Xiangyu Wang, Jianfeng Ma, Yinbin Miao, Ximeng Liu, Ruikang Yang
{"title":"Privacy-preserving Diverse Keyword Search and Online Pre-diagnosis in Cloud Computing","authors":"Xiangyu Wang, Jianfeng Ma, Yinbin Miao, Ximeng Liu, Ruikang Yang","doi":"10.1109/services51467.2021.00029","DOIUrl":"https://doi.org/10.1109/services51467.2021.00029","url":null,"abstract":"With the development of the Mobile Healthcare Monitoring Network (MHMN), patients’ data collected by body sensors not only allows patients to monitor their health or make online pre-diagnosis but also enables clinicians to make proper decisions by utilizing data mining techniques. In MHMN, patients’ personal data are collected by sensors per second and uploaded to the cloud server as multi-dimension vectors, cloud server stores the personal data as well as sends monitoring information to the hospital when the real-time data is abnormal. Hospital users (i.e., doctors, etc.) may query some samples which contain certain textual keywords or digital keywords in certain ranges for disease diagnosis or medical research. For example, a certain hospital user may query all samples with textual keywords ‘cancer; diabetes’ and digital vectors ‘age’ ∈ [30,50], ‘blood sugar’ ∈ [4,8], ‘heart rhythm’ ∈ [70,80]. Besides, the potential value of massive medical data has attracted considerable interests recently, for example, valuable results in diagnosis model can be yield with large-scale aggregation analysis of personal medical data. The cloud server can build a diagnosis model using data mining technology over massive data, so that hospital users or pre-diagnosis users upload medical data (i.e., age, blood pressure, blood sugar, etc.) to the cloud for diagnosis.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128602563","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":"Towards Purpose Driven Content Interaction Modeling and Processing based on DIKW","authors":"Yue Huang, Yucong Duan","doi":"10.1109/services51467.2021.00032","DOIUrl":"https://doi.org/10.1109/services51467.2021.00032","url":null,"abstract":"In this information and regularization era, people will encounter a variety of forms in their daily life and office, such as online shopping to fill in the recipient information, travel to fill in the epidemic prevention information and so on. People classify these as content filling problems. In the face of these forms, there are many problems, such as repeated filling, error, troublesome, leakage of information and so on. However, existing automatic filling technology often only stays at the level of data or information migration, which is difficult to deal with the above problems. Moreover, it does not analyze purpose of the preparer and the form in the filling process. This is easy to produce filling behavior contrary to purpose of the preparer. Aiming at this kind of problem, we proposes a content filling data, information, knowledge and purpose(DIKP) modeling method. This method transforms the contents of preparer and form into data, information, knowledge and purpose, and establishes DIKP system. Then, driven by the purpose of the preparer, we fully analyze and calculate the DIKP systems of preparer and form. We judge and grade the filling value. We fill the content through the methods such as comparison of purpose, reducing uncertainty, fuzzy transmission and content verification to achieve intelligence and rationality.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132660408","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":"Research on Service Aggregation Driving Mechanism of “Virtual Nursing Home” Based on Evolutionary Game","authors":"Z. Ren, Guangqing Zhou","doi":"10.1109/services51467.2021.00042","DOIUrl":"https://doi.org/10.1109/services51467.2021.00042","url":null,"abstract":"In response to the problem of seriously increasing aging population, a new mode called “virtual nursing home” was proposed which relies on new information technology. Although the mode is an ideal means to realize the aggregation of elderly care services, it is faced with such practical problems as the low willings to participate, which makes it difficult to realize the synergy effect. The aim of this paper is thus to realize the “virtual nursing home service aggregation”, we set up three main bodies (service providers, platform model, government) in a numerical MATLAB simulation and studied the effect on service aggregation. Results demonstrate that the government, as an exogenous variable of the service aggregation system, has a great impact on the system due to its supervision probability, government reward and government penalty. Finally, from the perspective of government inspection probability, government incentive and punishment, some suggestions are put forward for the service aggregation of “virtual nursing home”.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125792711","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":"A Modeling and Engineering Methodology for Developing Internet of Services from Scratch","authors":"Jianan Li, Jingying Wang, Hanchuan Xu, Zhongjie Wang, Xiaofei Xu","doi":"10.1109/services51467.2021.00040","DOIUrl":"https://doi.org/10.1109/services51467.2021.00040","url":null,"abstract":"In the Internet of Services(IoS), user requirements are becoming more and more complex, which leads to higher requirements put forward for the design and implementation of services. On the other hand, service systems are moving to the cloud, and the new requirements for the service are high availability, high scalability, easy deployment and maintenance, etc. To address these challenges, this paper proposes a modeling and engineering approach for developing services from scratch. This modeling approach uses the classical MDA concept to abstractly model the user’s value quality expectation and correlate the functional model with the user’s value quality in a concrete business scenario. At the same time, it incorporates the concept of DevOps and uses microservice architecture to realize service systems, and then obtains a service solution through the design of value-quality-constrained microservices. We implement a modeling tool to assist designers in the design and implementation of services according to the modeling approach, and validate the feasibility and practicality of the modeling approach on the health care case.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123439730","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":"Plenary Panel 2 - The Future of Digital Health: Bridging Behavioral Science and Engineering with Intensive Longitudinal Assessment","authors":"","doi":"10.1109/services51467.2021.00059","DOIUrl":"https://doi.org/10.1109/services51467.2021.00059","url":null,"abstract":"","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131599756","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":"Message from Congress General Chairs","authors":"","doi":"10.1109/services51467.2021.00006","DOIUrl":"https://doi.org/10.1109/services51467.2021.00006","url":null,"abstract":"","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115011552","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":"Service Recommendation based on Smart Contract and DIKW","authors":"Haiyang Zhang, Yuxiao Lei, Yucong Duan","doi":"10.1109/services51467.2021.00036","DOIUrl":"https://doi.org/10.1109/services51467.2021.00036","url":null,"abstract":"With the development of Internet technology, the number of Web services is growing rapidly, and various types of service recommendation systems emerge in a rapid stream. Although all major service recommendation systems show efficient data processing and service recommendation performance, most of the existing service recommendation systems are developed based on a centralized platform, with functions and data concentrated on a central server. There are still many problems with this over-centralized authority, such as data tamper, data leakage and so on. In response to the above problems, we designed and implemented a service recommendation system based on smart contracts and DIKW (Data, Information, Knowledge and Wisdom). The system data is stored in the blockchain, which effectively prevents data from being tampered. At the same time, the operating environment of the system is the decentralized environment of the Ethereum alliance chain, which overcomes the centralization drawbacks of the traditional service recommendation system and provides a new solution to the existing problems in the service recommendation domain.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124817305","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":"A Learning Automata-based Scheduling for Deadline Sensitive Task in The Cloud","authors":"Sampa Sahoo, B. Sahoo, A. K. Turuk","doi":"10.1109/services51467.2021.00021","DOIUrl":"https://doi.org/10.1109/services51467.2021.00021","url":null,"abstract":"Cloud computing is a revolutionary paradigm, which allows applications to run in a virtualized environment. The application runs on a virtual cloud resource makes the system scalable and cost-efficient. Noticeably many applications, such as healthcare systems, video streaming, Internet of Things (IoT) running in the cloud, are real-time in nature, i.e., these applications demand responses within a particular time limit, i.e., deadline. To meet the requirement of such applications, a Cloud Service Provider (CSP) must have a sufficient number of cloud resources (virtual machines). Further, the ever-growing demand for applications forces a CSP to deploy more and more cloud resources. Inevitably, the massive count of cloud resources in a cloud data center consumes a tremendous amount of energy. Specifically, it becomes cumbersome to offer services to deadline-sensitive tasks while minimizing energy consumption. An efficient task scheduling is an attractive way to reduce energy usage while ensuring satisfactory services for cloud users. Learning Automata (LA) is a reinforcement-based adaptive decision-making unit that learns and selects the best action from a set of actions applied in a dynamic environment. Similar to LA, in task scheduling, the best task and virtual machine combinations are chosen from a set of available combinations. In this context, this paper implemented the LA technique to solve a bi-objective deadline-sensitive task scheduling problem which includes minimization of energy consumption and makespan. At first, a learning automata-based scheduling framework is designed for deadline-sensitive tasks in the cloud. Later, a scheduling algorithm, namely, the LA-based Scheduling (LAS) algorithm, is proposed. The LAS algorithm exploits the heterogeneity of tasks and virtual machines (VMs) while guaranteeing the task’s deadline. Extensive simulation is carried out to designate the effectiveness and applicability of LAS for deadline-sensitive task scheduling in the heterogeneous cloud environment.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127010308","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":"Multi-Tenant Cloud-Edge Workflow Scheduling With Priority and Deadline Constraints","authors":"Dong Pan, Long Chen, Xiaoping Li","doi":"10.1109/services51467.2021.00048","DOIUrl":"https://doi.org/10.1109/services51467.2021.00048","url":null,"abstract":"The maximization of the Quality of Service (QoS) for multi-tenants is one of the key issues for cloud-edge service providers. Limited computing resources, different priorities, and deadlines of tenants make it difficult to satisfy the demands of all the multi-tenants. This paper considers the problem of scheduling limited cloud-edge resources to multi-tenant workflow applications with priority and deadline constraints. A level-based iterative greedy algorithm for the problem is proposed. The algorithm defines a priority-based multi-tenant instance success entropy to measure the total quality of service. The destruction & reconstruction and local search of the algorithm is performed based on the level of tasks. The proposed algorithm is compared to modified classical algorithms for similar problems. Experimental results demonstrate the effectiveness of the proposal for the considered problem.","PeriodicalId":210534,"journal":{"name":"2021 IEEE World Congress on Services (SERVICES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133101903","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}