• Journal of the Korean Society for Railway
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• v.16 no.6
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• pp.510-518
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• 2013

These days, interest in radio networks for railways has increased both at home and abroad. In response to this trend, not only the existing radio networks which focus on railway control signals but also the next-generation integrated radio network that can send videos and manage mass storage data are actively being investigated. This paper proposes wireless communication methods to establish integrated radio networks for railways. The paper further suggests a candidate frequency band that could be allocated as the frequency band for railways among the frequency bands currently used in Korea. Based on this paper, we can expect that the domestic railroad will operate more efficiently and that security and convenience of the railroad will reach a superior level. In addition, the Korean integrated radio networks for railways, which cope with the changes in the global technology market, will be established.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1689-1706
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• 2012

The preservation of temporal dependencies among a group of processes that exchange continuous media at runtime is a key issue for emerging mobile distributed systems (MDS), such as monitoring of biosignals and interactive multiuser games. Although several works are oriented to satisfy temporal dependencies, most of them are not suitable for MDSs. In general, an MDS is characterized by the absence of global references (e.g. shared memory and wall clock), host mobility, limited processing and storage capabilities in mobile hosts, and limited bandwidth on wireless communication channels. This paper proposes an asymmetric synchronization protocol to be used at runtime in an MDS without using a common reference. One main aspect of our synchronization protocol is that it translates temporal constraints to causal dependencies of the continuous media data as seen by the mobile hosts. We simulate the protocol by considering a cellular network environment and by using MPEG-4 encoders. The simulation results show that our protocol is effective in reducing the synchronization error. In addition, the protocol is efficient in terms of processing and storage costs at the mobile devices, as well as in the overhead attached per message across the wired and wireless channels.

• Proceedings of the IEEK Conference
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• summer
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• pp.405-409
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• 2004

The Pocket PC has become more popular in market because of the advantages of its small size and convenience for regular customers. Pocket PC is a mobile device so that we can receive the benefits of shared data over a wireless network. Enabling us to transmit data to a central location, simply messaging from one point to the next, its ability to share information across a wireless platform is becoming central to our communication needs. However, using Windows CE - an embedded operating system, as well as being designed for mobile users, there are many limitations to memory and speed of arithmetic operations on Pocket PC. As a result, developers have to deal with many difficulties in managing information storage when developing applications, especially Geography Information System (GIS) applications. In this paper, we propose some efficient methods to store GIS data and to increase the speed of displaying maps in GIS applications developed on Pocket PC and Windows CE 3.0.

• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.31-40
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• 2016

Wireless sensor networks have been used in many applications such as marine environment, army installation, etc. The sensor data is very important, because all these applications depend on sensor data. The possibility of communication failures becomes high since the surrounding environment of a wireless sense network has an sensitive effect on its communications. In particular, communication failures in underwater communications occur more frequently because of a narrow bandwidth, slow transmission speed, noises from the surrounding environments and so on. In cases of communication failures, the sensor data can be lost in the sensor data delivery process and these kinds of sensor data losses can make critical huge physical damages on human or environments in applications such as fire surveillance systems. For this reason, although a few of studies for storing and compressing sensor data have been proposed, there are lots of difficulties in actual realization of the studies due to none-existence of the framework using network communications. In this paper, we propose a framework for reducing loss of the sensor data and analyze its performance. The our analyzed results in non-framework application show a decreasing data recovery rate, T/t, as t time passes after a network failure, where T is a time period to fill the storage with sensor data after the network failure. Moreover, all the sensor data generated after a network failure are the errors impossible to recover. But, on the other hand, the analyzed results in framework application show 100% data recovery rate with 2~6% data error rate after data recovery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.236-245
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• 2007

Wireless sensor networks consist of numerous nodes equipped with small-sized and limited calculation capacities and storage space as well as low-capacity batteries. Therefore, the key issue is to reduce energy consumption of sensor nodes in sensor network environment. To reduce energy consumption of sensor nodes, consideration must be given to decreasing frequency of messages transmitted by nodes. Also, considering network application, security of sensor networks is also considered important. Therefore, this study proposes a key distribution scheme in dynamic clustering model. The dynamic clustering model used for this scheme is very effective in extending life span of wireless sensor networks. The proposed scheme provides improved security compared to the existing key distribution scheme by applying grid-based key distribution scheme and allocating polynomial s hare to the nodes forming a cluster. Also, comparison was made with the previously proposed grid-based, location-based and cluster-based key distribution schemes to illustrate the advantages of the proposed scheme.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.11-19
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• 2012

Construction supply chain management (CSCM) has become one of the critical factors that determine the success of a construction project as it becomes increasingly complicated and mega-sized. Particularly for high-rise or mega-sized building construction, just-in-time supply chain management is required due to lack of storage space and effective logistics for construction components and materials at a construction site. Despite the fact that research and development of radio frequency identification (RFID) and wireless sensor network (WSN) technology have been performed, construction project managers still need to carry mobile devices and check material and component flow at each stage of the supply chain process. This research proposes that the equipment used in the construction supply chain process, such as movers, trailers, gates, and hoists, can become main actors in the supply chain process using RFID and WSN technologies. And the proposed equipment and process focused on a solution to the redundancy identification problem, which has been observed in operations that use RFID/WSN-based processes for construction logistics. This paper also presents issues identified through verification and validation of the research results and proposes further studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3690-3713
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• 2019

According to the main group key management schemes logical key hierarchy (LKH), exclusion basis systems (EBS) and other group key schemes are limited in network structure, collusion attack, high energy consumption, and the single point of failure, this paper presents a group key management scheme for wireless sensor networks based on Lagrange interpolation polynomial characteristic (AGKMS). That Chinese remainder theorem is turned into a Lagrange interpolation polynomial based on the function property of Chinese remainder theorem firstly. And then the base station (BS) generates a Lagrange interpolation polynomial function f(x) and turns it to be a mix-function f(x)' based on the key information m(i) of node i. In the end, node i can obtain the group key K by receiving the message f(m(i))' from the cluster head node j. The analysis results of safety performance show that AGKMS has good network security, key independence, anti-capture, low storage cost, low computation cost, and good scalability.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.109-119
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• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.55-59
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• 2010

Most applications for solar-powered wireless sensor networks are usually deployed in remote areas without a continuous connection to the external networks and a regular maintenance by an administrator. In this case, sensory data has to be stored in the network as much as possible until it is uploaded by the data mule. For this purpose, a balanced data distribution over the network should be performed, and this can be achieved efficiently by taking the amount of available energy and storage into account, in the system layer of each node. In this paper, we introduce a simple but very efficient data distribution algorithm, by which each solar-powered node utilizes the harvested energy and the storage space maximally. This scheme running on each node determines the amount of energy which can be used for a data distribution as well as the amount of data which should be transferred to each neighbor, by using the local information of energy and storage status.