• Title/Summary/Keyword: Massive traffic data

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Dynamic Resource Reservation for Ultra-low Latency IoT Air-Interface Slice

  • Sun, Guolin;Wang, Guohui;Addo, Prince Clement;Liu, Guisong;Jiang, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3309-3328
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    • 2017
  • The application of Internet of Things (IoT) in the next generation cellular networks imposes a new characteristic on the data traffic, where a massive number of small packets need to be transmitted. In addition, some emerging IoT-based emergency services require a real-time data delivery within a few milliseconds, referring to as ultra-low latency transmission. However, current techniques cannot provide such a low latency in combination with a mice-flow traffic. In this paper, we propose a dynamic resource reservation schema based on an air-interface slicing scheme in the context of a massive number of sensors with emergency flows. The proposed schema can achieve an air-interface latency of a few milliseconds by means of allowing emergency flows to be transported through a dedicated radio connection with guaranteed network resources. In order to schedule the delay-sensitive flows immediately, dynamic resource updating, silence-probability based collision avoidance, and window-based re-transmission are introduced to combine with the frame-slotted Aloha protocol. To evaluate performance of the proposed schema, a probabilistic model is provided to derive the analytical results, which are compared with the numerical results from Monte-Carlo simulations.

Hybrid S-ALOHA/TDMA Protocol for LTE/LTE-A Networks with Coexistence of H2H and M2M Traffic

  • Sui, Nannan;Wang, Cong;Xie, Wei;Xu, Youyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.2
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    • pp.687-708
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    • 2017
  • The machine-to-machine (M2M) communication is featured by tremendous number of devices, small data transmission, and large uplink to downlink traffic ratio. The massive access requests generated by M2M devices would result in the current medium access control (MAC) protocol in LTE/LTE-A networks suffering from physical random access channel (PRACH) overload, high signaling overhead, and resource underutilization. As such, fairness should be carefully considered when M2M traffic coexists with human-to-human (H2H) traffic. To tackle these problems, we propose an adaptive Slotted ALOHA (S-ALOHA) and time division multiple access (TDMA) hybrid protocol. In particular, the proposed hybrid protocol divides the reserved uplink resource blocks (RBs) in a transmission cycle into the S-ALOHA part for M2M traffic with small-size packets and the TDMA part for H2H traffic with large-size packets. Adaptive resource allocation and access class barring (ACB) are exploited and optimized to maximize the channel utility with fairness constraint. Moreover, an upper performance bound for the proposed hybrid protocol is provided by performing the system equilibrium analysis. Simulation results demonstrate that, compared with pure S-ALOHA and pure TDMA protocol under a target fairness constraint of 0.9, our proposed hybrid protocol can improve the capacity by at least 9.44% when ${\lambda}_1:{\lambda}_2=1:1$and by at least 20.53% when ${\lambda}_1:{\lambda}_2=10:1$, where ${\lambda}_1,{\lambda}_2$ are traffic arrival rates of M2M and H2H traffic, respectively.

An Efficient Implementation of Key Frame Extraction and Sharing in Android for Wireless Video Sensor Network

  • Kim, Kang-Wook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3357-3376
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    • 2015
  • Wireless sensor network is an important research topic that has attracted a lot of attention in recent years. However, most of the interest has focused on wireless sensor network to gather scalar data such as temperature, humidity and vibration. Scalar data are insufficient for diverse applications such as video surveillance, target recognition and traffic monitoring. However, if we use camera sensors in wireless sensor network to collect video data which are vast in information, they can provide important visual information. Video sensor networks continue to gain interest due to their ability to collect video information for a wide range of applications in the past few years. However, how to efficiently store the massive data that reflect environmental state of different times in video sensor network and how to quickly search interested information from them are challenging issues in current research, especially when the sensor network environment is complicated. Therefore, in this paper, we propose a fast algorithm for extracting key frames from video and describe the design and implementation of key frame extraction and sharing in Android for wireless video sensor network.

A Study on Practical Method of Utility Curve for Deciding Priority Order of the Improvements in Traffic Safety Audit (교통안전진단 개선방안들의 우선순위 산정 연구)

  • Choi, Ji Hye;Kang, Soon Yang;Hong, Ji Yeon;Lim, Joon Beom
    • Journal of the Korean Society of Safety
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    • v.31 no.3
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    • pp.143-155
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    • 2016
  • Recently, a massive loss of life and property is occurring in Korea due to traffic accidents, with the rapid increase in cars. For improvement of traffic safety, the Korea Transportation Safety Authority intensively analyzes accident data in local governments with low traffic safety index, performs a field investigation to extract problems and offers local governments improvements for problems, by conducting the 'Special Survey of Actual Conditions of Traffic Safety' each year, starting 2008. But local governments cannot strongly push forward the improvement projects due to the limited budget and the uncertainty of the improvement plan effects. Therefore, this study suggested a model which applied the Utility concept to the AHP theory, in order to efficiently decide a priority of the improvement plans in accident black spots in consideration of the limited budget of local governments. The number of accidents in each spot for improvement and accident severity, traffic volume, pedestrian volume, the improvement project cost and the accident reduction effect were chosen as evaluation factors for deciding a priority, and data about the improvement plan costs and the accident reduction effects, traffic accidents and traffic volume in the spots to undergo the special research on the real condition of traffic accident in the past were collected from the existing studies. Then, regression analysis was carried out and the Utility Curve of each evaluation factor was computed. Based on the AHP analysis findings, this study devised a priority decision method which calculated the weight and the utility function of each evaluation factor and compared the total utility values. The AHP analysis findings showed that among the evaluation factors, accident severity had the biggest importance and it was followed by the improvement plan cost, the number of accidents, the improvement effect, traffic volume and pedestrian volume. The calculated utility function shows a rise in utility, as the variables of the 5 evaluation factors; the number of accidents, accident severity, the improvement plan effect, traffic volume and pedestrian volume increase and a fall in utility, as the variables of the improvement plan cost increase, since the improvement plan cost is included in the budget spent by a local government.

Towards Carbon-Neutralization: Deep Learning-Based Server Management Method for Efficient Energy Operation in Data Centers (탄소중립을 향하여: 데이터 센터에서의 효율적인 에너지 운영을 위한 딥러닝 기반 서버 관리 방안)

  • Sang-Gyun Ma;Jaehyun Park;Yeong-Seok Seo
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.4
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    • pp.149-158
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    • 2023
  • As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

An Improvement of Speed for Wavelength Multiplex Optical Network using Optical Micro Electro Mechanical Switches (광마이크로전자기계 스위치를 이용한 파장다중 광네트워크의 속도 재선)

  • Lee Sang-Wha;Song Hae-Sang
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.5 s.37
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    • pp.123-132
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    • 2005
  • In this Paper, we present an improvement of switch node for wavelength multiplex optical network. Currently because of quick increase of internet traffic a big network capacity is demanded. Wavelength multiplex optical network Provides the data transfer of high speed and the transparent characteristic of the data. Therefore optic network configuration is the most powerful technology in the future. It will be able to control the massive traffic from the optical network in order to transmit the multimedia information of very many quantify. Consequently the node where the traffic control is Possible, is demanded. The optical switch node which manages efficiently the multiple wavelength was Proposed. This switch is composed of a optical switch module for switching and a wavelength converter module for wavelength conversion. It will be able to compose the switch fabric without optical/electro or electro/optical conversion using optical MEMS(Micro Electro Mechanical Switches) module. Finally, we present the good test result regarding the operational qualify of the switch fabric and the performance of optical signal from the switch node. The proposed switch node of the optic network will be able to control the massive traffic with all optical.

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Big Data Based Dynamic Flow Aggregation over 5G Network Slicing

  • Sun, Guolin;Mareri, Bruce;Liu, Guisong;Fang, Xiufen;Jiang, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4717-4737
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    • 2017
  • Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

A Study on Development Project for The Yongsan International Business Station District : Focus on Foreign Example (용산 국제업무 지구 역세권 개발사업을 위한 기초연구 - 해외사례를 중심으로 -)

  • Lee, Tai-Sik;Chang, Kyung-Soo;Park, Eun-Soo;Koo, Ja-Kyung
    • Proceedings of the KSR Conference
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    • 2007.11a
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    • pp.1877-1882
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    • 2007
  • The Yongsan International Business District development work is a 20 billion$ project to raise facilities for national business, trade, residence, and culture. The project site is $566,800m^2$ and it covers the railroad maintenance center and Dongbuichon-dong. Developing railroad station region used to be done by private investment. However, problems existed; simple function as a massive selling market, traffic jam caused by massive market users, inadequacy to transfer to other transportations, interruption of the pedestrian way and separation of zone of life by the station. To solve this problem it is important to consider developing cases of other countries and devise a plan that is applicable to our circumstances. In the study, we compared our station development case with foreign station development cases and analyze the element for the plan what we should consider in our station development. In addition, The results of the study can be used as a preliminary data in the future planning the Yongsan International Business District development.

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A study on the Throughput Guarantee with TCP Traffic Control (전송률 보장을 위한 TCP 트래픽 제어에 관한 연구)

  • Lee, Myun-Sub
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.3
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    • pp.303-308
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    • 2016
  • Recently, as the rapid development of network technology and the increase of services required high bandwidth such as multimedia service, the network traffic dramatically increases. This massive increase of network traffic causes some problems such as the degradation of QoS and the lack of network resources and, to solve these problems, various research to guarantee QoS have been performing. Currently, The most representative method to guarantee the QoS is the DiffServ(: Differentiated Service). The DiffServ defines the AF(: Assured Forwarding) PHB(: Per Hop Behavior) and statistically ensures the throughput over the certain level of data rate. However, the TCP congestion control method that make up the majority of the Internet traffic is not fundamentally suitable to the DiffServ that guarantees the throughput without managing the individual flow. Therefore, in this paper, we present this mismatch through the simulation as an example and propose the solution by controlling the TCP of the terminal in the network. The proposed scheme utilizes the information of the reception window size included in the ACK frame and does not require any modification of the TCP algorithms currently in use.

Design of Formalized message exchanging method using XMDR (XMDR을 이용한 정형화된 메시지 교환 기법 설계)

  • Hwang, Chi-Gon;Jung, Kye-Dong;Choi, Young-Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.6
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    • pp.1087-1094
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    • 2008
  • Recently, XML has been widely used as a standard for a data exchange, and there has emerged the tendency that the size of XML document becomes larger. The data transfer can cause problems due to the increase in traffic, especially when a massive data such as Data Warehouse is being collected and analyzed. Therefore, an XMDR wrapper can solve this problem since it analyzes the tree structures of XML Schema, regenerates XML Schema using the analyzed tree structures, and sends it to each station with an XMDR Query. XML documents which are returned as an outcome encode XML tags according to XML Schema, and send standardized messages. As the formalized XML documents decrease network traffic and comprise XML class information, they are efficient for extraction, conversion, and alignment of data. In addition, they are efficient for the conversion process through XSLT, too, as they have standardized forms. In this paper we profuse a method in which XML Schema and XMDR_Query sent to each station are generated through XMDR(extended Meta-Data Registry) and the generation of products and XML conversion occur in each station wrapper.