Jianan Lin, Qiaoduo Zhang, Lingcui Zhang, Fenghua Li
With the wide application of the network and the rapid expansion of its scale, the types of network devices deployed in one network are getting more and more as well. Each kind of devices has its own management method, so there is an urgent need for a unified network device management system. This paper designs an extensible network device management system, which is able to manage multi-type network devices and is easy to extend its functions. The system achieves these features by loading corresponding components dynamically. It provides a component interface specification, and components developed according to the specification can be loaded to the system flexibly. The system also defines a communication protocol for admission control and management data transmission. The protocol has an advantage in security and extensibility. Experiments show that the system can manage common network devices properly and flexibly. It also shows that the system improves the convenience and security of the network device management.
{"title":"Design and Implementation of an Extensible Network Device Management System","authors":"Jianan Lin, Qiaoduo Zhang, Lingcui Zhang, Fenghua Li","doi":"10.1109/CISIS.2016.61","DOIUrl":"https://doi.org/10.1109/CISIS.2016.61","url":null,"abstract":"With the wide application of the network and the rapid expansion of its scale, the types of network devices deployed in one network are getting more and more as well. Each kind of devices has its own management method, so there is an urgent need for a unified network device management system. This paper designs an extensible network device management system, which is able to manage multi-type network devices and is easy to extend its functions. The system achieves these features by loading corresponding components dynamically. It provides a component interface specification, and components developed according to the specification can be loaded to the system flexibly. The system also defines a communication protocol for admission control and management data transmission. The protocol has an advantage in security and extensibility. Experiments show that the system can manage common network devices properly and flexibly. It also shows that the system improves the convenience and security of the network device management.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125613213","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}
Wireless Sensor and Actor Networks (WSANs) is becoming an important part of our technological reality as an autonomous systems, due to the advances of new technologies, such as 5G, Internet of Things (IoT) and ArtificialIntelligence (AI). One of the main challenges in autonomous systems is power management. Self-healing is a key feature of WSAN, which improves network connectivity and lifetime, by assigning actors tasks such as to connect separated network components, or recharge the sensors whose battery power is exhausted. In this paper, we propose a framework for actor selection in WSAN, which consists mainly of an adaptive neuro-fuzzy inference system. It considers network conditions when selecting actors for different tasks regarding network's connectivity restoration.
{"title":"Neuro-Adaptive Learning Fuzzy-Based System for Actor Selection inWireless Sensor and Actor Networks","authors":"Elis Kulla, Donald Elmazi, L. Barolli","doi":"10.1109/CISIS.2016.120","DOIUrl":"https://doi.org/10.1109/CISIS.2016.120","url":null,"abstract":"Wireless Sensor and Actor Networks (WSANs) is becoming an important part of our technological reality as an autonomous systems, due to the advances of new technologies, such as 5G, Internet of Things (IoT) and ArtificialIntelligence (AI). One of the main challenges in autonomous systems is power management. Self-healing is a key feature of WSAN, which improves network connectivity and lifetime, by assigning actors tasks such as to connect separated network components, or recharge the sensors whose battery power is exhausted. In this paper, we propose a framework for actor selection in WSAN, which consists mainly of an adaptive neuro-fuzzy inference system. It considers network conditions when selecting actors for different tasks regarding network's connectivity restoration.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127784366","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}
Andrei Dincu, E. Apostol, C. Leordeanu, M. Mocanu, Dan Huru
Nowadays the applications for real time processing of large amounts of data are encountered increasingly more frequently, as there are lots of system's types that can generate large comprehensive information in a relatively short time. In this paper we focus on sensor-based systems. Such systems may be found in several important domains, such as smart farming, medical field, water management, or smart cities. The proposed solution in this paper has the capacity to analyze data streams from different sensors but also considers historical data, in order to provide alerts or invoke different services. This is a new approach, as, to our knowledge, none of the existing stream-processing solutions support combining streaming with batch processing data. We tested our solution with data from sensors and actuators, using a smart farm test scenario.
{"title":"Real-Time Processing of Heterogeneous Data in Sensor-Based Systems","authors":"Andrei Dincu, E. Apostol, C. Leordeanu, M. Mocanu, Dan Huru","doi":"10.1109/CISIS.2016.133","DOIUrl":"https://doi.org/10.1109/CISIS.2016.133","url":null,"abstract":"Nowadays the applications for real time processing of large amounts of data are encountered increasingly more frequently, as there are lots of system's types that can generate large comprehensive information in a relatively short time. In this paper we focus on sensor-based systems. Such systems may be found in several important domains, such as smart farming, medical field, water management, or smart cities. The proposed solution in this paper has the capacity to analyze data streams from different sensors but also considers historical data, in order to provide alerts or invoke different services. This is a new approach, as, to our knowledge, none of the existing stream-processing solutions support combining streaming with batch processing data. We tested our solution with data from sensors and actuators, using a smart farm test scenario.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134322224","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 cloud computing paradigm has recently emerged as a convenient solution for running different workloads on highly parallel and scalable infrastructures. One major appeal of cloud computing is its capability of abstracting hardware resources and making them easy to use. Conversely, one of the major challenges for cloud providers is the energy efficiency improvement of their infrastructures. Aimed at overcoming this challenge, heterogeneous architectures have started to become part of the standard equipment used in data centers. Despite this effort, heterogeneous systems remain difficult to program and manage, while their effectiveness has been proven only in the HPC domain. Cloud workloads are different in nature and a way to exploit heterogeneity effectively is still lacking. This paper takes a first step towards an effective use of heterogeneous architectures in cloud infrastructures. It presents an in-depth analysis of cloud workloads, highlighting where energy efficiency can be obtained. The microservices paradigm is then presented as a way of intelligently partitioning applications in such a way that different components can take advantage of the heterogeneous hardware, thus providing energy efficiency. Finally, the integration of microservices and heterogeneous architectures, as well as the challenge of managing legacy applications, is presented in the context of the OPERA project.
{"title":"Workload Management for Power Efficiency in Heterogeneous Data Centers","authors":"P. Ruiu, A. Scionti, J. Nider, Mike Rapoport","doi":"10.1109/CISIS.2016.107","DOIUrl":"https://doi.org/10.1109/CISIS.2016.107","url":null,"abstract":"The cloud computing paradigm has recently emerged as a convenient solution for running different workloads on highly parallel and scalable infrastructures. One major appeal of cloud computing is its capability of abstracting hardware resources and making them easy to use. Conversely, one of the major challenges for cloud providers is the energy efficiency improvement of their infrastructures. Aimed at overcoming this challenge, heterogeneous architectures have started to become part of the standard equipment used in data centers. Despite this effort, heterogeneous systems remain difficult to program and manage, while their effectiveness has been proven only in the HPC domain. Cloud workloads are different in nature and a way to exploit heterogeneity effectively is still lacking. This paper takes a first step towards an effective use of heterogeneous architectures in cloud infrastructures. It presents an in-depth analysis of cloud workloads, highlighting where energy efficiency can be obtained. The microservices paradigm is then presented as a way of intelligently partitioning applications in such a way that different components can take advantage of the heterogeneous hardware, thus providing energy efficiency. Finally, the integration of microservices and heterogeneous architectures, as well as the challenge of managing legacy applications, is presented in the context of the OPERA project.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116671757","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}
Hiroki Kataoka, A. Sawada, Dilawaer Duolikun, T. Enokido, M. Takizawa
It is critical to reduce the electric energy consumed in information systems, especially server clusters. In this paper, we discuss an MLPCM (multi-level power consumption with multiple CPUs) model and an MLCM (multi-level computation with multiple CPUs) model of a server with multiple CPUs. In this paper, we newly propose a modified globally energy-aware (MEA) algorithm to select a server for a process in a cluster of m servers. In the MEA algorithm, a server where a process all is to be performed is selected with computation complexity O(m) if the total electric energy of the servers is minimum. We evaluate the MEA algorithm and show not only the total electric energy consumption of the servers but also the average execution time of processes are reduced in the MEA algorithm compared with other algorithms.
{"title":"Energy-Aware Algorithms to Select Servers in Scalable Clusters","authors":"Hiroki Kataoka, A. Sawada, Dilawaer Duolikun, T. Enokido, M. Takizawa","doi":"10.1109/CISIS.2016.124","DOIUrl":"https://doi.org/10.1109/CISIS.2016.124","url":null,"abstract":"It is critical to reduce the electric energy consumed in information systems, especially server clusters. In this paper, we discuss an MLPCM (multi-level power consumption with multiple CPUs) model and an MLCM (multi-level computation with multiple CPUs) model of a server with multiple CPUs. In this paper, we newly propose a modified globally energy-aware (MEA) algorithm to select a server for a process in a cluster of m servers. In the MEA algorithm, a server where a process all is to be performed is selected with computation complexity O(m) if the total electric energy of the servers is minimum. We evaluate the MEA algorithm and show not only the total electric energy consumption of the servers but also the average execution time of processes are reduced in the MEA algorithm compared with other algorithms.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"318 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115150346","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}
GPGPUs have been widely adopted as throughput processing platforms for modern big-data and cloud computing. Attaining a high performance design on a GPGPU requires careful tradeoffs among various design concerns. Data reuse, cache contention, and thread level parallelism, have been demonstrated as three imperative performance factors for a GPGPU. The correlated performance impacts of these factors pose non-trivial concerns when scheduling threads on GPGPUs. This paper proposes a three-staged scheduling scheme to coschedule the threads with consideration of the three factors. The experiment results on a set of irregular parallel applications, when compared with previous approaches, have demonstrated up to 70% execution time improvement.
{"title":"Enhancing Data Reuse in Cache Contention Aware Thread Scheduling on GPGPU","authors":"Chin-Fu Lu, Hsien-Kai Kuo, B. Lai","doi":"10.1109/CISIS.2016.132","DOIUrl":"https://doi.org/10.1109/CISIS.2016.132","url":null,"abstract":"GPGPUs have been widely adopted as throughput processing platforms for modern big-data and cloud computing. Attaining a high performance design on a GPGPU requires careful tradeoffs among various design concerns. Data reuse, cache contention, and thread level parallelism, have been demonstrated as three imperative performance factors for a GPGPU. The correlated performance impacts of these factors pose non-trivial concerns when scheduling threads on GPGPUs. This paper proposes a three-staged scheduling scheme to coschedule the threads with consideration of the three factors. The experiment results on a set of irregular parallel applications, when compared with previous approaches, have demonstrated up to 70% execution time improvement.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131297500","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 introduce the initial proposition and evaluation of the method that enables detection of clusters of trends among microblogging posts gathered from a given social graph. By the cluster of trends we mean the trending words that are popular among same group of people and which describes their common interests. The information about shared interests of group of people in the social network is very important for business. Knowing it we can for example perform directed advertising campaign aimed at single community of people. We validate our approach on large datasets that contains 22 030 252 tweets posted by 20 130 followers of the world-known actress. We found that clusters of trends detection in microblogging with simple natural language processing (namely lemmatization) did not give any valuable information for business. For the other side hashtags frequency filtering and probability conditional probabilities graph clustering resulted in valuable informative about structure of interest in social network.
{"title":"Clusters of Trends Detection in Microblogging: Simple Natural Language Processing vs Hashtags – Which is More Informative?","authors":"T. Hachaj, M. Ogiela","doi":"10.1109/CISIS.2016.44","DOIUrl":"https://doi.org/10.1109/CISIS.2016.44","url":null,"abstract":"In this paper we introduce the initial proposition and evaluation of the method that enables detection of clusters of trends among microblogging posts gathered from a given social graph. By the cluster of trends we mean the trending words that are popular among same group of people and which describes their common interests. The information about shared interests of group of people in the social network is very important for business. Knowing it we can for example perform directed advertising campaign aimed at single community of people. We validate our approach on large datasets that contains 22 030 252 tweets posted by 20 130 followers of the world-known actress. We found that clusters of trends detection in microblogging with simple natural language processing (namely lemmatization) did not give any valuable information for business. For the other side hashtags frequency filtering and probability conditional probabilities graph clustering resulted in valuable informative about structure of interest in social network.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"06 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127274311","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}
Nowadays, many MOOC platforms have arisen to provide free knowledge. These platforms have a large catalog of courses for different specializations that progressively demand more specific learning resources and assessment methods to evaluate the progression of students. Current MOOC platforms are gradually giving support to these new requirements but with a limited assistance. This paper presents the state of art of the analytical system for three relevant MOOC platforms, one of the main pillars for analyzing the progression of courses. Other initiatives are also reviewed to show that current MOOC analytical systems are not ready to support custom MOOC-aware intelligent tutoring systems (ITSs). Thus, the design of a learning analytics system to assist these tools for MOOC platforms is presented.
{"title":"Towards a Learning Analytics Support for Intelligent Tutoring Systems on MOOC Platforms","authors":"David Bañeres, S. Caballé, R. Clarisó","doi":"10.1109/CISIS.2016.48","DOIUrl":"https://doi.org/10.1109/CISIS.2016.48","url":null,"abstract":"Nowadays, many MOOC platforms have arisen to provide free knowledge. These platforms have a large catalog of courses for different specializations that progressively demand more specific learning resources and assessment methods to evaluate the progression of students. Current MOOC platforms are gradually giving support to these new requirements but with a limited assistance. This paper presents the state of art of the analytical system for three relevant MOOC platforms, one of the main pillars for analyzing the progression of courses. Other initiatives are also reviewed to show that current MOOC analytical systems are not ready to support custom MOOC-aware intelligent tutoring systems (ITSs). Thus, the design of a learning analytics system to assist these tools for MOOC platforms is presented.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"698 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116117816","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}
Yuanyuan Zhang, Jinbo Xiong, Xuan Li, Biao Jin, Suping Li, Xu An Wang
Rapid development of cloud storage services produces a tremendous amount of user data outsourcing to cloud servers. Therefore, it is easy to generate data multi-replica, which is able to improve data availability and users' experience. However, when the management of data is poor, the sensitive information will be disclosed more easily. This may bring serious security and privacy challenges for both user's data and its multi-replica in cloud environment. In order to tackle the above issues, in this paper, we propose a multi-replica associated deleting scheme (MADS) in cloud environment. We first introduce a replica associated model to organize all of data replicas among different cloud servers. Furthermore, we propose the MADS scheme which is consists of data storage algorithm, replica generation algorithm, replica deletion and feedback algorithm. Finally, we employ Amazon S3 to implement MADS and the results indicate that the proposed scheme is available and effective.
{"title":"A Multi-replica Associated Deleting Scheme in Cloud","authors":"Yuanyuan Zhang, Jinbo Xiong, Xuan Li, Biao Jin, Suping Li, Xu An Wang","doi":"10.1109/CISIS.2016.68","DOIUrl":"https://doi.org/10.1109/CISIS.2016.68","url":null,"abstract":"Rapid development of cloud storage services produces a tremendous amount of user data outsourcing to cloud servers. Therefore, it is easy to generate data multi-replica, which is able to improve data availability and users' experience. However, when the management of data is poor, the sensitive information will be disclosed more easily. This may bring serious security and privacy challenges for both user's data and its multi-replica in cloud environment. In order to tackle the above issues, in this paper, we propose a multi-replica associated deleting scheme (MADS) in cloud environment. We first introduce a replica associated model to organize all of data replicas among different cloud servers. Furthermore, we propose the MADS scheme which is consists of data storage algorithm, replica generation algorithm, replica deletion and feedback algorithm. Finally, we employ Amazon S3 to implement MADS and the results indicate that the proposed scheme is available and effective.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122453117","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}
Y. Murakami, Mizuki Ando, Miyuu Miyamoto, S. K. T. Utomo
Recently, ICT technology has spread in agriculture. Many IT vendors have developed the WEB application for recording the farm work diary. However, famers feel the burden because famers should input work information by manual operation. In this paper, we propose the system which records an farm work diary automatically. We reduce a farmer's burden. Our method obtains information using RFID (Radio Frequency IDentification) in the UHF band. Famers can get data unconsciously while working. Proposal system presumes farm work from the acquired tag data. Farmers correct incorrect presumption, and store in the server a set of tag data and work data as teacher data. By doing so, accuracy of presumption algorithm that implemented in the server grow up.
{"title":"Proposed of Automatic Collection System on Farm Work Recode by RFID","authors":"Y. Murakami, Mizuki Ando, Miyuu Miyamoto, S. K. T. Utomo","doi":"10.1109/CISIS.2016.77","DOIUrl":"https://doi.org/10.1109/CISIS.2016.77","url":null,"abstract":"Recently, ICT technology has spread in agriculture. Many IT vendors have developed the WEB application for recording the farm work diary. However, famers feel the burden because famers should input work information by manual operation. In this paper, we propose the system which records an farm work diary automatically. We reduce a farmer's burden. Our method obtains information using RFID (Radio Frequency IDentification) in the UHF band. Famers can get data unconsciously while working. Proposal system presumes farm work from the acquired tag data. Farmers correct incorrect presumption, and store in the server a set of tag data and work data as teacher data. By doing so, accuracy of presumption algorithm that implemented in the server grow up.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127352149","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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