Jing Chen, Wenjun Jiang, Jie Wu, Kenli Li, Keqin Li
The Point Of Interest (POI) sequence recommendation is the key task in itinerary and travel route planning. Existing works usually consider the temporal and spatial factors in travel planning. However, the external environment, such as the weather, is usually overlooked. In fact, the weather is an important factor because it can affect a user’s check-in behaviors. Furthermore, most of the existing research is based on a static environment for POI sequence recommendation. While the external environment (e.g., the weather) may change during travel, it is difficult for existing works to adjust the POI sequence in time. What’s more, people usually prefer the attractive routes when traveling. To address these issues, we first conduct comprehensive data analysis on two real-world check-in datasets to study the effects of weather and time, as well as the features of the POI sequence. Based on this, we propose a model of Dynamic Personalized POI Sequence Recommendation with fine-grained contexts (DPSR for short). It extracts user interest and POI popularity with fine-grained contexts and captures the attractiveness of the POI sequence. Next, we apply the Monte Carlo Tree Search model (MCTS for short) to simulate the process of recommending POI sequence in the dynamic environment, i.e., the weather and time change after visiting a POI. What’s more, we consider different speeds to reflect the fact that people may take different transportation to transfer between POIs. To validate the efficacy of DPSR, we conduct extensive experiments. The results show that our model can improve the accuracy of the recommendation significantly. Furthermore, it can better meet user preferences and enhance experiences.
{"title":"Dynamic Personalized POI Sequence Recommendation with Fine-Grained Contexts","authors":"Jing Chen, Wenjun Jiang, Jie Wu, Kenli Li, Keqin Li","doi":"10.1145/3583687","DOIUrl":"https://doi.org/10.1145/3583687","url":null,"abstract":"The Point Of Interest (POI) sequence recommendation is the key task in itinerary and travel route planning. Existing works usually consider the temporal and spatial factors in travel planning. However, the external environment, such as the weather, is usually overlooked. In fact, the weather is an important factor because it can affect a user’s check-in behaviors. Furthermore, most of the existing research is based on a static environment for POI sequence recommendation. While the external environment (e.g., the weather) may change during travel, it is difficult for existing works to adjust the POI sequence in time. What’s more, people usually prefer the attractive routes when traveling. To address these issues, we first conduct comprehensive data analysis on two real-world check-in datasets to study the effects of weather and time, as well as the features of the POI sequence. Based on this, we propose a model of Dynamic Personalized POI Sequence Recommendation with fine-grained contexts (DPSR for short). It extracts user interest and POI popularity with fine-grained contexts and captures the attractiveness of the POI sequence. Next, we apply the Monte Carlo Tree Search model (MCTS for short) to simulate the process of recommending POI sequence in the dynamic environment, i.e., the weather and time change after visiting a POI. What’s more, we consider different speeds to reflect the fact that people may take different transportation to transfer between POIs. To validate the efficacy of DPSR, we conduct extensive experiments. The results show that our model can improve the accuracy of the recommendation significantly. Furthermore, it can better meet user preferences and enhance experiences.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":" ","pages":"1 - 28"},"PeriodicalIF":5.3,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47225148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yibin Xu, Jia-Jung Shao, Tijs Slaats, Boris Düdder
Blockchain sharding splits a blockchain into several shards where consensus is reached at the shard level rather than over the entire blockchain. It improves transaction throughput and reduces the computational resources required of individual nodes. But a derivation of trustworthy consensus within a shard becomes an issue as the longest chain based mechanisms used in conventional blockchains can no longer be used. Instead, a vote-based consensus mechanism must be employed. However, existing vote-based Byzantine fault tolerance consensus protocols do not offer sufficient security guarantees for sharded blockchains. First, when used to support consensus where only one block is allowed at a time (binary consensus), these protocols are susceptible to progress-hindering attacks (i.e., unable to reach a consensus). Second, when used to support a stronger type of consensus where multiple concurrent blocks are allowed (strong consensus), their tolerance of adversary nodes is low. This article proposes a new consensus protocol to address all these issues. We call the new protocol MWPoW+, as its basic framework is based on the existing Multiple Winners Proof of Work (MWPoW) protocol but includes new mechanisms to address the issues mentioned previously. MWPoW+ is a vote-based protocol for strong consensus, asynchronous in consensus derivation but synchronous in communication. We prove that it can tolerate up to f < n/2 adversary nodes in a n-node system as if using a binary consensus protocol and does not suffer from progress-hindering attacks.
{"title":"MWPoW+: A Strong Consensus Protocol for Intra-Shard Consensus in Blockchain Sharding","authors":"Yibin Xu, Jia-Jung Shao, Tijs Slaats, Boris Düdder","doi":"10.1145/3584020","DOIUrl":"https://doi.org/10.1145/3584020","url":null,"abstract":"Blockchain sharding splits a blockchain into several shards where consensus is reached at the shard level rather than over the entire blockchain. It improves transaction throughput and reduces the computational resources required of individual nodes. But a derivation of trustworthy consensus within a shard becomes an issue as the longest chain based mechanisms used in conventional blockchains can no longer be used. Instead, a vote-based consensus mechanism must be employed. However, existing vote-based Byzantine fault tolerance consensus protocols do not offer sufficient security guarantees for sharded blockchains. First, when used to support consensus where only one block is allowed at a time (binary consensus), these protocols are susceptible to progress-hindering attacks (i.e., unable to reach a consensus). Second, when used to support a stronger type of consensus where multiple concurrent blocks are allowed (strong consensus), their tolerance of adversary nodes is low. This article proposes a new consensus protocol to address all these issues. We call the new protocol MWPoW+, as its basic framework is based on the existing Multiple Winners Proof of Work (MWPoW) protocol but includes new mechanisms to address the issues mentioned previously. MWPoW+ is a vote-based protocol for strong consensus, asynchronous in consensus derivation but synchronous in communication. We prove that it can tolerate up to f < n/2 adversary nodes in a n-node system as if using a binary consensus protocol and does not suffer from progress-hindering attacks.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"23 1","pages":"1 - 27"},"PeriodicalIF":5.3,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45019870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The popularity of intelligent devices provides straightforward access to the Internet and online social networks. However, the quick and easy data updates from networks also benefit the risk spreading, such as rumor, malware, or computer viruses. To this end, this article studies the problem of source detection, which is to infer the source node out of an aftermath of a cascade, that is, the observed infected graph GN of the network at some time. Prior arts have adopted various statistical quantities such as degree, distance, or infection size to reflect the structural centrality of the source. In this article, we propose a new metric that we call the infected tree entropy (ITE), to utilize richer underlying structural features for source detection. Our idea of ITE is inspired by the conception of structural entropy [21], which demonstrated that the minimization of average bits to encode the network structures with different partitions is the principle for detecting the natural or true structures in real-world networks. Accordingly, our proposed ITE based estimator for the source tries to minimize the coding of network partitions brought by the infected tree rooted at all the potential sources, thus minimizing the structural deviation between the cascades from the potential sources and the actual infection process included in GN. On polynomially growing geometric trees, with increasing tree heterogeneity, the ITE estimator remarkably yields more reliable detection under only moderate infection sizes, and returns an asymptotically complete detection. In contrast, for regular expanding trees, we still observe guaranteed detection probability of ITE estimator even with an infinite infection size, thanks to the degree regularity property. We also algorithmically realize the ITE based detection that enjoys linear time complexity via a message-passing scheme, and further extend it to general graphs. Extensive experiments on synthetic and real datasets confirm the superiority of ITE to the baselines. For example, ITE returns an accuracy of 85%, ranking the source among the top 10%, far exceeding 55% of the classic algorithm on scale-free networks.
{"title":"Finding the Source in Networks: An Approach Based on Structural Entropy","authors":"Chong Zhang, Qiang Guo, Luoyi Fu, Jiaxin Ding, Xinde Cao, Fei Long, Xinbing Wang, Cheng Zhou","doi":"10.1145/3568309","DOIUrl":"https://doi.org/10.1145/3568309","url":null,"abstract":"The popularity of intelligent devices provides straightforward access to the Internet and online social networks. However, the quick and easy data updates from networks also benefit the risk spreading, such as rumor, malware, or computer viruses. To this end, this article studies the problem of source detection, which is to infer the source node out of an aftermath of a cascade, that is, the observed infected graph GN of the network at some time. Prior arts have adopted various statistical quantities such as degree, distance, or infection size to reflect the structural centrality of the source. In this article, we propose a new metric that we call the infected tree entropy (ITE), to utilize richer underlying structural features for source detection. Our idea of ITE is inspired by the conception of structural entropy [21], which demonstrated that the minimization of average bits to encode the network structures with different partitions is the principle for detecting the natural or true structures in real-world networks. Accordingly, our proposed ITE based estimator for the source tries to minimize the coding of network partitions brought by the infected tree rooted at all the potential sources, thus minimizing the structural deviation between the cascades from the potential sources and the actual infection process included in GN. On polynomially growing geometric trees, with increasing tree heterogeneity, the ITE estimator remarkably yields more reliable detection under only moderate infection sizes, and returns an asymptotically complete detection. In contrast, for regular expanding trees, we still observe guaranteed detection probability of ITE estimator even with an infinite infection size, thanks to the degree regularity property. We also algorithmically realize the ITE based detection that enjoys linear time complexity via a message-passing scheme, and further extend it to general graphs. Extensive experiments on synthetic and real datasets confirm the superiority of ITE to the baselines. For example, ITE returns an accuracy of 85%, ranking the source among the top 10%, far exceeding 55% of the classic algorithm on scale-free networks.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"23 1","pages":"1 - 25"},"PeriodicalIF":5.3,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42896656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing popularity of social networks, many businesses have started implementing their branding or targeted advertising strategies to reach potential customers through social media platforms. It is desirable and essential to help businesses to reach mass audiences and assist users to find favorite business accounts on social media platforms. In the movie industry, movie companies often create business accounts (movie accounts) to promote their movies and capture the attention of followers on Instagram. Instagram contains rich information about movies and user feedback, while IMDb, one of the most popular online databases, contains well-organized information related to movies. The features extracted from the data collected from Instagram and IMDb can complement each other. Therefore, in this study, we propose a framework for recommending movie accounts to users on Instagram by using the data collected from Instagram and IMDb platforms. The experiment results show that our proposed framework outperforms the comparing methods in terms of precision, recall, F1-score, and Normalized Discounted Cumulative Gain (NDCG), and mitigates the effect of cold start problems. The proposed framework can help movie companies or businesses reach potential audiences and implement effective targeted advertising strategies.
{"title":"Movie Account Recommendation on Instagram","authors":"Yu-Jhen Wang, Anthony J. T. Lee","doi":"10.1145/3579852","DOIUrl":"https://doi.org/10.1145/3579852","url":null,"abstract":"With the increasing popularity of social networks, many businesses have started implementing their branding or targeted advertising strategies to reach potential customers through social media platforms. It is desirable and essential to help businesses to reach mass audiences and assist users to find favorite business accounts on social media platforms. In the movie industry, movie companies often create business accounts (movie accounts) to promote their movies and capture the attention of followers on Instagram. Instagram contains rich information about movies and user feedback, while IMDb, one of the most popular online databases, contains well-organized information related to movies. The features extracted from the data collected from Instagram and IMDb can complement each other. Therefore, in this study, we propose a framework for recommending movie accounts to users on Instagram by using the data collected from Instagram and IMDb platforms. The experiment results show that our proposed framework outperforms the comparing methods in terms of precision, recall, F1-score, and Normalized Discounted Cumulative Gain (NDCG), and mitigates the effect of cold start problems. The proposed framework can help movie companies or businesses reach potential audiences and implement effective targeted advertising strategies.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"23 1","pages":"1 - 21"},"PeriodicalIF":5.3,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43478361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While JavaScript established itself as a cornerstone of the modern web, it also constitutes a major tracking and security vector, thus raising critical privacy and security concerns. In this context, some browser extensions propose to systematically block scripts reported by crowdsourced trackers lists. However, this solution heavily depends on the quality of these built-in lists, which may be deprecated or incomplete, thus exposing the visitor to unknown trackers. In this article, we explore a different strategy by investigating the benefits of disabling JavaScript in the browser. More specifically, by adopting such a strict policy, we aim to quantify the JavaScript addiction of web elements composing a web page through the observation of web breakages. As there is no standard mechanism for detecting such breakages, we introduce a framework to inspect several page features when blocking JavaScript, that we deploy to analyze 6,384 pages, including landing and internal web pages. We discover that 43% of web pages are not strictly dependent on JavaScript and that more than 67% of pages are likely to be usable as long as the visitor only requires the content from the main section of the page, for which the user most likely reached the page, while reducing the number of tracking requests by 85% on average. Finally, we discuss the viability of currently browsing the web without JavaScript and detail multiple incentives for websites to be kept usable without JavaScript.
{"title":"Breaking Bad: Quantifying the Addiction of Web Elements to JavaScript","authors":"Romain Fouquet, Pierre Laperdrix, Romain Rouvoy","doi":"10.1145/3579846","DOIUrl":"https://doi.org/10.1145/3579846","url":null,"abstract":"While JavaScript established itself as a cornerstone of the modern web, it also constitutes a major tracking and security vector, thus raising critical privacy and security concerns. In this context, some browser extensions propose to systematically block scripts reported by crowdsourced trackers lists. However, this solution heavily depends on the quality of these built-in lists, which may be deprecated or incomplete, thus exposing the visitor to unknown trackers. In this article, we explore a different strategy by investigating the benefits of disabling JavaScript in the browser. More specifically, by adopting such a strict policy, we aim to quantify the JavaScript addiction of web elements composing a web page through the observation of web breakages. As there is no standard mechanism for detecting such breakages, we introduce a framework to inspect several page features when blocking JavaScript, that we deploy to analyze 6,384 pages, including landing and internal web pages. We discover that 43% of web pages are not strictly dependent on JavaScript and that more than 67% of pages are likely to be usable as long as the visitor only requires the content from the main section of the page, for which the user most likely reached the page, while reducing the number of tracking requests by 85% on average. Finally, we discuss the viability of currently browsing the web without JavaScript and detail multiple incentives for websites to be kept usable without JavaScript.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"77 1","pages":"1 - 28"},"PeriodicalIF":5.3,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64063297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiuwen Fu, P. Pace, G. Aloi, A. Guerrieri, Wenfeng Li, G. Fortino
In practical cyber-manufacturing systems (CMS), the node component is the forwarder of information and the provider of services. This dual role makes the whole system have the typical physical-services interaction characteristic, making CMS more vulnerable to cascading failures than general manufacturing systems. In this work, in order to reasonably characterize the cascading process of CMS, we first develop an interdependent network model for CMS from a physical-service networking perspective. On this basis, a realistic cascading failure model for CMS is designed with full consideration of the routing-oriented load distribution characteristics of the physical network and selective load distribution characteristics of the service network. Through extensive experiments, the soundness of the proposed model has been verified and some meaningful findings have been obtained: 1) attacks on the physical network are more likely to trigger cascading failures and may cause more damage; 2) interdependency failures are the main cause of performance degradation in the service network during cascading failures; 3) isolation failures are the main cause of performance degradation in the physical network during cascading failures. The obtained results can certainly help users to design a more reliable CMS against cascading failures.
{"title":"Tolerance Analysis of Cyber-Manufacturing Systems to Cascading Failures","authors":"Xiuwen Fu, P. Pace, G. Aloi, A. Guerrieri, Wenfeng Li, G. Fortino","doi":"10.1145/3579847","DOIUrl":"https://doi.org/10.1145/3579847","url":null,"abstract":"In practical cyber-manufacturing systems (CMS), the node component is the forwarder of information and the provider of services. This dual role makes the whole system have the typical physical-services interaction characteristic, making CMS more vulnerable to cascading failures than general manufacturing systems. In this work, in order to reasonably characterize the cascading process of CMS, we first develop an interdependent network model for CMS from a physical-service networking perspective. On this basis, a realistic cascading failure model for CMS is designed with full consideration of the routing-oriented load distribution characteristics of the physical network and selective load distribution characteristics of the service network. Through extensive experiments, the soundness of the proposed model has been verified and some meaningful findings have been obtained: 1) attacks on the physical network are more likely to trigger cascading failures and may cause more damage; 2) interdependency failures are the main cause of performance degradation in the service network during cascading failures; 3) isolation failures are the main cause of performance degradation in the physical network during cascading failures. The obtained results can certainly help users to design a more reliable CMS against cascading failures.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":" ","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48427794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michell Boerger, Philipp Lämmel, Nikolay Tcholtchev, M. Hauswirth
Climate change has put significant pressure on energy markets. Political decisions such as the plan of the German government to shut down coal power plants by 2038 are shifting electricity production towards renewable and distributed energy resources. The share of these resources will continue to grow significantly in the coming years. This trend changes the ways how energy markets work which mandates fundamental changes in the underlying IT infrastructure. In this paper, we propose a blockchain-based solution which enables an economically viable and grid-serving integration of distributed energy resources into the existing energy system. Our blockchain-based approach targets intraday and day-ahead operating reserve markets, on which energy grid operators and operators of distributed energy resources can trade flexibilities within the schedulable energy production and consumption of their resources. By utilizing these flexibilities as an operating reserve, renewable and climate-friendly technologies can contribute to maintaining the grid stability and security of supply while simultaneously creating economically interesting business models for their operators. We propose to define blockchain-based short-term energy markets by utilizing the concept of general-purpose smart contracts and cryptocurrencies. This enables direct and decentralized trading of energy flexibilities without any intermediary or central instance. We demonstrate the feasibility of our approach through an implementation of a prototype of the proposed markets based on the Ethereum blockchain and provide a detailed evaluation of its efficiency and scalability.
{"title":"Enabling Short-Term Energy Flexibility Markets Through Blockchain","authors":"Michell Boerger, Philipp Lämmel, Nikolay Tcholtchev, M. Hauswirth","doi":"10.1145/3542949","DOIUrl":"https://doi.org/10.1145/3542949","url":null,"abstract":"Climate change has put significant pressure on energy markets. Political decisions such as the plan of the German government to shut down coal power plants by 2038 are shifting electricity production towards renewable and distributed energy resources. The share of these resources will continue to grow significantly in the coming years. This trend changes the ways how energy markets work which mandates fundamental changes in the underlying IT infrastructure. In this paper, we propose a blockchain-based solution which enables an economically viable and grid-serving integration of distributed energy resources into the existing energy system. Our blockchain-based approach targets intraday and day-ahead operating reserve markets, on which energy grid operators and operators of distributed energy resources can trade flexibilities within the schedulable energy production and consumption of their resources. By utilizing these flexibilities as an operating reserve, renewable and climate-friendly technologies can contribute to maintaining the grid stability and security of supply while simultaneously creating economically interesting business models for their operators. We propose to define blockchain-based short-term energy markets by utilizing the concept of general-purpose smart contracts and cryptocurrencies. This enables direct and decentralized trading of energy flexibilities without any intermediary or central instance. We demonstrate the feasibility of our approach through an implementation of a prototype of the proposed markets based on the Ethereum blockchain and provide a detailed evaluation of its efficiency and scalability.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"22 1","pages":"1 - 25"},"PeriodicalIF":5.3,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41369045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sidharth Sharma, Aniruddha Kushwaha, Mohammad Alizadeh, G. Varghese, Ashwin Gumaste
We examine how to provide applications with dedicated bandwidth and guaranteed latency in a programmable mission-critical network. Unlike other SDN approaches such as B4 or SWAN, our system Tuneman optimizes both routes and packet schedules at each node to provide flows with sub-second bandwidth changes. Tuneman uses node-level optimization to compute node schedules in a slotted switch and does dynamic routing using a search procedure with Quality of Service– (QoS) based weights. This allows Tuneman to provide an efficient solution for mission-critical networks that have stringent QoS requirements. We evaluate Tuneman on a telesurgery network using a switch prototype built using FPGAs and also via simulations on India’s Tata Network. For mission-critical networks with multiple QoS levels, Tuneman has comparable or better utilization than SWAN while providing delay bounds guarantees.
{"title":"Tuneman: Customizing Networks to Guarantee Application Bandwidth and Latency","authors":"Sidharth Sharma, Aniruddha Kushwaha, Mohammad Alizadeh, G. Varghese, Ashwin Gumaste","doi":"10.1145/3575657","DOIUrl":"https://doi.org/10.1145/3575657","url":null,"abstract":"We examine how to provide applications with dedicated bandwidth and guaranteed latency in a programmable mission-critical network. Unlike other SDN approaches such as B4 or SWAN, our system Tuneman optimizes both routes and packet schedules at each node to provide flows with sub-second bandwidth changes. Tuneman uses node-level optimization to compute node schedules in a slotted switch and does dynamic routing using a search procedure with Quality of Service– (QoS) based weights. This allows Tuneman to provide an efficient solution for mission-critical networks that have stringent QoS requirements. We evaluate Tuneman on a telesurgery network using a switch prototype built using FPGAs and also via simulations on India’s Tata Network. For mission-critical networks with multiple QoS levels, Tuneman has comparable or better utilization than SWAN while providing delay bounds guarantees.","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"23 1","pages":"1 - 26"},"PeriodicalIF":5.3,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49063778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The outbreak of Covid-19 has exposed the lack of medical resources, especially the lack of medical personnel. This results in time and space restrictions for medical services, and patients cannot obtain health information all the time and everywhere. Based on the medical knowledge graph, healthcare bots alleviate this burden effectively by providing patients with diagnosis guidance, pre-diagnosis, and post-diagnosis consultation services in the way of human-machine dialogue. However, the medical utterance is more complicated in language structure, and there are complex intention phenomena in semantics. It is a challenge to detect the single intent, multi-intent, and implicit intent of a patient’s utterance. To this end, we create a high-quality annotated Chinese Medical query (utterance) dataset, CMedQ (about 16.8k queries in medical domain which includes single, multiple, and implicit intents). It is hard to detect intent on such a complex dataset through traditional text classification models. Thus, we propose a novel detect model Conco-ERNIE, using concept co-occurrence patterns to enhance the representation of pre-trained model ERNIE. These patterns are mined using Apriori algorithm and will be embedded via Node2Vec. Their features will be aggregated with semantic features into Conco-ERNIE by using an attention module, which can catch user explicit intents and also predict user implicit intents. Experiments on CMedQ demonstrates that Conco-ERNIE achieves outstanding performance over baseline. Based on Conco-ERNIE, we develop an intelligent healthcare bot, MedicalBot. To provide knowledge support for MedicalBot, we also build a Chinese medical graph, CMedKG (about 45k entities and 283k relationships).
{"title":"Conco-ERNIE: Complex User Intent Detect Model for Smart Healthcare Cognitive Bot","authors":"Bolin Zhang, Zhiying Tu, Shaoshi Hang, Dian-Hui Chu, Xiaofei Xu","doi":"10.1145/3574135","DOIUrl":"https://doi.org/10.1145/3574135","url":null,"abstract":"The outbreak of Covid-19 has exposed the lack of medical resources, especially the lack of medical personnel. This results in time and space restrictions for medical services, and patients cannot obtain health information all the time and everywhere. Based on the medical knowledge graph, healthcare bots alleviate this burden effectively by providing patients with diagnosis guidance, pre-diagnosis, and post-diagnosis consultation services in the way of human-machine dialogue. However, the medical utterance is more complicated in language structure, and there are complex intention phenomena in semantics. It is a challenge to detect the single intent, multi-intent, and implicit intent of a patient’s utterance. To this end, we create a high-quality annotated Chinese Medical query (utterance) dataset, CMedQ (about 16.8k queries in medical domain which includes single, multiple, and implicit intents). It is hard to detect intent on such a complex dataset through traditional text classification models. Thus, we propose a novel detect model Conco-ERNIE, using concept co-occurrence patterns to enhance the representation of pre-trained model ERNIE. These patterns are mined using Apriori algorithm and will be embedded via Node2Vec. Their features will be aggregated with semantic features into Conco-ERNIE by using an attention module, which can catch user explicit intents and also predict user implicit intents. Experiments on CMedQ demonstrates that Conco-ERNIE achieves outstanding performance over baseline. Based on Conco-ERNIE, we develop an intelligent healthcare bot, MedicalBot. To provide knowledge support for MedicalBot, we also build a Chinese medical graph, CMedKG (about 45k entities and 283k relationships).","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":" ","pages":"1 - 24"},"PeriodicalIF":5.3,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44518505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mathias Fischer, W. Lamersdorf, J. Liebeherr, M. Mühlhäuser
The history of research and development for the Internet has alternated between time periods of grand new visions and time periods concerned with integrating new advances in information and communication technology. As we entered the 21st century, many voices called for a redesign of the Internet architecture. The Internet was said to be ossified in the sense that its ability to incorporate major upgrades had been largely lost. Viewed as being in a state beyond repair, the era saw calls for and many efforts on a clean-slate design of the Internet architecture. A decade on – and with the Internet architecture largely unchanged – the appetite for big solutions has largely waned, and been replaced by efforts that seek to adapt networks and distributed systems to challenges posed by the advent of the Internet-of-Things, network softwarization, mission-critical applications, and artificial intelligence: IoT. The Internet-of-Things (IoT) will boost the number of Internet nodes well beyond the billions, which will lead to new traffic patterns (e.g., high-frequency low-volume) and resource requirements. SDN++. Softwarization is ‘conquering’ the net. Technologies such as software-defined networking (SDN) and network function virtualization (NFV) will continue to deliver increased flexibility for providing network services. As this softwarization significantly increases the complexity of today’s networks, new security problems will emerge. MCA. Mission-critical applications (MCA), which used to be confined to dedicated real-time systems and networks, such as time-sensitive networks (TSN), industrial Ethernet, and so on, are migrating to public and wide area networks. This impacts technologies and protocols, such as ultrareliable low latency communications (URLLC) in 5G networks. Moreover, delay requirements of real-time applications create a need to move cloud functionality closer to the action scene, e.g., via fog and edge computing. AI. The resurgence of artificial intelligence (AI), evoked by stunning successes of machine learning, boosts the need for computing resources that cannot be embedded in IoT devices and
{"title":"Introduction to the Special Section on Recent Advances in Networks and Distributed Systems","authors":"Mathias Fischer, W. Lamersdorf, J. Liebeherr, M. Mühlhäuser","doi":"10.1145/3584743","DOIUrl":"https://doi.org/10.1145/3584743","url":null,"abstract":"The history of research and development for the Internet has alternated between time periods of grand new visions and time periods concerned with integrating new advances in information and communication technology. As we entered the 21st century, many voices called for a redesign of the Internet architecture. The Internet was said to be ossified in the sense that its ability to incorporate major upgrades had been largely lost. Viewed as being in a state beyond repair, the era saw calls for and many efforts on a clean-slate design of the Internet architecture. A decade on – and with the Internet architecture largely unchanged – the appetite for big solutions has largely waned, and been replaced by efforts that seek to adapt networks and distributed systems to challenges posed by the advent of the Internet-of-Things, network softwarization, mission-critical applications, and artificial intelligence: IoT. The Internet-of-Things (IoT) will boost the number of Internet nodes well beyond the billions, which will lead to new traffic patterns (e.g., high-frequency low-volume) and resource requirements. SDN++. Softwarization is ‘conquering’ the net. Technologies such as software-defined networking (SDN) and network function virtualization (NFV) will continue to deliver increased flexibility for providing network services. As this softwarization significantly increases the complexity of today’s networks, new security problems will emerge. MCA. Mission-critical applications (MCA), which used to be confined to dedicated real-time systems and networks, such as time-sensitive networks (TSN), industrial Ethernet, and so on, are migrating to public and wide area networks. This impacts technologies and protocols, such as ultrareliable low latency communications (URLLC) in 5G networks. Moreover, delay requirements of real-time applications create a need to move cloud functionality closer to the action scene, e.g., via fog and edge computing. AI. The resurgence of artificial intelligence (AI), evoked by stunning successes of machine learning, boosts the need for computing resources that cannot be embedded in IoT devices and","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"22 1","pages":"1 - 3"},"PeriodicalIF":5.3,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41869274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：