Cloud computing has given rise to on-demand service provisioning and massive outsourcing of IT infrastructures and applications to virtual, commoditized ones. Despite the broad Service Level Agreement (SLA) usage in scientific settings, their role in cloud markets is peripheral and misinterpreted. The paper introduces a SLA graph data model that supports automated SLA formalization and data management through a property digraph. The data model is described as a directed graph (digraph). We elaborate on node and edge properties that indicate dependencies in the SLA data management flow. We sketch a realistic scenario of cloud data service provisioning to extract attributes that characterize the data service. The SLA graph model and data service attributes are used to demonstrate the formalization of a SLA template that is managed as a property graph. The graph structure enables the manipulation of SLA information in a modular, extensible way that considers the data flow and all inclusive data dependencies
The paper addresses the issue of Service Level Agreement (SLA) data management for the cloud computing domain. We discuss the SLA anatomy and provide an analysis of SLA data management requirements. The analysis highlights SLA data aspects considering the association of SLA terms with service management operations. Our work proposes a simple, structured way to store and manage SLA information through a digraph data model that is modular, extensible and expressive with respect to data operational dependencies. The proposed SLA digraph considers properties of SLA terms and service component dependencies. We sketch a realistic data-service provisioning scenario, where the proposed SLA digraph is applied. We illustrate the mapping of data service attributes into SLA terms and the role of edge properties in the definition of service dependencies
With the advent of the Internet and Internet-connected devices, modern business applications can experience rapid increases as well as variability in transactional workloads. Database replication has been employed to scale performance and improve availability of relational databases but past approaches have suffered from various issues including limited scalability, performance versus consistency tradeoffs, and requirements for database or application modifications. This paper presents Hihooi, a replication-based middleware system that is able to achieve workload scalability, strong consistency guarantees, and elasticity for existing transactional databases at a low cost. A novel replication algorithm enables Hihooi to propagate database modifications asynchronously to all replicas at high speeds, while ensuring that all replicas are consistent. At the same time, a fine-grained routing algorithm is used to load balance incoming transactions to available replicas in a consistent way. Our thorough experimental evaluation with several well-established benchmarks shows how Hihooi is able to achieve almost linear workload scalability for transactional databases. ! arXiv:2003.07432v2 [cs.DB]
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