Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

Many-to-many data aggregation scheduling in wireless sensor networks with two sinks

Traditionally, wireless sensor networks (WSNs) have been deployed with a single sink. Due to the emergence of sophisticated applications, WSNs may require more than one sink. Moreover, deploying more than one sink may prolong the network lifetime and address fault tolerance issues. Several protocols have been proposed for WSNs with multiple sinks. However, most of them are routing protocols. Differently, our main contribution, in this paper, is the development of a distributed data aggregation scheduling (DAS) algorithm for WSNs with two sinks. We also propose a distributed energy-balancing algorithm to balance the energy consumption for the aggregators. The energy-balancing algorithm first forms trees rooted at nodes which are termed virtual sinks and then balances the number of children at a given level to level the energy consumption. Subsequently, the DAS algorithm takes the resulting balanced tree and assigns contiguous slots to sibling nodes, to avoid unnecessary energy waste due to frequent active-sleep transitions. We prove a number of theoretical results and the correctness of the algorithms. Through simulation and testbed experiments, we show the correctness and performance of our algorithms

Source location privacy-aware data aggregation scheduling for wireless sensor networks

Source Location Privacy (SLP) is an important property for the class of asset monitoring problems in wireless sensor networks (WSNs). SLP aims to prevent an attacker from finding a valuable asset when a WSN node is broadcasting information due to the detection of the asset. Many different methods of protecting the location of a source have been devised for a variety of attacker models. Most common methods of providing SLP operate at the routing level of the network stack, imposing a high message overhead on the SLP-aware routing protocol. The objective of this thesis is to investigate the novel problem of utilising TDMA slot assignment schedules at the MAC layer in order to provide SLP. These schedules each give rise to different traffic patterns, manipulation of which can be used to divert an attacker away from the asset. Four main contributions are presented. First, a novel formalisation of a parameterised eavesdropping attacker model is created, allowing for comparison of attackers of different strengths. Second, a genetic algorithm is used to generate TDMA Data Aggregation Scheduling (DAS) schedules that contain a diversionary route that leads the attacker away from the source. Third, a distributed algorithm is created to perform the same task while operating online on a WSN. Finally, another distributed algorithm is presented that provides fault-tolerant guarantees with a minimal drop in performance

A Network Stability Monitoring Mechanism of Cluster-Oriented Wireless Sensor Network

In wireless sensor network (WSN), every sensor node could active dynamically. Therefore, those sensor nodes will affect the stability of network topology because of clustering and de-clustering, and continuously make reconfiguration for the clusters of wireless sensor network, all that will influence the overall function of network. It is an important issue that how to elect a cluster manager (CM) to keep the stability of network topology. In addition, large amount of events maybe flood suddenly in a local area. Such the case might raise the overload of CM, even lead CM to fail or crash and the WSN topology maybe self-organized. However, a mechanism needs to be considered that allows coping with the additional loads and can balance the workload of CM. In this study, a preventable and supportable monitor mechanism to avoid CM overload cause network unstable and to reduce load imbalance problem is proposed. Hence, it can prolong lifetime of network and raise performance of network efficiently

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment

Synchronous and Concurrent Transmissions for Consensus in Low-Power Wireless

With the emergence of the Internet of Things, autonomous vehicles and the Industry 4.0, the need for dependable yet adaptive network protocols is arising. Many of these applications build their operations on distributed consensus. For example, UAVs agree on maneuvers to execute, and industrial systems agree on set-points for actuators.Moreover, such scenarios imply a dynamic network topology due to mobility and interference, for example. Many applications are mission- and safety-critical, too.Failures could cost lives or precipitate economic losses.In this thesis, we design, implement and evaluate network protocols as a step towards enabling a low-power, adaptive and dependable ubiquitous networking that enables consensus in the Internet of Things. We make four main contributions:- We introduce Orchestra that addresses the challenge of bringing TSCH (Time Slotted Channel Hopping) to dynamic networks as envisioned in the Internet of Things. In Orchestra, nodes autonomously compute their local schedules and update automatically as the topology evolves without signaling overhead. Besides, it does not require a central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules.- We present A2 : Agreement in the Air, a system that brings distributed consensus to low-power multihop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this layer and enables the two- and three-phase commit protocols, and services such as group membership, hopping sequence distribution, and re-keying.- We present Wireless Paxos, a fault-tolerant, network-wide consensus primitive for low-power wireless networks. It is a new variant of Paxos, a widely used consensus protocol, and is specifically designed to tackle the challenges of low-power wireless networks. By utilizing concurrent transmissions, it provides a dependable low-latency consensus.- We present BlueFlood, a protocol that adapts concurrent transmissions to Bluetooth. The result is fast and efficient data dissemination in multihop Bluetooth networks. Moreover, BlueFlood floods can be reliably received by off-the-shelf Bluetooth devices such as smartphones, opening new applications of concurrent transmissions and seamless integration with existing technologies

Practical Aggregation in the Edge

Due to the increasing amounts of data produced by applications and devices, cloud infrastructures are becoming unable to timely process and provide answers back to users. This has led to the emergence of the edge computing paradigm that aims at moving computations closer to end user devices. Edge computing can be defined as performing computations outside the boundaries of cloud data centres. This however, can be materialised across very different scenarios considering the broad spectrum of devices that can be leveraged to perform computations in the edge. In this thesis, we focus on a concrete scenario of edge computing, that of multiple devices with wireless capabilities that collectively form a wireless ad hoc network to perform distributed computations. We aim at devising practical solutions for these scenarios however, there is a lack of tools to help us in achieving such goal. To address this first limitation we propose a novel framework, called Yggdrasil, that is specifically tailored to develop and execute distributed protocols over wireless ad hoc networks on commodity devices. As to enable distributed computations in such networks, we focus on the particular case of distributed data aggregation. In particular, we address a harder variant of this problem, that we dub distributed continuous aggregation, where input values used for the computation of the aggregation function may change over time, and propose a novel distributed continuous aggregation protocol, called MiRAge. We have implemented and validated both Yggdrasil and MiRAge through an extensive experimental evaluation using a test-bed composed of 24 Raspberry Pi’s. Our results show that Yggdrasil provides adequate abstractions and tools to implement and execute distributed protocols in wireless ad hoc settings. Our evaluation is also composed of a practical comparative study on distributed continuous aggregation protocols, that shows that MiRAge is more robust and achieves more precise aggregation results than competing state-of-the-art alternatives

Intrusion Tolerant Routing Protocols for Wireless Sensor Networks

This MSc thesis is focused in the study, solution proposal and experimental evaluation of security solutions for Wireless Sensor Networks (WSNs). The objectives are centered on intrusion tolerant routing services, adapted for the characteristics and requirements of WSN nodes and operation behavior. The main contribution addresses the establishment of pro-active intrusion tolerance properties at the network level, as security mechanisms for the proposal of a reliable and secure routing protocol. Those properties and mechanisms will augment a secure communication base layer supported by light-weigh cryptography methods, to improve the global network resilience capabilities against possible intrusion-attacks on the WSN nodes. Adapting to WSN characteristics, the design of the intended security services also pushes complexity away from resource-poor sensor nodes towards resource-rich and trustable base stations. The devised solution will construct, securely and efficiently, a secure tree-structured routing service for data-dissemination in large scale deployed WSNs. The purpose is to tolerate the damage caused by adversaries modeled according with the Dolev-Yao threat model and ISO X.800 attack typology and framework, or intruders that can compromise maliciously the deployed sensor nodes, injecting, modifying, or blocking packets, jeopardizing the correct behavior of internal network routing processing and topology management. The proposed enhanced mechanisms, as well as the design and implementation of a new intrusiontolerant routing protocol for a large scale WSN are evaluated by simulation. For this purpose, the evaluation is based on a rich simulation environment, modeling networks from hundreds to tens of thousands of wireless sensors, analyzing different dimensions: connectivity conditions, degree-distribution patterns, latency and average short-paths, clustering, reliability metrics and energy cost