However, some fairness constraints must be imposed on the scheduling policies to ensure the fair resource allocation.
However, finding an efficient and fair resource allocation is challenging mainly due to the heterogeneity of tenants.
Similarly, processor sharing (PS) is a commonly used scheduling policy that guarantees fair resource allocation among multiple users.
Proportional fair resource allocation plays a critical role to enhance the performance of slow adaptive orthogonal frequency division multiple access (OFDMA) system.
In this paper, we apply the bio-inspired flocking algorithm to fair resource allocation in vehicle-mounted mobile relay (VMR) deployed networks.
Based on this model, we adopt a multiagent-based technique that allows a group of autonomous tenants to reach an efficient and fair resource allocation.
Moreover, we survey the designs of existing fairness mechanisms, evaluate them via practical issues, and address some open research issues concerning fair resource allocation in wireless backhaul networks.
We consider the problem of fair resource allocation in a system containing different resource types, where each user may have different demands for each resource.
The NS2-based simulation results demonstrate that D2OFC2 outperforms default TCP and ATCP to achieve an efficient and fair resource allocation in Ad Hoc networks under three scenarios, including chain topology, grid topology, and random topology.
Based on our analysis, we obtain congestion control laws at links and sources that (i) are linearly stable regardless of the network topology, provided that a bound on round-trip-times is known, (ii) provide a utility proportional fair resource allocation in equilibrium.
In this work, we formulate a proportional fair resource allocation problem based on chance-constrained programming for slow adaptive OFDMA system which maximizes the average sum-rate in an adaptive time window and guarantees the Jain fair index (JFI) requirement with the target probability.
