Self-organizing Network Optimization via Placement of Additional Nodes

Das Hauptforschungsgebiet des Graduiertenkollegs "International Graduate School on Mobile Communication" (GS Mobicom) der Technischen Universität Ilmenau ist die Kommunikation in Katastrophenszenarien. Wegen eines Desasters oder einer Katastrophe können die terrestrischen Elementen der Infrastruktur eines Kommunikationsnetzwerks beschädigt oder komplett zerstört werden. Dennoch spielen verfügbare Kommunikationsnetze eine sehr wichtige Rolle während der Rettungsmaßnahmen, besonders für die Koordinierung der Rettungstruppen und für die Kommunikation zwischen ihren Mitgliedern. Ein solcher Service kann durch ein mobiles Ad-Hoc-Netzwerk (MANET) zur Verfügung gestellt werden. Ein typisches Problem der MANETs ist Netzwerkpartitionierung, welche zur Isolation von verschiedenen Knotengruppen führt. Eine mögliche Lösung dieses Problems ist die Positionierung von zusätzlichen Knoten, welche die Verbindung zwischen den isolierten Partitionen wiederherstellen können. Hauptziele dieser Arbeit sind die Recherche und die Entwicklung von Algorithmen und Methoden zur Positionierung der zusätzlichen Knoten. Der Fokus der Recherche liegt auf Untersuchung der verteilten Algorithmen zur Bestimmung der Positionen für die zusätzlichen Knoten. Die verteilten Algorithmen benutzen nur die Information, welche in einer lokalen Umgebung eines Knotens verfügbar ist, und dadurch entsteht ein selbstorganisierendes System. Jedoch wird das gesamte Netzwerk hier vor allem innerhalb eines ganz speziellen Szenarios - Katastrophenszenario - betrachtet. In einer solchen Situation kann die Information über die Topologie des zu reparierenden Netzwerks im Voraus erfasst werden und soll, natürlich, für die Wiederherstellung mitbenutzt werden. Dank der eventuell verfügbaren zusätzlichen Information können die Positionen für die zusätzlichen Knoten genauer ermittelt werden. Die Arbeit umfasst eine Beschreibung, Implementierungsdetails und eine Evaluierung eines selbstorganisierendes Systems, welche die Netzwerkwiederherstellung in beiden Szenarien ermöglicht.The main research area of the International Graduate School on Mobile Communication (GS Mobicom) at Ilmenau University of Technology is communication in disaster scenarios. Due to a disaster or an accident, the network infrastructure can be damaged or even completely destroyed. However, available communication networks play a vital role during the rescue activities especially for the coordination of the rescue teams and for the communication between their members. Such a communication service can be provided by a Mobile Ad-Hoc Network (MANET). One of the typical problems of a MANET is network partitioning, when separate groups of nodes become isolated from each other. One possible solution for this problem is the placement of additional nodes in order to reconstruct the communication links between isolated network partitions. The primary goal of this work is the research and development of algorithms and methods for the placement of additional nodes. The focus of this research lies on the investigation of distributed algorithms for the placement of additional nodes, which use only the information from the nodes’ local environment and thus form a self-organizing system. However, during the usage specifics of the system in a disaster scenario, global information about the topology of the network to be recovered can be known or collected in advance. In this case, it is of course reasonable to use this information in order to calculate the placement positions more precisely. The work provides the description, the implementation details and the evaluation of a self-organizing system which is able to recover from network partitioning in both situations

Use of Inferential Statistics to Design Effective Communication Protocols for Wireless Sensor Networks

This thesis explores the issues and techniques associated with employing the principles of inferential statistics to design effective Medium Access Control (MAC), routing and duty cycle management strategies for multihop Wireless Sensor Networks (WSNs). The main objective of these protocols are to maximise the throughput of the network, to prolong the lifetime of nodes and to reduce the end-to-end delay of packets over a general network scenario without particular considerations for specific topology configurations, traffic patterns or routing policies. WSNs represent one of the leading-edge technologies that have received substantial research efforts due to their prominent roles in many applications. However, to design effective communication protocols for WSNs is particularly challenging due to the scarce resources of these networks and the requirement for large-scale deployment. The MAC, routing and duty cycle management protocols are amongst the important strategies that are required to ensure correct operations of WSNs. This thesis makes use of the inferential statistics field to design these protocols; inferential statistics was selected as it provides a rich design space with powerful approaches and methods. The MAC protocol proposed in this thesis exploits the statistical characteristics of the Gamma distribution to enable each node to adjust its contention parameters dynamically based on its inference for the channel occupancy. This technique reduces the service time of packets and leverages the throughput by improving the channel utilisation. Reducing the service time minimises the energy consumed in contention to access the channel which in turn prolongs the lifetime of nodes. The proposed duty cycle management scheme uses non-parametric Bayesian inference to enable each node to determine the best times and durations for its sleeping durations without posing overheads on the network. Hence the lifetime of node is prolonged by mitigating the amount of energy wasted in overhearing and idle listening. Prolonging the lifetime of nodes increases the throughput of the network and reduces the end-to-end delay as it allows nodes to route their packets over optimal paths for longer periods. The proposed routing protocol uses one of the state-of-the-art inference techniques dubbed spatial reasoning that enables each node to figure out the spatial relationships between nodes without overwhelming the network with control packets. As a result, the end-to-end delay is reduced while the throughput and lifetime are increased. Besides the proposed protocols, this thesis utilises the analytical aspects of statistics to develop rigorous analytical models that can accurately predict the queuing and medium access delay and energy consumption over multihop networks. Moreover, this thesis provides a broader perspective for design of communication protocols for WSNs by casting the operations of these networks in the domains of the artificial chemistry discipline and the harmony search optimisation algorithm

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Generic Adaptation Support for Wireless Sensor Networks

Wireless Sensor Networks are used in various and expanding application scenarios and are also considered to be important elements of the Internet of Things. They monitor and deliver data, which is not only used for research but to an increasing degree also in business environments. With the increasing complexity of these scenarios and the increasing dependency on the availability of the sensor network data, the requirements to a Wireless Sensor Network increase at the same pace. Since Wireless Sensor Networks are typically implemented using resource-constrained platforms, sensor network algorithms are typically optimised for specific operating conditions such as static or mobile networks, high or low traffic etc. However, due to scenario complexity and dynamic real-world conditions a static configuration of a Wireless Sensor Network software cannot always meet the requirements. Moreover, these requirements of the sensor network's user can change over time, for example concerning accuracy. Therefore, the sensor network software has to adapt itself to cope with dynamic system conditions and user requirements. This thesis presents the TinyAdapt and TinySwitch frameworks to solve the aforementioned problems. TinyAdapt, our generic adaptation framework for Wireless Sensor Networks, allows for the autonomous adaptation of arbitrary sensor network algorithms based on explicit and intuitively defined user preferences and on automatically monitored network conditions. Due to a two-phase approach, run-time adaptation is executed completely and efficiently on standard sensor node hardware and does not need support from, e.g., the base station. The creation of adaptive applications is guided by a complete workflow, which is presented as well. When changing parameters of an algorithm is not enough to achieve the desired adaptation results, the algorithm has to be exchanged completely. However, several limitations of TinyOS and the sensor node hardware limit the use of simple code exchange by node reprogramming for efficient adaptation. TinySwitch, our generic switching framework, allows to switch between alternative algorithms that are already installed in parallel. TinySwitch analyses these algorithms, determines their dependencies and creates all code to enable one of the algorithms while isolating all others. Due to its minimal overhead, TinySwitch is perfectly suited for run-time adaptation in TinyAdapt

Journal of Telecommunications and Information Technology, 2019, nr 1

kwartalni

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

An investigation of mobile ad-hoc network performance with cognitive attributes applied

Mobile Ad-Hoc Networks (MANETs) are known for their versatility, which is they are capable of supporting many applications. In addition to this versatility MANETs are quick to deploy without need for an existing predefined communications infrastructure. However, although the lack of infrastructure allows for the quick deployment of the data communications network, it adds many factors that hinder packet delivery. Such hindrances occur because of the dynamic topology caused by the mobility of the nodes which results in link breakages. Routing protocols exist that attempt to refresh available routes; however, this is after link breakages have occurred. The nodes also usually have constrained resources (i.e. energy source and limited bandwidth). This thesis presents a novel approach of network behaviour and management by implementing cognitive attributes into a MANET environment. This allows an application to better meet its mission objectives, decreases the end-to-end delay, and increases packet delivery ratio. The network is able to make observations, consider previous actions and consequences of the actions, and make changes based on the prior knowledge and experience. This work also shows how the network can better utilise limited resources such as bandwidth allocation by applying cognitive attributes. Simulations conducted show promising results and prove that an increase in network performance is possible if adopting a cross-layered approach and allow the network to manage and to ‘think’ for itself. Various simulations were run with various scenarios and results are presented without cognition applied, with partial cognition applied and with full cognition applied. A total of 52 simulations were run and from this the results were compared and contrasted. The analysis shows that cognitive attributes does increase network performance in the majority of applications