• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권7호
• /
• pp.1935-1950
• /
• 2023

The arrival of the Internet of Things and 5G technology enables users to rely on edge computing platforms to process massive data. Data sharing based on edge computing refines the efficiency of data collection and analysis, saves the communication cost of data transmission back and forth, but also causes the privacy leakage of a lot of user data. Based on attribute-based encryption and blockchain technology, we design a fine-grained access control scheme for data in edge computing, which has the characteristics of verifiability, support for outsourcing decryption and user attribute revocation. User attributes are authorized by multi-attribute authorization, and the calculation of outsourcing decryption in attribute encryption is completed by edge server, which reduces the computing cost of end users. Meanwhile, We implemented the user's attribute revocation process through the dual encryption process of attribute authority and blockchain. Compared with other schemes, our scheme can manage users' attributes more flexibly. Blockchain technology also ensures the verifiability in the process of outsourcing decryption, which reduces the space occupied by ciphertext compared with other schemes. Meanwhile, the user attribute revocation scheme realizes the dynamic management of user attribute and protects the privacy of user attribute.

• 디지털산업정보학회논문지
• /
• 제11권3호
• /
• pp.63-68
• /
• 2015

We consider a cell edge environment. In cell edge, a user interfered by signal which is generated by a base stations not including the user. In cell edge environment, that is, there are inter cell interference (ICI) as well as multi user interference (MUI). Coordinated multi-point transmission (CoMP) is a technique which mitigates ICI between base stations. In CoMP, therefore, base stations can coordinate with each other by sharing user state information (CSI) in order to mitigate ICI. To improve sum rate performance in CoMP, each base station should generate optimal user group and transmit data to users selected in the optimal user group. In this paper, we propose a user selection algorithm in CoMP. The proposed method use signal to interference plus noise ratio (SINR) as criterion of selecting users. Because base station can't measure accurate SINR of users, in this paper, we estimate SINR equation considering ICI as well as MUI. Also, we propose a user selection algorithm based on the estimated SINR. Through MATAL simulation, we verify that the proposed method improves the system sum rate by an average of 1.5 ~ 3 bps/Hz compared to the conventional method.

• IEIE Transactions on Smart Processing and Computing
• /
• 제1권2호
• /
• pp.117-124
• /
• 2012

A client collaboration (CC) system is proposed for a user relay system. The proposed scheme focuses on the management of transmit power and leakage interference. In the proposed CC system, edge users transmit signals to the masters considered as user relays. The masters relay the signals of the edge users to the base station using the resource blocks (RBs) that are assigned to the edge users. The leakage interference and power consumption were analyzed in the CC system. In addition, an optimal master location problem was formulated based on the signal-to-leakage-plus-noise ratio (SLNR). Because the optimal master location problem is quite complex, a sub-optimal master location problem was proposed and a closed-form sub-optimal master location was obtained. The edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC. The numerical results showed that the edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC, and the average throughput increases.

• 한국통신학회논문지
• /
• 제34권4A호
• /
• pp.316-323
• /
• 2009

본 논문은 셀간 간섭을 제어하여 셀 경계 사용자의 데이터 전송율을 증가시키는 기술인 소프트 주파수 재사용시 전력 할당에 관한 것이다. 소프트 주파수 재사용 기술은 셀 경계 사용자의 데이터 전송율을 개선하는데 유용한 기술이나 주파수 재사용 지수가 증가되어 셀 평균 데이터 전송율을 감소시키는 문제가 있다. 본 논문에서는 하나의 중앙 제어기가 물리적 거리가 인접한 여러 개의 셀을 제어하는 환경에서, 셀 경계 사용자의 데이터 전송율 개선하면서도 셀 평균 전송율 감소를 최소화하도록 소프트 주파수 재사용을 위한 송신 전력 할당 기법을 제안한다. 시스템 시뮬레이션을 통하여 인접한 두 셀에 소프트 주파수 재사용 기술을 적용하여 소프트 주파수 재사용에 의한 셀 평균 데이터 전송율 감소 정도와 제안하는 전력 할당 기법에 의한 셀 평균 데이터 전송을 개선을 살펴본다.

• 한국통신학회논문지
• /
• 제41권7호
• /
• pp.789-798
• /
• 2016

본 논문에서는 home 소형셀 대비 넓은 커버리지를 갖고 많은 사용자를 서비스 하는 enterprise/urban 소형셀 환경에서 적용할 수 있는 사용자 컨텍스트 기반 캐시 알고리즘을 제안한다. 소형셀 캐시 기법은 소형셀 사용자의 웹 트래픽을 소형셀 내부에 위치한 저장 공간에 저장하는 방법으로 코어망 트래픽을 감소시키는 효과가 있다. 본 논문에서는 기존의 알고리즘과 달리 Mobile Edge Computing(MEC)의 개념을 적용하여 소형셀 내부가 아닌 edge server에 사용자 트래픽을 캐시하며 사용자 특성을 반영하기 위해 사용자를 그룹화한다. 또한, 그룹별 저장 공간의 크기를 달리하고, 캐시 업데이트 주기를 캐시 적중률에 따라 변경하여 코어망으로부터 제공받는 트래픽을 감소하고자 하였다. 성능 분석 결과 기존 알고리즘 대비 캐시 적중률 측면에서 약 11%, cache efficiency 측면에서 약 5.5%의 성능 향상을 확인할 수 있었다.

• Journal of Web Engineering
• /
• 제21권1호
• /
• pp.27-52
• /
• 2021

With recent increases in the number of network-connected devices, the number of edge computing services that provide similar functions has increased. Therefore, it is important to recommend an optimal edge computing service, based on quality-of-service (QoS). However, in the real world, there is a cold-start problem in QoS data: highly sparse invocation. Therefore, it is difficult to recommend a suitable service to the user. Deep learning techniques were applied to address this problem, or context information was used to extract deep features between users and services. However, edge computing environment has not been considered in previous studies. Our goal is to predict the QoS values in real edge computing environments with improved accuracy. To this end, we propose a GAIN-QoS technique. It clusters services based on their location information, calculates the distance between services and users in each cluster, and brings the QoS values of users within a certain distance. We apply a Generative Adversarial Imputation Nets (GAIN) model and perform QoS prediction based on this reconstructed user service invocation matrix. When the density is low, GAIN-QoS shows superior performance to other techniques. In addition, the distance between the service and user slightly affects performance. Thus, compared to other methods, the proposed method can significantly improve the accuracy of QoS prediction for edge computing, which suffers from cold-start problem.

• Journal of Information Processing Systems
• /
• 제17권3호
• /
• pp.615-629
• /
• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제12권2호
• /
• pp.47-52
• /
• 2023

최근 스마트 디바이스 및 스트리밍 서비스의 수요 증가에 따른 네트워크 트래픽을 효과적으로 관리하기 위한 방법으로 Mobile Edge Computing(MEC)기술이 주목받고 있다. MEC는 Base Station(BS)과 같은 네트워크 엣지에 캐시를 설치함으로써 사용자에게 보다 가까운 곳에서 서비스를 제공하므로 낮은 지연시간을 제공하고, 네트워크 부하를 감소시킬 수 있다. 또한, 엣지 네트워크에서 사용자는 가장 가까운 BS와 연결되는 것보다 요청된 콘텐츠가 캐싱되어 있는 BS와 연결하는 것이 서비스 지연시간 감소에 유리하다. 따라서 본 논문에서는 캐시 적중률 향상을 위한 이동성 기반 캐싱 및 사용자 연결(user association)알고리즘을 제안한다. 제안 알고리즘은 체류시간과 콘텐츠 요청 유사도를 토대로 사용자 연결을 결정하고 콘텐츠를 캐싱한다. 시뮬레이션을 통해 기존 연구 대비 제안 알고리즘의 향상된 캐시 적중률과 감소된 지연시간을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권11호
• /
• pp.2903-2923
• /
• 2023

Knowledge recommendation is a type of recommendation system that recommends knowledge content to users in order to satisfy their needs. Although using graph neural networks to extract data features is an effective method for solving the recommendation problem, there is information loss when modeling real-world problems because an edge in a graph structure can only be associated with two nodes. Because one super-edge in the hypergraph structure can be connected with several nodes and the effectiveness of knowledge graph for knowledge expression, a dual-channel hypergraph convolutional neural network model (DCHC) based on hypergraph structure and knowledge graph is proposed. The model divides user data and knowledge data into user subhypergraph and knowledge subhypergraph, respectively, and extracts user data features by dual-channel hypergraph convolution and knowledge data features by combining with knowledge graph technology, and finally generates recommendation results based on the obtained user embedding and knowledge embedding. The performance of DCHC model is higher than the comparative model under AUC and F1 evaluation indicators, comparative experiments with the baseline also demonstrate the validity of DCHC model.

• 대한임베디드공학회논문지
• /
• 제18권4호
• /
• pp.141-150
• /
• 2023

Currently, various companies are actively participating in research and development of drone delivery services. Existing studies do not comprehensively provide integrated functions for future drone delivery services such as mission automation, customer verification, and overcoming performance limitations, which can lead to high manpower demand, reduced user service trust, and potentially overloading low-end devices. Therefore, this study proposes a drone mission automation system (DMAS) using EdgeCPS technology to provide the three aforementioned functions in an integrated manner. Real-world experiments were conducted to evaluate the proposed system, demonstrating that the DMAS components operate according to the specified roles in the delivery scenario. In addition, the system achieved user verification with a similarity of more than 90% in the process of receiving the product, and verified a faster inference speed and a lower resource share than the existing method.