Edge computing coalitions adapt resource sharing under demand uncertainty
Dynamic Coalition Formation Under Capacity Constraints: A Regime-Switching Value-Investing Game
Computer Science and Game TheoryDistributed, Parallel, and Cluster Computing
Summary
This paper looks at how different service providers and a network operator can work together every day to share limited computing resources at the edge of the network. The authors model how demand for services changes randomly over time and create rules for who gets access and when services might be paused. They also design a way to fairly calculate each provider’s value and share payments, while encouraging truthful reporting. Their approach can improve resource use and earnings compared to always staying in one big group, especially when capacity is limited.
What this means in practice
- •For network operators: Implement dynamic coalition rules to allocate limited edge resources daily, improving efficiency and fairness under uncertain user demand.
- •For service providers: Use audit-based cooperation frameworks to optimize infrastructure investment decisions and operational participation for edge services with demand variability.
Authors
Rosario Patanè
Abstract
Edge computing service deployment requires the Network Operator (NO) and Service Providers (SPs) to coordinate investment and resource allocation under uncertain demand. This paper develops an audit-based service management framework for daily coalition formation with fixed capacity and service-level agreement (SLA) reservations. A two-stage coalitional game separates infrastructure investment from operational participation. Demand follows a Geometric Random Walk (GRW), and SPs apply an ordered admission and suspension rule using reported marginal contributions. With the NO held fixed, the operational coalition value is submodular; mandatory reservations can produce negative Shapley payoffs. We derive a separable benchmark, compute operational Shapley allocations, and give a sufficient condition for convergence to an individual equilibrium. A probabilistic audit mechanism provides a conditional daily truthfulness guarantee under verified settlement and enforceable penalties. For five service classes over three years, the reference run gains 12.4% over static grand-coalition membership and recovers 94.6% of the full-information optimum. Across 30 runs, the median gain is 13.3%. Sensitivity tests examine policy parameters, capacity and alternative demand models. The gain depends on capacity and update order; abundant capacity can make the admission rule underperform static membership.