A Type-Theoretic Framework for Efficient and Safe Colocation of Periodic Real-time Systems

Desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs) that specify fixed fractions of resource capacities that must be allocated for unencumbered use by the application. The mapping between what constitutes desirable performance and SLAs is not unique: multiple SLA expressions might be functionally equivalent. Having the flexibility to transform SLAs from one form to another in a manner that is provably safe would enable hosting solutions to achieve significant efficiencies. This paper demonstrates the promise of such an approach by proposing a type-theoretic framework for the representation and safe transformation of SLAs. Based on that framework, the paper describes a methodical approach for the inference of efficient and safe mappings of periodic, real-time tasks to the physical and virtual hosts that constitute a hierarchical scheduler. Extensive experimental results support the conclusion that the flexibility afforded by safe SLA transformations has the potential to yield significant savings

MorphoSys: efficient colocation of QoS-constrained workloads in the cloud

In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.National Science Foundation (0720604, 0735974, 0820138, 0952145, 1012798

MORPHOSYS: efficient colocation of QoS-constrained workloads in the cloud

In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the IaaS provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MorphoSys: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of workloads. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. The results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MorphoSys.First author draf

Strategic and operational services for workload management in the cloud

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts' resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework

Strategic and operational services for workload management in the cloud (PhD thesis)

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts’ resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework. (Major Advisor: Azer Bestavros

Colocation as a Service

By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of self-interested users that would benefit from colocation on shared instances. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. CaaS could be incorporated into an IaaS offering by providers; it could be implemented as a value-added proposition by IaaS resellers; or it could be directly leveraged in a peer-to-peer fashion by IaaS users. To establish the practicality of such offerings, this paper presents XCS – a prototype implementation of CaaS on top of the Xen hypervisor. XCS makes specific choices with respect to the various elements of the CaaS framework: it implements strategic services based on a game-theoretic formulation of colocation; it features novel concurrent migration heuristics which are shown to be efficient; and it offers monitoring and accounting services at both the hypervisor and VM layers. Extensive experimental results obtained by running PlanetLab trace-driven workloads on the XCS prototype confirm the premise of CaaS – by demonstrating the efficiency and scalability of XCS, and by quantifying the potential cost savings accrued through the use of XCS

A Domain-Specific Language for Incremental and Modular Design of Large-Scale Verifiably-Safe Flow Networks (Preliminary Report)

We define a domain-specific language (DSL) to inductively assemble flow networks from small networks or modules to produce arbitrarily large ones, with interchangeable functionally-equivalent parts. Our small networks or modules are "small" only as the building blocks in this inductive definition (there is no limit on their size). Associated with our DSL is a type theory, a system of formal annotations to express desirable properties of flow networks together with rules that enforce them as invariants across their interfaces, i.e, the rules guarantee the properties are preserved as we build larger networks from smaller ones. A prerequisite for a type theory is a formal semantics, i.e, a rigorous definition of the entities that qualify as feasible flows through the networks, possibly restricted to satisfy additional efficiency or safety requirements. This can be carried out in one of two ways, as a denotational semantics or as an operational (or reduction) semantics; we choose the first in preference to the second, partly to avoid exponential-growth rewriting in the operational approach. We set up a typing system and prove its soundness for our DSL.Comment: In Proceedings DSL 2011, arXiv:1109.032