Appraisal of Cloud Multi-Tenant Database Infrastructure Usability in Public-Safety and Emergency Delivery Services

Abstract

In this era of multiplicity of security challenges, information technology (IT) techniques and infrastructures could enhance public safety services. Cloud computing models can serve hundreds of thousands of customers using sharable resource (database) to reduce costs and offer performance. With these models, organizations no longer have to buy, build and manage costly computing resources to provide for security via public safety networking. IaaS and SaaS models made IT more affordable than Traditional IT. Data activities (processing, storage, management) and collaboration over ‘encapsulated’ Internet environment is enabled for optimal performance. This study critically appraises multi-tenant database as IT infrastructure and/or software for public safety networking where robust, fail-safe mission critical communication deliveries are expedient. Emergency situations and daily routine of public safety agencies require more broadband services for life-saving information to be securely/reliably transmitted between control centers and field responders using separate databases. Through virtualization, database is separated from infrastructure but is also conceptualized as infrastructure for users/customers to benefit as tenants and multi-tenants (MTs) in data centres. Using decision tree and Bayesian classifier models, database is classified into public utility (PU) or emergency need (EN) servicing two-defined customer segments: low-workload and high-workload tenants. A confusion matrix detailed the service requirement instances’ analysis of MT infrastructure for performance while the research concludes by iterating MT database excellence for collaborative work. Cloud concept, IaaS and SaaS as power station and core modules leverage MT database as infrastructure and software to increase usability and provide trade-off between storage-space (cost) and performance. It helps overcome challenges of continuous changing and higher-frequency data-refreshing needs of both emergent and autonomous computing.