3,626 research outputs found
Scalable user data management in multi-tenant cloud environments
The rise of cloud computing and its elastic, on-demand resource provisioning introduces the need for a flexible and scalable multi-tenant architecture. In a multi-tenant application every tenant (client) makes use of shared application instances, but each tenant typically has its own user data. The shared application instance behaves like a private instance by guaranteeing both data separation and performance separation for every tenant. As the number of tenants increases, the amount of data grows. A scalable solution for the storage is needed, allowing tenant data to be divided over multiple database instances, but taking into account performance isolation and custom data assurance policies.
In this paper we introduce an abstraction layer for achieving high scalability for the storage of tenant data. This layer uses data allocation algorithms to determine an acceptable allocation of tenant data to different databases. We describe a mathematical model for the allocation of tenant data which can be optimized using existing linear programming techniques, and introduce the BDAA-n and FDAA, two algorithms that will find an optimal allocation of data by iterating over the possible permutations. The proposed solutions are evaluated based on their flexibility, complexity and efficiency. The flexibility of the BDAA and FDAA makes them easy to customize and extend to fit most scenarios, but the algorithms will achieve best results for tenants with a limited number of subtenants. Linear programming is an alternative for tenants with a higher number of subtenants, but the customizability of the algorithm for specific use cases is limited due to the need for linear functions
CyberGuarder: a virtualization security assurance architecture for green cloud computing
Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
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