Moti Bachar, Gal Elimelech, Itai Gat, Gil Sobol, Nicolo Rivetti, A. Gal
The ACM DEBS 2018 Grand Challenge focuses on (soft) real-time prediction of both the destination port and the time of arrival of vessels, monitored through the Automated Identification System (AIS). Venilia prediction mechanism is based on a variety of machine learning techniques, including Markov predictive models. To improve the accuracy of a model, trained off-line on historical data, Venilia supports also on-line continuous training using an incoming event stream. The software architecture enables a low latency, highly parallelized, and load balanced prediction pipeline. Aiming at a portable and reusable solution, Venilia is implemented on top of the Akka Actor framework. Finally, Venilia is also equipped with a visualization tool for data exploration.
{"title":"Venilia, On-line Learning and Prediction of Vessel Destination","authors":"Moti Bachar, Gal Elimelech, Itai Gat, Gil Sobol, Nicolo Rivetti, A. Gal","doi":"10.1145/3210284.3220505","DOIUrl":"https://doi.org/10.1145/3210284.3220505","url":null,"abstract":"The ACM DEBS 2018 Grand Challenge focuses on (soft) real-time prediction of both the destination port and the time of arrival of vessels, monitored through the Automated Identification System (AIS). Venilia prediction mechanism is based on a variety of machine learning techniques, including Markov predictive models. To improve the accuracy of a model, trained off-line on historical data, Venilia supports also on-line continuous training using an incoming event stream. The software architecture enables a low latency, highly parallelized, and load balanced prediction pipeline. Aiming at a portable and reusable solution, Venilia is implemented on top of the Akka Actor framework. Finally, Venilia is also equipped with a visualization tool for data exploration.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114309443","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}
Alejandro Santos, W. Vandelli, P. García, H. Fröning
The data acquisition system of the ATLAS experiment, a major experiment of the Large Hadron Collider (LHC) at CERN, will go through a major upgrade in the next decade. The upgrade is driven by experimental physics requirements, calling for increased data rates on the order of 6 TB/s. By contrast, the data rate of the existing system is 160 GB/s. Among the changes in the upgraded system will be a very large buffer with a projected size on the order of 70 PB. The buffer role will be decoupling of data production from on-line data processing, storing data for periods of up to 24 hours until it can be analyzed by the event processing system. The larger buffer will allow a new data recording strategy, providing additional margins to handle variable data rates. At the same time it will provide sensible trade-offs between buffering space and on-line processing capabilities. This compromise between two resources will be possible since the data production cycle includes time periods where the experiment will not produce data. In this paper we analyze the consequences of such trade-offs, and introduce a tool that allows a detailed exploration of different strategies for resource provisioning. It is based on a model of the upgraded data acquisition system, implemented in a simulation framework. From this model it is possible to obtain insight into the dynamics of the running system. Given predefined resource constraints, we provide bounds for the provisioning of buffering space and on-line processing requirements.
{"title":"Buffer Provisioning for Large-Scale Data-Acquisition Systems","authors":"Alejandro Santos, W. Vandelli, P. García, H. Fröning","doi":"10.1145/3210284.3210288","DOIUrl":"https://doi.org/10.1145/3210284.3210288","url":null,"abstract":"The data acquisition system of the ATLAS experiment, a major experiment of the Large Hadron Collider (LHC) at CERN, will go through a major upgrade in the next decade. The upgrade is driven by experimental physics requirements, calling for increased data rates on the order of 6 TB/s. By contrast, the data rate of the existing system is 160 GB/s. Among the changes in the upgraded system will be a very large buffer with a projected size on the order of 70 PB. The buffer role will be decoupling of data production from on-line data processing, storing data for periods of up to 24 hours until it can be analyzed by the event processing system. The larger buffer will allow a new data recording strategy, providing additional margins to handle variable data rates. At the same time it will provide sensible trade-offs between buffering space and on-line processing capabilities. This compromise between two resources will be possible since the data production cycle includes time periods where the experiment will not produce data. In this paper we analyze the consequences of such trade-offs, and introduce a tool that allows a detailed exploration of different strategies for resource provisioning. It is based on a model of the upgraded data acquisition system, implemented in a simulation framework. From this model it is possible to obtain insight into the dynamics of the running system. Given predefined resource constraints, we provide bounds for the provisioning of buffering space and on-line processing requirements.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130783001","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 this paper, we design a novel platform that facilitates integrated healthcare services without a centralized orchestration. Events that reflect dynamically changing conditions of patients are published using a scalable messaging middleware built on top of a publish/subscribe broker overlay network. Events matching service rules are routed to the appropriate caretakers. Services rules are issued autonomously by the caretakers who subscribe to the future matching events. Through this event-driven system, we aim to help the caretakers and medical staff to recommend and offer services to patients in a more timely and seamless manner.
{"title":"A Platform for Choreography of Heterogeneous Healthcare Services","authors":"Wonjae Kim, Young Yoon","doi":"10.1145/3210284.3219771","DOIUrl":"https://doi.org/10.1145/3210284.3219771","url":null,"abstract":"In this paper, we design a novel platform that facilitates integrated healthcare services without a centralized orchestration. Events that reflect dynamically changing conditions of patients are published using a scalable messaging middleware built on top of a publish/subscribe broker overlay network. Events matching service rules are routed to the appropriate caretakers. Services rules are issued autonomously by the caretakers who subscribe to the future matching events. Through this event-driven system, we aim to help the caretakers and medical staff to recommend and offer services to patients in a more timely and seamless manner.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122448470","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}
An essential security concern in the publish/subscribe paradigm is that of guaranteeing the confidentiality of the data being transmitted. Existing solutions require that some initial parameters, keys or secrets be exchanged or otherwise established between communicating entities before secure end-to-end communication can occur. Most existing solutions in the literature either weaken the desirable decoupling properties of pub/sub or rely on a completely trusted out-of-band service to disseminate these values. This problem can be avoided through the use of Shamir's secret sharing scheme, at the cost of a prohibitively large number of messages, scaling exponentially with the path length between publisher and subscriber. Intel's Software Guard Extensions (SGX) offers trusted execution environments to shield application data from untrusted software running at a higher privilege level. Unfortunately, SGX requires the use of Intel's proprietary hardware and architecture. We mitigate these problems through HyShare, a hybrid broker network used for the purposes of sharing a secret between communicating publishers and subscribers. The broker network is composed of regular brokers that use Shamir's secret sharing scheme and brokers with SGX to reduce the overall number of messages needed to share a secret. By fine tuning the combination of these brokers, it is possible to strike a balance between network resource use and hardware heterogeneity.
{"title":"Secret Sharing in Pub/Sub Using Trusted Execution Environments","authors":"Javier Munster, H. Jacobsen","doi":"10.1145/3210284.3210290","DOIUrl":"https://doi.org/10.1145/3210284.3210290","url":null,"abstract":"An essential security concern in the publish/subscribe paradigm is that of guaranteeing the confidentiality of the data being transmitted. Existing solutions require that some initial parameters, keys or secrets be exchanged or otherwise established between communicating entities before secure end-to-end communication can occur. Most existing solutions in the literature either weaken the desirable decoupling properties of pub/sub or rely on a completely trusted out-of-band service to disseminate these values. This problem can be avoided through the use of Shamir's secret sharing scheme, at the cost of a prohibitively large number of messages, scaling exponentially with the path length between publisher and subscriber. Intel's Software Guard Extensions (SGX) offers trusted execution environments to shield application data from untrusted software running at a higher privilege level. Unfortunately, SGX requires the use of Intel's proprietary hardware and architecture. We mitigate these problems through HyShare, a hybrid broker network used for the purposes of sharing a secret between communicating publishers and subscribers. The broker network is composed of regular brokers that use Shamir's secret sharing scheme and brokers with SGX to reduce the overall number of messages needed to share a secret. By fine tuning the combination of these brokers, it is possible to strike a balance between network resource use and hardware heterogeneity.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133962902","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}
Benjamin Erb, Dominik Meißner, Ferdinand Ogger, F. Kargl
Event sourcing is increasingly used and implemented in event-based systems for maintaining the evolution of application state. However, unbounded event logs are impracticable for many systems, as it is difficult to align scalability requirements and long-term runtime behavior with the corresponding storage requirements. To this end, we explore the design space of log pruning approaches suitable for event-sourced systems. Furthermore, we survey specific log pruning mechanisms for event-sourced logs. In a brief evaluation, we point out the trade-offs when applying pruning to event logs and highlight the applicability of log pruning to event-sourced systems.
{"title":"Log Pruning in Distributed Event-sourced Systems","authors":"Benjamin Erb, Dominik Meißner, Ferdinand Ogger, F. Kargl","doi":"10.1145/3210284.3219767","DOIUrl":"https://doi.org/10.1145/3210284.3219767","url":null,"abstract":"Event sourcing is increasingly used and implemented in event-based systems for maintaining the evolution of application state. However, unbounded event logs are impracticable for many systems, as it is difficult to align scalability requirements and long-term runtime behavior with the corresponding storage requirements. To this end, we explore the design space of log pruning approaches suitable for event-sourced systems. Furthermore, we survey specific log pruning mechanisms for event-sourced logs. In a brief evaluation, we point out the trade-offs when applying pruning to event logs and highlight the applicability of log pruning to event-sourced systems.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124772740","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}
We design Fogstore, a key-value store for event-based systems, that exploits the concept of relevance to guarantee low-latency access to relevant data with strong consistency guarantees, while providing tolerance from geographically correlated failures. Distributed event-based processing pipelines are envisioned to utilize the resources of densely geo-distributed infrastructures for low-latency responses - enabling real-time applications. Increasing complexity of such applications results in higher dependence on state, which has driven the incorporation of state-management as a core functionality of contemporary stream processing engines a la Apache Flink and Samza. Processing components executing under the same context (like location) often produce information that may be relevant to others, thereby necessitating shared state and an out-of-band globally-accessible data-store. Efficient access to application state is critical for overall performance, thus centralized data-stores are not a viable option due to the high-latency of network traversals. On the other hand, a highly geo-distributed datastore with low-latency implemented with current key-value stores would necessitate degrading client expectation of consistency as per the PACELC theorem. In this paper we exploit the notion of contextual relevance of events (data) in situation-awareness applications - and offer differential consistency guarantees for clients based on their context. We highlight important systems concerns that may arise with a highly geo-distributed system and show how Fogstore's design tackles them. We present, in detail, a prototype implementation of Fogstore's mechanisms on Apache Cassandra and a performance evaluation. Our evaluations show that Fogstore is able to achieve the throughput of eventually consistent configurations while serving data with strong consistency to the contextually relevant clients.
{"title":"FogStore","authors":"H. Gupta, U. Ramachandran","doi":"10.1145/3210284.3210297","DOIUrl":"https://doi.org/10.1145/3210284.3210297","url":null,"abstract":"We design Fogstore, a key-value store for event-based systems, that exploits the concept of relevance to guarantee low-latency access to relevant data with strong consistency guarantees, while providing tolerance from geographically correlated failures. Distributed event-based processing pipelines are envisioned to utilize the resources of densely geo-distributed infrastructures for low-latency responses - enabling real-time applications. Increasing complexity of such applications results in higher dependence on state, which has driven the incorporation of state-management as a core functionality of contemporary stream processing engines a la Apache Flink and Samza. Processing components executing under the same context (like location) often produce information that may be relevant to others, thereby necessitating shared state and an out-of-band globally-accessible data-store. Efficient access to application state is critical for overall performance, thus centralized data-stores are not a viable option due to the high-latency of network traversals. On the other hand, a highly geo-distributed datastore with low-latency implemented with current key-value stores would necessitate degrading client expectation of consistency as per the PACELC theorem. In this paper we exploit the notion of contextual relevance of events (data) in situation-awareness applications - and offer differential consistency guarantees for clients based on their context. We highlight important systems concerns that may arise with a highly geo-distributed system and show how Fogstore's design tackles them. We present, in detail, a prototype implementation of Fogstore's mechanisms on Apache Cassandra and a performance evaluation. Our evaluations show that Fogstore is able to achieve the throughput of eventually consistent configurations while serving data with strong consistency to the contextually relevant clients.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121704186","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}
EXTENDED ABSTRACT Stream processing has been an area of ongoing research since the early 2000s. Fueled by industry’s growing interest in dealing with high-velocity big data in near real-time settings, there has been a resurgence of recent activity in both research and engineering of large-scale stream processing systems. In this talk, we will examine the state of the art, focusing in particular on key trends of the past five years with an outlook towards the next five years. I will also give examples from our own work, including stream processing in transactional settings as well as predictive time series analytics for the Internet of Things. Transactional stream processing broadly refers to processing streaming data with correctness guarantees. These guarantees include not only properties that are intrinsic to stream processing (e.g., order, exactly-once semantics), but also ACID properties of traditional OLTP-oriented databases, which arise in streaming applications with shared mutable state. In our recent work, we have designed and built the S-Store System, a scalable main-memory system that supports hybrid OLTP+streaming workloads with strict correctness needs [5]. A use case that best exemplifies the strengths of S-Store is real-time data ingestion [4]. Thus, I will also discuss the requirements of modern data ingestion and how to meet them using S-Store, especially within the context of our BigDAWG Polystore System [1, 6].
{"title":"New Challenges and Opportunities in Stream Processing: Transactions, Predictive Analytics, and Beyond: (Invited Keynote)","authors":"Nesime Tatbul","doi":"10.1145/3210284.3214706","DOIUrl":"https://doi.org/10.1145/3210284.3214706","url":null,"abstract":"EXTENDED ABSTRACT Stream processing has been an area of ongoing research since the early 2000s. Fueled by industry’s growing interest in dealing with high-velocity big data in near real-time settings, there has been a resurgence of recent activity in both research and engineering of large-scale stream processing systems. In this talk, we will examine the state of the art, focusing in particular on key trends of the past five years with an outlook towards the next five years. I will also give examples from our own work, including stream processing in transactional settings as well as predictive time series analytics for the Internet of Things. Transactional stream processing broadly refers to processing streaming data with correctness guarantees. These guarantees include not only properties that are intrinsic to stream processing (e.g., order, exactly-once semantics), but also ACID properties of traditional OLTP-oriented databases, which arise in streaming applications with shared mutable state. In our recent work, we have designed and built the S-Store System, a scalable main-memory system that supports hybrid OLTP+streaming workloads with strict correctness needs [5]. A use case that best exemplifies the strengths of S-Store is real-time data ingestion [4]. Thus, I will also discuss the requirements of modern data ingestion and how to meet them using S-Store, especially within the context of our BigDAWG Polystore System [1, 6].","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"473 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434680","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}
This paper presents Moscato, a web-based tool for a more effective management of large-scale data and event processing platforms. With Moscato, composing data and event processing services can be done intuitively. The process of deploying new service instances including the task of installation and configuration can be automated. With such automation feature, we expect administrators tedious and error-prone management tasks are reduced. Instead, administrators can leverage Moscato's various novel visual cues in order to conduct multilateral situation analysis.
{"title":"Moscato","authors":"Yongjun Choi, Young Yoon","doi":"10.1145/3210284.3219772","DOIUrl":"https://doi.org/10.1145/3210284.3219772","url":null,"abstract":"This paper presents Moscato, a web-based tool for a more effective management of large-scale data and event processing platforms. With Moscato, composing data and event processing services can be done intuitively. The process of deploying new service instances including the task of installation and configuration can be automated. With such automation feature, we expect administrators tedious and error-prone management tasks are reduced. Instead, administrators can leverage Moscato's various novel visual cues in order to conduct multilateral situation analysis.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115265059","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}
Pablo Graubner, Christoph Thelen, Michael Körber, Artur Sterz, G. Salvaneschi, M. Mezini, B. Seeger, Bernd Freisleben
Mobile devices are increasingly being used in edge and fog computing environments to process contextual data collected by sensors. Although complex event processing (CEP) is a suitable approach for realizing context-aware services on mobile devices in these environments, existing mobile CEP engines do not leverage the full potential of modern mobile hardware/software architectures. In this paper, we present multimodal CEP, a novel approach to process streams of events on-device in user space (user mode), in the operating system (kernel mode), on the Wi-Fi chip (Wi-Fi mode), and/or on a sensor hub (hub mode), providing significant improvements in terms of power consumption and throughput. Multimodal CEP automatically breaks up CEP queries and selects the most adequate execution mode for the involved CEP operators. Filter, aggregation, and correlation operators can be expressed in a high-level language without requiring system-level domain-specific knowledge. Multimodal CEP enables developers to efficiently detect user activities, collect environmental conditions, or interpret operating system and network events. Furthermore, it facilitates novel context-aware services, demonstrated by a use case for gathering and analyzing mobility data by Wi-Fi probe request tracking.
{"title":"Multimodal Complex Event Processing on Mobile Devices","authors":"Pablo Graubner, Christoph Thelen, Michael Körber, Artur Sterz, G. Salvaneschi, M. Mezini, B. Seeger, Bernd Freisleben","doi":"10.1145/3210284.3210289","DOIUrl":"https://doi.org/10.1145/3210284.3210289","url":null,"abstract":"Mobile devices are increasingly being used in edge and fog computing environments to process contextual data collected by sensors. Although complex event processing (CEP) is a suitable approach for realizing context-aware services on mobile devices in these environments, existing mobile CEP engines do not leverage the full potential of modern mobile hardware/software architectures. In this paper, we present multimodal CEP, a novel approach to process streams of events on-device in user space (user mode), in the operating system (kernel mode), on the Wi-Fi chip (Wi-Fi mode), and/or on a sensor hub (hub mode), providing significant improvements in terms of power consumption and throughput. Multimodal CEP automatically breaks up CEP queries and selects the most adequate execution mode for the involved CEP operators. Filter, aggregation, and correlation operators can be expressed in a high-level language without requiring system-level domain-specific knowledge. Multimodal CEP enables developers to efficiently detect user activities, collect environmental conditions, or interpret operating system and network events. Furthermore, it facilitates novel context-aware services, demonstrated by a use case for gathering and analyzing mobility data by Wi-Fi probe request tracking.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122226928","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}
We propose a sequence-to-sequence based method to predict vessels' destination port and estimated arrival time. We consider this problem as an extension of trajectory prediction problem, that takes a sequence of historical locations as input and returns a sequence of future locations, which is used to determine arrival port and estimated arrival time. Our solution first represents the trajectories on a spatial grid covering Mediterranean Sea. Then, we train a sequence-to-sequence model to predict the future movement of vessels based on movement tendency and current location. We built our solution using distributed architecture model and applied load balancing techniques to achieve both high performance and scalability.
{"title":"Vessel Destination and Arrival Time Prediction with Sequence-to-Sequence Models over Spatial Grid","authors":"Duc-Duy Nguyen, Chan Le Van, M. Ali","doi":"10.1145/3210284.3220507","DOIUrl":"https://doi.org/10.1145/3210284.3220507","url":null,"abstract":"We propose a sequence-to-sequence based method to predict vessels' destination port and estimated arrival time. We consider this problem as an extension of trajectory prediction problem, that takes a sequence of historical locations as input and returns a sequence of future locations, which is used to determine arrival port and estimated arrival time. Our solution first represents the trajectories on a spatial grid covering Mediterranean Sea. Then, we train a sequence-to-sequence model to predict the future movement of vessels based on movement tendency and current location. We built our solution using distributed architecture model and applied load balancing techniques to achieve both high performance and scalability.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131680402","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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