Federations of Infrastructure Service Providers (InfSPs) have emerged as an effective practice to cater for demanding applications in cloud- and edge-computing environments, by overcoming the limitations of each such provider (in terms of available resources, geographic coverage etc.). In this paper, we develop innovative mechanisms and policies for the decentralized management of InfSP federations, considering the needs both for resource allocation meeting service composition requirements, and for performing a fair and efficient distribution of profits. Resource allocation is performed by means of a greedy algorithm that includes an opportunistic and an adjustment phase. To determine the payments of participating InfSPs, we introduce an innovative sealed-bid reverse auction that combines VCG and first-price auction mechanisms. This hybrid mechanism, coupled with a sophisticated federation wallet management mechanism, serves as a revenue sink for the federation. Notably, our approach exhibits several nice properties, including efficiency, long-term budget balance, truthfulness and individual rationality. Furthermore, we present how our solution can be implemented in a decentralized, privacy-preserving and trustworthy manner over a blockchain, achieving bid privacy, non-repudiation and public verifiability. Our approach is evaluated by means of extensive experiments, the results of which reveal that resource allocation is either optimal or very close thereto, while individual InfSP profits as well as total federation profits are maximized. The results underscore the inadequacy of relying solely on the VCG mechanism for budget balance, justifying the necessity of our sophisticated hybrid solution.

Network slicing allows Mobile Network Operators (MNOs) to partition their physical infrastructure into multiple virtual logical networks, enabling the simultaneous servicing of applications with diverse Quality of Service characteristics. In this paper, we introduce and evaluate economic models and policies for the provisioning, across multiple MNOs, of network slice services to Application Providers. We introduce a Network-Slice-as-a-Service model that maps the service offered by a network slice to requirements on virtualized resources. The placement of virtualized resources over the physical infrastructure of MNOs is determined by an embedding problem, formulated as a Mixed Integer Program. We investigate the embedding under: (i) centralized approaches, where a central Broker determines the embedding for all network slice requests, and (ii) peer-to-peer approaches, where each MNO determines the embedding for the sub-set of network slice requests coming from its own customers. We introduce policies for cooperative modes, with the objective of total profit maximization, and for “coopetitive” (cooperative competition) modes, where MNOs aim to maximize their individual profits. The numerical results reveal that MNOs can maximize their aggregate and individual profits under any approach or mode, if they comply with the proposed policies.

Sharing economy is a game-changing business paradigm that is currently permeating several industrial sectors. This paper aims to build a fundamental theory of the sharing economy of the computational capacity resource of Cloud Service Providers (CSPs). CSPs aim to cost-efficient serve geographically dispersed customers that often request computational resource-demanding services. The formation of CSP federations arises as an effective means to manage these diverse and time-varying service requests. In this paper, we introduce innovative federation models and policies for profitable federations that also achieve adequate QoS for their customers. Taking in account the flexible cloud computing service model, we abstract the virtualized infrastructure of each CSP to an M/M/1 queueing system, we formulate the CSP revenue and cost functions, and we study the task forwarding-based (TF) and the capacity sharing-based (CS) federation approaches. Under TF, each CSP may forward part of its workload to other federated CSPs, while under CS each CSP may share parts of its computational infrastructure with others. For both approaches, we propose two operation modes with different degree of CSPs' cooperation: (i) the joint business mode, where the CSPs fully cooperate: they jointly decide on the federation policies that maximize the total federation profit which is shared fairly among them; (ii) the reward-driven mode, where selfinterested CSPs participate in a game: they adjust their responses to federation policies aiming to maximize their individual profits. The results reveal that our policies lead to effective federations, which are beneficial both for CSPs and for customers.

IT and telco providers are preparing for the era of 5G; in terms of technology, the driving force is virtualization, both for computing and networking. The 5G services will be superior than today's online services not only in technological aspects, but also from an economic and business perspective: fast service creation, effective utilization of resources, dynamic adaption to actual demand are all direct benefits of the virtualized infrastructure. In this paper we study the economic interactions between 5G resource providers and customers: we formalize how resources should be priced and selected for being booked. In particular we show that usage-based pricing is an income-maximizing scheme for providers, and we derive the problem the customers need to solve for cost-optimizing service deployment.