QoS and preemption aware scheduling in federated and virtualized Grid computing environments

Abstract

Resource provisioning is one of the challenges in federated Grid environments. In these environments each Grid serves requests from external users along with local users. Recently, this resource provisioning is performed in the form of Virtual Machines (VMs). The problem arises when there are insufficient resources for local users to be served. The problem gets complicated further when external requests have different QoS requirements. Serving local users could be solved by preempting VMs from external users which impose overheads on the system. Therefore, the question is how the number of VM preemptions in a Grid can be minimized. Additionally, how we can decrease the likelihood of preemption for requests with more QoS requirements. We propose a scheduling policy in InterGrid, as a federated Grid, which reduces the number of VM preemptions and dispatches external requests in a way that fewer requests with QoS constraints get affected by preemption. Extensive simulation results indicate that the number of VM preemptions is decreased at least by 60%, particularly, for requests with more QoS requirements.

Introduction

Resource provisioning for user applications is one of the main challenges and research areas in federated Grid environments. Federated Grids, such as InterGrid, enable sharing, selection, and aggregation of resources across several Grids, which are connected through high bandwidth network connections. Nowadays, heavy computational requirements, mostly from scientific communities, are supplied by these federated environments such as PlanetLab [8]. Job abstraction is widely used in resource management of Grid environments. However, due to advantages of Virtual Machine (VM) technology, recently, many resource management systems have emerged to enable another style of resource management based on lease abstraction [38].

InterGrid, as a federated Grid environment, also aims to provide a software system that interconnects islands of virtualized Grids. It provides resources in the form of VMs and allows users to create execution environments for their applications on the VMs [12]. In each constituent Grid, the provisioning rights over several clusters inside the Grid are delegated to the InterGrid Gateway (IGG). IGGs coordinate resource allocation for requests coming from other Grids (external users) through predefined contracts between Grids [11]. On the other hand, local users in each cluster send their requests directly to the local resource manager (LRM) of the cluster.

Hence, resource provisioning is done for two different types of users, namely: local users and external users. As illustrated in Fig. 1, local users (hereafter termed as local requests), refer to users who ask their local cluster resource manager (LRM) for resources. External users (hereafter termed as external requests) are those users who send their requests to a gateway (IGG) to get access to a larger amount of shared resources. Typically, local requests have priority over external requests in each cluster [6]. In other words, the organization that owns the resources would like to ensure that its community has priority access to the resources. Under such a circumstance, external requests are welcome to use resources if they are available. Nonetheless, external requests should not delay the execution of local requests.

In our previous research [33], we demonstrated how preemption of external requests in favor of local requests can help serving more local requests. However, the side-effects of preemption are twofold:

• From the system owner perspective, preempting VMs imposes a notable overhead to the underlying system and degrades resource utilization [38].

• From the external user perspective, preemption increases the response time of the external requests.

As a result, both the resource owner (who prefers to increase resource utilization) and external users (who are interested in shorter response time) benefit from fewer VM preemptions in the system. We believe that with the extensive current trend in applying VMs in distributed systems, and considering preemption as an outstanding feature of VMs, it is crucial to investigate policies that minimize these side-effects. Therefore, one problem we are dealing with in this research is how to decrease the number of VM preemptions that take place in a virtualized Grid environment.

The problem gets complicated further when external requests have different levels of Quality of Service (QoS) requirements (also termed different request types in this paper). For instance, some external requests can have deadlines whereas others do not. Preemption affects the QoS constraints of such requests. This implies that some external requests are more valuable than others and, therefore, more precedence should be given to valuable requests by reducing the chance of preemption of these requests.

To address these problems, in this paper, we propose a QoS and preemption-aware scheduling policy for a virtualized Grid which contributes resources to a federated Grid. This scheduling policy comprises of two parts.

The first part, called workload allocation policy, determines the fraction of external requests that should be allocated to each cluster in a way that minimizes the number of VM preemptions. The proposed policy is based on the stochastic analysis of routing in parallel, non-observable queues. Moreover, this policy is knowledge-free (i.e. it is not dependent on the availability information of the clusters). Thus, this policy does not impose any overhead on the system. However, it does not decide the cluster that each single external request should be dispatched upon arrival. In other words, dispatching of the external requests to clusters is random.

Therefore, in the second part, called dispatch policy, we propose a policy to find out the cluster to which each request should be allocated to. The dispatch policy has the awareness of request types and aims to minimize the likelihood of preempting valuable requests. This is performed by working out a deterministic sequence for dispatching external requests. In summary, our paper makes the following contributions:

• Providing an analytical queuing model for a Grid, based on the routing in parallel non-observable queues.

• Adapting the proposed analytical model to a preemption-aware workload allocation policy.

• Proposing a deterministic dispatch policy to give more priority to more valuable users and meet their QoS requirements.

• Evaluating the proposed policies under realistic workload models and considering performance metrics such as number of VM preemptions, utilization, and average weighted response time.

We utilize InterGrid [10], which is a virtualized federated Grid environment, as the context of our work. In the next section, InterGrid structure is discussed in detail. The rest of this paper is organized as follows: In Section 2, an overview of the InterGrid environment is provided. The proposed analytical queuing model is described in Section 3 which is followed by the preemption-aware scheduling policy in Section 4. Performance evaluation of the proposed policy is reported in Section 5. Then, in Section 6 related research works are introduced. Finally, conclusion and future works are provided in Section 7.