A Scored Semantic Cache Replacement Strategy for Mobile Cloud Database Systems

International audienceCurrent mobile cloud database systems are widespread and require special considerations for mobile devices. Although many systems rely on numerous metrics for use and optimization, few systems leverage metrics for decisional cache replacement on the mobile device. In this paper we introduce the Lowest Scored Replacement (LSR) policy-a novel cache replacement policy based on a predefined score which leverages contextual mobile data and user preferences for decisional replacement. We show an implementation of the policy using our previously proposed MOCCAD-Cache as our decisional semantic cache and our Normalized Weighted Sum Algorithm (NWSA) as a score basis. Our score normalization is based on the factors of query response time, energy spent on mobile device, and monetary cost to be paid to a cloud provider. We then demonstrate a relevant scenario for LSR, where it excels in comparison to the Least Recently Used (LRU) and Least Frequently Used (LFU) cache replacement policies

A Persistent Memory-Aware Buffer Pool Manager Simulator for Multi-Tenant Cloud Databases

International audienceNon-Volatile Memory (NVM) is a promising development for Database Management Systems (DBMS), offering abundant and fast storage to complement traditional disk and main memory architectures. NVM introduces additional data migration possibilities to the traditional buffer pool (BP) managers used by the DBMS. Hence, the efficient use of this new technology requires a redesign of the BP manager. For the cloud Database-as-a-Service products, this need for a redesign is further complicated by the traditional cloud providers' goal to minimize the Service Level Agreement (SLA) violation penalties paid to their tenants. Unfortunately, current research in the area does not provide a comprehensive picture of the components constituting a multi-tenant persistent memory aware BP manager for a cloud database that makes use of NVM. Furthermore, researchers lack the software tools needed to quickly prototype and estimate the effectiveness of novel data management policies guiding those components. In this paper, we attempt to remedy both issues, first, by proposing a generalized framework that defines the purpose and the abstract interfaces of various multi-tenant persistent memory-aware BP manager components, and second, by developing and demonstrating a simulator algorithm that is shown to aid in quick testing of different implementations of those BP manager components