| S. No. | IEEE TITLE | ABSTRACT | IEEE YEAR |
| 1 | CDA Generation and Integration for Health Information Exchange Based on Cloud Computing System | Successful deployment of Electronic Health Record helps improve patient safety and quality of care, but it has the prerequisite of interoperability between Health Information Exchange at different hospitals. The Clinical Document Architecture (CDA) developed by HL7 is a core document standard to ensure such interoperability, and propagation of this document format is critical for interoperability. Unfortunately, hospitals are reluctant to adopt interoperable HIS due to its deployment cost except for in a handful countries. A problem arises even when more hospitals start using the CDA document format because the data scattered in different documents are hard to manage. In this paper, we describe our CDA document generation and integration Open API service based on cloud computing, through which hospitals are enabled to conveniently generate CDA documents without having to purchase proprietary software. Our CDA document integration system integrates multiple CDA documents per patient into a single CDA document and physicians and patients can browse the clinical data in chronological order. Our system of CDA document generation and integration is based on cloud computing and the service is offered in Open API. Developers using different platforms thus can use our system to enhance interoperability. | 2016 |
| 2 | Heuristics for Provisioning Services to Workflows in XaaS Clouds | In XaaS clouds, resources as services (e.g., infrastructure, platform and software as a service) are sold to applications such as scientific and big data analysis workflows. Candidate services with various configurations (CPU type, memory size, number of machines and so on) for the same task may have different execution time and cost. Further, some services are priced rented by intervals that be shared among tasks of the same workflow to save service rental cost. Establishing a task-mode (service) mapping (to get a balance between time and cost) and tabling tasks on rented service instances are crucial for minimizing the client-oriented cost to rent services for the whole workflow. In this paper, a multiple complete critical-path based heuristic (CPIS) is developed for the task-mode mapping problem. A list based heuristic (LHCM) concerning the task processing cost and task-slot matching is developed for tabling tasks on service instances based on the result of task-mode mapping. Then, the effectiveness of the proposed CPIS is compared with that of the previously proposed CPIL, the existing state-of-the-art heuristics including PCP, SC-PCP ( an extension to PCP), DET, and CPLEX. The effectiveness of the proposed LHCM is evaluated with its use with different task-mode mapping algorithms. Experimental results show that the proposed heuristics can reduce 24 percent of the service renting cost than the compared algorithms on the test benchmarks at most for non-shareable services. In addition, half of the service renting cost could be saved when LHCM is applied to consolidate tasks on rented service instances. | 2016 |
| 3 | Trust-but-Verify: Verifying Result Correctness of Outsourced Frequent Itemset Mining in Data-Mining-As-a-Service Paradigm | Cloud computing is popularizing the computing paradigm in which data is outsourced to a third-party service provider (server) for data mining. Outsourcing, however, raises a serious security issue: how can the client of weak computational power verify that the server returned correct mining result? In this paper, we focus on the specific task of frequent itemset mining. We consider the server that is potentially untrusted and tries to escape from verification by using its prior knowledge of the outsourced data. We propose efficient probabilistic and deterministic verification approaches to check whether the server has returned correct and complete frequent itemsets. Our probabilistic approach can catch incorrect results with high probability, while our deterministic approach measures the result correctness with 100 percent certainty. We also design efficient verification methods for both cases that the data and the mining setup are updated. We demonstrate the effectiveness and efficiency of our methods using an extensive set of empirical results on real datasets. | 2016 |