Computing resource allocation in three-tier IoT fog networks: a joint optimization approach combining Stackelberg game and matching

Fog computing is a promising architecture to provide economical and low latency data services for future Internet of Things (IoT)-based network systems. Fog computing relies on a set of low-power fog nodes (FNs) that are located close to the end users to offload the services originally targeting at cloud data centers. In this paper, we consider a specific fog computing network consisting of a set of data service operators (DSOs) each of which controls a set of FNs to provide the required data service to a set of data service subscribers (DSSs). How to allocate the limited computing resources of FNs to all the DSSs to achieve an optimal and stable performance is an important problem. Therefore, we propose a joint optimization framework for all FNs, DSOs, and DSSs to achieve the optimal resource allocation schemes in a distributed fashion. In the framework, we first formulate a Stackelberg game to analyze the pricing problem for the DSOs as well as the resource allocation problem for the DSSs. Under the scenarios that the DSOs can know the expected amount of resource purchased by the DSSs, a many-to-many matching game is applied to investigate the pairing problem between DSOs and FNs. Finally, within the same DSO, we apply another layer of many-to-many matching between each of the paired FNs and serving DSSs to solve the FN-DSS pairing problem. Simulation results show that our proposed framework can significantly improve the performance of the IoT-based network systems

Natural Four-Generation Mass Textures in MSSM Brane Worlds

A fourth generation of Standard Model (SM) fermions is usually considered unlikely due to constraints from direct searches, electroweak precision measurements, and perturbative unitarity. We show that fermion mass textures consistent with all constraints may be obtained naturally in a model with four generations constructed from intersecting D6 branes on a T^6/(Z_2 x Z_2) orientifold. The Yukawa matrices of the model are rank 2, so that only the third- and fourth-generation fermions obtain masses at the trilinear level. The first two generations obtain masses via higher-order couplings and are therefore naturally lighter. In addition, we find that the third and fourth generation automatically split in mass, but do not mix at leading order. Furthermore, the SM gauge couplings automatically unify at the string scale, and all the hidden-sector gauge groups become confining in the range 10^{13}--10^{16} GeV, so that the model becomes effectively a four-generation MSSM at low energies.Comment: Accepted for publication in Physical Review