Pricing strategies of an oligopolist in federated cloud markets

In this paper, we study how an oligopolist influences the coalition structure in federated cloud markets. Specifically, we use cooperative game theory to model the circumstances under which a cloud provider prefers to join a cloud federation vis-a-vis consider taking a price offer made by an oligopolist. We consider two price offering strategies for an oligopolist: non-adaptive and adaptive. In non-adaptive strategy, an oligopolist makes a price offer to all the cloud providers simultaneously. It can be noted that the oligopolist can buy-out all the cloud providers by making a price offer which is equal to a core allocation and the total price offer made by the oligopolist is equal to the value of the grand coalition. In adaptive strategy, the oligopolist approaches the cloud providers one after another in a sequential manner. We show that by using the adaptive strategy, the oligopolist can buy-out all the cloud providers at a total price offer which is less than that of the non-adaptive strategy.

Adaptive IWD-based algorithm for deployment of business processes into cloud federations

Purpose The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs. Design/methodology/approach This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models. Findings The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment. Originality/value An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.

Knowledge Management Framework for Cloud Federation

A cloud federation (CF) is an alliance of cloud service providers (CSPs) working together to overcome scalability and portability barriers. However, there are some business challenges (e.g., lack of trust, lack of schemes for revenue sharing, and lack of schemes for resource sharing) and technological challenges (e.g., missing schemes for resource provisioning, lack of coordinated resource management, and little load balancing), causing instability in CFs. As CF alliances pursue strategic goals, they require intensive knowledge sharing. In fact, practitioners have confirmed a positive impact of knowledge management on stability and success of strategic alliances (SA). According to the literature, SAs may also face learning issues such as non–controlled information revelation or unbalanced dissemination of core competencies. These findings pose challenges about the nature of the knowledge and how to share it within a CF. Nonetheless, there is only scarce literature on KM in CF. Thus, the purpose of the paper is to propose a KM framework for CFs with the aim of strengthening stability and potential CF commercialization.