Reliable Provisioning of Spot Instances for Compute-intensive Applications

Cloud computing providers are now offering their unused resources for leasing in the spot market, which has been considered the first step towards a full-fledged market economy for computational resources. Spot instances are virtual machines (VMs) available at lower prices than their standard on-demand counterparts. These VMs will run for as long as the current price is lower than the maximum bid price users are willing to pay per hour. Spot instances have been increasingly used for executing compute-intensive applications. In spite of an apparent economical advantage, due to an intermittent nature of biddable resources, application execution times may be prolonged or they may not finish at all. This paper proposes a resource allocation strategy that addresses the problem of running compute-intensive jobs on a pool of intermittent virtual machines, while also aiming to run applications in a fast and economical way. To mitigate potential unavailability periods, a multifaceted fault-aware resource provisioning policy is proposed. Our solution employs price and runtime estimation mechanisms, as well as three fault tolerance techniques, namely checkpointing, task duplication and migration. We evaluate our strategies using trace-driven simulations, which take as input real price variation traces, as well as an application trace from the Parallel Workload Archive. Our results demonstrate the effectiveness of executing applications on spot instances, respecting QoS constraints, despite occasional failures.Comment: 8 pages, 4 figure

Resource provisioning in Science Clouds: Requirements and challenges

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the needs of high-performance applications, such as local clusters, high-performance computing systems, and computing grids. Different workloads are needed from different computational models, and the cloud is already considered as a promising paradigm. The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads, hence, their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service provider supporting scientific applications

A Reliable and Cost-Efficient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances

Cloud providers sell their idle capacity on markets through an auction-like mechanism to increase their return on investment. The instances sold in this way are called spot instances. In spite that spot instances are usually 90% cheaper than on-demand instances, they can be terminated by provider when their bidding prices are lower than market prices. Thus, they are largely used to provision fault-tolerant applications only. In this paper, we explore how to utilize spot instances to provision web applications, which are usually considered availability-critical. The idea is to take advantage of differences in price among various types of spot instances to reach both high availability and significant cost saving. We first propose a fault-tolerant model for web applications provisioned by spot instances. Based on that, we devise novel auto-scaling polices for hourly billed cloud markets. We implemented the proposed model and policies both on a simulation testbed for repeatable validation and Amazon EC2. The experiments on the simulation testbed and the real platform against the benchmarks show that the proposed approach can greatly reduce resource cost and still achieve satisfactory Quality of Service (QoS) in terms of response time and availability

Hybrid spot instance based resource provisioning strategy in dynamic cloud environment

Utilization of resources to the maximum extent in large scale distributed cloud environment is a major challenge due to the nature of cloud. Spot Instances in the Amazon Elastic Compute Cloud (EC2) are provisioned based on highest bid with no guarantee of task completion but incurs the overhead of longer task execution time and price. The paper demonstrates the last partial hour and cost overhead that can be avoided by the proposed strategy of Hybrid Spot Instance. It aims to provide reliable service to the ongoing task so as to complete the execution without abruptly interrupting the long running tasks by redefining the bid price. The strategy also considers that on-demand resource services can be acquired when spot price crosses on-demand price and thereby availing high reliability. This will overcome the overhead involved during checkpointing, restarting and workload migration as in the existing system, leading to efficient resources usage for both the providers and users. Service providers revenue is carefully optimized by eliminating the free issue of last partial hour which is a taxing factor for the provider. Simulation carried out based on real time price of various instances considering heterogenous applications shows that the number of out-of-bid scenarios can be reduced largely which leads to the increased number of task completion. Checkpointing is also minimized maximally due to which the overhead associated with it is reduced. This resource provisioning strategy aims to provide preference to existing customers and the task which are nearing the execution completion

Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other