Automatically constructing a composite service from a set of basic services is not desirable in practice because the composition assumption often over-simplifies the realistic constraints and states. We try to propose a stepwise methodology to step-by-step construct a composite service, where the event-driven principle and process declaration principle are used to realize process flexibility, and user knowledge aggregation way is adopted to clarify users' demands and intents. For modeling services with flexibility, service decoupling feature based on events is utilized to decouple different parts of a business process, and to independently define process fragments. Process coordination logic among different process fragments is extracted as independent building blocks such that its enactment can be adapted at run-time. Thus, we get a method to model, deploy and run declarative business processes based on events. At run-time, we propose a service construction assistant to learn the complex relation between user clicks and service quality.
{"title":"Knowledge-Learning Service Construction Based on Events","authors":"Yang Zhang, Junliang Chen","doi":"10.1109/SCC.2016.94","DOIUrl":"https://doi.org/10.1109/SCC.2016.94","url":null,"abstract":"Automatically constructing a composite service from a set of basic services is not desirable in practice because the composition assumption often over-simplifies the realistic constraints and states. We try to propose a stepwise methodology to step-by-step construct a composite service, where the event-driven principle and process declaration principle are used to realize process flexibility, and user knowledge aggregation way is adopted to clarify users' demands and intents. For modeling services with flexibility, service decoupling feature based on events is utilized to decouple different parts of a business process, and to independently define process fragments. Process coordination logic among different process fragments is extracted as independent building blocks such that its enactment can be adapted at run-time. Thus, we get a method to model, deploy and run declarative business processes based on events. At run-time, we propose a service construction assistant to learn the complex relation between user clicks and service quality.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131160762","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}
Large organizations often have multiple branches situated in different locations, each branch may collaborate and learn from other branches' experience. Their Business processes (BPs) share often similar business goals and are slightly different. These branches are eager to develop new process variants to satisfy new requirements. Process execution logs, so called process event logs, can be used to analyze requirement changing situations and efficiently develop BP variants. However, these logs often have heterogeneous data-sources which prevent an easy and dynamic interoperability between different branches. In this paper, we propose a semantic framework tackling this heterogeneity issue. This framework promotes the creation of a semantic knowledge base from process event logs. Using this knowledge base, we offer BP designers the means to discover suitable BP fragments to assist process variant modeling. We performed experiments on a large public dataset and experimental results show that our approach is feasible and accurate in realistic situations.
{"title":"A Semantic Framework Supporting Business Process Variability Using Event Logs","authors":"Karn Yongsiriwit, M. Sellami, Walid Gaaloul","doi":"10.1109/SCC.2016.28","DOIUrl":"https://doi.org/10.1109/SCC.2016.28","url":null,"abstract":"Large organizations often have multiple branches situated in different locations, each branch may collaborate and learn from other branches' experience. Their Business processes (BPs) share often similar business goals and are slightly different. These branches are eager to develop new process variants to satisfy new requirements. Process execution logs, so called process event logs, can be used to analyze requirement changing situations and efficiently develop BP variants. However, these logs often have heterogeneous data-sources which prevent an easy and dynamic interoperability between different branches. In this paper, we propose a semantic framework tackling this heterogeneity issue. This framework promotes the creation of a semantic knowledge base from process event logs. Using this knowledge base, we offer BP designers the means to discover suitable BP fragments to assist process variant modeling. We performed experiments on a large public dataset and experimental results show that our approach is feasible and accurate in realistic situations.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127633658","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}
Shou-lu Hou, Shuai Zhao, B. Cheng, Yong-Yang Cheng, Junliang Chen
Modern Internet of Things (IoT)-aware business processes consist of various geographically dispersed sensor devices. Large amounts of raw data acquired from sensors need to be regularly transmitted to the targeted processes in enterprise data centers, which results in a significant increase in network traffic and latency. It is necessary to execute such processes in a distributed way. A major challenge for distributed business processes is to design an optimal fragmentation and deployment scheme to improve the overall performance of the process. To tackle this challenge, we propose a novel location-based fragmentation algorithm to partition a process, and apply the Kuhn-Munkres algorithm to solve the optimal deployment of process fragments. These distributed fragments can collaborate together to complete a common goal by using a topic-based publish/subscribe infrastructure. This approach can reduce network traffic and save the process execution time. In our experiment, an integrated monitoring process is used to illustrate the effectiveness of the proposed solution. The results show that the performances of distributed execution outperform the centralized one.
{"title":"Fragmentation and Optimal Deployment for IoT-Aware Business Process","authors":"Shou-lu Hou, Shuai Zhao, B. Cheng, Yong-Yang Cheng, Junliang Chen","doi":"10.1109/SCC.2016.91","DOIUrl":"https://doi.org/10.1109/SCC.2016.91","url":null,"abstract":"Modern Internet of Things (IoT)-aware business processes consist of various geographically dispersed sensor devices. Large amounts of raw data acquired from sensors need to be regularly transmitted to the targeted processes in enterprise data centers, which results in a significant increase in network traffic and latency. It is necessary to execute such processes in a distributed way. A major challenge for distributed business processes is to design an optimal fragmentation and deployment scheme to improve the overall performance of the process. To tackle this challenge, we propose a novel location-based fragmentation algorithm to partition a process, and apply the Kuhn-Munkres algorithm to solve the optimal deployment of process fragments. These distributed fragments can collaborate together to complete a common goal by using a topic-based publish/subscribe infrastructure. This approach can reduce network traffic and save the process execution time. In our experiment, an integrated monitoring process is used to illustrate the effectiveness of the proposed solution. The results show that the performances of distributed execution outperform the centralized one.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133565069","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}
Migrating to microservices (microservitization) enables optimising the autonomy, replaceability, decentralised governance and traceability of software architectures. Despite the hype for microservitization , the state of the art still lacks consensus on the definition of microservices, their properties and their modelling techniques. This paper summarises views of microservices from informal literature to reflect on the foundational context of this paradigm shift. A strong foundational context can advance our understanding of microservitization and help guide software architects in addressing its design problems. One such design problem is finalising the optimal level of granularity of a microservice architecture. Related design trade-offs include: balancing the size and number of microservices in an architecture and balancing the nonfunctional requirement satisfaction levels of the individual microservices as well as their satisfaction for the overall system. We propose how self-adaptivity can assist in addressing these design trade-offs and discuss some of the challenges such a selfadaptive solution. We use a hypothetical online movie streaming system to motivate these design trade-offs. A solution roadmap is presented in terms of the phases of a feedback control loop.
{"title":"Microservices and Their Design Trade-Offs: A Self-Adaptive Roadmap","authors":"S. Hassan, R. Bahsoon","doi":"10.1109/SCC.2016.113","DOIUrl":"https://doi.org/10.1109/SCC.2016.113","url":null,"abstract":"Migrating to microservices (microservitization) enables optimising the autonomy, replaceability, decentralised governance and traceability of software architectures. Despite the hype for microservitization , the state of the art still lacks consensus on the definition of microservices, their properties and their modelling techniques. This paper summarises views of microservices from informal literature to reflect on the foundational context of this paradigm shift. A strong foundational context can advance our understanding of microservitization and help guide software architects in addressing its design problems. One such design problem is finalising the optimal level of granularity of a microservice architecture. Related design trade-offs include: balancing the size and number of microservices in an architecture and balancing the nonfunctional requirement satisfaction levels of the individual microservices as well as their satisfaction for the overall system. We propose how self-adaptivity can assist in addressing these design trade-offs and discuss some of the challenges such a selfadaptive solution. We use a hypothetical online movie streaming system to motivate these design trade-offs. A solution roadmap is presented in terms of the phases of a feedback control loop.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134096684","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}
Emerging Internet of Things (IoT) system consists of heterogeneous physical devices that are interconnected via the Internet Protocol (IP) networks. In order to integrate the front-end physical things in the IoT management systems, Business Process Management Systems (BPMS) have gained attention as a viable option. However, enabling the participation of the resource constrained IoT devices in the business process execution raises the question, when considering the agility and energy conservation, whether the device should embed a standard workflow engine or it is better to execute a program representing the workflow. This paper aims to provide a guideline to developers by investigating the two business process workflow execution approaches for resource constrained IoT devices via the comparison of performance and resource usage. The experiments show the comprehensive comparison between the two approaches together with the discussion of the lessons learned.
{"title":"Workflow Model Distribution or Code Distribution? Ideal Approach for Service Composition of the Internet of Things","authors":"Jakob Mass, Chii Chang, S. Srirama","doi":"10.1109/SCC.2016.90","DOIUrl":"https://doi.org/10.1109/SCC.2016.90","url":null,"abstract":"Emerging Internet of Things (IoT) system consists of heterogeneous physical devices that are interconnected via the Internet Protocol (IP) networks. In order to integrate the front-end physical things in the IoT management systems, Business Process Management Systems (BPMS) have gained attention as a viable option. However, enabling the participation of the resource constrained IoT devices in the business process execution raises the question, when considering the agility and energy conservation, whether the device should embed a standard workflow engine or it is better to execute a program representing the workflow. This paper aims to provide a guideline to developers by investigating the two business process workflow execution approaches for resource constrained IoT devices via the comparison of performance and resource usage. The experiments show the comprehensive comparison between the two approaches together with the discussion of the lessons learned.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"59 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993319","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}
With the sweeping progress of services technology and crowdsourcing, individuals are offering their capability as a service and companies are orchestrating them for problem solving over the web. As a consequence, recent years have witnessed a rapid development of a human service ecosystem. In contrast to web service ecosystem, human service ecosystem is more complicated by the fact that humans grow capability overtime and their collaborations typically imply human involvement. It is thus worthy to understand the modeling of evolution of human capabilities and collaborations for optimization and more effective management. This paper proposes a three-layer time-aware heterogeneous network model, and based on it, a novel method is developed to study how human service providers and consumers develop their service provision and orchestrating capabilities as well as how they collaborate with each other. Exploratory analysis uncovers some evolution patterns which open a gateway for building possible applications such as human service recommendation for consumers, human capability development, and mechanism design for platform management.
{"title":"Human-as-a-Service: Growth in Human Service Ecosystem","authors":"Keman Huang, Jinhui Yao, Jia Zhang, Zhiyong Feng","doi":"10.1109/SCC.2016.19","DOIUrl":"https://doi.org/10.1109/SCC.2016.19","url":null,"abstract":"With the sweeping progress of services technology and crowdsourcing, individuals are offering their capability as a service and companies are orchestrating them for problem solving over the web. As a consequence, recent years have witnessed a rapid development of a human service ecosystem. In contrast to web service ecosystem, human service ecosystem is more complicated by the fact that humans grow capability overtime and their collaborations typically imply human involvement. It is thus worthy to understand the modeling of evolution of human capabilities and collaborations for optimization and more effective management. This paper proposes a three-layer time-aware heterogeneous network model, and based on it, a novel method is developed to study how human service providers and consumers develop their service provision and orchestrating capabilities as well as how they collaborate with each other. Exploratory analysis uncovers some evolution patterns which open a gateway for building possible applications such as human service recommendation for consumers, human capability development, and mechanism design for platform management.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124771484","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}
Sen Niu, Guobing Zou, Yanglan Gan, Zhimin Zhou, Bofeng Zhang
The inherent uncertainty of Web service is the most important characteristic due to its deployment and invocation within a real and highly dynamic Internet environment. Web service composition with uncertainty (U-WSC) has become an important research issue in service computing. Although some research has been done on U-WSC via non-deterministic planning in Artificial Intelligence, they cannot handle the situation that uncertain Web services with the same functionality exist in a service repository and could not get all of possible solution plans that constitute an uncertain composition solution for a given request. To solve above research challenges, this paper models a U-WSC problem into a U-WSC planning problem. Accordingly, two novel uncertain planning algorithms using heuristic search called UCLAO* and BHUC, are presented to solve the U-WSC planning problem with state space reduction, which leads to high efficiency of finding a service composition solution. We have conducted empirical experiments based on a running example in e-commerce application as well as our large-scale simulated datasets. The experimental results demonstrate that our proposed algorithms outperform the state-of-the-art non-deterministic planning algorithms in terms of effectiveness, efficiency and scalability.
{"title":"UCLAO* and BHUC: Two Novel Planning Algorithms for Uncertain Web Service Composition","authors":"Sen Niu, Guobing Zou, Yanglan Gan, Zhimin Zhou, Bofeng Zhang","doi":"10.1109/SCC.2016.75","DOIUrl":"https://doi.org/10.1109/SCC.2016.75","url":null,"abstract":"The inherent uncertainty of Web service is the most important characteristic due to its deployment and invocation within a real and highly dynamic Internet environment. Web service composition with uncertainty (U-WSC) has become an important research issue in service computing. Although some research has been done on U-WSC via non-deterministic planning in Artificial Intelligence, they cannot handle the situation that uncertain Web services with the same functionality exist in a service repository and could not get all of possible solution plans that constitute an uncertain composition solution for a given request. To solve above research challenges, this paper models a U-WSC problem into a U-WSC planning problem. Accordingly, two novel uncertain planning algorithms using heuristic search called UCLAO* and BHUC, are presented to solve the U-WSC planning problem with state space reduction, which leads to high efficiency of finding a service composition solution. We have conducted empirical experiments based on a running example in e-commerce application as well as our large-scale simulated datasets. The experimental results demonstrate that our proposed algorithms outperform the state-of-the-art non-deterministic planning algorithms in terms of effectiveness, efficiency and scalability.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129373179","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}
Xuekai Du, ZhiHui Lv, Jie Wu, Chengrong Wu, Shi Chen
There is a trend that more and more enterprises utilize SDN (Software Defined Network) technology to manage the network of their cloud platform. For example, cloud computing datacenters define their own virtual networks or virtual firewalls using SDN controller. Tenants need the network components of cloud platform to call northbound interfaces of SDN controller if they want to manage the network of cloud platform. If there are a large number of tenants, the interaction between the cloud platform and the SDN controller is very frequent. In order to simplify this process, we propose a policy-driven based batch processing network operation SDN controller scheme in which the cloud datacenter manager sends the SDN-related policies to the SDN controller, and the SDN controller processes the policies received according to user's permissions and operations priority. The management of network resources can integrate with other resources management in the cloud datacenter environment effectively. We then build a prototype, a policy-driven SDN controller (PDSDN), to demonstrate the efficiency and performance of our design.
{"title":"PDSDN: A Policy-Driven SDN Controller Improving Scheme for Multi-tenant Cloud Datacenter Environments","authors":"Xuekai Du, ZhiHui Lv, Jie Wu, Chengrong Wu, Shi Chen","doi":"10.1109/SCC.2016.57","DOIUrl":"https://doi.org/10.1109/SCC.2016.57","url":null,"abstract":"There is a trend that more and more enterprises utilize SDN (Software Defined Network) technology to manage the network of their cloud platform. For example, cloud computing datacenters define their own virtual networks or virtual firewalls using SDN controller. Tenants need the network components of cloud platform to call northbound interfaces of SDN controller if they want to manage the network of cloud platform. If there are a large number of tenants, the interaction between the cloud platform and the SDN controller is very frequent. In order to simplify this process, we propose a policy-driven based batch processing network operation SDN controller scheme in which the cloud datacenter manager sends the SDN-related policies to the SDN controller, and the SDN controller processes the policies received according to user's permissions and operations priority. The management of network resources can integrate with other resources management in the cloud datacenter environment effectively. We then build a prototype, a policy-driven SDN controller (PDSDN), to demonstrate the efficiency and performance of our design.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"13 49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129679932","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}
Fitriyah Hasny, Samuel Mensah, Deliang Yi, Chune Li, Richong Zhang
The development of web services and web APIs offers software developers great opportunities for choosing reliable services. However, the quality of these web services are often not available. Existing quality of web service prediction methods adopts the recommender system related techniques to predict the service quality. In these approaches, the behaviour of service invokers do not change. In reality, the service invokers network conditions are changing all the time. This fact inspires us jointly to consider the stability of service invokers network environment when building a prediction model. In specific, a reliability model is adopted for stability calculation and a recommendation algorithm is proposed in this paper. The advantages of our proposed algorithm is confirmed via experiments on a real-life quality of web service data set and comparison with existing quality of web service predicting algorithms.
{"title":"Predicting the Quality of Web Services Based on User Stability","authors":"Fitriyah Hasny, Samuel Mensah, Deliang Yi, Chune Li, Richong Zhang","doi":"10.1109/SCC.2016.124","DOIUrl":"https://doi.org/10.1109/SCC.2016.124","url":null,"abstract":"The development of web services and web APIs offers software developers great opportunities for choosing reliable services. However, the quality of these web services are often not available. Existing quality of web service prediction methods adopts the recommender system related techniques to predict the service quality. In these approaches, the behaviour of service invokers do not change. In reality, the service invokers network conditions are changing all the time. This fact inspires us jointly to consider the stability of service invokers network environment when building a prediction model. In specific, a reliability model is adopted for stability calculation and a recommendation algorithm is proposed in this paper. The advantages of our proposed algorithm is confirmed via experiments on a real-life quality of web service data set and comparison with existing quality of web service predicting algorithms.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120944039","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}
Wei Chen, Chaochao Liang, Yijun Wan, Chushu Gao, Guoquan Wu, Jun Wei, Tao Huang
The operation of a cloud-based IT system (system for short) is time-consuming and error-prone due to the system scale, heterogeneity and configuration dependency. Although administrators can manage their systems with various configuration management tools, a plenty of knowledge spanning various domains is necessary. To alleviate this situation, we present a model-driven service MORE (Model-driven Operation seRvicE) to automate the initial deployment and the dynamic configuration of a system. Firstly, a model is proposed to specify the high-level view of a system in the form of a desired deployment topology. Then the topology model is transformed into executable code automatically, bridging the gap between high-level abstractions and low-level details. With those executable code as input, a runtime framework is designed based on a transaction-based self-configuration protocol to achieve automation and configuration consistency. Finally, we evaluate the service abilities (including modeling system topology, automating system provisioning, performing runtime reconfiguration) with a case study.
{"title":"MORE: A Model-Driven Operation Service for Cloud-Based IT Systems","authors":"Wei Chen, Chaochao Liang, Yijun Wan, Chushu Gao, Guoquan Wu, Jun Wei, Tao Huang","doi":"10.1109/SCC.2016.88","DOIUrl":"https://doi.org/10.1109/SCC.2016.88","url":null,"abstract":"The operation of a cloud-based IT system (system for short) is time-consuming and error-prone due to the system scale, heterogeneity and configuration dependency. Although administrators can manage their systems with various configuration management tools, a plenty of knowledge spanning various domains is necessary. To alleviate this situation, we present a model-driven service MORE (Model-driven Operation seRvicE) to automate the initial deployment and the dynamic configuration of a system. Firstly, a model is proposed to specify the high-level view of a system in the form of a desired deployment topology. Then the topology model is transformed into executable code automatically, bridging the gap between high-level abstractions and low-level details. With those executable code as input, a runtime framework is designed based on a transaction-based self-configuration protocol to achieve automation and configuration consistency. Finally, we evaluate the service abilities (including modeling system topology, automating system provisioning, performing runtime reconfiguration) with a case study.","PeriodicalId":115693,"journal":{"name":"2016 IEEE International Conference on Services Computing (SCC)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116354080","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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