• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1017-1024
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• 2004

Ubiquitous system requires intelligent environment and system that perceives context in a proactive manner. This paper describes proactive retrieval method using context patterns in ubiquitous computing. And as the user's contexts change, new information is delivered proactively based on user's context patterns. For proactive retrieval, we extract context patterns based on sequential pattern discovery and association rule in data mining. By storing only information to be needed in near future using the context patterns, we solved the problem of speed and storage capacity of mobile devices in ubiquitous computing. We explain algorithms and an example. Several experiments are performed and the experimental results show that our method has a good information retrieval.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.189-195
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• 2005

One of the major components of any pervasive system is its proactive behavior. Various models have been developed to provide system wide changes which would enable proactive behavior. A major drawback of these approaches is that they do not address the need to make use of existing applications without modifying the applications. To overcome this drawback, a middleware architecture called 'Concord' is proposed. Concord is based on a simple model which consists of Lookup Server and Database. The rewards for this simple model are many. First, Concord uses the existing computing infrastructure. Second, Concord standardizes the interfaces for all services and platforms. Third, new services can be added dynamically without any need for reconfiguration. Finally, Concord consists of Database that can maintain and publish the active set of available resources. Thus Concord provides a solid system for integration of various entities to provide seamless connectivity and enable proactive behavior.

• Asia pacific journal of information systems
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• v.15 no.2
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• pp.195-218
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• 2005

The emergence of ubiquitous computing environment will change the service architecture of business information systems such as Decision Support System(DSS), which will be a new application. Recent mobile DSSs allow the decision makers to be benefited from web and mobile technology. However, they seldom refer to context data, which are useful for proactive decision support. Meanwhile, ubiquitous applications so far provide restricted personalization service using context and preference of the user, that is, they do not fully make use of decision making capabilities. Hence, this paper aims to describe how the decision making capability and context-aware computing are jointly used to establish ubiquitous applications. To do so, an amended DSS paradigm: CKDDM(Context-Knowledge-Dialogue-Data-Model) is proposed in this paper. What will be considered for the future decision support systems when we regard ubiquitous computing technology as an inevitable impact that enforces the change of the way of making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems(ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, CAMA-myOpt(Context-Aware Multi Agent System-My Optimization) has been implemented as an illustrative example system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.43-52
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• 2013

Pervasive computing and social network are good resources in recommendation method. Collaborative filtering is one of the most popular recommendation methods, but it has some limitations such as rating sparsity. Moreover, it does not consider social network in pervasive computing environment. We propose an effective proactive friend recommendation method using social network and contexts in pervasive computing environment. In collaborative filtering method, users need to rate sufficient number of items. However, many users don't rate items sufficiently, because the rating information must be manually input into system. We solve the rating sparsity problem in the collaboration filtering method by using contexts. Our method considers both a static and a dynamic friendship using contexts and social network. It makes more effective recommendation. This paper describes a new friend recommendation method and then presents a music friend scenario. Our work will help e-commerce recommendation system using collaborative filtering and friend recommendation applications in social network services.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.198-205
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• 2009

In this paper, design of framework architecture of pervasive computing system providing seamless inter space interactions between private and public smart spaces is presented. The seamless inter space interaction issues are related to establishing user's service environment by allocating relevant resources in a new location where there are no prior settings for the user or where there are current users already being served in the new location. In the realm of pervasive computing, we can have different types of smart spaces, offering proactive and intelligent services, which are islands of smart spaces independent from each other. As users move about, they will have to roam from private smart space to public smart space and vice versa. When they enter a new island of smart space, they will have to setup their devices and service manually to get the same or different services they had at the previous location. Users might be living in a non-pervasive computing environment because this manual operation is inappropriate to its generic features of proactive and intelligent services of pervasive computing. The framework architecture will provide seamless inter space interactions initiated by changes in users' location to acquire negotiations of resources for new and current residents regarding service provision with limited available networked devices.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.153-158
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• 2006

The emergence of ubiquitous autonomic computing and network environment will change the service architecture information system which will be a new application area in SCM/logistics systems. In this study we surveyed the technical trend map of ubiquitous and its application in SCM/logistics support system design. We described the evolutional model of ubiquitous computing community for SCM/logistics system. It is consisted of three view points; self-growing, autonomic, and context-aware, which will allow the decision makers to be benefited from web and mobile technology and are useful for proactive SCM/logistics support system. Finally, we suggested a cooperative research planning for the development ubiquitous system between the government research center, university, and industry research activities.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.43-50
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• 2009

Flooding and SPIN, which are well-known WSN(Wireless Sensor Network) proactive protocols, spontaneously disseminate the sensed data without a request from an arbitrary sink node. However, these methods disseminate the data even to some nodes that do not need it, which is energy inefficient. In this paper, we introduce a semi-proactive protocol to disseminate only to pertinent nodes instead of all nodes in order to overcome this weakness. Thus some nodes, such as arbitrary sink nodes that need the sensed data, could easily obtain the data within some hops. The simulation result shows that the proposed protocol has higher average node energy efficiency than that of well-known earlier work, SPIN. If a proactive protocol, such as SPIN, is changed to semi-proactive and has only a 1-hop burden, then the energy efficiency enhancement is up to about 83% compared with SPIN.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.8-13
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• 2007

The context-aware environment focuses on recognizing the context and physical entities. For this reason, there has been an increasement in research of context-aware computing environment. Ontology-based context models are widely used in ubiquitous environment because of context sharing and reusing. In this paper, we propose a proactive retrieval method using ontology in context-aware environment. The method use a concept level of hierarchical concept tree in ontology for more efficient retrieval. This paper describes the proactive retrieval method and ontology model. Several experiments are performed and the results verify that the proposed method's efficiency is better than other existing methods.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.15-25
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• 2008

Due to the differences between a mobile ad-hoc network and a sensor network, the pre-existing autoconfiguration for a mobile ad-hoc network cannot be simply applied to a sensor network. But. a mechanism is still necessary to assign locally unique addresses to sensor nodes efficiently. This paper proposes a hybrid IDs assignment scheme of local area sensor networks. The IDs assignment scheme of hybrid method combines a proactive IDs assignment with a reactive IDs assignment scheme. The proposed scheme considers efficient communication using reactive IDs assignment, and security for potential attacks using zone-based self-organized clustering with Byzantine Agreement in sensor networks. Thus, this paper has solved the shortage of security due to minimizing network traffic and the problem of repairing the network from the effects of an aberrant node in sensor networks.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.