A Survey Analysis of Memory Elasticity Techniques

Abstract

Abstract. Elasticity is an important feature in cloud computing environments. This feature allows a Virtual Machine to adapt resource allocation according to the nature of its workload. Until now, most memory elasticity implementations require human intervention. The implementation of memory elasticity is not very straightforward, due to old Operating System concepts; in general an Operating System assumes that all installed memory will be static and will not increase or decrease until the next shutdown. This paper compares two techniques for the implementation of memory elasticity, one based on the concept of Exponential Moving Average and the other based on Page Faults. To compare these modes of implementation, a method to measure allocation efficiency based on the space-time product was used. With an Exponential Moving Average, memory could be used more efficiently. When Page Faults were used as the main criteria to allocate or remove memory, the performance improved when compared to the Exponential Moving Average technique.

Coordinating Vertical Elasticity of both Containers and Virtual Machines

“…For the VM vertical elasticity, there are some works which focus on CPU resizing, e.g, (Lakew et al, 2014) and (Dawoud et al, 2012), while others concentrate on memory resizing, e.g., (Baruchi and Midorikawa, 2011) as well as combination of both such as the work of (Farokhi et al, 2015). (Monsalve et al, 2015) proposed an approach that controls CPU shares of a container, this approach uses CFS scheduling mode.…”

“…Therefore, this paper addresses the combination of vertical elasticity of containers and vertical elasticity of VMs. Many works (Baruchi and Midorikawa, 2011), (Dawoud et al, 2012), (Farokhi et al, 2015) handle the vertical elasticity of VMs, other works (Monsalve et al, 2015), (Paraiso et al, 2016) manage the resources of containers. However, no attention was given to the coordination of both elasticities.…”

Performance-Based Vertical Memory Elasticity

“…has not yet been well investigated; (iii) we have looked at memory elasticity from a performance point of view instead of memory utilization as the most common used indicator of the memory scarcity [4]. In other words, we consider application performance, i.e., response time (RT), as a decision making criterion to scale up or scale down the allocated memory of VMs.…”

“…2, while the used Wikipedia trace has a hourly incremental pattern, the FIFA trace includes sudden and temporal peaks. To facilitate the reproduction of our research, we released the source code (in Python) that prepares these traces 4 . The experiments were conducted on a single Linux Ubuntu 14.04 server, equipped with 16 processors and 32GB of memory.…”