• Title/Summary/Keyword: mobile edge network

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Deep Neural Network-Based Critical Packet Inspection for Improving Traffic Steering in Software-Defined IoT

  • Tam, Prohim;Math, Sa;Kim, Seokhoon
    • Journal of Internet Computing and Services
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    • v.22 no.6
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    • pp.1-8
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    • 2021
  • With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

The Design and Implementation of Mobile base on Access Control System Using ZigBee Method (지그비 기술을 이용한 무선기반의 출입 통제 시스템 설계 및 구현)

  • Joo, Heon-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.2
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    • pp.211-220
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    • 2008
  • The home network technology which used USN is developing quickly. Use yet line to a lot of part as home network technology. Recently be leap into prominence to technology core of home network as wireless technology a ZigBee. ZigBee Perceive with cognition from tag and sensor as use USN, and processing, save, integration, and provide information. Implement the access control system which used technology BigBee with design at these papers. The wireless-based construction that used ZigBee. The influence that can let you implement early a Ubiquitous society is technology there being. Also, show by a large spinoff in an allied industry field, and improve the quality of life, and invention calls value added of leading edge IT service and product. The implementation of mobile base on access control system using zigbee method is expected to be helpful for the convenience in home network use.

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Intelligent Massive Traffic Handling Scheme in 5G Bottleneck Backhaul Networks

  • Tam, Prohim;Math, Sa;Kim, Seokhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.874-890
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    • 2021
  • With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

Modeling and Analysis of Load-Balancing Based on Base-Station CoMP with Guaranteed QoS

  • Feng, Lei;Li, WenJing;Yin, Mengjun;Qiu, Xuesong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.2982-3003
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    • 2014
  • With the explosive deployment of the wireless communications technology, the increased QoS requirement has sparked keen interest in network planning and optimization. As the major players in wireless network optimization, the BS's resource utilization and mobile user's QoS can be improved a lot by the load-balancing technology. In this paper, we propose a load-balancing strategy that uses Coordinated Multiple Points (CoMP) technology among the Base Stations (BS) to effectively extend network coverage and increase edge users signal quality. To use universally, different patterns of load-balancing based on CoMP are modeled and discussed. We define two QoS metrics to be guaranteed during CoMP load balancing: call blocking rate and efficient throughput. The closed-form expressions for these two QoS metrics are derived. The load-balancing capacity and QoS performances with different CoMP patterns are evaluated and analyzed in low-dense and high-dense traffic system. The numerical results present the reasonable CoMP load balancing pattern choice with guaranteed QoS in each system.

APPLICATIONS OF GRAPH THEORY

  • Pirzada, S.;Dharwadker, Ashay
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.11 no.4
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    • pp.19-38
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    • 2007
  • Graph theory is becoming increasingly significant as it is applied of mathematics, science and technology. It is being actively used in fields as varied as biochemistry(genomics), electrical engineering(communication networks and coding theory), computer science(algorithms and computation) and operations research(scheduling). The powerful results in other areas of pure mathematics. Rhis paper, besides giving a general outlook of these facts, includes new graph theoretical proofs of Fermat's Little Theorem and the Nielson-Schreier Theorem. New applications to DNA sequencing (the SNP assembly problem) and computer network security (worm propagation) using minimum vertex covers in graphs are discussed. We also show how to apply edge coloring and matching in graphs for scheduling (the timetabling problem) and vertex coloring in graphs for map coloring and the assignment of frequencies in GSM mobile phone networks. Finally, we revisit the classical problem of finding re-entrant knight's tours on a chessboard using Hamiltonian circuits in graphs.

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Hybrid Centralized-Distributed Mobility Management Scheme in SDN-Based LTE/EPC Networks (SDN 기반 LTE/EPC 네트워크에서 하이브리드 중앙-분산 이동성 관리 기법)

  • Lim, Hyun-Kyo;Kim, Yong-hwan;Han, Youn-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.4
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    • pp.768-779
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    • 2017
  • Recently, the great number of mobile devices causes excessive data/control traffic problems in the centralized LTE/EPC network and such dramatically increased traffic is emerging as a critical issue. In the Centralized Mobility Management (CMM) based LTE/EPC network, the Packet Data Network Gateway (P-GW) plays the centralized mobility anchor role and it accommodates most of data traffic. To solve this problem, the IETF has proposed the Distributed Mobility Management (DMM) scheme, but it has only focused on the data traffic load balancing and could not solve the control traffic overload problem. In this paper, therefore, we propose a new SDN based hybrid CMM/DMM Mobility Management (C-DMM) architecture based on Packet Network Edge Gateway (P-EGW), and introduce a selection scheme between CMM and DMM according to a device's mobility and the number of PDN connections. In order to prove the efficiency of the proposed architecture and scheme, we compare the data traffic processing load and the control traffic processing load over each scheme by emulating them in the ONOS controller and the Mininet environment.

Application of Adaptive Neuro-Fuzzy Inference System for Interference Management in Heterogeneous Network

  • Palanisamy, Padmaloshani;Sivaraj, Nirmala
    • ETRI Journal
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    • v.40 no.3
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    • pp.318-329
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    • 2018
  • Femtocell (FC) technology envisaged as a cost-effective approach to attain better indoor coverage of mobile voice and data service. Deployment of FCs over macrocell forms a heterogeneous network. In urban areas, the key factor limits the successful deployment of FCs is inter-cell interference (ICI), which severely affects the performance of victim users. Autonomous FC transmission power setting is one straightforward way for coordinating ICI in the downlink. Application of intelligent control using soft computing techniques has not yet explored well for wireless networks. In this work, autonomous FC transmission power setting strategy using Adaptive Neuro Fuzzy Inference System is proposed. The main advantage of the proposed method is zero signaling overhead, reduced computational complexity and bare minimum delay in performing power setting of FC base station because only the periodic channel measurement reports fed back by the user equipment are needed. System level simulation results validate the effectiveness of the proposed method by providing much better throughput, even under high interference activation scenario and cell edge users can be prevented from going outage.

Reducing Cybersecurity Risks in Cloud Computing Using A Distributed Key Mechanism

  • Altowaijri, Saleh M.
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.1-10
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    • 2021
  • The Internet of things (IoT) is the main advancement in data processing and communication technologies. In IoT, intelligent devices play an exciting role in wireless communication. Although, sensor nodes are low-cost devices for communication and data gathering. However, sensor nodes are more vulnerable to different security threats because these nodes have continuous access to the internet. Therefore, the multiparty security credential-based key generation mechanism provides effective security against several attacks. The key generation-based methods are implemented at sensor nodes, edge nodes, and also at server nodes for secure communication. The main challenging issue in a collaborative key generation scheme is the extensive multiplication. When the number of parties increased the multiplications are more complex. Thus, the computational cost of batch key and multiparty key-based schemes is high. This paper presents a Secure Multipart Key Distribution scheme (SMKD) that provides secure communication among the nodes by generating a multiparty secure key for communication. In this paper, we provide node authentication and session key generation mechanism among mobile nodes, head nodes, and trusted servers. We analyzed the achievements of the SMKD scheme against SPPDA, PPDAS, and PFDA schemes. Thus, the simulation environment is established by employing an NS 2. Simulation results prove that the performance of SMKD is better in terms of communication cost, computational cost, and energy consumption.

Performance Evaluation Using Neural Network Learning of Indoor Autonomous Vehicle Based on LiDAR (라이다 기반 실내 자율주행 차량에서 신경망 학습을 사용한 성능평가 )

  • Yonghun Kwon;Inbum Jung
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.3
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    • pp.93-102
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    • 2023
  • Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

Ontology-based Semantic Matchmaking for Service-oriented Mission Operation (서비스 지향 임무 수행을 위한 온톨로지 기반 시맨틱 매칭 방법)

  • Song, Seheon;Lee, SangIl;Park, JaeHyun
    • Journal of Advanced Navigation Technology
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    • v.20 no.3
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    • pp.238-245
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    • 2016
  • There are technological, operational and environmental constraints at tactical edge, which are disconnected operation, intermittent connectivity, and limited bandwidth (DIL), size, weight and power (SWaP) limitations, ad-hoc and mobile network, and so on. To overcome these limitations and constraints, we use service-oriented architecture (SOA) based technologies. Moreover, the operation environment is highly dynamic: requirements change in response to the emerging situation, and the availability of resources needs to be updated constantly due to the factors such as technical failures. In order to use appropriate resources at the right time according to the mission, it needs to find the best resources. In this context, we identify ontology-based mission service model including mission, task, service, and resource, and develop capability-based matching in tactical edge environment. The goal of this paper is to propose a capability-based semantic matching for dynamic resource allocation. The contributions of this paper are i) military domain ontologies ii) semantic matching using ontology relationship; and (iii) the capability-based matching for the mission service model.