Controlling the mobility and enhancing the performance of multiple message ferries in delay tolerant networks

In einem drahtlosen Netzwerk mit isolierten und stationären Knoten können Adhoc und verzögerungstolerante Netzwerk Routing-Protokolle nicht verwendet werden. Message Ferry Netzwerke sind die Lösung für diese Fälle, in denen ein (oder mehrere) Message Ferry Knoten den store-carry-forward Mechanismus verwendet und zwischen den Knoten reist, um Nachrichten auszutauschen. In diesem Fall erfahren die Nachrichten für gewöhnlich eine lange Verzögerung. Um die Performance der Message Ferry Netzwerke zu verbessern, kann die Mobilität der Message Ferry Knoten gesteuert werden. In dieser Doktorarbeit werden zwei Strategien zur Steuerung der Mobilität der Message Ferry Knoten studiert. Die Strategien sind das on-the-fly Entscheidungsverfahren in Ferry Knoten und die offline Wegplanung für Ferry Knoten. Für die on-the-fly Strategie untersucht diese Arbeit Decision-maker in Ferry Knoten, der die Entscheidung auf Grundlage der lokalen Observation eines Ferry Knoten trifft. Zur Koordinierung mehrerer Ferry Knoten, die keine globale Kenntnis über das Netzwerk haben, wird eine indirekte Signalisierung zwischen Ferry Knoten vorgeschlagen. Zur Kooperation der Ferry Knoten für die Zustellung der Nachrichten werden einige Ansätze zum Nachrichtenaustausch zwischen Ferry Knoten vorgeschlagen, in denen der Decision-maker eines Ferry Knotens seine Information mit dem verzögerungstoleranten Router des Ferry Knoten teilt, um die Effizienz des Nachrichtenaustauschs zwischen Ferry Knoten zu verbessern. Umfangreiche Simulationsstudien werden zur Untersuchung der vorgeschlagenen Ansätze und des Einflusses verschiedener Nachrichtenverkehrsszenarien vorgenommen. Außerdem werden verschiedene Szenarien mit unterschiedlicher Anzahl von Ferry Knoten, verschiedener Geschwindigkeit der Ferry Knoten und verschiedener Ansätze zum Nachrichtenaustausch zwischen Ferry Knoten studiert. Zur Evaluierung der offline Wegplanungsstrategie wird das Problem als Multiple Traveling Salesmen Problem (mTSP) modelliert und ein genetischer Algorithmus zur Approximation der Lösung verwendet. Es werden verschiedene Netzwerkarchitekturen zur Pfadplanung der Ferry Knoten vorgestellt und studiert. Schließlich werden die Strategien zur Steuerung der Mobilität der Ferry Knoten verglichen. Die Ergebnisse zeigen, dass die Performance der Strategien in Bezug auf die Ende-zu-Ende-Verzögerung von dem Szenario des Nachrichtenverkehrs abhängt. In Szenarien, wie Nachrichtenverkehr in Sensor-Netzwerken, in denen ein Knoten die Nachrichten zu allen anderen Knoten sendet oder von allen anderen Knoten empfängt, zeigt die offline Wegplanung, basierend auf der mTSP Lösung, bessere Performance als die on-the-fly Strategie. Andererseits ist die on-the-fly Stratgie eine bessere Wahl in Szenarien wie Nachrichtenaustausch zwischen Rettungskräften während einer Katastrophe, in denen alle drahtlose Knoten die Nachrichten austauschen müssen. Zudem ist die on-the-fly Strategie flexibler, robuster als offline Wegplanung und benötigt keine Initialisierungszeit.In a wireless network with isolated and stationary nodes, ad hoc and delay tolerant routing approaches fail to deliver messages. Message ferry networks are the solution for such networks where one or multiple mobile nodes, i.e. message ferry, apply the store-carry-forward mechanism and travel between nodes to exchange their messages. Messages usually experience a long delivery delay in this type of network. To improve the performance of message ferry networks, the mobility of ferries can be controlled. In this thesis, two main strategies to control mobility of multiple message ferries are studied. The strategies are the on-the-fly mobility decision making in ferries and the offline path planning for ferries. To apply the on-the-fly strategy, this work proposes a decision maker in ferries which makes mobility decisions based on the local observations of ferries. To coordinate multiple ferries, which have no global view from the network, an indirect signaling of ferries is proposed. For cooperation of ferries in message delivery, message forwarding and replication schemes are proposed where the mobility decision maker shares its information with the delay tolerant router of ferries to improve the efficiency of message exchange between ferries. An extensive simulation study is performed to investigate the performance of the proposed schemes and the impact of different traffic scenarios in a network. Moreover, different scenarios with different number of ferries, different speed of ferries and different message exchange approaches between ferries are studied. To study the offline path planning strategy, the problem is modeled as multiple traveling salesmen problem (mTSP) and a genetic algorithm is applied to approximate the solution. Different network architectures are proposed and studied where the path of ferries are planned in advance. Finally, the strategies to control the mobility of ferries are compared. The results show that the performance of each strategy, in terms of the average end-to-end delay of messages, depends on the traffic scenario in a network. In traffic scenarios same as the traffic in sensor networks, where only a single node generates messages to all nodes or receives messages from all node, the offline path planning based on mTSP solution performs better than the on-the-fly decision making. On the other hand, in traffic scenarios same as the traffic in disaster scenarios, where all nodes in a network may send and receive messages, the on-the-fly decision making provides a better performance. Moreover, the on-thy-fly decision making is always more flexible, more robust and does not need any initialization time

Unified Role Assignment Framework For Wireless Sensor Networks

Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing. The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue this by first developing a Role-based Hierarchical Self-Organization (RBSHO) protocol that organizes a connected dominating set (CDS) of nodes called dominators. This is done by hierarchically selecting nodes that possess cumulatively high energy, connectivity, and sensing capabilities in their local neighborhood. The RBHSO protocol then assigns specific tasks such as sensing, coordination, and routing to appropriate dominators that end up playing a certain role in the network. Roles, though abstract and implicit, expose role-specific resource controls by way of role assignment and scheduling. Based on this concept, we have designed a Unified Role-Assignment Framework (URAF) to model application services as roles played by local in-network sensor nodes with sensor capabilities used as rules for role identification. The URAF abstracts domain specific role attributes by three models: the role energy model, the role execution time model, and the role service utility model. The framework then generalizes resource management for services by providing abstractions for controlling the composition of a service in terms of roles, its assignment, reassignment, and scheduling. To the best of our knowledge, a generic role-based framework that provides a simple and unified network management solution for wireless sensor networks has not been proposed previously

A Biologically Inspired Networking Model for Wireless Sensor Networks

Wireless sensor networks (WSNs) have emerged in strategic applications such as target detection, localization, and tracking in battlefields, where the large-scale na- ture renders centralized control prohibitive. In addition, the finite batteries in sensor nodes demand energy-aware network control. In this thesis, we propose an energy- efficient topology management model inspired by biological inter-cellular signaling schemes. The model allows sensor nodes to cluster around imminent targets in a purely distributed and autonomous fashion. In particular, nodes in the target vicinity collaborate to form clusters based on their relative observation quality values. Sub- sequently, the clustered sensor nodes compete based on their energy levels until some of them gain active status while the rest remain idle, again according to a distributed algorithm based on biological processes. A final phase of the model has the active cluster members compete until one of them becomes the clusterhead. We examine the behavior of such a model in both finite-size and infinite-size networks. Specifically, we show that the proposed model is inherently stable and achieves superior energy efficiency against reference protocols for networks of finite size. Furthermore, we dis- cuss the behavior of the model in the asymptotic case when the number of nodes goes to infinity. In this setting, we study the average number of cluster members

Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved

Security and Privacy in Molecular Communication and Networking: Opportunities and Challenges

International audienceMolecular Communication (MC) is an emerging andpromising communication paradigm for several multi-disciplinarydomains like bio-medical, industry and military. Differently to thetraditional communication paradigm, the information is encodedon the molecules, that are then used as carriers of information.Novel approaches related to this new communication paradigmhave been proposed, mainly focusing on architectural aspects andcategorization of potential applications. So far, security and privacyaspects related to the molecular communication systems havenot been investigated at all and represent an open question thatneed to be addressed. The main motivation of this paper lies onproviding some first insights about security and privacy aspects ofMC systems, by highlighting the open issues and challenges andabove all by outlining some specific directions of potential solutions.Existing cryptographicmethods and security approaches arenot suitable for MC systems since do not consider the pecific issuesand challenges, that need ad-hoc solutions.We will discuss directionsin terms of potential solutions by trying to highlight themain advantages and potential drawbacks for each direction considered.We will try to answer to the main questions: 1) why thissolution can be exploited in the MC field to safeguard the systemand its reliability? 2) which are the main issues related to the specificapproach

Mobile Ad hoc Networking: Imperatives and Challenges

Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, "ad-hoc" network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-existing communication infrastructure, e.g., disaster recovery environments. Ad hoc networking concept is not a new one, having been around in various forms for over 20 years. Traditionally, tactical networks have been the only communication networking application that followed the ad hoc paradigm. Recently, the introduction of new technologies such as the Bluetooth, IEEE 802.11 and Hyperlan are helping enable eventual commercial MANET deployments outside the military domain. These recent evolutions have been generating a renewed and growing interest in the research and development of MANET. This paper attempts to provide a comprehensive overview of this dynamic field. It first explains the important role that mobile ad hoc networks play in the evolution of future wireless technologies. Then, it reviews the latest research activities in these areas, including a summary of MANET\u27s characteristics, capabilities, applications, and design constraints. The paper concludes by presenting a set of challenges and problems requiring further research in the future

Energy Harvesting-Aware Design for Wireless Nanonetworks

Nanotechnology advancement promises to enable a new era of computing and communication devices by shifting micro scale chip design to nano scale chip design. Nanonetworks are envisioned as artifacts of nanotechnology in the domain of networking and communication. These networks will consist of nodes of nanometer to micrometer in size, with a communication range up to 1 meter. These nodes could be used in various biomedical, industrial, and environmental monitoring applications, where a nanoscale level of sensing, monitoring, control and communication is required. The special characteristics of nanonetworks require the revisiting of network design. More specifically, nanoscale limitations, new paradigms of THz communication, and power supply via energy harvesting are the main issues that are not included in traditional network design methods. In this regard, this dissertation investigates and develops some solutions in the realization of nanonetworks. Particularly, the following major solutions are investigated. (I) The energy harvesting and energy consumption processes are modeled and evaluated simultaneously. This model includes the stochastic nature of energy arrival as well as the pulse-based communication model for energy consumption. The model identifies the effect of various parameters in this joint process. (II) Next, an optimization problem is developed to find the best combination of these parameters. Specifically, optimum values for packet size, code weight, and repetition are found in order to minimize the energy consumption while satisfying some application requirements (i.e., delay and reliability). (III) An optimum policy for energy consumption to achieve the maximum utilization of harvested energy is developed. The goal of this scheme is to take advantage of available harvested energy as much as possible while satisfying defined performance metrics. (IV) A communication scheme that tries to maximize the data throughput via a distributed and scalable coordination while avoiding the collision among neighbors is the last problem to be investigated. The goal is to design an energy harvesting-aware and distributed mechanism that could coordinate data transmission among neighbors. (V) Finally, all these solutions are combined together to create a data link layer model for nanonodes. We believe resolving these issues could be the first step towards an energy harvesting-aware network design for wireless nanosensor networks

High Accuracy Distributed Target Detection and Classification in Sensor Networks Based on Mobile Agent Framework

High-accuracy distributed information exploitation plays an important role in sensor networks. This dissertation describes a mobile-agent-based framework for target detection and classification in sensor networks. Specifically, we tackle the challenging problems of multiple- target detection, high-fidelity target classification, and unknown-target identification. In this dissertation, we present a progressive multiple-target detection approach to estimate the number of targets sequentially and implement it using a mobile-agent framework. To further improve the performance, we present a cluster-based distributed approach where the estimated results from different clusters are fused. Experimental results show that the distributed scheme with the Bayesian fusion method have better performance in the sense that they have the highest detection probability and the most stable performance. In addition, the progressive intra-cluster estimation can reduce data transmission by 83.22% and conserve energy by 81.64% compared to the centralized scheme. For collaborative target classification, we develop a general purpose multi-modality, multi-sensor fusion hierarchy for information integration in sensor networks. The hierarchy is com- posed of four levels of enabling algorithms: local signal processing, temporal fusion, multi-modality fusion, and multi-sensor fusion using a mobile-agent-based framework. The fusion hierarchy ensures fault tolerance and thus generates robust results. In the meanwhile, it also takes into account energy efficiency. Experimental results based on two field demos show constant improvement of classification accuracy over different levels of the hierarchy. Unknown target identification in sensor networks corresponds to the capability of detecting targets without any a priori information, and of modifying the knowledge base dynamically. In this dissertation, we present a collaborative method to solve this problem among multiple sensors. When applied to the military vehicles data set collected in a field demo, about 80% unknown target samples can be recognized correctly, while the known target classification ac- curacy stays above 95%