A VPC (Virtual Private Cloud) in a public cloud often allocates private IP addresses which are not globally routable, to virtual resources, e.g., ECSs (Elastic Cloud Server), ELBs (Elastic Load Balancer) and so on. An EIP (Elastic IP) is a static IP that can be mapped to a private IP address of virtual resource deployed in VPC to make it reachable from outside of a public cloud, e.g., from a client in the Internet. As a public cloud usually holds millions of EIPs which can be dynamically allocated to virtual entities inside of VPCs, legacy firewall or router-based NAT (Network Address Translation) solutions cannot fulfil the requirements of public cloud in dynamicity, flexibility, scalability, and some other aspects. In this paper we propose a hierarchically clustered EIP implementation system for public cloud. The system implements the translation from private IP to EIP in two stages, and stage 1 performs the translation from a private IP to a floating IP which is in a locally routable IP space while stage 2 performs the translation from a floating IP to an EIP which is allocated from IANA (Internet Assigned Numbers Authority) directly or from an Internet service provider and can be accessed from the Internet. This hierarchically clustered implementation system brings many benefits such as good scalability to support millions of EIPs, more flexibility to apply access control to the traffic between different VPCs, support of dynamically allocating an EIP to different virtual entities when needed.
{"title":"Implementation of Elastic IP for Public Cloud","authors":"Zhangfeng Hu, Siqing Sun, Chuanji Gao, Yanjun Li, Qiuzheng Ren, Baozhu Li, Xiong Li","doi":"10.1145/3507971.3507996","DOIUrl":"https://doi.org/10.1145/3507971.3507996","url":null,"abstract":"A VPC (Virtual Private Cloud) in a public cloud often allocates private IP addresses which are not globally routable, to virtual resources, e.g., ECSs (Elastic Cloud Server), ELBs (Elastic Load Balancer) and so on. An EIP (Elastic IP) is a static IP that can be mapped to a private IP address of virtual resource deployed in VPC to make it reachable from outside of a public cloud, e.g., from a client in the Internet. As a public cloud usually holds millions of EIPs which can be dynamically allocated to virtual entities inside of VPCs, legacy firewall or router-based NAT (Network Address Translation) solutions cannot fulfil the requirements of public cloud in dynamicity, flexibility, scalability, and some other aspects. In this paper we propose a hierarchically clustered EIP implementation system for public cloud. The system implements the translation from private IP to EIP in two stages, and stage 1 performs the translation from a private IP to a floating IP which is in a locally routable IP space while stage 2 performs the translation from a floating IP to an EIP which is allocated from IANA (Internet Assigned Numbers Authority) directly or from an Internet service provider and can be accessed from the Internet. This hierarchically clustered implementation system brings many benefits such as good scalability to support millions of EIPs, more flexibility to apply access control to the traffic between different VPCs, support of dynamically allocating an EIP to different virtual entities when needed.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123875542","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}
Shard-Based blockchain technology is currently one of the effective ways to improve the throughput of permissionless blockchain. By distributing transactions into multiple shards, the validators in each shard verify transactions and reach in consensus in parallel, thereby increasing system throughput and scalability. However, most of the existing Shard-Based Blockchain schemes lack an incentive scheme that can promote mutual cooperation among the nodes in the shard and participate in consensus as much as possible, which leads some selfish nodes to adopt strategies that are not conducive to the maintenance of the blockchain system in order to obtain higher profits, thereby endangering the stability and security of the entire blockchain system. In this paper, we introduce the concept of node reputation to evaluate node behavior, and establish the correlation between reputation and profit. In that case, nodes with higher reputation can get more rewards, thereby achieving the fairness of reward distribution. In addition, we use the N-player static game model in game theory to analyze the changes in utility corresponding to different strategies for node, and design a dynamic transaction distribution scheme through genetic algorithm(GA) to ensure that the majority of nodes participate in consensus and shard liveness. Our research results show that our solution can better improve incentive fairness and liveness compared to the general transaction uniform distribution scheme.
{"title":"Intra-Shard and Inter-Shard Collaborative Incentive Scheme for Shard-Based Permissionless Blockchain","authors":"Heng Quan, Tianyu Kang, Li Guo","doi":"10.1145/3507971.3507995","DOIUrl":"https://doi.org/10.1145/3507971.3507995","url":null,"abstract":"Shard-Based blockchain technology is currently one of the effective ways to improve the throughput of permissionless blockchain. By distributing transactions into multiple shards, the validators in each shard verify transactions and reach in consensus in parallel, thereby increasing system throughput and scalability. However, most of the existing Shard-Based Blockchain schemes lack an incentive scheme that can promote mutual cooperation among the nodes in the shard and participate in consensus as much as possible, which leads some selfish nodes to adopt strategies that are not conducive to the maintenance of the blockchain system in order to obtain higher profits, thereby endangering the stability and security of the entire blockchain system. In this paper, we introduce the concept of node reputation to evaluate node behavior, and establish the correlation between reputation and profit. In that case, nodes with higher reputation can get more rewards, thereby achieving the fairness of reward distribution. In addition, we use the N-player static game model in game theory to analyze the changes in utility corresponding to different strategies for node, and design a dynamic transaction distribution scheme through genetic algorithm(GA) to ensure that the majority of nodes participate in consensus and shard liveness. Our research results show that our solution can better improve incentive fairness and liveness compared to the general transaction uniform distribution scheme.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123999964","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}
Xiumei Chen, Xiangtao Zheng, Kaijian Zhu, Xiaoqiang Lu
Fully unsupervised person re-identification aims to train a discriminative model with unlabeled person images. Most existing methods first generate pseudo labels by clustering image features (convolutional features) and then fine-tune the convolutional neural network (CNN) with pseudo labels. However, these methods are greatly limited by the quality of the pseudo labels. In this paper, a cluster sample enhancement method is introduced to increase the reliability of pseudo-label samples to facilitate the CNN training. Specifically, when generating pseudo labels, only the samples with high-confidence pseudo-label predictions are selected. In addition, to enhance the selected samples for training, two different image transformations are adopted and coupled with specific-design loss functions to boost the model performance. Experiments demonstrate the effectiveness of the proposed method. Concretely, the proposed method achieves 87.1% rank-1 and 70.2% mAP accuracy on Market-1501.
{"title":"Fully Unsupervised Person Re-Identification by Enhancing Cluster Samples","authors":"Xiumei Chen, Xiangtao Zheng, Kaijian Zhu, Xiaoqiang Lu","doi":"10.1145/3507971.3507984","DOIUrl":"https://doi.org/10.1145/3507971.3507984","url":null,"abstract":"Fully unsupervised person re-identification aims to train a discriminative model with unlabeled person images. Most existing methods first generate pseudo labels by clustering image features (convolutional features) and then fine-tune the convolutional neural network (CNN) with pseudo labels. However, these methods are greatly limited by the quality of the pseudo labels. In this paper, a cluster sample enhancement method is introduced to increase the reliability of pseudo-label samples to facilitate the CNN training. Specifically, when generating pseudo labels, only the samples with high-confidence pseudo-label predictions are selected. In addition, to enhance the selected samples for training, two different image transformations are adopted and coupled with specific-design loss functions to boost the model performance. Experiments demonstrate the effectiveness of the proposed method. Concretely, the proposed method achieves 87.1% rank-1 and 70.2% mAP accuracy on Market-1501.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123043025","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}
Conglin Pan, Si Chen, Huijie Zhu, Wei Wu, Jiachuan Qian, Lijun Wang
Aiming at the blind identification of space-time block codes (STBC) in multiple input multiple output (MIMO) system, this paper proposes a new convolutional neural network (CNN-N) to realize the blind identification. Compared to traditional algorithms using statistical features of received signal, CNN-N can reduce the computation with a higher correct identification rate. Consist of multiple layers with special functions, CNN-N has good generalization ability in complex MIMO channels. The network in this paper can recognize 6 STBC codes include spatial multiplexing signal (SM) and some OSTBC codes. The simulation result shows that this new convolutional neural network can finish STBC identification with a high correct rate even in low SNR by consuming moderate amounts of time.
{"title":"Blind identification of MIMO Space-Time Block Codes Based on Convolutional Neural Network","authors":"Conglin Pan, Si Chen, Huijie Zhu, Wei Wu, Jiachuan Qian, Lijun Wang","doi":"10.1145/3507971.3508009","DOIUrl":"https://doi.org/10.1145/3507971.3508009","url":null,"abstract":"Aiming at the blind identification of space-time block codes (STBC) in multiple input multiple output (MIMO) system, this paper proposes a new convolutional neural network (CNN-N) to realize the blind identification. Compared to traditional algorithms using statistical features of received signal, CNN-N can reduce the computation with a higher correct identification rate. Consist of multiple layers with special functions, CNN-N has good generalization ability in complex MIMO channels. The network in this paper can recognize 6 STBC codes include spatial multiplexing signal (SM) and some OSTBC codes. The simulation result shows that this new convolutional neural network can finish STBC identification with a high correct rate even in low SNR by consuming moderate amounts of time.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124041768","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}
In complex networks, the community division of nodes is often based on the topology of the network. In contrast, in real networks, the attributes of nodes themselves also affect the relationships between and within communities. Due to the multi-attribute diversity of social network platforms, it is not accurate to divide network users only from network topology. Therefore, a community division algorithm is proposed based on tag propagation algorithm combining node topology and attribute characteristics. And randomness of label propagation algorithm and instability, so the degree of similarity between nodes will combine influence and to optimize the spread of the label the initial stage, reduce the randomness, and combining the network users interested in tag attributes and the user activity to improve the communication process, makes the division of the community structure of the community more and more obvious attribute. To prove the effectiveness of the proposed method, we compare single attribute, multi-attribute, and the strength of community structure on the real microblog user datasets.
{"title":"Community Partitioning Combining Topological Structure and Multi-attribute Characteristics","authors":"Ye Lv, Guanghui Yan, Yishu Wang, Zhe Li","doi":"10.1145/3507971.3507979","DOIUrl":"https://doi.org/10.1145/3507971.3507979","url":null,"abstract":"In complex networks, the community division of nodes is often based on the topology of the network. In contrast, in real networks, the attributes of nodes themselves also affect the relationships between and within communities. Due to the multi-attribute diversity of social network platforms, it is not accurate to divide network users only from network topology. Therefore, a community division algorithm is proposed based on tag propagation algorithm combining node topology and attribute characteristics. And randomness of label propagation algorithm and instability, so the degree of similarity between nodes will combine influence and to optimize the spread of the label the initial stage, reduce the randomness, and combining the network users interested in tag attributes and the user activity to improve the communication process, makes the division of the community structure of the community more and more obvious attribute. To prove the effectiveness of the proposed method, we compare single attribute, multi-attribute, and the strength of community structure on the real microblog user datasets.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128580908","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}
Teaching style refers to the teaching performance of the teacher's personal characteristics, teaching skills and teaching methods formed in the long-term teaching process. It plays an important role in helping students achieve academic success. With the continuous reform of the teaching system, more and more courses are taught in the form of videos. In this paper, we established a teaching style evaluation system and classification model based on teachers’ teaching behavior based on facial expressions, voices and postures in the teaching process. We adopted principal component analysis and autoencoder feature selection methods, and designed based on The multi-modal step-by-step fusion algorithm of deep neural network classifies teaching styles.
{"title":"Evaluation Method of Teaching Styles Based on Multi-modal Fusion","authors":"Wenyan Tang, Chongwen Wang, Yi Zhang","doi":"10.1145/3507971.3507974","DOIUrl":"https://doi.org/10.1145/3507971.3507974","url":null,"abstract":"Teaching style refers to the teaching performance of the teacher's personal characteristics, teaching skills and teaching methods formed in the long-term teaching process. It plays an important role in helping students achieve academic success. With the continuous reform of the teaching system, more and more courses are taught in the form of videos. In this paper, we established a teaching style evaluation system and classification model based on teachers’ teaching behavior based on facial expressions, voices and postures in the teaching process. We adopted principal component analysis and autoencoder feature selection methods, and designed based on The multi-modal step-by-step fusion algorithm of deep neural network classifies teaching styles.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128194490","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}
Jonilyn Tejada Dabalos, Christine Mae Asibal Edullantes, Mark Van Merca Buladaco, Girley Santiago Gumanao
Accurate species identification is essential in preserving biodiversity. Understanding how each species can be uniquely identified determines how we can shape essential conservation efforts. One of the challenging species to identify is the Giant Clams. Due to its uniquely colored mantles and sometimes similarities in other attributes like sizes, it is challenging to distinguish each Taklobo species. A field expert is sometimes needed to identify each species correctly. The study aims to assess the possibility of automating the identification of the Giant Clams species (Taklobo) by using machine learning techniques. Different image features extraction techniques such as Scale-Invariant Feature Transform (SIFT) and Oriented FAST and Rotated Brief (ORB) were used to extract image descriptors, and color representations were used during experiments. Experimental results show that the Artificial Neural Network (ANN) with the RGB, YCbCr, HSV, CiELab color representation gained the highest accuracy rate of 89.69%.
{"title":"Identifying Giant Clams Species using Machine Learning Techniques","authors":"Jonilyn Tejada Dabalos, Christine Mae Asibal Edullantes, Mark Van Merca Buladaco, Girley Santiago Gumanao","doi":"10.1145/3507971.3508013","DOIUrl":"https://doi.org/10.1145/3507971.3508013","url":null,"abstract":"Accurate species identification is essential in preserving biodiversity. Understanding how each species can be uniquely identified determines how we can shape essential conservation efforts. One of the challenging species to identify is the Giant Clams. Due to its uniquely colored mantles and sometimes similarities in other attributes like sizes, it is challenging to distinguish each Taklobo species. A field expert is sometimes needed to identify each species correctly. The study aims to assess the possibility of automating the identification of the Giant Clams species (Taklobo) by using machine learning techniques. Different image features extraction techniques such as Scale-Invariant Feature Transform (SIFT) and Oriented FAST and Rotated Brief (ORB) were used to extract image descriptors, and color representations were used during experiments. Experimental results show that the Artificial Neural Network (ANN) with the RGB, YCbCr, HSV, CiELab color representation gained the highest accuracy rate of 89.69%.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114458444","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}
∗Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.
*最近的研究发现，女性和男性之间有头痛的可能性，女性头痛通常高于男性。此外，头痛会降低人们工作的效率。因此，头痛是我们所说的现代疾病。本研究的目的是利用基于案例推理(Case Based Reasoning, CBR)的方法，建立智能头痛诊断模型，以诊断头痛类型的概率，并为头痛患者推荐医生治疗方案。所提出的智能诊断模型准确率在70%以上，对减少诊断错误、提高医疗质量有很大帮助。
{"title":"Constructing the Intelligence Headache Diagnosis Model by CBR","authors":"Kuan-Wei Huang, Chien-Hua Wang","doi":"10.1145/3507971.3507978","DOIUrl":"https://doi.org/10.1145/3507971.3507978","url":null,"abstract":"∗Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133093792","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}
Simultaneous wireless information and power transfer (SWIPT) can provide power and information synchronously, which assists to solve the problem of the limited battery capacity and inconvenient charging of Internet of Things (IoT) devices. In this paper, we investigate a SWIPT system assisted by UAV in jamming environment, where the UAV can transfer power to nodes and nodes can collect energy from the UAV. In order to maximize the minimum throughput among all IoTDs, we jointly optimize the transmit power of IoTDs and the trajectory of UAV during a fix period, while ensuring the lowest energy requirement of each node and avoiding jamming. However, the problem we proposed is NP-hard and difficult to be settled efficiently by existing methods. To address the intractable problem, we develop an iterative algorithm based on the successive convex approximation (SCA) approach. Simulation results indicate that our joint optimization can improve the minimum throughput greatly.
{"title":"UAV-Assisted SWIPT in Jamming Environment: Joint Power and Trajectory Optimization","authors":"Fei Song, Qiming Sun, Xiaojing Chu, Xiao Zhang","doi":"10.1145/3507971.3508015","DOIUrl":"https://doi.org/10.1145/3507971.3508015","url":null,"abstract":"Simultaneous wireless information and power transfer (SWIPT) can provide power and information synchronously, which assists to solve the problem of the limited battery capacity and inconvenient charging of Internet of Things (IoT) devices. In this paper, we investigate a SWIPT system assisted by UAV in jamming environment, where the UAV can transfer power to nodes and nodes can collect energy from the UAV. In order to maximize the minimum throughput among all IoTDs, we jointly optimize the transmit power of IoTDs and the trajectory of UAV during a fix period, while ensuring the lowest energy requirement of each node and avoiding jamming. However, the problem we proposed is NP-hard and difficult to be settled efficiently by existing methods. To address the intractable problem, we develop an iterative algorithm based on the successive convex approximation (SCA) approach. Simulation results indicate that our joint optimization can improve the minimum throughput greatly.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133981514","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}
Distributed oracle protocol is proposed to support on-chain transaction execution which depends on off-chain information without a trusted party as source. Although the commit-reveal mechanism based on commitment scheme used in distributed oracle protocol solve the problem of freeloading, it introduces a new one of availability, which is significant when information requester would like to obtain protocol output before expiration. To address the issue, we describe an architecture of distributed oracle protocol in time-sensitive scenario. Then we propose a new protocol which satisfies all requirements defined in the architecture by applying timed commitment scheme. Finally, a prototype program is implemented to evaluate additional cost caused by the core algorithm in new protocol, which shows that the cost is acceptable.
{"title":"Blockchain based Distributed Oracle in Time Sensitive Scenario","authors":"Langchen He, Tianyu Kang, Li Guo","doi":"10.1145/3507971.3507990","DOIUrl":"https://doi.org/10.1145/3507971.3507990","url":null,"abstract":"Distributed oracle protocol is proposed to support on-chain transaction execution which depends on off-chain information without a trusted party as source. Although the commit-reveal mechanism based on commitment scheme used in distributed oracle protocol solve the problem of freeloading, it introduces a new one of availability, which is significant when information requester would like to obtain protocol output before expiration. To address the issue, we describe an architecture of distributed oracle protocol in time-sensitive scenario. Then we propose a new protocol which satisfies all requirements defined in the architecture by applying timed commitment scheme. Finally, a prototype program is implemented to evaluate additional cost caused by the core algorithm in new protocol, which shows that the cost is acceptable.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114778020","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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