• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.45-52
• /
• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.97-105
• /
• 2010

This paper proposes an effective medium access mechanism which is based on IEEE 802.11 to transmit an urgent message, The main features of the proposed mechanism are as follows. First, when it comes to channel access to have high priority, it has a shorter interval between frames than that specified in standard document. Second, we use fixed window size instead of back-off window with an exponential increase. Performance evaluation of proposed mechanism is executed by simulation and compare with the node using the specified mechanism in standard document. Performance evaluation results show that according to increasing competition the nodes using proposed method have less accessing time than the conventional methods. Also, the proposed method can improve processing time because of the decreasing transmission delay.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.2
• /
• pp.39-44
• /
• 2020

In this paper, we show a modified Diffie-Hellman key exchange protocol that can exchange keys by exposing only minimal information using pre-computable session key pairs. The discrete logarithm problem, which provides the safety of existing Diffie-Hellman and Diffie-Hellman based techniques, is modified to prevent exposure of primitive root. We prove the algorithm's operation by applying the actual value to the proposed scheme and compare the execution time and safety with the existing algorithm, shown that the security of the algorithm is improved more than the product of the time complexity of the two base algorithms while maintaining the computation amount at the time of key exchange. Based on the proposed algorithm, it is expected to provide a key exchange environment with improved security.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.2 no.2
• /
• pp.63-81
• /
• 2008

WiMAX has been introduced as a competitive alternative for metropolitan broadband wireless access technologies. It is connection oriented and it can provide very high data rates, large service coverage, and flexible quality of services (QoS). Due to the large number of connections and flexible QoS supported by WiMAX, the uplink access in WiMAX networks is very challenging since the medium access control (MAC) protocol must efficiently manage the bandwidth and related channel allocations. In this paper, we propose and investigate a cost-effective WiMAX bandwidth management scheme, named the WiMAX partial sharing scheme (WPSS), in order to provide good QoS while achieving better bandwidth utilization and network throughput. The proposed bandwidth management scheme is compared with a simple but inefficient scheme, named the WiMAX complete sharing scheme (WCPS). A maximum entropy (ME) based analytical model (MEAM) is proposed for the performance evaluation of the two bandwidth management schemes. The reason for using MEAM for the performance evaluation is that MEAM can efficiently model a large-scale system in which the number of stations or connections is generally very high, while the traditional simulation and analytical (e.g., Markov models) approaches cannot perform well due to the high computation complexity. We model the bandwidth management scheme as a queuing network model (QNM) that consists of interacting multiclass queues for different service classes. Closed form expressions for the state and blocking probability distributions are derived for those schemes. Simulation results verify the MEAM numerical results and show that WPSS can significantly improve the network’s performance compared to WCPS.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.2
• /
• pp.99-113
• /
• 1992

In general, TDMA and FDMA have been used for multiple access communication methods. Recently. However, ALOHA and CSMA protocols came to exist as new schemes for VSAT data networks and LANs, respectively. These schemes are proven to be effective for packet switched communication systems that has bursty traffic but packet collisions. In this paper we analyze capture statistics arising from fading channels in packet radio communication systems in the context of ALOHA protocol. We derive general results of the exact form of capture probabilities and present numerical data for wide range of fading parameters. Since the capture probabilities are found to approach zero when the number of transmitted signals become larger, we are able to determine the achievable channel throughput by a least squares fitting of an exponential-type function to the probabilities.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6B
• /
• pp.406-415
• /
• 2005

The standards which use shared medium like IEEE 802.11 wireless LAN have transmission opportunity by contention in contention period. If there are collisions in contention period, medium access control protocol may solve problem by using backoff algorithm. Backoff algorithm is important part in medium access control, but legacy backoff method which is used under IEEE 802.11 standards is not adjusted when load is heavy because of increasing collisions. In this paper, we propose a new load-based dynamic backoff algorithm in contention-based wireless shared medium to improve throughput of medium and to reduce the number of collisions. Proposed backoff algorithm can increase the network utilization about $20\%$ higher than that of binary exponential backoff algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.165-182
• /
• 2014

An RFID systems employ efficient Anti-Collision Algorithms (ACAs) to enhance the performance in various applications. The EPC-Global G2 RFID system utilizes Frame Slotted Aloha (FSA) as its ACA. One of the common approaches used to maximize the system performance (tag identification efficiency) of FSA-based RFID systems involves finding the optimal value of the frame length relative to the contending population size of the RFID tags. Several analytical models for finding the optimal frame length have been developed; however, they are not perfectly optimized because they lack precise characterization for the timing details of the underlying ACA. In this paper, we investigate this promising direction by precisely characterizing the timing details of the EPC-Global G2 protocol and use it to derive a precise-optimal frame length model. The main objective of the model is to determine the optimal frame length value for the estimated number of tags that maximizes the performance of an RFID system. However, because precise estimation of the contending tags is difficult, we utilize a parametric-heuristic approach to maximize the system performance and propose two simple schemes based on the obtained optimal frame length-namely, Improved Dynamic-Frame Slotted Aloha (ID-FSA) and Exponential Random Partitioning-Frame Slotted Aloha (ERP-FSA). The ID-FSA scheme is based on the tag set estimation and frame size update mechanisms, whereas the ERP-FSA scheme adjusts the contending tag population in such a way that the applied frame size becomes optimal. The results of simulations conducted indicate that the ID-FSA scheme performs better than several well-known schemes in various conditions, while the ERP-FSA scheme performs well when the frame size is small.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.63-73
• /
• 2015

In the end to end data transfer protocols, it is very important to correctly estimate available bandwidth. In UDT (UDP based Data Transfer), receiver estimates the MTR (Maximum Transfer Rate) of the current link using pair packets transmitted periodically from sender and, then sender finally decides the MTR through EWMA (Exponential Weighted Moving Average) algorithm. Here, MTR has to be exactly estimated because available bandwidth is calculated with difference of MTR and current transfer rate. However, when network is congested due to traffic load and where competing flows are coexisted, it bring about a severe fairness problem. This paper proposes a congestion degree based MTR estimation algorithm. Here, the congestion degree stands a relative index for current congestion status on bottleneck link, which is calculated with arriving intervals of a pair packets. The algorithm try to more classify depending on the congestion degree to estimate more actual available bandwidth. With the network simulation results, our proposed method showed that the fairness problem among the competing flows is significantly resolved in comparison with that of UDT.