ICC 2020 - 2020 IEEE International Conference on Communications (ICC)最新文献_第2页

Success Probability in Wirelessly Powered Networks with Energy Correlation 基于能量关联的无线供电网络的成功概率

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9149367

Na Deng, M. Haenggi

引用次数: 1

VoI Based Information Collection for AUV Assisted Underwater Acoustic Sensor Networks 基于VoI的AUV辅助水声传感器网络信息采集

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9149149

Ruiyang Duan, Jun Du, Junming Ren, Chunxiao Jiang, Yong Ren, A. Benslimane

{"title":"VoI Based Information Collection for AUV Assisted Underwater Acoustic Sensor Networks","authors":"Ruiyang Duan, Jun Du, Junming Ren, Chunxiao Jiang, Yong Ren, A. Benslimane","doi":"10.1109/ICC40277.2020.9149149","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149149","url":null,"abstract":"This paper considers value based information collection for underwater acoustic sensor networks (UWASNs). In the considered system, the sensor nodes collect, store and update monitoring information with an initial value related to associated events. The value of information (VoI), however, decays with time. An autonomous underwater vehicle (AUV) is dispatched to retrieve data from the sensor nodes through acoustic communication. Our objective is to find the optimal traversal path for the AUV to maximize the VoI of the whole network. To achieve this goal, we first establish a realistic model for characterizing the behaviors of AUV and sensor nodes as well as the challenging environment, based on which the expression of the total VoI is derived. Then, we formulate the problem as a combinatorial optimization problem. We provide an optimal solution for this problem based on the branch and bound (BB) method, in which the lower bound (LB) and upper bound (UB) calculation strategies are specifically designed. A near-optimal heuristic algorithm based on the ant colony method is also adopted for further reducing computation complexity. Finally, simulations validate the effectiveness of the proposed algorithms.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125915392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Efficient and Secure Data Integrity Auditing Scheme with Traceability for Cloud-Based EMR 基于云的EMR的高效、安全的数据完整性审计方案

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148673

Lei Zhou, Anmin Fu, Jingyu Feng, Chunyi Zhou

{"title":"An Efficient and Secure Data Integrity Auditing Scheme with Traceability for Cloud-Based EMR","authors":"Lei Zhou, Anmin Fu, Jingyu Feng, Chunyi Zhou","doi":"10.1109/ICC40277.2020.9148673","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148673","url":null,"abstract":"Cloud computing provides an effective way to manage and share massive medical data for Electronic Medical Record (EMR), hence establishing cloud-based EMR has attracted more and more attention. The data integrity and privacy issue in cloud-based EMR should be emphasized since users do not want their medical records to be damaged or disclosed to others. To address the concern in this paper, we propose an efficient and secure Data Integrity Auditing scheme with Traceability for cloud-based EMR (DIAT), which provides data integrity and privacy. We store multiple copies so that data can be recovered quickly from damage as long as one copy remains intact; meanwhile, data cannot be leaked to unauthorized entities since it is stored as ciphertext. For supporting data dynamics, we have designed a two-dimensional data structure, called Dynamic Mapping Hash Table (DMHT). It does not require large auxiliary validation information, nor does it affect the sequence numbers of other blocks. Moreover, data traceability is achieved by organizing all versions of a data block as a chain so that doctors are enabled to track the changes of patients condition in their records. In addition, formal security analysis and experiment results confirm that DIAT is provably secure and efficient.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123321972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Two-dimensional Intensity Distribution and Connectivity in Ultraviolet Ad-Hoc Network 紫外自组织网络中的二维强度分布和连通性

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148886

Hong Qi, Difan Zou, Chen Gong, Zhengyuan Xu

引用次数: 0

Adaptive Coherent Sampling for Network Delay Measurement 网络时延测量的自适应相干采样

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9149155

Shuo Liu, Qiaoling Wang

{"title":"Adaptive Coherent Sampling for Network Delay Measurement","authors":"Shuo Liu, Qiaoling Wang","doi":"10.1109/ICC40277.2020.9149155","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149155","url":null,"abstract":"End-to-end network delay, as a metric to indicate the QoS (Quality-of-Service), plays an important role in distributed services. Unfortunately, it is infeasible in practice to know all node-pair delay information due to the quadratic growth of overhead by active probing. In this paper, we leverage the stateof-the-art matrix completion technology for better network delay estimation from limited measurements. Although the number of samples required for exact matrix completion is theoretically bounded, it is practically less helpful as the number cannot be specified. This motivates us to propose an adaptive coherent sampling algorithm to select the elements with larger leverage scores to maintain the characteristic of important rows or columns in the delay matrix. The number of samples is adaptively determined by a proposed stopping criterion. Simulation results based on real-world network delay datasets indicate that our proposed algorithm is capable of providing better performance (improves estimation error by 16.9% and convergence stress by 28.9%) at less cost (reduces number of samples by 3.9% and processing time by 78.6%) than traditionally used algorithms.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Deep Reinforcement Learning based Task Scheduling in Mobile Blockchain for IoT Applications 基于深度强化学习的物联网移动区块链任务调度

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148888

Yang Gao, Wenjun Wu, Haixiang Nan, Yang Sun, Pengbo Si

{"title":"Deep Reinforcement Learning based Task Scheduling in Mobile Blockchain for IoT Applications","authors":"Yang Gao, Wenjun Wu, Haixiang Nan, Yang Sun, Pengbo Si","doi":"10.1109/ICC40277.2020.9148888","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148888","url":null,"abstract":"Nowadays, the Internet of Things (IoT) has developed rapidly. To deal with the security problems in some of the IoT applications, blockchain has aroused lots of attention in both academia and industry. In this paper, we consider the mobile blockchain supporting IoT applications, and the mobile edge computing (MEC) is deployed at the Small-cell Base Station (SBS) as a supplement to enhance the computation ability of IoT devices. To encourage the participation of the SBS in the mobile blockchain networks, the long-term revenue of the SBS is considered. The task scheduling problem maximizing the long-term mining reward and minimizing the resource cost of the SBS is formulated as a Markov Decision Process (MDP). To achieve an efficient intelligent strategy, the deep reinforcement learning (DRL) based solution named policy gradient based computing tasks scheduling (PG-CTS) algorithm is proposed. The policy mapping from the system state to the task scheduling decision is represented by a deep neural network. The episodic simulations are built and the REINFORCE algorithm with baseline is used to train the policy network. According to the training results, the PG-CTS method is about 10% better than the second-best method greedy. The generalization ability of PG-CTS is proved theoretically, and the testing results also show that the PG-CTS method has better performance over the other three strategies, greedy, first-in-first-out (FIFO) and random in different environments.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"27 19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115200432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148697

Yuting Wu, Yanxiang Jiang, M. Bennis, F. Zheng, Xiqi Gao, X. You

{"title":"Content Popularity Prediction in Fog Radio Access Networks: A Federated Learning Based Approach","authors":"Yuting Wu, Yanxiang Jiang, M. Bennis, F. Zheng, Xiqi Gao, X. You","doi":"10.1109/ICC40277.2020.9148697","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148697","url":null,"abstract":"In this paper, the content popularity prediction problem in fog radio access networks (F-RANs) is investigated. In order to obtain accurate prediction with low complexity, we propose a novel context-aware popularity prediction policy based on federated learning. Firstly, user preference learning is applied by considering that users prefer to request the contents they are interested in. Then, users’ context information is utilized to cluster users efficiently by adaptive context space partitioning. After that, we formulate a popularity prediction optimization problem to learn the local model parameters using the stochastic variance reduced gradient (SVRG) algorithm. Finally, federated learning based model integration is proposed to construct the global popularity prediction model based on local models by combining the distributed approximate Newton (DANE) algorithm with SVRG. Our proposed popularity prediction policy not only predicts content popularity accurately, but also significantly reduces computational complexity. Simulation results show that our proposed policy increases the cache hit rate by up to 21.5 % compared to the traditional policies.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115202866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Secure Resource Allocation for Polarization-Based Non-Linear Energy Harvesting Over 5G Cooperative Cognitive Radio Networks 5G协同认知无线网络基于极化非线性能量采集的安全资源分配

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148702

Fei Wang, Xi Zhang

引用次数: 4

An Online Verifiable Rating System Based on Unverified Rating Output (URTO) 基于未验证评级输出(URTO)的在线可验证评级系统

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148867

Changxin Yang, Erwu Liu, Rui Wang

引用次数: 0

Accurate Energy-Efficient Localization Algorithm for IoT Sensors 物联网传感器精确节能定位算法

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) Pub Date : 2020-06-01 DOI: 10.1109/ICC40277.2020.9148860

Mahshid Mehrabi, Pooria Taghdiri, Vincent Latzko, H. Salah, F. Fitzek

{"title":"Accurate Energy-Efficient Localization Algorithm for IoT Sensors","authors":"Mahshid Mehrabi, Pooria Taghdiri, Vincent Latzko, H. Salah, F. Fitzek","doi":"10.1109/ICC40277.2020.9148860","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148860","url":null,"abstract":"Wireless Sensor Networks (WSNs) applications have attracted attention in Internet of Things (IoT) as a novel networking paradigm consisting of billions of small sensor nodes. These sensors collect environmental information and communicate with each other to provide solutions for real time IoT applications’ requirements. Since the majority of applications require location-based services, it is necessary to improve the accuracy of localization algorithms. DV-Hop is one of the most attractive range-free localization algorithms in wireless sensor networks and several works have been undertaken to improve its accuracy, however, since sensor nodes have limited power resources, the energy consumption of nodes should be also considered. In this paper, we propose a method based on DV-Hop to improve both accuracy and power consumption. Each unknown node calculates the Hopsize of each anchor node according to the limited information it has from the network topology; therefore there is no need to broadcast the Hopsize from anchor nodes, and in this way energy can be saved. In the next step, we use Shuffled Frog Leaping Algorithm (SFLA) as an evolutionary algorithm to improve the accuracy of estimated Hopsizes and a hybrid Genetic-PSO algorithm is applied to the third step of DV-Hop to achieve more accurate values for unknown nodes’ positions. Simulation results show that our proposed method decreases the localization error significantly by jointly considering the energy consumption of sensors and is overall 44% more accurate than DV-Hop.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115464455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0