest growth potential in the M2M market today. M2M platform is the future ubiquitous network technologies which provide the integrated service with the networks and devices. The promising technologies to tackle these problems are the Semantic technologies, for interoperability, and the Agent technologies for management of complex systems. In this paper the information communication technique based on the disaster prevention system's for the M2M, concepts and its requirement technology and application are studied.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.6214-6242
• /
• 2019

Routing in mobile ad hoc networks is performed in a distributed fashion where each node acts as host and router, such that it forwards incoming packets for others without relying on a dedicated router. Nodes are mostly resource constraint and the users are usually inclined to conserve their resources and exhibit selfish behaviour by not contributing in the routing process. The trust and reputation models have been proposed to motivate selfish nodes for cooperation in the packet forwarding process. Nodes having bad trust or reputation are detected and secluded from the network, eventually. However, due to the lack of proper identity management and use of non-persistent identities in ad hoc networks, malicious nodes can pose various threats to these methods. For example, a malicious node can discard the bad reputed identity and enter into the system with another identity afresh, called whitewashing. Similarly, a malicious node may create more than one identity, called Sybil attack, for self-promotion, defame other nodes, and broadcast fake recommendations in the network. These identity-based attacks disrupt the overall detection of the reputation systems. In this paper, we propose a reputation-based scheme that detects selfish nodes and deters identity attacks. We address the issue in such a way that, for normal selfish nodes, it will become no longer advantageous to carry out a whitewash. Sybil attackers are also discouraged (i.e., on a single battery, they may create fewer identities). We design and analyse our rationale via game theory and evaluate our proposed reputation system using NS-2 simulator. The results obtained from the simulation demonstrate that our proposed technique considerably diminishes the throughput and utility of selfish nodes with a single identity and selfish nodes with multiple identities when compared to the benchmark scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.5
• /
• pp.1569-1586
• /
• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.5
• /
• pp.730-737
• /
• 2016

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load's specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9B
• /
• pp.1390-1398
• /
• 2010

We present the concept of applying Wireless Mesh Networking (WMN) technology into Smart Grid, which is recently rising as a potential technology in various areas thanks to its advantages such as low installation costs, high scalability, and high flexibility. Smart Grid is an intelligent, next-generation electrical power network that can maximize energy efficiency by monitoring utility information in real-time and controlling the flow of electricity with IT communications technology converged to the existing power grid. WMNs must be designed for Smart Grid communication systems considering not only the high level of reliability, QoS support and mass-data treatment but also the properties of the traditional power grid. In addition, it is essential to design techniques based on international standards to support interoperability and scalability. In this paper, we evaluate the performance of IEEE 802.11s based Smart Grid Mesh Networks by conducting preliminary simulation studies with the ns-3 simulator. We also outline some challenging issues that should be reviewed when considering WMNs as the candidate for Smart Grid communication infrastructure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.1
• /
• pp.1145-1148
• /
• 2005

In this paper, we introduce a probabilistic model based on Bayesian networks (BNs) for inferring human fatigue by integrating information from various visual cues and certain relevant contextual information. Visual parameters, typically characterizing the cognitive states of a person including parameters related to eyelid movement, gaze, head movement, and facial expression, serve as the sensory observations. But, an individual visual cue or contextual Information does not provide enough information to determine human fatigue. Therefore in this paper, a Bayesian network model was developed to fuse as many as possible contextual and visual cue information for monitoring human fatigue. At the experiment results, display the utility of the proposed BNs for predicting and modeling fatigue.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.4748-4765
• /
• 2016

We consider a virtualized cognitive radio (CR) network, where multiple virtual network operators (VNOs) who own different virtual cognitive base stations (VCBSs) share the same physical CBS (PCBS) which is owned by an infrastructure provider (InP), sharing the spectrum with the primary user (PU). The uplink scenario is considered where the secondary users (SUs) transmit to the VCBSs. The PU is protected by constraining the interference power from the SUs. Such constraint is applied by the InP through pricing the interference. A Stackelberg game is formulated to jointly maximize the revenue of the InP and the individual utilities of the VNOs, and then the Stackelberg equilibrium is investigated. Specifically, the optimal interference price and channel allocation for the VNOs to maximize the revenue of the InP and the optimal power allocation for the SUs to maximize the individual utilities of the VNOs are derived. In addition, a low‐complexity ±‐optimal solution is also proposed for obtaining the interference price and channel allocation for the VNOs. Simulations are provided to verify the proposed strategies. It is shown that the proposed strategies are effective in resource allocation and the ±‐optimal strategy achieves practically the same performance as the optimal strategy can achieve. It is also shown that the InP will not benefit from a large interference power limit, and selecting VNOs with higher unit rate utility gain to share the resources of the InP is beneficial to both the InP and the VNOs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.3917-3941
• /
• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.