Time-Varying Graphs and Dynamic Networks

The past few years have seen intensive research efforts carried out in some apparently unrelated areas of dynamic systems -- delay-tolerant networks, opportunistic-mobility networks, social networks -- obtaining closely related insights. Indeed, the concepts discovered in these investigations can be viewed as parts of the same conceptual universe; and the formal models proposed so far to express some specific concepts are components of a larger formal description of this universe. The main contribution of this paper is to integrate the vast collection of concepts, formalisms, and results found in the literature into a unified framework, which we call TVG (for time-varying graphs). Using this framework, it is possible to express directly in the same formalism not only the concepts common to all those different areas, but also those specific to each. Based on this definitional work, employing both existing results and original observations, we present a hierarchical classification of TVGs; each class corresponds to a significant property examined in the distributed computing literature. We then examine how TVGs can be used to study the evolution of network properties, and propose different techniques, depending on whether the indicators for these properties are a-temporal (as in the majority of existing studies) or temporal. Finally, we briefly discuss the introduction of randomness in TVGs.Comment: A short version appeared in ADHOC-NOW'11. This version is to be published in Internation Journal of Parallel, Emergent and Distributed System

Internet of Satellites (IoSat): analysis of network models and routing protocol requirements

The space segment has been evolved from monolithic to distributed satellite systems. One of these distributed systems is called the federated satellite system (FSS) which aims at establishing a win-win collaboration between satellites to improve their mission performance by using the unused on-board resources. The FSS concept requires sporadic and direct communications between satellites, using inter satellite links. However, this point-to-point communication is temporal and thus it can break existent federations. Therefore, the conception of a multi-hop scenario needs to be addressed. This is the goal of the Internet of satellites (IoSat) paradigm which, as opposed to a common backbone, proposes the creation of a network using a peer-to-peer architecture. In particular, the same satellites take part of the network by establishing intermediate collaborations to deploy a FSS. This paradigm supposes a major challenge in terms of network definition and routing protocol. Therefore, this paper not only details the IoSat paradigm, but it also analyses the different satellite network models. Furthermore, it evaluates the routing protocol candidates that could be used to implement the IoSat paradigm.Peer ReviewedPostprint (author's final draft

Dynamic Routing for Integrated Satellite-Terrestrial Networks: A Constrained Multi-Agent Reinforcement Learning Approach

The integrated satellite-terrestrial network (ISTN) system has experienced significant growth, offering seamless communication services in remote areas with limited terrestrial infrastructure. However, designing a routing scheme for ISTN is exceedingly difficult, primarily due to the heightened complexity resulting from the inclusion of additional ground stations, along with the requirement to satisfy various constraints related to satellite service quality. To address these challenges, we study packet routing with ground stations and satellites working jointly to transmit packets, while prioritizing fast communication and meeting energy efficiency and packet loss requirements. Specifically, we formulate the problem of packet routing with constraints as a max-min problem using the Lagrange method. Then we propose a novel constrained Multi-Agent reinforcement learning (MARL) dynamic routing algorithm named CMADR, which efficiently balances objective improvement and constraint satisfaction during the updating of policy and Lagrange multipliers. Finally, we conduct extensive experiments and an ablation study using the OneWeb and Telesat mega-constellations. Results demonstrate that CMADR reduces the packet delay by a minimum of 21% and 15%, while meeting stringent energy consumption and packet loss rate constraints, outperforming several baseline algorithms

Routing in the Space Internet: A contact graph routing tutorial

A Space Internet is possible, as long as the delay and disruption challenges imposed by the space environment are properly tackled. Because these conditions are not well addressed by terrestrial Internet, more capable Delay-Tolerant Networking (DTN) protocols and algorithms are being developed. In particular, the principles and techniques for routing among ground elements and spacecraft in near-Earth orbit and deep-space are enacted in the Contact Graph Routing (CGR) framework. CGR blends a set of non-trivial algorithm adaptations, space operations concepts, time-dynamic scheduling, and specific graph models. The complexity of that framework suggests a need for a focused discussion to facilitate its direct and correct apprehension. To this end, we present an in-depth tutorial that collects and organizes first-hand experience on researching, developing, implementing, and standardizing CGR. Content is laid out in a structure that considers the planning, route search and management, and forwarding phases bridging ground and space domains. We rely on intuitive graphical examples, supporting code material, and references to flight-grade CGR implementations details where pertinent. We hope this tutorial will serve as a valuable resource for engineers and that researchers can also apply the insights presented here to topics in DTN research.Fil: Fraire, Juan Andres. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Universitat Saarland; AlemaniaFil: De Jonckère, Olivier. Technische Universität Dresden; AlemaniaFil: Burleigh, Scott C.. California Institute of Technology; Estados Unido

A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

This article proposes a new digital signal recovery (DSR) technique for next-generation power efficient low Earth orbit (LEO) satellite-To-ground communication systems, which feature additive white Gaussian noise (AWGN) channel and significant power variation. This technique utilizes the prior knowledge [i.e., nonlinearities of radio frequency power amplifiers (RF-PAs)] of space-borne transmitters to improve the quality of the signal received at ground stations by modeling and mitigating the imperfection using deep neural networks (DNNs). Benefiting from its robustness against noise and power variation, the proposed DNN based DSR technique (DNN-DSR), can correct high signal distortions caused by the nonlinearities and hence allows RF-PAs to work close to their saturation region, leading to a high power efficiency of the LEO satellites. This work has been validated by both simulations and experiments, in comparison with the power back-off technique as well as memory polynomial-based DSR solutions. Experimental results show that the DNN-DSR technique can increase the drain efficiency of the space-borne RF-PA from 32.6% to 45% while maintaining the same error vector magnitude as the power back-off technique. It has also been demonstrated that the proposed DNN-DSR technique can handle a signal power variation of 12 dB, which is challenging for conventional solutions.</p