Resource Description Framework (RDF) inherently supports data mergers from various resources into a single federated graph that can become very large even for an application of modest size. This results in severe performance degradation in the execution of RDF queries. As every RDF query essentially traverses a graph to find the output of the Query, an efficient path traversal reduces the execution time of RDF queries. Hence, query path optimization is required to reduce the execution time as well as the cost of a query. Query path optimization is an NP-hard problem that cannot be solved in polynomial time. Genetic algorithms have proven to be very useful in optimization problems. We propose a hybrid genetic algorithm for query path optimization. The proposed algorithm selects an initial population using iterative improvement thus reducing the initial solution space for the genetic algorithm. The proposed algorithm makes significant improvements in the overall performance. We show that the overall number of joins for complex queries is reduced considerably, resulting in reduced cost.
{"title":"RDF Query Path Optimization Using Hybrid Genetic Algorithms: Semantic Web vs. Data-Intensive Cloud Computing","authors":"Qazi Mudassar Ilyas, Muneer Ahmad, Sonia Rauf, Danish Irfan","doi":"10.4018/ijcac.2022010101","DOIUrl":"https://doi.org/10.4018/ijcac.2022010101","url":null,"abstract":"Resource Description Framework (RDF) inherently supports data mergers from various resources into a single federated graph that can become very large even for an application of modest size. This results in severe performance degradation in the execution of RDF queries. As every RDF query essentially traverses a graph to find the output of the Query, an efficient path traversal reduces the execution time of RDF queries. Hence, query path optimization is required to reduce the execution time as well as the cost of a query. Query path optimization is an NP-hard problem that cannot be solved in polynomial time. Genetic algorithms have proven to be very useful in optimization problems. We propose a hybrid genetic algorithm for query path optimization. The proposed algorithm selects an initial population using iterative improvement thus reducing the initial solution space for the genetic algorithm. The proposed algorithm makes significant improvements in the overall performance. We show that the overall number of joins for complex queries is reduced considerably, resulting in reduced cost.","PeriodicalId":51857,"journal":{"name":"International Journal of Cloud Applications and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70451544","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 : 2022-01-01DOI: 10.4018/ijcac.2022010106
V. Vinothina, G. JasmineBeulah, Sridaran Rajagopal
Resource allocation and scheduling algorithms are the two essential factors that determine the satisfaction of cloud users. The major cloud resources involved here are servers, storage, network, databases, software and so on based on requirements of customers. In the competitive scenario, each service provider tries to use factors like optimal configuration of resources, pricing, Quality of Service (QoS) parameters and Service Level Agreement (SLA) in order to benefit cloud users and service providers. Since, many researchers have proposed different scheduling algorithms and resource allocation strategies, it becomes a cumbersome task to conclude which ones really benefit customers and service providers. Hence, this paper analyses and presents the most relevant considerations that would help the cloud researchers in achieving their goals in terms of mapping of tasks to cloud resources.
{"title":"Review on Mapping of Tasks to Resources in Cloud Computing","authors":"V. Vinothina, G. JasmineBeulah, Sridaran Rajagopal","doi":"10.4018/ijcac.2022010106","DOIUrl":"https://doi.org/10.4018/ijcac.2022010106","url":null,"abstract":"Resource allocation and scheduling algorithms are the two essential factors that determine the satisfaction of cloud users. The major cloud resources involved here are servers, storage, network, databases, software and so on based on requirements of customers. In the competitive scenario, each service provider tries to use factors like optimal configuration of resources, pricing, Quality of Service (QoS) parameters and Service Level Agreement (SLA) in order to benefit cloud users and service providers. Since, many researchers have proposed different scheduling algorithms and resource allocation strategies, it becomes a cumbersome task to conclude which ones really benefit customers and service providers. Hence, this paper analyses and presents the most relevant considerations that would help the cloud researchers in achieving their goals in terms of mapping of tasks to cloud resources.","PeriodicalId":51857,"journal":{"name":"International Journal of Cloud Applications and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70451991","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 : 2022-01-01DOI: 10.4018/ijcac.2022010107
N. Kumbhojkar, Arun Balakrishna Menon
Enterprises are adopting digital transformation with an exponential rate to drive growth through new business models and the use of digital technologies. Digital transformation is a business imperative rather than technology imperative. Hence, customer experience during and post-transformation is key to the success of the digital transformation. The present paper proposes an Integrated Predictive Experience Management Framework (IPEMF) for improving customer experience. IPEMF is- a structured and methodological business processes centric connected experience framework with the customer at the centre. The uniqueness of IPEMF is that it seamlessly integrates business processes, technology, organisation, and customer behaviour. It is agnostic of the business vertical or the geography. The framework puts forth an approach to predict the impact on customer experience proactively and provides a feedback loop to help continuously improve the experience. IPEMF helps enterprises build intuitive, trusted relationships and hyper-personalised customer experience through the customer journey.
{"title":"Integrated Predictive Experience Management Framework (IPEMF) for Improving Customer Experience: In the Era of Digital Transformation","authors":"N. Kumbhojkar, Arun Balakrishna Menon","doi":"10.4018/ijcac.2022010107","DOIUrl":"https://doi.org/10.4018/ijcac.2022010107","url":null,"abstract":"Enterprises are adopting digital transformation with an exponential rate to drive growth through new business models and the use of digital technologies. Digital transformation is a business imperative rather than technology imperative. Hence, customer experience during and post-transformation is key to the success of the digital transformation. The present paper proposes an Integrated Predictive Experience Management Framework (IPEMF) for improving customer experience. IPEMF is- a structured and methodological business processes centric connected experience framework with the customer at the centre. The uniqueness of IPEMF is that it seamlessly integrates business processes, technology, organisation, and customer behaviour. It is agnostic of the business vertical or the geography. The framework puts forth an approach to predict the impact on customer experience proactively and provides a feedback loop to help continuously improve the experience. IPEMF helps enterprises build intuitive, trusted relationships and hyper-personalised customer experience through the customer journey.","PeriodicalId":51857,"journal":{"name":"International Journal of Cloud Applications and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70452108","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 : 2022-01-01DOI: 10.4018/ijcac.2022010110
Sharifah Ahmed Alamer, Qazi Mudassar Ilyas, Muneer Ahmad, Danish Irfan
The exponential growth of big data demands an efficient knowledge discovery. The electronic medical records of patients on medical data Clouds contain implicit medical information. Although the periodic health examination (PHE) reports describing a set of screening tests for healthy individuals performed periodically, common individuals require the assistance of an expert to interpret the results for a medical opinion. This research study proposes a metaphoric design of Electronic Medical Record (EMR) for PHE reports of patients. The outcomes of this study glimpses useful findings for the common people in the self-interpretation of their medical reports. Besides, among a variety of solutions, the study uses the metaphoric representation to convert the numerical data and medical terminology to familiar graphic representations from real life. The study identifies the detailed requirements to propose a conceptual architecture for metaphoric EMR reports. The future work will result in a prototype design, evaluation, and refinement of metaphors based on stakeholders' feedback.
{"title":"A Metaphoric Design of Electronic Medical Record (EMR) for Periodic Health Examination Reports: An Initiative to Cloud's Medical Data Analysis","authors":"Sharifah Ahmed Alamer, Qazi Mudassar Ilyas, Muneer Ahmad, Danish Irfan","doi":"10.4018/ijcac.2022010110","DOIUrl":"https://doi.org/10.4018/ijcac.2022010110","url":null,"abstract":"The exponential growth of big data demands an efficient knowledge discovery. The electronic medical records of patients on medical data Clouds contain implicit medical information. Although the periodic health examination (PHE) reports describing a set of screening tests for healthy individuals performed periodically, common individuals require the assistance of an expert to interpret the results for a medical opinion. This research study proposes a metaphoric design of Electronic Medical Record (EMR) for PHE reports of patients. The outcomes of this study glimpses useful findings for the common people in the self-interpretation of their medical reports. Besides, among a variety of solutions, the study uses the metaphoric representation to convert the numerical data and medical terminology to familiar graphic representations from real life. The study identifies the detailed requirements to propose a conceptual architecture for metaphoric EMR reports. The future work will result in a prototype design, evaluation, and refinement of metaphors based on stakeholders' feedback.","PeriodicalId":51857,"journal":{"name":"International Journal of Cloud Applications and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70451828","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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