StrawMAN: Making Sudden Traffic Surges Graceful in Low-Power Wireless Networks

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Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Field-Deployable Concurrent-Transmitter Networks for Long Term Environmental Monitoring

In this work, I draw upon my experience with field deployments of low-power data collection systems to come up with new approaches to long-term environmental monitoring (LTEM). Our goal is to develop long-lived, reliable systems that can be deployed by non-experts. The specific requirements of LTEM systems lead us to pursue techniques which can take advantage of the natural heirarchies that exist in sensor deployments while avoiding the difficulties inherent in selecting efficient data transmission routes in the face of unreliable hardware and difficult-to-measure link dynamics. The approach we advocate eschews traditional single-path routing and transmission methods in favor of approaches that leverage non-destructive simultaneous packet transmissions over subsets of the network. We apply this principle to develop a medium access protocol suitable for dense networks (Flip-MAC) as well as a method for identifying the set of potentially-useful forwarders between a data source and its destination (CX). This document not only characterizes and evaluates the low-level behavior of these protocols, but also describes the design of a larger multi-tiered data collection system based on CX, a suite of hardware which is well-suited to both CX and common deployment patterns, and the design of a ``dirt-to-database'' system which gives domain scientists the tools they need to deploy and manage networks on their own

Topics in Distributed Algorithms: On Wireless Networks, Distributed Storage and Streaming

Distributed algorithms are executed on a set of computational instances. Werefer to these instances as nodes. Nodes are runningconcurrently and are independent from each other. Furthermore, they have their own instructions and information. In this context, the challenges are to show thatthe algorithm is correct, regardless of computational, or communication delaysand to show bounds on the usage of communication.We are especially interested the behaviour after transient faults and underthe existence of Byzantine nodes.This thesis discusses fundamental communication models for distributed algorithms. These models are implementing abstract communication methods. First, we address medium access control for a wireless medium with guaranteeson the communication delay. We discuss time division multiple access(TDMA) protocols for ad-hoc networks and we introduce an algorithm that creates aTDMA schedule without using external references for localisation, or time. We justify our algorithm by experimental results.The second topic is the emulation of shared memory on message passingnetworks. Both, shared memory and message passing are basic interprocessorcommunication models for distributed algorithms. We are providing a way ofemulating shared memory on top of an existing message passing network underthe presence of data corruption and stop-failed nodes. Additionally, we ensurethe privacy of the data that is stored in the shared memory. The third topic looks into streaming algorithms and optimisation. We study the problem of sorting a stream ofvehicles on a highway with severallanes so that each vehicle reaches its target lane. We look into optimality interms of minimising the number of move operations, as well as, minimising the length of the output stream. We present an exact algorithm for the case oftwo lanes and show that NP-Hardness for a increasing number of lanes

Towards reliable communication in low-power wireless body area networks

Es wird zunehmend die Ansicht vertreten, dass tragbare Computer und Sensoren neue Anwendungen in den Bereichen Gesundheitswesen, personalisierte Fitness oder erweiterte Realität ermöglichen werden. Die am Körper getragenen Geräte sind dabei mithilfe eines Wireless Body Area Network (WBAN) verbunden, d.h. es wird drahtlose Kommunikation statt eines drahtgebundenen Kanals eingesetzt. Der drahtlose Kanal ist jedoch typischerweise ein eher instabiles Kommunikationsmedium und die Einsatzbedingungen von WBANs sind besonders schwierig: Einerseits wird die Kanalqualität stark von den physischen Bewegungen der Person beeinflusst, andererseits werden WBANs häufig in lizenzfreien Funkbändern eingesetzt und sind daher Störungen von anderen drahtlosen Geräten ausgesetzt. Oft benötigen WBAN Anwendungen aber eine zuverlässige Datenübertragung. Das erste Ziel dieser Arbeit ist es, ein besseres Verständnis dafür zu schaffen, wie sich die spezifischen Einsatzbedingungen von WBANs auf die intra-WBAN Kommunikation auswirken. So wird zum Beispiel analysiert, welchen Einfluss die Platzierung der Geräte auf der Oberfläche des menschlichen Körpers und die Mobilität des Benutzers haben. Es wird nachgewiesen, dass während regelmäßiger Aktivitäten wie Laufen die empfangene Signalstärke stark schwankt, gleichzeitig aber Signalstärke-Spitzen oft einem regulären Muster folgen. Außerdem wird gezeigt, dass in urbanen Umgebungen die Effekte von 2.4 GHz Radio Frequency (RF) Interferenz im Vergleich zu den Auswirkungen von fading (Schwankungen der empfangenen Signalstärke) eher gering sind. Allerdings führt RF Interferenz dazu, dass häufiger Bündelfehler auftreten, d.h. Fehler zeitlich korrelieren. Dies kann insbesondere in Anwendungen, die eine geringe Übertragungslatenz benötigen, problematisch sein. Der zweite Teil dieser Arbeit beschäftigt sich mit der Analyse von Verfahren, die potentiell die Zuverlässigkeit der Kommunikation in WBANs erhöhen, ohne dass wesentlich mehr Energie verbraucht wird. Zunächst wird der Trade-off zwischen Übertragungslatenz und der Zuverlässigkeit der Kommunikation analysiert. Diese Analyse basiert auf einem neuen Paket-Scheduling Algorithmus, der einen Beschleunigungssensor nutzt, um die WBAN Kommunikation auf die physischen Bewegungen der Person abzustimmen. Die Analyse zeigt, dass unzuverlässige Kommunikationsverbindungen oft zuverlässig werden, wenn Pakete während vorhergesagter Signalstärke-Spitzen gesendet werden. Ferner wird analysiert, inwiefern die Robustheit gegen 2.4 GHz RF Interferenz verbessert werden kann. Dazu werden zwei Verfahren betrachtet: Ein bereits existierendes Verfahren, das periodisch einen Wechsel der Übertragungsfrequenz durchführt (channel hopping) und ein neues Verfahren, das durch RF Interferenz entstandene Bitfehler reparieren kann, indem der Inhalt mehrerer fehlerhafter Pakete kombiniert wird (packet combining). Eine Schlussfolgerung ist, dass Frequenzdiversität zwar das Auftreten von Bündelfehlern reduzieren kann, dass jedoch die statische Auswahl eines Kanals am oberen Ende des 2.4 GHz Bandes häufig schon eine akzeptable Abhilfe gegen RF Interferenz darstellt.There is a growing belief that wearable computers and sensors will enable new applications in areas such as healthcare, personal fitness or augmented reality. The devices are attached to a person and connected through a Wireless Body Area Network (WBAN), which replaces the wires of traditional monitoring systems by wireless communication. This comes, however, at the cost of turning a reliable communication channel into an unreliable one. The wireless channel is typically a rather unstable medium for communication and the conditions under which WBANs have to operate are particularly harsh: not only is the channel strongly influenced by the movements of the person, but WBANs also often operate in unlicensed frequency bands and may therefore be exposed to a significant amount of interference from other wireless devices. Yet, many envisioned WBAN applications require reliable data transmission. The goals of this thesis are twofold: first, we aim at establishing a better understanding of how the specific WBAN operating conditions, such as node placement on the human body surface and user mobility, impact intra-WBAN communication. We show that during periodic activities like walking the received signal strength on an on-body communication link fluctuates strongly, but signal strength peaks often follow a regular pattern. Furthermore, we find that in comparison to the effects of fading 2.4 GHz Radio Frequency (RF) interference causes relatively little packet loss - however, urban 2.4 GHz RF noise is bursty (correlated in time), which may be problematic for applications with low latency bounds. The second goal of this thesis is to analyze how communication reliability in WBANs can be improved without sacrificing a significant amount of additional energy. To this end, we first explore the trade-off between communication latency and communication reliability. This analysis is based on a novel packet scheduling algorithm, which makes use of an accelerometer to couple WBAN communication with the movement patterns of the user. The analysis shows that unreliable links can often be made reliable if packets are transmitted at predicted signal strength peaks. In addition, we analyze to what extent two mechanisms can improve robustness against 2.4 GHz RF interference when adopted in a WBAN context: we analyze the benefits of channel hopping, and we examine how the packet retransmission process can be made more efficient by using a novel packet combining algorithm that allows to repair packets corrupted by RF interference. One of the conclusions is that while frequency agility may decrease "burstiness" of errors the static selection of a channel at the upper end of the 2.4 GHz band often already represents a good remedy against RF interference

Perpetual Sensing: Experiences with Energy-Harvesting Sensor Systems

Industry forecasts project the number of connected devices will outpace the global population by orders of magnitude in the next decade or two. These projections are application driven: smart cities, implantable health monitors, responsive buildings, autonomous robots, driverless cars, and instrumented infrastructure are all expected to be drivers for the growth of networked devices. Achieving this immense scale---potentially trillions of smart and connected sensors and computers, popularly called the "Internet of Things"---raises a host of challenges including operating system design, networking protocols, and orchestration methodologies. However, another critical issue may be the most fundamental: If embedded computers outnumber people by a factor of a thousand, how are we going to keep all of these devices powered? In this dissertation, we show that energy-harvesting operation, by which devices scavenge energy from their surroundings to power themselves after they are deployed, is a viable answer to this question. In particular, we examine a range of energy-harvesting sensor node designs for a specific application: smart buildings. In this application setting, the devices must be small and sleek to be unobtrusively and widely deployed, yet shrinking the devices also reduces their energy budgets as energy storage often dominates their volume. Additionally, energy-harvesting introduces new challenges for these devices due to the intermittent access to power that stems from relying on unpredictable ambient energy sources. To address these challenges, we present several techniques for realizing effective sensors despite the size and energy constraints. First is Monjolo, an energy metering system that exploits rather than attempts to mask the variability in energy-harvesting by using the energy harvester itself as the sensor. Building on Monjolo, we show how simple time synchronization and an application specific sensor can enable accurate, building-scale submetering while remaining energy-harvesting. We also show how energy-harvesting can be the foundation for highly deployable power metering, as well as indoor monitoring and event detection. With these sensors as a guide, we present an architecture for energy-harvesting systems that provides layered abstractions and enables modular component reuse. We also couple these sensors with a generic and reusable gateway platform and an application-layer cloud service to form an easy-to-deploy building sensing toolkit, and demonstrate its effectiveness by performing and analyzing several modest-scale deployments.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138686/1/bradjc_1.pd