Pub Date : 2009-11-17DOI: 10.1007/978-3-642-10488-6_24
K. Froeschl, Norbert Walchhofer, Milan Hronsky
{"title":"The Online Market Observatory: A Domain Model Approach","authors":"K. Froeschl, Norbert Walchhofer, Milan Hronsky","doi":"10.1007/978-3-642-10488-6_24","DOIUrl":"https://doi.org/10.1007/978-3-642-10488-6_24","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121938390","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}
Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users' requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.
{"title":"Adaptive resource allocation for service-based systems","authors":"S. Yau, Ho G. An","doi":"10.1145/1640206.1640209","DOIUrl":"https://doi.org/10.1145/1640206.1640209","url":null,"abstract":"Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users' requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132732372","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}
Pub Date : 2008-12-15DOI: 10.1007/978-3-540-89197-0_33
R. Scherl, Tran Cao Son, Chitta Baral
{"title":"State-Based Regression with Sensing and Knowledge","authors":"R. Scherl, Tran Cao Son, Chitta Baral","doi":"10.1007/978-3-540-89197-0_33","DOIUrl":"https://doi.org/10.1007/978-3-540-89197-0_33","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127707237","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}
Pub Date : 2008-12-15DOI: 10.1007/978-3-540-89197-0_10
P. Cohen, C. Beal
{"title":"Temporal Data Mining for Educational Applications","authors":"P. Cohen, C. Beal","doi":"10.1007/978-3-540-89197-0_10","DOIUrl":"https://doi.org/10.1007/978-3-540-89197-0_10","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126057176","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}
Pub Date : 1900-01-01DOI: 10.21655/ijsi.1673-7288.00245
Yanjun Wu
System software, the software that manages the hardware and supports the applications in computing systems, is a core component of IT ecosystem that covers operating system, programming language, compiler, runtime environment, integrated development environment, etc. In industrial competition, system software is the “moat” and “accelerator” of CPU and the “soil” of APPs. The prosperity of academic research on system software in one country often represents its leadership in core software and hardware technologies in the world. Compared with the prosperity of Internet software or smartphone applications, there is still a large gap in the development of system software in China. The research topics on system software usually come from large processor vendors and large application platforms. In the past, there were few research groups in Chinese universities and institutes on system software due to the lack of demand from domestic industrial giants. People have no choice but use the ISAs, micro-architectures, and platforms from international IT giants, e.g. IBM, Intel, and Qualcomm. Therefore, a virtuous cycle of “industrial demand–academic research–production application–new industrial demand” did not exist in China in past decades. The situation has changed in recent years, and system software has become a hot area in both academia and industry for the first time in the history of China. One reason is the rise of domestic chip vendors. The vendors represented by Huawei and Cambricon have taken the lead in the design of smartphone chips and AI chips, and developed their own system software products, and even make them open source, such as openEuler, OpenHarmony, MindSpore, and BANG. Another reason is the expansion of business stack of Internet companies. Internet giants such as Baidu, Tencent, Alibaba, and ByteDance have begun to develop their own chips or invest heavily in the chip industry, and actively joined the game of open source on system software, e.g. Apollo autopilot platform and PaddlePaddle deep learning framework. The cutting-edge demands from chip vendors and Internet giants have ignited the interest of academic research on system software. Many research results have gained international influence, such as the virtualization, IPC/RPC, RDMA, and TEE conducted by Prof. Haibo Chen’s group (IPADS Lab) at Shanghai Jiao Tong University, the graph computing and distributed parallel computing conducted by Prof. Wenguang Chen’s group at Tsinghua University, and the NVM/SSD storage system conducted by Prof. Jiwu Shu’s group at Tsinghua University/Xiamen University.
{"title":"Preface: Special Issue on Advances in System Software","authors":"Yanjun Wu","doi":"10.21655/ijsi.1673-7288.00245","DOIUrl":"https://doi.org/10.21655/ijsi.1673-7288.00245","url":null,"abstract":"System software, the software that manages the hardware and supports the applications in computing systems, is a core component of IT ecosystem that covers operating system, programming language, compiler, runtime environment, integrated development environment, etc. In industrial competition, system software is the “moat” and “accelerator” of CPU and the “soil” of APPs. The prosperity of academic research on system software in one country often represents its leadership in core software and hardware technologies in the world. Compared with the prosperity of Internet software or smartphone applications, there is still a large gap in the development of system software in China. The research topics on system software usually come from large processor vendors and large application platforms. In the past, there were few research groups in Chinese universities and institutes on system software due to the lack of demand from domestic industrial giants. People have no choice but use the ISAs, micro-architectures, and platforms from international IT giants, e.g. IBM, Intel, and Qualcomm. Therefore, a virtuous cycle of “industrial demand–academic research–production application–new industrial demand” did not exist in China in past decades. The situation has changed in recent years, and system software has become a hot area in both academia and industry for the first time in the history of China. One reason is the rise of domestic chip vendors. The vendors represented by Huawei and Cambricon have taken the lead in the design of smartphone chips and AI chips, and developed their own system software products, and even make them open source, such as openEuler, OpenHarmony, MindSpore, and BANG. Another reason is the expansion of business stack of Internet companies. Internet giants such as Baidu, Tencent, Alibaba, and ByteDance have begun to develop their own chips or invest heavily in the chip industry, and actively joined the game of open source on system software, e.g. Apollo autopilot platform and PaddlePaddle deep learning framework. The cutting-edge demands from chip vendors and Internet giants have ignited the interest of academic research on system software. Many research results have gained international influence, such as the virtualization, IPC/RPC, RDMA, and TEE conducted by Prof. Haibo Chen’s group (IPADS Lab) at Shanghai Jiao Tong University, the graph computing and distributed parallel computing conducted by Prof. Wenguang Chen’s group at Tsinghua University, and the NVM/SSD storage system conducted by Prof. Jiwu Shu’s group at Tsinghua University/Xiamen University.","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123018949","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}
Pub Date : 1900-01-01DOI: 10.21655/ijsi.1673-7288.00264
Ting Cai, Hui-En Lin, Wuhui Chen, Zibin Zheng, Yang Yu
{"title":"Efficient Blockchain-Empowered Data Sharing Incentive Scheme for Internet of Things","authors":"Ting Cai, Hui-En Lin, Wuhui Chen, Zibin Zheng, Yang Yu","doi":"10.21655/ijsi.1673-7288.00264","DOIUrl":"https://doi.org/10.21655/ijsi.1673-7288.00264","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121883864","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}
Pub Date : 1900-01-01DOI: 10.21655/IJSI.1673-7288.00242
Anbiao Wu, Ye Yuan, Yuliang Ma, Guoren Wang
{"title":"Node Embedding Research Over Temporal Graph","authors":"Anbiao Wu, Ye Yuan, Yuliang Ma, Guoren Wang","doi":"10.21655/IJSI.1673-7288.00242","DOIUrl":"https://doi.org/10.21655/IJSI.1673-7288.00242","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130598636","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}
Pub Date : 1900-01-01DOI: 10.21655/ijsi.1673-7288.00279
Zhong Ming, Lijun Zhang, S. Qin
{"title":"Preface to Special Issue on Analysis and Verification of Intelligent Systems","authors":"Zhong Ming, Lijun Zhang, S. Qin","doi":"10.21655/ijsi.1673-7288.00279","DOIUrl":"https://doi.org/10.21655/ijsi.1673-7288.00279","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122281864","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}
Pub Date : 1900-01-01DOI: 10.21655/ijsi.1673-7288.00284
Hengjun Zhao, Quanzhong Li, Xia Zeng, Zhiming Liu
{"title":"Safe Reinforcement Learning Algorithm and Its Application in Intelligent Control for CPS","authors":"Hengjun Zhao, Quanzhong Li, Xia Zeng, Zhiming Liu","doi":"10.21655/ijsi.1673-7288.00284","DOIUrl":"https://doi.org/10.21655/ijsi.1673-7288.00284","url":null,"abstract":"","PeriodicalId":218849,"journal":{"name":"Int. J. Softw. Informatics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132675982","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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