• Journal of information and communication convergence engineering
• /
• v.9 no.4
• /
• pp.452-456
• /
• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.5820-5834
• /
• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.2 no.4
• /
• pp.233-241
• /
• 2007

In an ubiquitous environment, for controlling user access according to environment of users, a number of access control models enforcing dynamic environment of users have been proposed. However, they do not support personalized environments of each user and have a run-time overhead of searching active roles. In this paper, we propose a new model, PE-RBAC, that extends the RBAC architecture by addition of a personalized environment component as a constraint to accommodate dynamic and mobile users. In this model, a dynamic role activation is presented by using a new role-to-environment structure instead of the conventional role hierarchy, which makes it efficient to find the active roles according to a user's personalized environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.4
• /
• pp.1192-1207
• /
• 2014

Dynamic spectrum sharing is a key technology to improve spectrum utilization in wireless networks. The elastic spectrum management provides a new opportunity for licensed primary users and unlicensed secondary users to efficiently utilize the scarce wireless resource. In this paper, we present a game-theoretic framework for dynamic spectrum allocation where the primary users rent the unutilized spectrum to the secondary users for a monetary profit. In reality, due to the ON-OFF behavior of the primary user, the quantity of spectrum that can be opportunistically shared by the secondary users is limited. We model this situation with the renewal theory and formulate the spectrum pricing scheme with the Bertrand game, taking into account the scarcity of the spectrum. By the Nash-equilibrium pricing scheme, each player in the game continually converges to a strategy that maximizes its own profit. We also investigate the impact of several properties, including channel quality and spectrum substitutability. Based on the equilibrium analysis, we finally propose a decentralized algorithm that leads the primary users to the Nash-equilibrium, called DST. The stability of the proposed algorithm in terms of convergence to the Nash equilibrium is also studied.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.11
• /
• pp.2547-2552
• /
• 2013

To achieve better performance in dynamic spectrum access networks, each secondary user tracks channels and chooses a good channel to transmit its packet. When all secondary users adopt the same dynamic spectrum access policy, they have similar channel information, which leads secondary users to choose the same channel and more collisions among them. To relieve this problem, we propose an access policy using belief vector tracking method for other competing secondary users. Simulation results are provided to show that the proposed policy yields better performance than the existing policies which do not take into account what other secondary users are doing.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.604-607
• /
• 2003

Most recommendation systems recommend the products or other information satisfying preferences of users on the basis of the users' previous profile information and other information related to product searches and purchase of users visiting web sites. This study aims to apply these application categories to e-mail more necessary to users. The E-Mail System has the strong personality so that there will be some problems even if e-mails are automatically classified by category through the learning on the basis of the personal rules. In consideration with this aspect, we need the semi-automatic system enabling both automatic classification and recommendation method to enhance the satisfaction of users. Accordingly, this paper uses two approaches as the solution against the misclassification that the users consider as the accuracy of classification itself using the dynamic threshold in Bayesian Learning Algorithm and the second one is the methodological approach using the recommendation agent enabling the users to make the final decision.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.126-128
• /
• 2004

As e-mail is becoming increasingly important in every day life activity, mail users spend more and more time organizing and classifying the e-mails they receive into folder. Many existing recommendation systems or text classification are mostly focused on recommending the products for the commercial purposes or web documents. So this study aims to apply these application to e-mail more necessary to users. This paper suggests a dynamic recommendation agent system based on Rule Filtering Component recommending the relevant category to enable users directly to manage the optimum classification when a new e-mail is received as the effective method for E-Mail Management. Moreover we try to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, we prove to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. We designed main modules by rule filtering component for enhanced scalability and reusability of our system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1532-1553
• /
• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• Journal of the Korea Society for Simulation
• /
• v.14 no.1
• /
• pp.33-42
• /
• 2005

Service Level Agreement (SLA) is a service providing scheme by a service class agreement between a user and a service provider SLA allows that a user can select an expected service class in various service classes provided from a service provider. Recently, SLA management is adapted to support the end-to-end Qos for service users in Beyond 3 Generation (B3G) networks. In B3G networks, SLA provides multiple service classes on access networks so that service classes should be managed to assure the service satisfaction for users. In this paper, we propose a dynamic Qos management scheme by IP traffic class controlling based on SLA in B3G networks. Also, to manage dynamic traffic service, we consider Differentiated services (Diffserv) mechanism for the resource management by SLA. An If service traffic class on SLA can be dynamically changed by Diffserv traffic management to support dynamic end-to-end Qos. Hence, in this paper, we consider the buffer threshold scheme for controlling traffic loads and the traffic level control scheme for implementing the dynamic traffic management by the SLA.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.9
• /
• pp.4529-4548
• /
• 2016

DDoS attacks have had a devastating effect on the Internet, which can cause millions of dollars of damage within hours or even minutes. In this paper we propose a practical dynamic defense approach that overcomes the shortage of static defense mechanisms. Our approach employs a group of SDN-based proxy switches to relay data flow between users and servers. By substituting backup proxy switches for attacked ones and reassigning suspect users onto the new proxy switches, innocent users are isolated and saved from malicious attackers through a sequence of remapping process. In order to improve the speed of attacker segregation, we have designed and implemented an efficient greedy algorithm which has been demonstrated to have little influence on legitimate traffic. Simulations, which were then performed with the open source controller Ryu, show that our approach is effective in alleviating DDoS attacks and quarantining the attackers by numerable remapping process. The simulations also demonstrate that our dynamic defense imposes little effect on legitimate users, and the overhead introduced by remapping procedure is acceptable.