Jochen Stößer

Cloud Computing – A Classification, Business Models, and Research Directions

Lately, a new computing paradigm has emerged: “Cloud Computing”. It seems to be promoted as heavily as the “Grid” was a few years ago, causing broad discussions on the differences between Grid and Cloud Computing. The first contribution of this paper is thus a detailed discussion about the different characteristics of Grid Computing and Cloud Computing. This technical classification allows for a well-founded discussion of the business opportunities of the Cloud Computing paradigm. To this end, this paper first presents a business model framework for Clouds. It subsequently reviews and classifies current Cloud offerings in the light of this framework. Finally, this paper discusses challenges that have to be mastered in order to make the Cloud vision come true and points to promising areas for future research.

A Framework for Commercial Grids—Economic and Technical Challenges

This paper argues that the technology of Grid computing has not yet been adopted in commercial settings due to the lack of viable business models. While in academia Grid technology has already been taken up, the sharing approach among non for-profit organizations is not suitable for enterprises. In this paper, the idea of a Grid market is taken up to overcome this Grid adoption gap. We propose a framework for building up a Grid market and identifies the associated economic and technical challenges. Based on this framework, we identify a catalogue of possible market mechanisms which offer a promising fit to the Grid environment’s characteristics and which may thus help to carry the idea of Grid markets from theory to practice.

Market-based pricing in grids: On strategic manipulation and computational cost

Grid technologies and the related concepts of utility computing and cloud computing enable the dynamic sourcing of computer resources and services, thus allowing enterprises to cut down on hardware and software expenses and to focus on key competencies and processes. Resources are shared across administrative boundaries, e.g. between enterprises and/or business units. In this dynamic and inter-organizational setting, scheduling and pricing become key challenges. Market mechanisms show promise for enhancing resource allocation and pricing in grids. Current mechanisms, however, are not adequately able to handle large-scale settings with strategic users and providers who try to benefit from manipulating the mechanism. In this paper, a market-based heuristic for clearing large-scale grid settings is developed. The proposed heuristic and pricing schemes find an interesting match between scalability and strategic behavior.

Bridging the Adoption Gap-Developing a Roadmap for Trading in Grids

Grid computing describes a computing model that distributes processing across an administratively and locally dispersed infrastructure to create virtual supercomputers at low cost. However, currently Grids are mainly employed within enterprises to connect internal divisions and business units. This paper attempts to explain why Grid market initiatives have failed. The explanation mainly focuses on the object traded in Grid markets. What is needed to extend Grid technologies beyond company borders is a set of mechanisms that enable users to discover, negotiate and pay for the use of Grid services on demand. This paper derives a roadmap for the design of market mechanisms based on a solid understanding of the technical possibilities. This roadmap underlines the need for a catalogue of market mechanisms to increase the impact of Grid markets in commercial settings.

The Power of Preemption in Economic Online Markets

In distributed computer networks where resources are under decentralized control, selfish users will generally not work towards one common goal, such as maximizing the overall value provided by the system, but will instead try to strategically maximize their individual benefit. This shifts the scheduling policy in such systems --- the decision about which user may access what resource --- from being a purely algorithmic challenge to the domain of mechanism design. In this paper we will showcase the benefit of allowing preemptionin such economic online settings regarding the performance of market mechanisms by extending the Decentralized Local Greedy Mechanism of Heydenreich et al. [11]. This mechanism was shown to be 3.281-competitive with respect to total weighted completion time if the players act rationally. We show that the preemptive versionof this mechanism is 2-competitive. As a by-product, preemption allows to relax the assumptions on jobs upon which this competitiveness relies. In addition to this worst case analysis, we provide an in-depth empirical analysis of the average case performanceof the original mechanism and its preemptive extension based on real workload traces. Our empirical findings indicate that introducing preemption improves both the utility and the slowdown of the jobs. Furthermore, this improvement does not come at the expense of low-priority jobs.

A Combinatorial Exchange for Complex Grid Services

The Grid is a promising concept to solve the dilemma of increasingly complex and demanding applications being confronted with the need for a more efficient and flexible use of existing computer resources. Even though Grid technologies have made progress within the context of large enterprises and academic projects, there has not yet been a widespread adoption by public institutions and small enterprises. One barrier to this adoption is the lack of economic paradigms which support the dynamic and efficient sharing of Grid resources by balancing resource scarity and idle capacities. Economic algorithms promise to provide a good fit to the Grid’s inherent strategic dimension by enabling users to express their valuation for computer resources. At the same time they provide incentives to contribute idle resources to the Grid in return for the market price.