Coordination and Privacy Preservation in Multi-Agent Systems

This dissertation considers two key problems in multi-agent systems: coordination (including both synchronization and desynchronization) and privacy preservation. For coordination in multi-agent systems, we focus on synchronization/desynchronization of distributed pulse-coupled oscillator (PCO) networks and their applications in collective motion coordination. Pulse-coupled oscillators were originally proposed to model synchronization in biological systems such as flashing fireflies and firing neurons. In recent years, with proven scalability, simplicity, accuracy, and robustness, the PCO based synchronization strategy has become a powerful clock synchronization primitive for wireless sensor networks. Driven by these increased applications in biological networks and wireless sensor networks, synchronization of pulse-coupled oscillators has gained increased popularity. However, most existing results address the local synchronization of PCOs with initial phases constrained in a half cycle, and results on global synchronization from any initial condition are very sparse. In our work, we address global PCO synchronization from an arbitrary phase distribution under chain or directed tree graphs. More importantly, different from existing global synchronization studies on decentralized PCO networks, our work allows heterogeneous coupling functions and perturbations on PCOs\u27 natural frequencies, and our results hold under any coupling strength between zero and one, which is crucial because a large coupling strength has been shown to be detrimental to the robustness of PCO synchronization to disturbances. Compared with synchronization, desynchronization of PCOs is less explored. Desynchronization spreads the phase variables of all PCOs uniformly apart (with equal difference between neighboring phases). It has also been found in many biological phenomena, such as neuron spiking and fish signaling. Recently, phase desynchronization has been employed to achieve round-robin scheduling, which is crucial in applications as diverse as media access control of communication networks, realization of analog-to-digital converters, and scheduling of traffic flows in intersections. In our work, we systematically characterize pulse-coupled oscillators based decentralized phase desynchronization and propose an interaction function that is more general than existing results. Numerical simulations show that the proposed pulse based interaction function also has better robustness to pulse losses, time delays, and frequency errors than existing results. Collective motion coordination is fundamental in systems as diverse as mobile sensor networks, swarm robotics, autonomous vehicles, and animal groups. Inspired by the close relationship between phase synchronization/desynchronization of PCOs and the heading dynamics of connected vehicles/robots, we propose a pulse-based integrated communication and control approach for collective motion coordination. Our approach only employs simple and identical pulses, which significantly reduces processing latency and communication delay compared with conventional packet based communications. Not only can heading control be achieved in the proposed approach to coordinate the headings (orientations) of motions in a network, but also spacing control for circular motion is achievable to design the spacing between neighboring nodes (e.g., vehicles or robots). The second part of this dissertation is privacy preservation in multi-agent systems. More specifically, we focus on privacy-preserving average consensus as it is key for multi-agent systems, with applications ranging from time synchronization, information fusion, load balancing, to decentralized control. Existing average consensus algorithms require individual nodes (agents) to exchange explicit state values with their neighbors, which leads to the undesirable disclosure of sensitive information in the state. In our work, we propose a novel average consensus algorithm for time-varying directed graphs which can protect the privacy of participating nodes\u27 initial states. Leveraging algorithm-level obfuscation, the algorithm does not need the assistance of any trusted third party or data aggregator. By leveraging the inherent robustness of consensus dynamics against random variations in interaction, our proposed algorithm can guarantee privacy of participating nodes without compromising the accuracy of consensus. The algorithm is distinctly different from differential-privacy based average consensus approaches which enable privacy through compromising accuracy in obtained consensus value. The approach is able to protect the privacy of participating nodes even in the presence of multiple honest-but-curious nodes which can collude with each other

Distributed Database Management Techniques for Wireless Sensor Networks

Authors and/or their employers shall have the right to post the accepted version of IEEE-copyrighted articles on their own personal servers or the servers of their institutions or employers without permission from IEEE, provided that the posted version includes a prominently displayed IEEE copyright notice and, when published, a full citation to the original IEEE publication, including a link to the article abstract in IEEE Xplore. Authors shall not post the final, published versions of their papers.In sensor networks, the large amount of data generated by sensors greatly influences the lifetime of the network. In order to manage this amount of sensed data in an energy-efficient way, new methods of storage and data query are needed. In this way, the distributed database approach for sensor networks is proved as one of the most energy-efficient data storage and query techniques. This paper surveys the state of the art of the techniques used to manage data and queries in wireless sensor networks based on the distributed paradigm. A classification of these techniques is also proposed. The goal of this work is not only to present how data and query management techniques have advanced nowadays, but also show their benefits and drawbacks, and to identify open issues providing guidelines for further contributions in this type of distributed architectures.This work was partially supported by the Instituto de Telcomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, by the Ministerio de Ciencia e Innovacion, through the Plan Nacional de I+D+i 2008-2011 in the Subprograma de Proyectos de Investigacion Fundamental, project TEC2011-27516, by the Polytechnic University of Valencia, though the PAID-05-12 multidisciplinary projects, by Government of Russian Federation, Grant 074-U01, and by National Funding from the FCT-Fundacao para a Ciencia e a Tecnologia through the Pest-OE/EEI/LA0008/2013 Project.Diallo, O.; Rodrigues, JJPC.; Sene, M.; Lloret, J. (2013). Distributed Database Management Techniques for Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems. PP(99):1-17. https://doi.org/10.1109/TPDS.2013.207S117PP9

SUTMS - Unified Threat Management Framework for Home Networks

Home networks were initially designed for web browsing and non-business critical applications. As infrastructure improved, internet broadband costs decreased, and home internet usage transferred to e-commerce and business-critical applications. Today’s home computers host personnel identifiable information and financial data and act as a bridge to corporate networks via remote access technologies like VPN. The expansion of remote work and the transition to cloud computing have broadened the attack surface for potential threats. Home networks have become the extension of critical networks and services, hackers can get access to corporate data by compromising devices attacked to broad- band routers. All these challenges depict the importance of home-based Unified Threat Management (UTM) systems. There is a need of unified threat management framework that is developed specifically for home and small networks to address emerging security challenges. In this research, the proposed Smart Unified Threat Management (SUTMS) framework serves as a comprehensive solution for implementing home network security, incorporating firewall, anti-bot, intrusion detection, and anomaly detection engines into a unified system. SUTMS is able to provide 99.99% accuracy with 56.83% memory improvements. IPS stands out as the most resource-intensive UTM service, SUTMS successfully reduces the performance overhead of IDS by integrating it with the flow detection mod- ule. The artifact employs flow analysis to identify network anomalies and categorizes encrypted traffic according to its abnormalities. SUTMS can be scaled by introducing optional functions, i.e., routing and smart logging (utilizing Apriori algorithms). The research also tackles one of the limitations identified by SUTMS through the introduction of a second artifact called Secure Centralized Management System (SCMS). SCMS is a lightweight asset management platform with built-in security intelligence that can seamlessly integrate with a cloud for real-time updates

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results

Improving Large-Scale Network Traffic Simulation with Multi-Resolution Models

Simulating a large-scale network like the Internet is a challenging undertaking because of the sheer volume of its traffic. Packet-oriented representation provides high-fidelity details but is computationally expensive; fluid-oriented representation offers high simulation efficiency at the price of losing packet-level details. Multi-resolution modeling techniques exploit the advantages of both representations by integrating them in the same simulation framework. This dissertation presents solutions to the problems regarding the efficiency, accuracy, and scalability of the traffic simulation models in this framework. The ``ripple effect\u27\u27 is a well-known problem inherent in event-driven fluid-oriented traffic simulation, causing explosion of fluid rate changes. Integrating multi-resolution traffic representations requires estimating arrival rates of packet-oriented traffic, calculating the queueing delay upon a packet arrival, and computing packet loss rate under buffer overflow. Real time simulation of a large or ultra-large network demands efficient background traffic simulation. The dissertation includes a rate smoothing technique that provably mitigates the ``ripple effect\u27\u27, an accurate and efficient approach that integrates traffic models at multiple abstraction levels, a sequential algorithm that achieves real time simulation of the coarse-grained traffic in a network with 3 tier-1 ISP (Internet Service Provider) backbones using an ordinary PC, and a highly scalable parallel algorithm that simulates network traffic at coarse time scales

Impact of step size on convergence in swarmalator systems

openGroup robotics is one of the key areas of the development of robotic systems. This is due to the fact that for a wide class of practical tasks, the use of a group of relatively simple robots is much more efficient than using a single large multi-purpose device. The modern development of computer technology and communication systems opens up wide opportunities for the construction of such systems. The most progressive and effective approach is the implementation of the collective behavior of robots according to the swarm principle, when each of them interacts only with neighboring individuals, synchronously exchanging the collected information about the environment and their condition. Such a group compensates for the weakness of its detection and communication devices by joining a team. The problems of introducing group robotics into the modern world are studied in this thesis. If they combine two concepts, synchronization and swarming, they are called a swarmalator. In swarmalator systems, the movement of the robots is governed by differential equations. These equations are solved with the Euler method, where the location and phase are determined. The Euler method is time-discrete and allows the integration of first-order differential equations. Therefore, there is a step size to be chosen. The main task is to study group movement, which is based on transmitting information with a definite step size. The step value affects how often the swarmalators share their location and phase. Three main conclusions are made. The first research is what happens when varying the step size - is it most optimal to use with small step sizes? The second conclusion is that when increasing the step size with a small increment or using randomization of the step size. Such methods are typically, more optimal to use with a gradual increase in the step size because the convergence time is lower. The third is when decreasing the step size using a small increment. The results showed that this method is optimal to use when the step size exceeds 1. The states converge at a rather large interval, compared with previous results, but at the same time with a large value of the convergence time. The values of optimal step sizes are presented and analyzed. As performance criteria, we consider the computational power that is required, the average convergence time, the coupling probability and the step size. The behavior of all parameters is graphically represented in plots. The conclusions are based on the simulations done for the results.Group robotics is one of the key areas of the development of robotic systems. This is due to the fact that for a wide class of practical tasks, the use of a group of relatively simple robots is much more efficient than using a single large multi-purpose device. The modern development of computer technology and communication systems opens up wide opportunities for the construction of such systems. The most progressive and effective approach is the implementation of the collective behavior of robots according to the swarm principle, when each of them interacts only with neighboring individuals, synchronously exchanging the collected information about the environment and their condition. Such a group compensates for the weakness of its detection and communication devices by joining a team. The problems of introducing group robotics into the modern world are studied in this thesis. If they combine two concepts, synchronization and swarming, they are called a swarmalator. In swarmalator systems, the movement of the robots is governed by differential equations. These equations are solved with the Euler method, where the location and phase are determined. The Euler method is time-discrete and allows the integration of first-order differential equations. Therefore, there is a step size to be chosen. The main task is to study group movement, which is based on transmitting information with a definite step size. The step value affects how often the swarmalators share their location and phase. Three main conclusions are made. The first research is what happens when varying the step size - is it most optimal to use with small step sizes? The second conclusion is that when increasing the step size with a small increment or using randomization of the step size. Such methods are typically, more optimal to use with a gradual increase in the step size because the convergence time is lower. The third is when decreasing the step size using a small increment. The results showed that this method is optimal to use when the step size exceeds 1. The states converge at a rather large interval, compared with previous results, but at the same time with a large value of the convergence time. The values of optimal step sizes are presented and analyzed. As performance criteria, we consider the computational power that is required, the average convergence time, the coupling probability and the step size. The behavior of all parameters is graphically represented in plots. The conclusions are based on the simulations done for the results

Estruturas de dados retroativas: aplicações na dinamização de algoritmos

The retroactivity in programming is the study of a modification in a timeline for a data structure and the effects that this modification exerts throughout its existence. In general, the analysis and implementation tend to be more costly computationally, because a modification on these data structure in the past can generate a cascade effect through all the data structure timeline. The concept of retroactivity generates tools and structures that optimize the solutions facing these temporal problems. This type of data structure can be used in, for example, shortest path algorithms, security applications, and geometric problems. In this thesis, we have the theoretical subsidies about these data structures, a detailed material about the implementation of this structures, using retroactivity, and the implementation of some problems that retroactivity can be used, for example, the fully dynamic minimum spanning tree problem. For each data structure, we executed practical tests about this data retroactive data structures and a comparison between these solutions and other approaches. The tests showed that the retroactive implementations proposed by Demaine et. al (2007) [13] obtained the best results from a temporal point of view. It was proposed two algorithms which used the retroactivity concepts inside its development: the fully retroactive minimum spanning tree and the single source dynamic shortest path problem in dynamic graphs. Let m be data structure’s timeline, V(G) and A(G) the sets of vertices and edges from graph G. We reached an amortized time complexity O( √ m· lg |V(G)|) per query/update operation in the fully retroactive minimum spanning tree algorithm. The algorithm to solve the single source dynamic shortest path problem in dynamic graphs proposed by Sunita et. al [52] obtained a time complexity O(|A(G)| · lg |V(G)|) per modification using a non-oblivious retroactive priority queue.Agência 1A retroatividade em programação é um conceito que pode ser definido como o estudo da modificação da linha temporal em uma estrutura de dados, bem como a análise dos efeitos dessa modificação através de toda a sua existência. Em geral, essa análise e implementação tendem a serem mais custosas do ponto de vista computacional, observando-se que uma modificação no passado pode gerar um efeito cascata por toda a existência dessa estrutura. O conceito de retroatividade gera ferramentas e estruturas que otimizam as soluções para a natureza desses problemas temporais. Esse tipo de estrutura pode ser utilizada nas aplicações das mais diversas naturezas, desde em algoritmos de caminho mínimo, aplicações em segurança e até em aplicações geométricas. Nessa dissertação, tem-se os subsídios teóricos sobre essas estruturas, um material detalhado sobre a implementação das estruturas mais comuns utilizando o paradigma da retroatividade, e a implementação de alguns problemas que podem ser resolvidos utilizando técnicas de retroatividade, como, por exemplo, o algoritmo de árvore geradora mínima totalmente dinâmica. Para cada estrutura, foram executados testes práticos sobre as estruturas retroativas e seu desempenho foi comparado às outras implementações dessas mesmas estruturas. Os testes mostraram que as implementações retroativas propostas por Demaine et. al (2007) obtiveram os melhores resultados do ponto de vista temporal. Além disso, foram propostos dois algoritmos que utilizam os conceitos de retroatividade para sua construção: o algoritmo para o problema da árvore geradora mínima totalmente retroativa e o algoritmo do caminho mínimo a partir de um vértice inicial fixo em grafos dinâmicos. Seja m o tamanho da linha temporal em que a estrutura está implementada, V(G) e A(G) o conjunto de vértices e arestas de um grafo G respectivamente. Foi alcançada a complexidade de tempo amortizada de O(√m· log |V(G)|) por operação de atualização ou consulta, para o problema da árvore geradora mínima totalmente retroativa. Para o algoritmo do caminho mínimo, a partir de um vértice inicial fixo em grafos dinâmicos, por meio do algoritmo proposto por Sunita et. al [52], foi obtida a complexidade temporal de O(|A(G)| · lg |V(G)|) por modificação, utilizando filas de prioridade com retroatividade não-consistente

Bearing-Only Control Laws For Balanced Circular Formations of Ground Robots

Abstract — For a group of constant-speed ground robots, a simple control law is designed to stabilize the motion of the group into a balanced circular formation using a consensus approach. It is shown that the measurements of the bearing angles between the robots are sufficient for reaching a balanced circular formation. We consider two different scenarios that the connectivity graph of the system is either a complete graph or a ring. Collision avoidance capabilities are added to the team members and the effectiveness of the control laws are demonstrated on a group of mobile robots. I