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Über dieses Buch

This book constitutes the refereed post-proceedings of the 8th International Workshop on Economics of Grids, Clouds, Systems, and Services, GECON 2011, held in Paphos, Cyprus, in December 2011. The 9 revised full papers presented together with 5 work in progress papers were carefully reviewed and selected from 27 papers. The papers are organized in topical sections on market mechanisms and negotiation; cost models, charging, and trading platforms; resource allocation, scheduling, and admission control; and two work in progress sections: risk assessment and economics of cloud services; and cost-aware adoption of cloud services.



Session A: Market Mechanisms and Negotiation

An Inspiration for Solving Grid Resource Management Problems Using Multiple Economic Models

Economic models can motivate resource providers to share resources across multiple administrations in Grid computing. Our survey on existing economic models in Grid computing identified that different economic models are suitable for different scenarios. In this paper, we conduct an experiment to quantify the strengths and weaknesses of widely proposed economic models in the Grid - Commodity Market, Continuous Double Auction, English Auction, Contract-Net-Protocol and Bargaining. Based on this experimental analysis, we identify regions where a particular economic model outperforms others. Then, we indicate that switching between the economic models could be used to maximize benefits in a specific scenario.

Aminul Haque, Saadat M. Alhashmi, Rajendran Parthiban

Concurrent Negotiations in Cloud-Based Systems

Utilizing cloud-based services, consumers gain a high level of flexibility, but they cannot obtain individual Quality of Service guarantees or request service compositions according to their specific business needs. Therefore, appropriate mechanisms for an automated negotiation of Quality of Service parameters are required that do not only consider the individual business objectives and strategies of the negotiation partners involved, but do also account for the dependencies between the different services and service tiers in cloud computing. This enables enterprises to increase the quality and flexibility of their business processes and lays the foundation for market-based complex service provisioning. In this paper, we present one such negotiation approach and evaluate the application of different negotiation strategies.

Melanie Siebenhaar, The An Binh Nguyen, Ulrich Lampe, Dieter Schuller, Ralf Steinmetz

A Reverse Auction Market for Cloud Resources

The proliferation of the Infrastructure-as-a-Service (IaaS) paradigm has introduced possibilities for trading computational resources on a scale that moves beyond the individual provider level. At present however, the adoption of open markets for trading IaaS resources has been largely unexplored. This paper investigates the design of such an open market. Our focus thereby lies on flexibility and the ability to model and integrate currently deployed pricing schemes of real-world providers instead of imposing new schemes. We discuss the issues encountered by the Continuous Double Auction (CDA) in this regard and introduce a Continuous Reverse Auction (CRA) that is paired with a novel bidding language based on tag and constraint sets.

Joris Roovers, Kurt Vanmechelen, Jan Broeckhove

Session B: Cost Models, Charging, and Trading Platforms

A Cost Model for Hybrid Clouds

Cloud computing aims at allowing customers to utilize computational resources and software hosted by service providers. Thus, it shifts the complex and tedious resource and software management tasks typically done by customers to the service providers. Besides promising to eliminate these obstacles of resource management for consumers, Cloud computing also promises to reduce the cost of IT infrastructure. In particular, it promises to reduce the cost of IT through lower capital and operational expenses, stemming from a Cloud’s economies of scale and from allowing organizations to purchase just as much computer and storage resources as needed whenever needed. A clear specification of savings however requires a detailed specification of the costs incurred. Although there are some efforts to define cost models for Clouds, the need for a comprehensive cost model, which covers all cost factors, is undeniable. In this paper, we cover this gap by suggesting a cost model for hybrid Clouds (i.e., the combinations of a private data center (private Cloud) and the public Cloud). This model is based on a comprehensive literature research on cost factors and the idea of combining cost of data centers and cost for using Clouds. Finally, we demonstrate the workings of the suggested cost model by applying it to a specific Cloud scenario.

Mohammad Mahdi Kashef, Jörn Altmann

How to Do Successful Chargeback for Cloud Services

With pay-per-use pricing models, elastic scaling of resources, and the usage of shared virtualized infrastructure, ‘the Cloud’ offers more efficient use of capital, great cost reductions, and breakthrough agility. Yet, it turns out that to leverage the cloud advantages, organizations have to introduce cloud-specific chargeback practices. That is, they have to allocate IT service costs to business users in a way that reflects service consumption. To help organizations transition to a cloud environment, this work provides an overview of the factors that impact the design of successful cloud-specific chargeback models. The findings can assist organizations in the design of chargeback models that allow the business flexibility and cost reductions associated with the Cloud to be fully leveraged. The results are based on an empirical study involving twenty-five field experts from IBM and its client and partner network.

Hristo Stefanov, Slinger Jansen, Ronald Batenburg, Eugene van Heusden, Ravi Khadka

A Marketplace Framework for Trading Cloud-Based Services

The importance of marketplace frameworks, where demand and supply for electronic services meet, has gained momentum with the recent technological innovations of cloud computing. In particular the emerging market for cloud and XaaS offerings is, in the current early stage of development, scattered and represented by many single offerings. New intermediaries are required for the consolidation of the available service offerings and for providing a one-stop-shopping opportunity for customers. This paper proposes a new cloud marketplace solution that enables on the one hand an integrated platform for the development and selling of XaaS products and on the other hand a one-stop-shopping for customers interested in services. Service providers can merchandise and sell their products through the marketplace supporting the whole lifecycle of these products. Service consumers are provided with a unique personalized service search and resolution engine, helping them to find and customize the products they need.

Andreas Menychtas, Sergio Garcia Gomez, Andrea Giessmann, Anna Gatzioura, Katarina Stanoevska, Jürgen Vogel, Vrettos Moulos

Session C: Resource Allocation, Scheduling, and Admission Control

Client Classification Policies for SLA Negotiation and Allocation in Shared Cloud Datacenters

In Utility Computing business model, the owners of the computing resources negotiate with their potential clients to sell computing power. The terms of the Quality of Service (QoS) to be provided as well as the economic conditions are established in a Service-Level Agreement (SLA). There are situations in which providers must differentiate the SLAs in function of the type of Client that is willing to access the resources or the agreed QoS e.g. when the hardware resources are shared between users of the company that own the resources and external users.

This paper proposes to consider the information of potential users when the SLA is under negotiation to allow providers to prioritize users (e.g. internal users over external users, or preferential users over common users). Two policies for negotiation are introduced: price discrimination and client-aware overselling of resources. The validity of the policies is demonstrated through exhaustive experiments.

Mario Macías, Jordi Guitart

Budget-Deadline Constrained Workflow Planning for Admission Control in Market-Oriented Environments

There is an increasing interest for distributed computing technologies to be delivered through a market-based paradigm, which allows consumers to make use of and pay for services that meet certain Quality of Service requirements. In turn, providers receive income for successful provision of these services. In this paper, we assume an environment with multiple, heterogeneous resources, which provide services of different capabilities and of a different cost. Users want to make use of these services to execute a workflow application, within a certain deadline and budget. The problem considered in this paper is to find a plan for admission control. This allows providers to agree on constraints set by the user and allocate services for the execution of a workflow so that both deadline and budget constraints are met while account is also taken of the existing load (confirmed reservations) in the environment and the planning costs. A novel heuristic is proposed and evaluated using simulation with four different real-world workflow applications.

Wei Zheng, Rizos Sakellariou

Virtual Machine Placement for Predictable and Time-Constrained Peak Loads

We present an approach to optimal virtual machine placement within datacenters for predicable and time-constrained load peaks. A method for optimal load balancing is developed, based on binary integer programming. For tradeoffs between quality of solution and computation time, we also introduce methods to pre-process the optimization problem before solving it. Upper bound based optimizations are used to reduce the time required to compute a final solution, enabling larger problems to be solved. For further scalability, we also present three approximation algorithms, based on heuristics and/or greedy formulations. The proposed algorithms are evaluated through simulations based on synthetic data sets. The evaluation suggests that our algorithms are feasible, and that these can be combined to achieve desired tradeoffs between quality of solution and execution time.

Wubin Li, Johan Tordsson, Erik Elmroth

Session D: Work in Progress: Risk Assessment and Economics of Cloud Services

Risk Assessment in Service Provider Communities

On-line service delivery undertaken between clients and service providers often incurs risks for both the client and the provider, especially when such an exchange takes place in the context of an electronic service market. For the client, the risk involves determining whether the requested service will be delivered on time and based on the previously agreed Service Level Agreement (SLA). Often risk to the client can be mitigated through the use of a penalty clause in an SLA. For the provider, the risk revolves around ensuring that the client will pay the advertised price and more importantly whether the provider will be able to deliver the advertised service to not incur the penalty identified in the SLA. This becomes more significant when the service providers outsource the actual enactment/execution to a data centre – a trend that has become dominant in recent years, with the emergence of infrastructure providers such as In this work we investigate the notion of “risk” from a variety of different perspectives and demonstrate how risk to a service owner (who uses an external, third party data centre for service hosting) can be managed more effectively. A simulation based approach is used to validate our findings.

Ioan Petri, Omer F. Rana, Yacine Rezgui, Gheorghe Cosmin Silaghi

A Game-Theoretical Approach to the Benefits of Cloud Computing

In order to answer the question whether or not to utilize the cloud for processing, this paper aims at identifying characteristics of potential cloud beneficiaries and advisable actions to actually gain financial benefits. A game-theoretic model of an

Infrastructure-as-a-Service (IaaS)

cloud market, covering dynamics of pricing and usage, is suggested. Incorporating the possibility of hybrid clouds (clouds plus own infrastructure) into this model turns out essential for cloud computing being significantly in favor of not only the provider but the client as well. Parameters like load profiles and economy of scale have a huge effect on likely future pricing as well as on a cost-optimal split-up of client demand between a client’s own data center and a public cloud service.

Jörn Künsemöller, Holger Karl

Session E: Work in Progress: Cost-Aware Adoption of Cloud Services

Planning for Optimal Multi-site Data Distribution for Disaster Recovery

In this paper, we present DDP-DR: a Data Distribution Planner for Disaster Recovery. DDP-DR provides an optimal way of backing-up critical business data into data centres (DCs) across several Geographic locations. DDP-DR provides a plan for replication of backup data across potentially large number of data centres so that (i) the client data is recoverable in the event of catastrophic failure at one or more data centres (disaster recovery) and, (ii) the client data is replicated and distributed in an optimal way taking into consideration major business criteria such as cost of storage, protection level against site failures, and other business and operational parameters like recovery point objective (RPO), and recovery time objective (RTO). The planner uses Erasure Coding (EC) to divide and codify data chunks into fragments and distribute the fragments across DR sites or storage zones so that failure of one or more site / zone can be tolerated and data can be regenerated.

Shubhashis Sengupta, K. M. Annervaz

Saga: A Cost Efficient File System Based on Cloud Storage Service

Cloud Storage service providers such as Amazon Simple Storage Service (S3) and Google Storage for Developers offer low-cost and highly available scale storage resource with a simple pay-as-you-go charging model. The cost of running storage systems on such a Cloud Storage service mainly depends on occupied storage space, number of requests and amount of data transfer. Traditional design of storage stack based on disk driver or tape didn’t consider cost as a system metric, hence it brings considerable optimization space for the design of storage system based on Cloud Storage.

In this paper we propose Saga, a user mode file system based on Cloud Storage service, that is designed to support POSIX interface with the goal of minimizing cost. Saga is specially designed under the cost efficient principle that minimizes occupied storage space by store-one-copy and copy-on-write strategies and minimizes number of requests by distinguishing objects loaded by write or read requests. Saga is also efficient from a performance perspective and utilizes parallel characteristics of Cloud Storage to boost the performance. Experimental results show that Saga is cost efficient and works well with general-purpose I/O workloads.

Wei Shi, Dapeng Ju, Dongsheng Wang

Developing a Cost-Effective Virtual Cluster on the Cloud

The Cloud provides highly democratic access to computer services on a pay-per-use basis. A fact that has encouraged many researchers to adopt the Cloud for the processing of large computational tasks and data storage. This has been used in the past for single research endeavours or as mechanism for coping with excessive load on conventional computational resources (clusters). In this paper we investigate, through the use of simulation, the applicability of running an entire computer cluster on the Cloud. We investigate a number of policy decisions which can be made over such a virtual cluster to reduce the running cost and the effect these policies have on the users of the cluster.

A. Stephen McGough

Erratum: Risk Assessment in Service Provider Communities

In the originally published version of the paper “Risk Assessment in Service Provider Communities” the name of the author Yacine Rezgui was misspelled as Yacine Regzui.

Ioan Petri, Omer F. Rana, Yacine Rezgui, Gheorghe Cosmin Silaghi


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