A Hybrid Batch Mode Fault Tolerance Strategy in Desktop Grids

Desktop grids make use of unused resources of personal computers provided by volunteers to work as a huge processor and make them available to users that need them. The rate of heterogeneity, volatility, and unreliability is higher in case of a desktop grid in comparison to conventional systems. Therefore, the application of fault tolerance strategies becomes an inevitable requirement. In this article, a hybrid fault tolerance strategy is proposed which works in three phases. First, two phases deal with the task and resource scheduling in which appropriate scheduling decisions are taken in order to select the most suitable resource for a task. Even if any failure occurs, it is then recovered in the third phase by using rescheduling and checkpointing. The proposed strategy is compared against existing hybrid fault tolerance scheduling strategies and ensures a 100% success rate and processor utilization and outperforms by a factor of 3.5%, 0.4%, and 0.1% when turnaround time, throughput, and makespan, respectively, are taken into account

A Hybrid Batch Mode Fault Tolerance Strategy in Desktop Grids

Desktop grids make use of unused resources of personal computers provided by volunteers to work as a huge processor and make them available to users that need them. The rate of heterogeneity, volatility, and unreliability is higher in case of a desktop grid in comparison to conventional systems. Therefore, the application of fault tolerance strategies becomes an inevitable requirement. In this article, a hybrid fault tolerance strategy is proposed which works in three phases. First, two phases deal with the task and resource scheduling in which appropriate scheduling decisions are taken in order to select the most suitable resource for a task. Even if any failure occurs, it is then recovered in the third phase by using rescheduling and checkpointing. The proposed strategy is compared against existing hybrid fault tolerance scheduling strategies and ensures a 100% success rate and processor utilization and outperforms by a factor of 3.5%, 0.4%, and 0.1% when turnaround time, throughput, and makespan, respectively, are taken into account

A Resource Allocation Model for Desktop Clouds

Cloud computing is a new paradigm that promises to move IT a step further towards utility computing, in which computing services are delivered as a utility service. Traditionally, Cloud employs dedicated resources located in one or more data centres in order to provide services to clients. Desktop Cloud computing is a new type of Cloud computing that aims at providing Cloud capabilities at low or no cost. Desktop Clouds harness non dedicated and idle resources in order to provide Cloud services. However, the nature of such resources can be problematic because they are prone to failure at any time without prior notice. This research focuses on the resource allocation mechanism in Desktop Clouds.The contributions of this chapter are threefold. Firstly, it defines and explains Desktop Clouds by comparing them with both Traditional Clouds and Desktop Grids. Secondly, the paper discusses various research issues in Desktop Clouds. Thirdly, it proposes a resource allocation model that is able to handle node failures.

Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

Task Scheduling in Desktop Grids: Open Problems

We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, “needle in a haystack” paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids.