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

Efficient Routing and Scheduling in Wireless Networks

The temporal and spatial variation in wireless channel conditions, node mobility make it challenging to design protocols for wireless networks. In this thesis, we design efficient routing and scheduling algorithms which adapt to changing network conditions caused by varying link quality or node mobility to improve user-level performance. We design and analyze routing protocols for static, mobile and heterogeneous wireless networks. We analyze the performance of opportunistic and cooperative forwarding in static mesh networks showing that opportunism outperforms cooperation; we identify interference as the main cause for mitigating the potential gains achievable with cooperative forwarding. For mobile networks, we quantitatively analyze the tradeoff between state information collection (sampling frequency and number of bits per sample) and power consumption for a fixed source-to-destination goodput constraint. For heterogeneous networks comprising of both static and mobile nodes, we propose a greedy algorithm (adaptive-flood) which dynamically classifies individual nodes as routers/flooders depending on network conditions and demonstrate that it achieves performance equivalent to, and in some cases significantly better than, that of network-wide routing or flooding alone. Last, we consider an application-level wireless streaming scenario where multiple clients are streaming different videos from a cellular base station. We design a greedy algorithm for efficiently scheduling multiple video streams from a base station to mobile clients so as to minimize the total number of application-playout stalls. We develop models for coarse timescale wireless channel variation to aid network and application-layer protocol design

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications

Modelización de la difusión y persistencia de datos en redes oportunistas de comunicación móvil

[EN] In this thesis, we will study how mobile devices can share and keep information and what are the best protocols to achieve different goals. Moreover, we will try to guess which mathematical models best describe our situation so we can do precise forecasts. The two main traits that distinguish MANETs (Mobile ad hoc Networks) and traditional technologies are the following: First, there is no fixed infrastructure, since the messages are carried and received/sent by the nodes themselves, and second, those nodes are, of course, generally moving. One of the main problems of those networks is to assure that the messages will arrive from the node who generated the message to the one we want to receive it, if necessary, jumping from one to another until reaching to the objective. This can fail for multiple reasons: one of the nodes in between has not enough storage capacity, they are too far apart, etc. For this reason, we need to simulate different protocols to check which ones are the best, and for this, we need high-quality traces whose behavior assimilate to real-life moving nodes. The steps that we will follow in this work are the following: • Obtain information from a real-life scenario (“La plaza de San Vicente Ferrer”) • Feed this data into PEdSim to realistic traces. • Use these traces into ONE simulator to check the performance of a protocol. • Understand different mathematical models used to describe these processes. To obtain the above-mentioned information from this square, we visited “La plaza de San Vicente Ferrer” and one by one, wrote done from where to where people moved and how long it took them. Then, other metrics such as speed can be directly calculated. After that, we used this data, and altogether with the design of the square, we simulated it to get the traces. We right after simulated them with ONE. Lastly, different mathematical models can be used in this situation, such as: SIR type models and dynamic graphs, etc. They are generally used in epidemiological disease situations, where there is a group of infected people, susceptible people, and recovered people. Such models admit many different nuances, so it is easily fitted into MANETs experiments. The analogy is clear, since we have nodes without the message (susceptible), and nodes with it (infected) which will infect other nodes if some requirements are met The first ones are valid as long as the population remaining in the place is large enough. The second ones are more accurate when the size of the population in the place is small. We will describe the theoretical part of both models and we will see how the second one work with the data obtained.[ES] Con la llegada de la tecnología 5G y el esperado cresimiento explosivo de estos dispositivos, el ancho de banda puede resultar limitante. Una opción para mitigar este efecto es la descarga directa por WIFi entre dispositivos próximos. Las comunicaciones en redes móviles oportunistas tienen lugar cuando se establecen contactos efímeros entre nodos móviles mediante comunicación directa. A partir de trazas movilidad reales y gracias al simulador PedSim (PEDestrian crowd SIMulation) modelizamos la disfusión y persistencia de la información en un determinado recinto con el paso del tiempo, estudiando la relación entre los distintos parámetros y contrastando los resultados con otros modelos existentes.Orea Hueso, C. (2019). Modelización de la difusión y persistencia de datos en redes oportunistas de comunicación móvil. http://hdl.handle.net/10251/129515TFG

Edge-powered Assisted Driving For Connected Cars

Assisted driving for connected cars is one of the main applications that 5G-and-beyond networks shall support. In this work, we propose an assisted driving system leveraging the synergy between connected vehicles and the edge of the network infrastructure, in order to envision global traffic policies that can effectively drive local decisions. Local decisions concern individual vehicles, e.g., which vehicle should perform a lane-change manoeuvre and when; global decisions, instead, involve whole traffic flows. Such decisions are made at different time scales by different entities, which are integrated within an edge-based architecture and can share information. In particular, we leverage a queuing-based model and formulate an optimization problem to make global decisions on traffic flows. To cope with the problem complexity, we then develop an iterative, linear-time complexity algorithm called Bottleneck Hunting (BH). We show the performance of our solution using a realistic simulation framework, integrating a Python engine with ns-3 and SUMO, and considering two relevant services, namely, lane change assistance and navigation, in a real-world scenario. Results demonstrate that our solution leads to a reduction of the vehicles' travel times by 66 in the case of lane change assistance and by 20 for navigation, compared to traditional, local-coordination approaches.Comment: arXiv admin note: text overlap with arXiv:2008.0933

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Improving network reliability by exploiting path diversity in ad hoc networks with bursty losses

In wireless mobile ad hoc networks, end-to-end connections are often subject to failures which do not make the connection non-operational indefinitely but interrupt the communication for intermittent short periods of time. These intermittent failures usually arise from the mobility of hosts, dynamics of the wireless medium or energy-saving mechanisms, and cause bursty packet losses. Reliable communication in this kind of an environment is becoming more important with the emerging use of ad hoc networks for carrying diverse multimedia applications such as voice, video and data. In this thesis, we present a new path reliability model that captures intermittent availability of the paths, and we devise a routing strategy based on our path reliability model in order to improve the network reliability. Our routing strategy takes the advantage of path diversity in the network and uses a diversity coding scheme in order not to compromise efficiency. In diversity coding scheme, if the original information is encoded by using a (N,K) code, then it is enough for the destination to receive any K bits correctly out of N bits to successfully decode the original information. In our scheme, the original information is divided into N subpackets and subpackets are distributed among the available disjoint paths in the network. The distribution of subpackets among the diverse paths is a crucial decision. The subpackets should be distributed 'intelligently' so that the probability of successful reconstruction of the original information is maximized. Given the failure statistics of the paths, and the code rate (N, K), our strategy determines the allocation of subpackets to each path in such a manner that the probability of reconstruction of the original information at the destination is maximized. Simulation results justify the accuracy and efficiency of our approach. Additionally, simulation results show that our multipath routing strategy improves the network reliability substantially compared to the single path routing. In wireless networks, a widely used strategy is to place the nodes into a low energy consuming sleep mode in order to prolong the battery life. In this study, we also consider the cases where the intermittent availability of the nodes is due to the sleep/awake cycles of wireless nodes. A sleep/awake scheduling strategy is proposed which minimizes the packet latency while satisfying the energy saving ratio specified by the energy saving mechanism

Design and Performance Analysis of Genetic Algorithms for Topology Control Problems

In this dissertation, we present a bio-inspired decentralized topology control mechanism, called force-based genetic algorithm (FGA), where a genetic algorithm (GA) is run by each autonomous mobile node to achieve a uniform spread of mobile nodes and to provide a fully connected network over an unknown area. We present a formal analysis of FGA in terms of convergence speed, uniformity at area coverage, and Lyapunov stability theorem. This dissertation emphasizes the use of mobile nodes to achieve a uniform distribution over an unknown terrain without a priori information and a central control unit. In contrast, each mobile node running our FGA has to make its own movement direction and speed decisions based on local neighborhood information, such as obstacles and the number of neighbors, without a centralized control unit or global knowledge. We have implemented simulation software in Java and developed four different testbeds to study the effectiveness of different GA-based topology control frameworks for network performance metrics including node density, speed, and the number of generations that GAs run. The stochastic behavior of FGA, like all GA-based approaches, makes it difficult to analyze its convergence speed. We built metrically transitive homogeneous and inhomogeneous Markov chain models to analyze the convergence of our FGA with respect to the communication ranges of mobile nodes and the total number of nodes in the system. The Dobrushin contraction coefficient of ergodicity is used for measuring convergence speed for homogeneous and inhomogeneous Markov chain models of our FGA. Furthermore, convergence characteristic analysis helps us to choose the nearoptimal values for communication range, the number of mobile nodes, and the mean node degree before sending autonomous mobile nodes to any mission. Our analytical and experimental results show that our FGA delivers promising results for uniform mobile node distribution over unknown terrains. Since our FGA adapts to local environment rapidly and does not require global network knowledge, it can be used as a real-time topology controller for commercial and military applications