Virtual Reality (VR) applications delivered over wireless networks have attracted interest from academia and industry. The delay of VR applications is mainly composed of computing delay and communication delay. Although cloud computing centers have adequate computing power, accessing them requires long communication delay. Mobile edge computing (MEC), which offloads the computing power from the cloud computing center to the edge, is regarded as a feasible way to alleviate communication delay. However, due to the differences in the capability and location of MEC nodes, the selection of MEC nodes will affect both the computing delay and communication delay. In this paper, we focus on the joint representation of computing and communication resources and the selection of the optimal MEC node. First, we adopt graph-based joint computing and communication resources (GCC) model for VR applications routing and formulate the VR routing problem as an ILP problem. Then we design a Computing Nodes Expanded (CNE) algorithm, which allows us to use the Dijkstra algorithm to quickly obtain the optimal computing node and the path of shortest total delay. Finally, we run numerical experiments to evaluate the performance of the proposal algorithm. Simulation shows that the CNE algorithm can reduce the total delay by 42.9% and increase the delay satisfaction ratio by 23.3% compared to other benchmark algorithms.

Deterministic networking technologies play significant roles in Internet of Things, Augmented Reality and so on. In fact, the resource reservation policy is employed to guarantee the time-deterministic transmission of flows in deterministic networks. However, for flows with dynamic bandwidth demands, this policy will allocate bandwidths according to the peak volume in rush hours, and the link bandwidths may be just authorized but not fully utilized, which results in bandwidth overprovision and low resource utilization. Besides, due to the time-varying characteristics of both the network topology and link bandwidths, traditional static graph based routing schemes are inefficient for time-varying networks. Therefore, it is important to find a feasible way to improve the bandwidth utilization while guaranteeing the deterministic performance of flows. In this paper, we explore the deterministic routing problem for flows with dynamic bandwidth demands in stochastic time-varying networks (STN). First, we adopt the stochastic time-varying graph to characterize the dynamic attributes of networks, including the link bandwidth and topology, where random variables are utilized to depict the dynamicness of both dynamic bandwidth demands of flows and time-varying bandwidth resources of links. Then, we design an overcommitment rule, which allows us to design a bandwidth resource overcommitment shortest path algorithm in STN (ROSP-STN) to guarantee the delay of flows. Finally, we run numerical experiments to evaluate performance of the ROSP schme. Simulation shows that the proposed ROSP scheme can increase the bandwidth utilization by 24% and the transmission delay of flows can also be guaranteed into a deterministic range.

Deterministic networking technologies play significant roles in Internet of Things, Augmented Reality and so on. In fact, the resource reservation policy is employed to guarantee the time-deterministic transmission of flows in deterministic networks. However, for flows with dynamic bandwidth demands, this policy will allocate bandwidths according to the peak volume in rush hours, and the link bandwidths may be just authorized but not fully utilized, which results in bandwidth overprovision and low resource utilization. Besides, due to the time-varying characteristics of both the network topology and link bandwidths, traditional static graph based routing schemes are inefficient for time-varying networks. Therefore, it is important to find a feasible way to improve the bandwidth utilization while guaranteeing the deterministic performance of flows. In this paper, we explore the deterministic routing problem for flows with dynamic bandwidth demands in stochastic time-varying networks (STN). First, we adopt the stochastic time-varying graph to characterize the dynamic attributes of networks, including the link bandwidth and topology, where random variables are utilized to depict the dynamicness of both dynamic bandwidth demands of flows and time-varying bandwidth resources of links. Then, we design an overcommitment rule, which allows us to design a bandwidth resource overcommitment shortest path algorithm in STN (ROSP-STN) to guarantee the delay of flows. Finally, we run numerical experiments to evaluate performance of the ROSP schme. Simulation shows that the proposed ROSP scheme can increase the bandwidth utilization by 24% and the transmission delay of flows can also be guaranteed into a deterministic range.

Nowadays satellite networks are playing an increasing role in earth observation, global communication, etc. Many space missions require to deliver large amounts of data to the ground system for different purposes, and analyzing the maximum throughput of the given satellite network is a prerequisite for efficient data transmission. However, satellite networks possess the time-varying topologies, dynamic bandwidth and limited on-board energy, which restricts the end-to-end capacity and poses challenges to the analysis. In this paper, we utilize temporal graphs for better solving the end-to-end max-flow problem over energy-limited satellite networks. An energy time-expanded graph (eTEG) is constructed to accurately represent the restriction of on-board limited energy on data transmission capability. Furthermore, to maximize flow delivery and energy utilization, we proposed an eTEG-based max-flow routing algorithm with time-dependent residual network update rules. Simulation results are also presented to verify the efficacy of our algorithm.