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.
Deterministic routing has emerged as a promising technology for future non-terrestrial networks (NTNs), offering the potential to enhance service performance and optimize resource utilization. However, the dynamic nature of network topology and resources poses challenges in establishing deterministic routing. These challenges encompass the intricacy of jointly scheduling transmission links and cycles, as well as the difficulty of maintaining stable end-to-end (E2E) routing paths. To tackle these challenges, our work introduces an efficient temporal graph-based deterministic routing strategy. Initially, we utilize a time-expanded graph (TEG) to represent the heterogeneous resources of an NTN in a time-slotted manner. With TEG, we meticulously define each necessary constraint and formulate the deterministic routing problem. Subsequently, we transform this nonlinear problem equivalently into solvable integer linear programming (ILP), providing a robust yet time-consuming performance upper bound. To address the considered problem with reduced complexity, we extend TEG by introducing virtual nodes and edges. This extension facilitates a uniform representation of heterogeneous network resources and traffic transmission requirements. Consequently, we propose a polynomial-time complexity algorithm, enabling the dynamic selection of optimal transmission links and cycles on a hop-by-hop basis. Simulation results validate that the proposed algorithm yields significant performance gains in traffic acceptance, justifying its additional complexity compared to existing routing strategies.
Due to the capability of simultaneously delivering the same information to multiple users, the multicast transmission has been widely applied over the satellite networks. Furthermore, more and more information needs to ensure the transmission delay within a predefined bound. However, the satellite networks possess the time-varying characteristics and limited energy, which causes challenges for the low delay multicast design. In this paper, we investigate the energy-efficient delay-bounded (EEDB) multicast problem to accomplish the multicast transmission within the given delay bound, but to consume energy as less as possible. Specially, with the help of the time-expanded graph (TEG), we construct the multicast time-expanded graph (MTEG) through introducing some auxiliary vertices and arcs to accurately depict the across-time multicast transmission and the "wireless multicast advantage". Then, we formulate the EEDB multicast problem as one combinatorial optimization and propose an iterative heuristic algorithm to achieve the suboptimal multicast scheme. Simulation results are also presented to verify our proposed algorithm.
Due to the high dynamic characteristics of the low-orbit satellite networks, the frequent handovers of the users led to heavy mobility management load and large handover delay. To solve these problems, one mobility management mechanism based on the virtual agent domain (VAD) is proposed. In this mechanism, a virtual agent cluster (VAC) is designed to co-manage the network architecture of users in the corresponding VAD. With the on-board processing and switching capabilities, the architecture of the distributed mobility management mechanism is adopted to support the information sharing between the VACs, which reduces the performance requirements for single satellite and improves the system scalability. Then, we construct the home mobile-agent-anchor (HMAA) and the local MAA. In this way, the MN triggers a binding update to the HA only when the home MAA is lost, and the MN's switching within the VAD only needs to update its intra-domain relations, which reduces the overhead of mobility management and switching delay. Furthermore, the proposed scheme is theoretically evaluated in terms of the signaling overhead and handover latency. Finally, the numerical simulation results are presented to verify the efficacy of our scheme. The experimental platform also demonstrates the availability and efficiency of the new mechanism.
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.
The Taihu Lake drainage basin is the birthplace of the Mulberry-dyke and Fish-pond System (MFS), a traditional eco-agricultural system. In 2017, the largest and best-preserved “Zhejiang Huzhou Mulberry-dyke and Fish-pond System” located by the South Bank of Taihu Lake, China was recognized as Globally Important Agricultural Heritage Systems (GIAHS) by the Food and Agriculture Organization of the United Nations (FAO), and its value has been appreciated. As a dynamic heritage, the sustainable development of MFS is a fundamental requirement of the conservation of GIAHS. In this regard, it is necessary to figure out an approach to evaluating the status of its sustainable development. This paper analyzes and contrasts the emergy embodied in the three patterns of MFS over different periods, then constructs an index system of sustainability evaluation involving the production and consumption processes based on that. Finally, it provides the evaluation and analysis. The three patterns of MFS differ in the system structure. In the Ming and Qing Dynasties (abbreviated as Ming-Qing pattern), MFS was an integrated system compromised of mulberry cultivation, silkworm breeding, fish breeding, and sheep breeding, while other patterns exclude sheep breeding, but increase the input of fertilizer, and add the production of mulberry-leaf tea and other local specialties. The results show that the MFS in the Ming-Qing pattern has the highest integrated evaluation index of sustainable development, followed by the traditional MFS pattern and the new MFS pattern employed nowadays. This indicates that the current capability of sustainable development has decreased compared to that in the Ming and Qing Dynasties. The integrated evaluation index regarding the consumption process of the new MFS pattern is higher than the traditional one, suggesting that it needs to promote sustainability in the production process, especially via the utilization rates of renewable resources and wastes.
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.
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