Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149367
Na Deng, M. Haenggi
In the analysis of large-scale wirelessly powered networks, the energy correlation is often ignored for analytical tractability. Accounting for the energy correlation, this paper introduces and promotes the Poisson disk process (PDP) as a model for the active RF-powered nodes that succeed in harvesting energy. To show that the model leads to tractable results in several cases of interest, we derive the density and second moment density of the PDP and find the key property that the PDP can be fully characterized by its first- and second-order statistics. Tight bounds for its probability generating functional (PGFL) are also provided. To show that the model is relevant for wirelessly powered networks that exhibit positive energy correlation, we fit the PDP to a given energized point process incorporating practical energy harvesting factors and derive the information transmission success probability. It turns out that the resulting PDP can closely model the distribution of actual energized RFpowered nodes in terms of the success probability and other statistics while preserving analytical tractability.
{"title":"Success Probability in Wirelessly Powered Networks with Energy Correlation","authors":"Na Deng, M. Haenggi","doi":"10.1109/ICC40277.2020.9149367","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149367","url":null,"abstract":"In the analysis of large-scale wirelessly powered networks, the energy correlation is often ignored for analytical tractability. Accounting for the energy correlation, this paper introduces and promotes the Poisson disk process (PDP) as a model for the active RF-powered nodes that succeed in harvesting energy. To show that the model leads to tractable results in several cases of interest, we derive the density and second moment density of the PDP and find the key property that the PDP can be fully characterized by its first- and second-order statistics. Tight bounds for its probability generating functional (PGFL) are also provided. To show that the model is relevant for wirelessly powered networks that exhibit positive energy correlation, we fit the PDP to a given energized point process incorporating practical energy harvesting factors and derive the information transmission success probability. It turns out that the resulting PDP can closely model the distribution of actual energized RFpowered nodes in terms of the success probability and other statistics while preserving analytical tractability.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"1 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":"125822392","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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149149
Ruiyang Duan, Jun Du, Junming Ren, Chunxiao Jiang, Yong Ren, A. Benslimane
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148673
Lei Zhou, Anmin Fu, Jingyu Feng, Chunyi Zhou
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.
云计算为电子病历(Electronic medical Record, EMR)提供了管理和共享海量医疗数据的有效途径，因此建立基于云的电子病历越来越受到重视。在基于云的电子病历中，数据完整性和隐私问题应该得到强调，因为用户不希望他们的医疗记录被损坏或泄露给他人。为了解决本文所关注的问题，我们提出了一种高效安全的基于云的EMR (DIAT)数据完整性审计方案，该方案具有可追溯性，可提供数据完整性和隐私性。我们存储多个副本，以便数据可以从损坏中快速恢复，只要一个副本保持完整;同时，数据以密文形式存储，不会泄露给未经授权的实体。为了支持数据动态，我们设计了一个二维数据结构，称为动态映射哈希表(DMHT)。它不需要大量的辅助验证信息，也不会影响其他块的序列号。此外，数据可追溯性是通过将数据块的所有版本组织成一个链来实现的，这样医生就可以在他们的记录中跟踪患者病情的变化。此外，正式的安全性分析和实验结果证实了DIAT的安全性和有效性。
{"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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148886
Hong Qi, Difan Zou, Chen Gong, Zhengyuan Xu
Consider directional antenna array in an ultraviolet (UV) scattering communication Ad-Hoc network. To efficiently obtain the link gain coverage of single antenna, we propose an algorithm based on one-dimensional (1D) numerical integration and an off-line data library. We also analyze the two-dimensional (2D) scattering intensity distribution, where numerical results show that the path loss profile can be well fitted by elliptic models. In addition, assume that the node distribution in Ad-Hoc network obeys Poisson point process (PPP). For both directional antenna array and omnidirectional antenna, adopting ellipses and circles to represent the coverage of nodes, we investigate the minimum power such that the network still keeps connected. Simulation results show that employing directional antenna array can effectively reduce the minimum power that guarantees coverage.
{"title":"Two-dimensional Intensity Distribution and Connectivity in Ultraviolet Ad-Hoc Network","authors":"Hong Qi, Difan Zou, Chen Gong, Zhengyuan Xu","doi":"10.1109/ICC40277.2020.9148886","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148886","url":null,"abstract":"Consider directional antenna array in an ultraviolet (UV) scattering communication Ad-Hoc network. To efficiently obtain the link gain coverage of single antenna, we propose an algorithm based on one-dimensional (1D) numerical integration and an off-line data library. We also analyze the two-dimensional (2D) scattering intensity distribution, where numerical results show that the path loss profile can be well fitted by elliptic models. In addition, assume that the node distribution in Ad-Hoc network obeys Poisson point process (PPP). For both directional antenna array and omnidirectional antenna, adopting ellipses and circles to represent the coverage of nodes, we investigate the minimum power such that the network still keeps connected. Simulation results show that employing directional antenna array can effectively reduce the minimum power that guarantees coverage.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"119 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":"123332406","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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149155
Shuo Liu, Qiaoling Wang
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148888
Yang Gao, Wenjun Wu, Haixiang Nan, Yang Sun, Pengbo Si
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148697
Yuting Wu, Yanxiang Jiang, M. Bennis, F. Zheng, Xiqi Gao, X. You
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.
{"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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148702
Fei Wang, Xi Zhang
We address secure resource allocation for the energy harvesting (EH) based 5G cooperative cognitive radio networks (CRNs). To guarantee that the size-limited secondary users (SUs) can simultaneously send the primary user’s and their own information, we assume that SUs are equipped with orthogonally dual-polarized antennas (ODPAs). In particular, we propose, develop, and analyze an efficient resource allocation scheme under a practical non-linear EH model, which can capture the nonlinear characteristics of the end-to-end wireless power transfer (WPT) for radio frequency (RF) based EH circuits. Our obtained numerical results validate that a substantial performance gain can be obtained by employing the non-linear EH model.
{"title":"Secure Resource Allocation for Polarization-Based Non-Linear Energy Harvesting Over 5G Cooperative Cognitive Radio Networks","authors":"Fei Wang, Xi Zhang","doi":"10.1109/ICC40277.2020.9148702","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148702","url":null,"abstract":"We address secure resource allocation for the energy harvesting (EH) based 5G cooperative cognitive radio networks (CRNs). To guarantee that the size-limited secondary users (SUs) can simultaneously send the primary user’s and their own information, we assume that SUs are equipped with orthogonally dual-polarized antennas (ODPAs). In particular, we propose, develop, and analyze an efficient resource allocation scheme under a practical non-linear EH model, which can capture the nonlinear characteristics of the end-to-end wireless power transfer (WPT) for radio frequency (RF) based EH circuits. Our obtained numerical results validate that a substantial performance gain can be obtained by employing the non-linear EH model.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"27 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":"115205862","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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148867
Changxin Yang, Erwu Liu, Rui Wang
Ratings online are often listed alongside product recommendations, but to date, limited attention has been paid as to how credible these ratings present to end-users. For lack of an effective rating verification scheme, a cheater could fabricate some high ratings and the recommended product usually does not match the corresponding ratings. To make ratings verifiable, we encapsulate each rating into a specific structure whose core is unverified rating output (URTO) that we propose. The URTO is designed based on unspent transaction output (UTXO) in Bitcoin. On this foundation, we propose the online verifiable rating system. Our system can make ratings verifiable and the evaluated validation and mining time of a rating by the whole network peers demonstrate the high reliability of our system.
{"title":"An Online Verifiable Rating System Based on Unverified Rating Output (URTO)","authors":"Changxin Yang, Erwu Liu, Rui Wang","doi":"10.1109/ICC40277.2020.9148867","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148867","url":null,"abstract":"Ratings online are often listed alongside product recommendations, but to date, limited attention has been paid as to how credible these ratings present to end-users. For lack of an effective rating verification scheme, a cheater could fabricate some high ratings and the recommended product usually does not match the corresponding ratings. To make ratings verifiable, we encapsulate each rating into a specific structure whose core is unverified rating output (URTO) that we propose. The URTO is designed based on unspent transaction output (UTXO) in Bitcoin. On this foundation, we propose the online verifiable rating system. Our system can make ratings verifiable and the evaluated validation and mining time of a rating by the whole network peers demonstrate the high reliability of our system.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"38 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":"115358373","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}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148860
Mahshid Mehrabi, Pooria Taghdiri, Vincent Latzko, H. Salah, F. Fitzek
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.
{"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}
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