Self-adaptive systems alter their behavior in response to environmental changes to continually satisfy their requirements. Self-adaptive systems employ an environment model, which should be updated during runtime to maintain consistency with the real environment. Although some techniques have been proposed to learn environment model based on execution traces at the design time, these techniques are time consuming and consequently inappropriate for runtime learning. Herein, a technique using a stochastic gradient descent and the difference in the data acquired during the runtime is proposed as an efficient learning environment model. The computational time and accuracy of our technique are verified through study.
{"title":"Learning environment model at runtime for self-adaptive systems","authors":"Moeka Tanabe, K. Tei, Y. Fukazawa, S. Honiden","doi":"10.1145/3019612.3019776","DOIUrl":"https://doi.org/10.1145/3019612.3019776","url":null,"abstract":"Self-adaptive systems alter their behavior in response to environmental changes to continually satisfy their requirements. Self-adaptive systems employ an environment model, which should be updated during runtime to maintain consistency with the real environment. Although some techniques have been proposed to learn environment model based on execution traces at the design time, these techniques are time consuming and consequently inappropriate for runtime learning. Herein, a technique using a stochastic gradient descent and the difference in the data acquired during the runtime is proposed as an efficient learning environment model. The computational time and accuracy of our technique are verified through study.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78962525","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}
The large-scale deployments of Internet of Things (IoT) systems have introduced several new challenges in terms of processing their data. The massive amount of IoT-generated data requires design solutions to speed up data processing, scale up with the data volume and improve data adaptability and extensibility. Beyond existing techniques for IoT data collection, filtering, and analytics, innovative service computing technologies are required for provisioning data-centric and scalable IoT services. This paper presents a service-oriented design model and framework for realizing scalable and efficient acquisition, processing and integration of data-centric IoT services. In this approach, data-centric IoT services are organized in a service integrating tree structure, adhering to the architecture of many large-scale IoT systems, including recent fog-based IoT computing models. A service node in the tree is called a Big Service and acts as an integrator, collecting data from lower level Big Services, processing them, and delivering the result to higher level IoT Big Services. The service tree thereby encapsulates required data processing functions in a hierarchical manner in order to achieve scalable and real-time data collection and processing. We have implemented the IoT Big Services framework leveraging a popular cloud-based service and data platform called Firebase, and evaluated its performance in terms of real-time requirements.
{"title":"From IoT big data to IoT big services","authors":"Amirhosein Taherkordi, F. Eliassen, G. Horn","doi":"10.1145/3019612.3019700","DOIUrl":"https://doi.org/10.1145/3019612.3019700","url":null,"abstract":"The large-scale deployments of Internet of Things (IoT) systems have introduced several new challenges in terms of processing their data. The massive amount of IoT-generated data requires design solutions to speed up data processing, scale up with the data volume and improve data adaptability and extensibility. Beyond existing techniques for IoT data collection, filtering, and analytics, innovative service computing technologies are required for provisioning data-centric and scalable IoT services. This paper presents a service-oriented design model and framework for realizing scalable and efficient acquisition, processing and integration of data-centric IoT services. In this approach, data-centric IoT services are organized in a service integrating tree structure, adhering to the architecture of many large-scale IoT systems, including recent fog-based IoT computing models. A service node in the tree is called a Big Service and acts as an integrator, collecting data from lower level Big Services, processing them, and delivering the result to higher level IoT Big Services. The service tree thereby encapsulates required data processing functions in a hierarchical manner in order to achieve scalable and real-time data collection and processing. We have implemented the IoT Big Services framework leveraging a popular cloud-based service and data platform called Firebase, and evaluated its performance in terms of real-time requirements.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76730533","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}
Pikakshi Manchanda, E. Fersini, M. Palmonari, Debora Nozza, E. Messina
Numerous state-of-the-art Named Entity Recognition (NER) systems use different classification schemas/ontologies. Comparisons and integration among NER systems, thus, becomes complex. In this paper, we propose a transfer-learning approach where we use supervised learning methods to automatically learn mappings between ontologies of NER systems, where an input probability distribution over a set of entity types defined in a source ontology is mapped to a target distribution over the entity types defined for a target ontology. Experiments conducted with benchmark data show valuable re-classification performance of entity mentions, suggesting our approach as a promising one for domain adaptation of NER systems.
{"title":"Towards adaptation of named entity classification","authors":"Pikakshi Manchanda, E. Fersini, M. Palmonari, Debora Nozza, E. Messina","doi":"10.1145/3019612.3022188","DOIUrl":"https://doi.org/10.1145/3019612.3022188","url":null,"abstract":"Numerous state-of-the-art Named Entity Recognition (NER) systems use different classification schemas/ontologies. Comparisons and integration among NER systems, thus, becomes complex. In this paper, we propose a transfer-learning approach where we use supervised learning methods to automatically learn mappings between ontologies of NER systems, where an input probability distribution over a set of entity types defined in a source ontology is mapped to a target distribution over the entity types defined for a target ontology. Experiments conducted with benchmark data show valuable re-classification performance of entity mentions, suggesting our approach as a promising one for domain adaptation of NER systems.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79427316","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 proposes Architectural Pattern Recommender (APR) system which helps in such architecture selection process. Main contribution of this work is in replacing the manual effort required to identify and analyse relevant architectural patterns in context of a particular set of software requirements. Key input to APR is a set of architecturally significant use cases concerning the application being developed. Central idea of APR's design is two folds: a) transform the unstructured information about software architecture design into a structured form which is suitable for recognizing textual entailment between a requirement scenario and a potential architectural pattern, b) leverage the rich experiential knowledge embedded in discussions on professional developer support forums such as Stackoverflow to check the sentiment about a design decision. APR makes use of both the above elements to identify a suitable architectural pattern and assess its suitability for a given set of requirements. Efficacy of APR has been evaluated by comparing its recommendations for "ground truth" scenarios (comprising of applications whose architecture is well known).
{"title":"APR: architectural pattern recommender","authors":"Shipra Sharma, B. Sodhi","doi":"10.1145/3019612.3019780","DOIUrl":"https://doi.org/10.1145/3019612.3019780","url":null,"abstract":"This paper proposes Architectural Pattern Recommender (APR) system which helps in such architecture selection process. Main contribution of this work is in replacing the manual effort required to identify and analyse relevant architectural patterns in context of a particular set of software requirements. Key input to APR is a set of architecturally significant use cases concerning the application being developed. Central idea of APR's design is two folds: a) transform the unstructured information about software architecture design into a structured form which is suitable for recognizing textual entailment between a requirement scenario and a potential architectural pattern, b) leverage the rich experiential knowledge embedded in discussions on professional developer support forums such as Stackoverflow to check the sentiment about a design decision. APR makes use of both the above elements to identify a suitable architectural pattern and assess its suitability for a given set of requirements. Efficacy of APR has been evaluated by comparing its recommendations for \"ground truth\" scenarios (comprising of applications whose architecture is well known).","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77095788","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}
The loosely coupled interoperability of heterogeneous existing systems, together with the ongoing replacement of monolithic systems design with Off-The-Shelf (OTS) approaches, promotes a new architectural paradigm that is called System of Systems (SoS). In SoSs, independent and autonomous constituent systems (CSs) cooperate to achieve higher-level goals. Some inherent challenges are that boundaries of the SoS may be partially unknown and the components may be governed by different authorities, affecting the ability to observe the system as a whole. Further, novel challenges related to dependability and security are introduced, such as the detection of emerging and possibly unexpected behaviors resulting from the interconnection of previous disconnected CSs. In this paper we explore these challenges questioning if a novel mindset to error, malware or intrusion detection is needed when dealing with SoSs. With the support of a state of the art review, we first identify the design principles and the performance targets of a monitoring and anomaly detection framework. Then we discuss these principles at the light of SoS fundamentals. Ultimately, we propose an approach to design a monitoring and anomaly detection framework for SoSs aggregating i) monitoring approaches ii) SoS properties, and iii) anomaly detection techniques.
异构现有系统的松散耦合互操作性，以及用现成(Off-The-Shelf, OTS)方法不断替代单片系统设计，促进了一种新的体系结构范例，称为系统的系统(System of systems, SoS)。在社会责任系统中，独立和自治的组成系统(CSs)相互协作以实现更高层次的目标。一些固有的挑战是，SoS的边界可能部分未知，组件可能由不同的权威管理，从而影响观察整个系统的能力。此外，引入了与可靠性和安全性相关的新挑战，例如检测由于先前断开的CSs互连而产生的新行为和可能的意外行为。在本文中，我们探讨了这些挑战，质疑在处理sos时是否需要一种新的错误，恶意软件或入侵检测的心态。在最新技术综述的支持下，我们首先确定了监视和异常检测框架的设计原则和性能目标。然后我们根据SoS的基本原理来讨论这些原则。最后，我们提出了一种方法来设计一个监测和异常检测框架，用于聚合i)监测方法ii) SoS属性和iii)异常检测技术。
{"title":"Exploring anomaly detection in systems of systems","authors":"T. Zoppi, A. Ceccarelli, A. Bondavalli","doi":"10.1145/3019612.3019765","DOIUrl":"https://doi.org/10.1145/3019612.3019765","url":null,"abstract":"The loosely coupled interoperability of heterogeneous existing systems, together with the ongoing replacement of monolithic systems design with Off-The-Shelf (OTS) approaches, promotes a new architectural paradigm that is called System of Systems (SoS). In SoSs, independent and autonomous constituent systems (CSs) cooperate to achieve higher-level goals. Some inherent challenges are that boundaries of the SoS may be partially unknown and the components may be governed by different authorities, affecting the ability to observe the system as a whole. Further, novel challenges related to dependability and security are introduced, such as the detection of emerging and possibly unexpected behaviors resulting from the interconnection of previous disconnected CSs. In this paper we explore these challenges questioning if a novel mindset to error, malware or intrusion detection is needed when dealing with SoSs. With the support of a state of the art review, we first identify the design principles and the performance targets of a monitoring and anomaly detection framework. Then we discuss these principles at the light of SoS fundamentals. Ultimately, we propose an approach to design a monitoring and anomaly detection framework for SoSs aggregating i) monitoring approaches ii) SoS properties, and iii) anomaly detection techniques.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73773762","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}
Sayan Sen Sarma, K. Sinha, G. Chakraborty, B. Sinha
We consider the problem of traffic routing in a road network in the event of a disaster, when there is a surge in vehicle movement from dense residential areas to designated safe-shelters. We address the problem with multiple sources and a fixed sink in a k × k Manhattan grid road network to find a traffic distribution over the network such that the average time of travel from sources to sink is minimized. We consider queuing delay at each grid point of the Manhattan network when multiple grid points can become potential sources of new traffic generation, and then propose an optimal traffic distribution algorithm to minimize the total queuing delay of all vehicles to reach the given destination point. We then extend our technique to consider variable link delay (as a function of the volume of traffic flow through a link) along the links of the network.
{"title":"Distributed algorithm for traffic dissemination in manhattan networks with optimal routing-time","authors":"Sayan Sen Sarma, K. Sinha, G. Chakraborty, B. Sinha","doi":"10.1145/3019612.3019702","DOIUrl":"https://doi.org/10.1145/3019612.3019702","url":null,"abstract":"We consider the problem of traffic routing in a road network in the event of a disaster, when there is a surge in vehicle movement from dense residential areas to designated safe-shelters. We address the problem with multiple sources and a fixed sink in a k × k Manhattan grid road network to find a traffic distribution over the network such that the average time of travel from sources to sink is minimized. We consider queuing delay at each grid point of the Manhattan network when multiple grid points can become potential sources of new traffic generation, and then propose an optimal traffic distribution algorithm to minimize the total queuing delay of all vehicles to reach the given destination point. We then extend our technique to consider variable link delay (as a function of the volume of traffic flow through a link) along the links of the network.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74674626","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 present an empirical study on patterns of operating system failure causes. We surveyed 566 computers and collected 7,007 real failures of operating systems. We found that 87.97+ of the failures were caused by faults related to software updating. We found strong evidences of autocorrelation among operating system failure causes, i.e., the same failure occurs multiple times successively and due to the same cause; or different failures occur simultaneously due to a common cause. Cross-correlation among different failure causes was also observed and discussed. We discovered 47 genuine patterns of operating system failure causes with 156,866 occurrences in the analyzed dataset.
{"title":"An empirical study on patterns of failure causes in a mass-market operating system","authors":"C. A. R. D. Santos, Rivalino Matias","doi":"10.1145/3019612.3019740","DOIUrl":"https://doi.org/10.1145/3019612.3019740","url":null,"abstract":"In this paper we present an empirical study on patterns of operating system failure causes. We surveyed 566 computers and collected 7,007 real failures of operating systems. We found that 87.97+ of the failures were caused by faults related to software updating. We found strong evidences of autocorrelation among operating system failure causes, i.e., the same failure occurs multiple times successively and due to the same cause; or different failures occur simultaneously due to a common cause. Cross-correlation among different failure causes was also observed and discussed. We discovered 47 genuine patterns of operating system failure causes with 156,866 occurrences in the analyzed dataset.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74687053","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}
{"title":"Session details: EMBS - embedded systems track","authors":"","doi":"10.1145/3243969","DOIUrl":"https://doi.org/10.1145/3243969","url":null,"abstract":"","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74702016","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}
The skyline query aims to filter out a set of eligible points on the basis of a set of evaluation criteria and out of a potentially large dataset of points. The computation of this decision support problem has been studied across a wide range of environments and of types of data. A field of research that has remained unexplored in the context of this problem, and which would also greatly benefit from the study of the computation of the skyline query, is that of temporal databases. A solution for computing skyline queries and some of its variants over temporal data is put forward here. An experimental study indicates the promising effectiveness and practicability of the proposed extension of the skyline query processing in real-life temporal data applications.
{"title":"Processing skyline queries in temporal databases","authors":"Christos Kalyvas, T. Tzouramanis, Y. Manolopoulos","doi":"10.1145/3019612.3019677","DOIUrl":"https://doi.org/10.1145/3019612.3019677","url":null,"abstract":"The skyline query aims to filter out a set of eligible points on the basis of a set of evaluation criteria and out of a potentially large dataset of points. The computation of this decision support problem has been studied across a wide range of environments and of types of data. A field of research that has remained unexplored in the context of this problem, and which would also greatly benefit from the study of the computation of the skyline query, is that of temporal databases. A solution for computing skyline queries and some of its variants over temporal data is put forward here. An experimental study indicates the promising effectiveness and practicability of the proposed extension of the skyline query processing in real-life temporal data applications.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80106572","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}
The optimization of similarity queries is often done with specialized data structures known as metric access methods. It has recently been proposed the use of B+trees to index high dimensional data for range and nearest neighbor search in metric spaces. This work1 introduces a new access method called GroupSim and query algorithms for indexing and retrieving complex data by similarity. It employs a single B+tree in order to dynamically index data elements with regard to a set of one-dimensional embeddings. Our strategy uses a new scheme to store distance information, allowing to determine directly if each element lies on the intersection of the embeddings. We compare GroupSim with two related methods, iDistance and OmniB-Forest, and we show empirically the new access method outperforms them with regard to the time required to run similarity queries.
{"title":"Similarity search through one-dimensional embeddings","authors":"H. Razente, Rafael L. Bernardes Lima, M. Barioni","doi":"10.1145/3019612.3019674","DOIUrl":"https://doi.org/10.1145/3019612.3019674","url":null,"abstract":"The optimization of similarity queries is often done with specialized data structures known as metric access methods. It has recently been proposed the use of B+trees to index high dimensional data for range and nearest neighbor search in metric spaces. This work1 introduces a new access method called GroupSim and query algorithms for indexing and retrieving complex data by similarity. It employs a single B+tree in order to dynamically index data elements with regard to a set of one-dimensional embeddings. Our strategy uses a new scheme to store distance information, allowing to determine directly if each element lies on the intersection of the embeddings. We compare GroupSim with two related methods, iDistance and OmniB-Forest, and we show empirically the new access method outperforms them with regard to the time required to run similarity queries.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90396480","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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