We are living in the age of information technology, where we are fully occupied with the revolutionary innovations of the last few decades such as the Internet, mobile devices, wireless communications, social networks, wearables, cloud computing, etc. While these technologies have become integral part of our daily life, we are now anxiously waiting to embrace Internet-of-Things (IoT), intelligent digital assistants, driver-less cars, drone deliveries, virtual reality, and smart city applications. Recently, research community is demonstrating increasing interests about Cyber-Physical Systems (CPS) that resides in the cross-section of embedded systems, network communications, and scalable distributed infrastructures. The main responsibility of a CPS is to collect sensory data about the physical world and to inform the computation module using communication technologies that processes the data, identifies important insights and notifies back using a feedback loop. These notifications can however be control commands to reconfigure the physical world. Such a setup is a useful method to deploy smart city applications. In this dissertation, we keep our focus onto the smart transport objective using vehicular CPS (VCPS) based systems organization. We have compiled this dissertation with our research contributions in this growing field of VCPS. One of our key contributions in this field is an architecture reference model for the cloud-based CPS, C2PS, where we analytically describe the key properties of a CPS: computation, communication and control, while integrating cloud features to it. We have identified various types of computation and interaction modes of this paradigm as well as describe Bayesian network and fuzzy logic based smart connection to select a mode at any time. It is considered that the true adoption of CPS is only possible through the deployment of the IoT systems. Thus, it is important to have IoT as a foundation in the CPS architectures. Our next contribution is to leverage existing Vehicular Adhoc Network (VANET) technologies and map them with the standard IoT-Architecture reference model to design the VCPS, Social Internet-of-Vehicles (SIoV). In this process, we have identified the social structures and system interactions among the subsystems involved in the SIoV. We also present a message structure to facilitate different types of SIoV interactions. The ability of dynamic reconfiguration in a C2PS is very appealing. We capture this feature in the VCPS by designing a model-based reconfiguration scheme for the SIoV, where we measure the data workloads of distinct subsystems involved in various types of SIoV interactions. We further use these models to design dynamic adaptation schemes for the subsystems involved in VCPS interactions. Our final contribution is an application development platform based on C2PS design technique that uses server-client based system communications. In this platform, server side is built using JAVA, client side uses Android, message communication uses JSON and every component has its own MySQL database to store the interactions. We use this platform to emulate and deploy SIoV related applications and scenarios. Such a platform is necessary to continue C2PS related research and developments in the laboratory environment.

With the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric F(j) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments.

TCP/IP protocol gradually exposes many shortcomings such as poor scalability and mobility. Content-Centric Networking is a new architecture which cares about the content itself rather than its source. Therefore, this paper proposes a novel IoV architecture which based on Content-Centric Networking and tests its transmission interference time, transmission delay, and throughout in network layer. The experimental results show that the novel architecture is superior to the current IoV in the communication performance.

In this thesis, the trade-offs between latency and transmitted data volume in vehicle-to-cloud communication for different choices of application layer messaging protocols and binary serialization formats are studied. This is done with the purpose of getting enough performance improvement to enable delay-sensitive Intelligent Transport System (ITS) features, and to reduce data usage in mobile networks. The studied protocols are Constrained Application Protocol (CoAP), Advanced Message Queuing Protocol (AMQP) and Message Queuing Telemetry Transport (MQTT), and the serialization formats studied are Protobuf and Flatbuffers.  The results show that CoAP — the only User Datagram Protocol (UDP) based protocol — has the lowest latency and overhead while not being able to guarantee reliable transfer. The best performer that can guarantee reliable transfer is MQTT. For the serialization formats, Protobuf is shown to have three times smaller serialized message size than Flatbuffers and also faster serialization speed. Flatbuffers is the winner in the case of memory use and deserialization time, which could make up for the poor performance in other aspects of data processing in the cloud. Further, the implications of these results in ITS communication are discussed suggestions made into future research topics.

Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are particularly difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that can satisfy these requirements. Spline function-based IDSs have shown to be effective in traditional network settings. By examining the various construction of splines and testing their robustness, the viability for a spline-based IDS can be determined.

As automotive development advances, connectivity features are continually added to vehicles that, in conjunction, form an Internet of Vehicles. For numerous reasons, it is vital for vehicle manufacturers to collect telemetry from their fleets. However, the volume of the generated data is too immense to feasibly be transmitted to a server due to CPU and memory limitations of embedded hardware and the monetary cost of cellular network usage. The purpose of this thesis is thus to investigate how these issues can be alleviated by the use of real-time compression of time series data before off-board transmission. A hybrid approach is proposed that results in fast and effective performance on a variety of time series exhibiting varying numerical data features, all while limiting the maximum reconstruction error to a user-specified absolute value. We first perform a literature review to identify state of the art compression algorithms for time series compression that run online and provide max-error guarantees. We then choose a subset of lossless and lossy algorithms that are implemented and benchmarked with regards to their compression ratio, resource usage, and reconstruction error when used on time series that exhibit a variety of data features. Finally, we ask whether we are able to run a lossy and lossless algorithm in succession in order to further increase the compression ratio. The literature review identifies a diverse range of compression algorithms. Out of these, the algorithms Poor Man's Compression - MidRange (PMC-MR) and Swing filter are selected as lossy algorithms, and Run-length Binary Encoding (RLBE) and Gorilla are selected as lossless algorithms. The experiments yield positive results for the lossy algorithms, which excel on different data sets. These are able to achieve compression ratios between 22.0% and 99.5%, depending on the data set, while limiting the max-error to 1%. In contrast, Gorilla achieves compression ratios between 66.6% and 83.7%, outperforming RLBE in nearly all aspects. Moreover, we conclude that there is a strictly positive improvement to the compression ratio when losslessly compressing the result of lossily compressed data. When combining either PMC-MR or Swing filter with Gorilla, we achieve compression ratios between 83.1% and 99.6% across a variety of time series with a maximum error for any given data point of 1%.

The development of IT has enabled the Internet of Things. Internet of Things is connected devices that communicate with each other and generate data that can then be used for different purposes. The number of connected devices is estimated to 20.4 billion by year 2020. The technology allows the automotive industry to connect its vehicles, which is called Internet of Vehicles, an application of the Internet of Things and intelligent cars. The amount of scientific literature that addresses the economic aspects related to the Internet of Things is scarce and need to be investigated further. The connected car is a disruptive technology that is expected to affect the automotive industry and their business models radically in the next few years and nobody really knows how the industry may look like the next 10-15 years. This type of disruptive technology requires companies to have the competence to implement innovative business models. The study focuses on the connected car from a business perspective and makes no insight into technical aspects or security challenges. The purpose of the study is to create an under-standing of the challenges facing the automotive business models with the introduction of the Internet of Things, which gives the automotive industry the opportunity to connect their cars to a greater extent than before. The study's results show that the value proposition and the channels are the most important parts to focus on in the business model. In order for companies to capitalize on the connection, it is extremely important that the customers understand the value of the connection and that the companies properly manage the information derived from the connected cars. Today, companies offer services or increased value in existing business models to strengthen their brand. The respondents share the opinion that the traditional business models will not change radically as long as the ownership of the car stay the same. Ownership and autonomous cars are the factors that are expected to affect the automotive industry the most. According to the respondents in the study, in order to deal with disruptive innovations in the industry, courage, adaptability, prospects and innovative thinking are required. / IT-utvecklingen har möjliggjort sakernas internet, Internet of Things. Internet of Things är uppkopplade enheter som kommunicerar med varandra och genererar data som sedan kan användas i olika syften. Antalet anslutna enheter beräknas att uppgå till 20,4 miljarder år 2020. Tekniken ger bilindustrin möjligheten att koppla upp sina fordon vilket benämns som Internet of Vehicles, en applikation av Internet of Things och intelligenta bilar. Vetenskaplig litteratur som tar upp de ekonomiska aspekterna i relation till Internet of Things är begränsad och behöver undersökas i större utsträckning. Den uppkopplade bilen är en disruptiv teknologi som förväntas påverka bilindustrin och deras affärsmodeller radikalt inom de närmaste åren och det är ingen som riktigt vet hur industrin kan komma att se ut de närmsta 10-15 åren. Denna typ av disruptiv teknologi kräver att företagen har kompetensen att implementera innovativa affärsmodeller. Studien fokuserar på den uppkopplade bilen ur ett affärsperspektiv och gör ingen fördjupning i tekniska aspekter eller säkerhetsutmaningar. Syftet med studien är att skapa förståelse för vilka utmaningar bilindustrins affärsmodeller står inför med introduktionen av Internet of Things som ger industrin möjligheten att koppla upp sina bilar i en större omfattning än tidigare. Studiens resultat visar att värdeerbjudandet och kanalerna är de viktigaste delarna att fokusera på i affärsmodellen. För att företagen ska kunna kapitalisera på uppkopplingen är det viktigt att kunderna förstår värdet av uppkoppling och att företagen förvaltar informationen från de uppkopplade bilarna på rätt sätt. Idag erbjuder företagen tjänster eller utökat värde i befintlig affärsmodell för att stärka sitt varumärke. Respondenterna delar uppfattningen om att de traditionella affärsmodellerna inte kommer förändras radikalt så länge ägandet av bilen inte gör en helomvändning. Ägandeskapet och autonoma bilar är de faktorer som förväntas påverka industrin störst. Respondenterna i studien nämner fyra viktiga egenskaper för att kunna hantera disruptiva innovationer i branschen, mod, anpassningsbarhet, framtidsutsikt och nytänkande.

For an environmentally sustainable future, electric vehicle (EV) adoption rates have been growing exponentially around the world. There is a pressing need for constructing smart charging infrastructures that can successfully integrate the large influx of connected and autonomous EVs (CAEVs) into the smart grids. To fulfill the aspiration of massive deployment of autonomous mobility on demand (AMoD) services, the proposed fast and secure framework will need to address the long charging times and long waiting times of static charging. It will also need to consider dynamic wireless charging as a viable solution for the CAEVs on the move. In this thesis, a novel three-layer charging system design of static and dynamic wireless charging that can operate with the existing wired charging infrastructure and standards for Intelligent Transportation System (ITS) is presented. This internet of things (IoT) application is accompanied by a proposed handshake protocol with light-weight request message frames. It employs vehicle to infrastructure (V2I) and vehicle to grid (V2G) communications for fulfilling charging requests of CAEVs with the shortest possible route to the destination. The charging requests of the CAEV users are fulfilled by dynamically distributing the request over the three different types of charging equipment. Further, the requests are serviced and billed privately and securely using two different proposed payment schemes with the encrypted virtual currency. The hardware independent system can detect misalignment of the CAEVs on the wireless charging pads and the speed issue errors in dynamic wireless charging systems as well as avoid free-riders. Additionally, the proposed dynamic wireless charging network (DWCN) design specification tool is analyzed. The suggestions made by the tool for building a DWCN can enable implementers to achieve the desired charging delivery performance at the lowest cost possible. Finally, the presented system is simulated, and this verified and validated simulator is revealed to make reservations and plan trips with minimum waiting times, travel costs, and battery consumption per vehicle trip. The system results proved 90.25% charge delivery efficiency. This system is then compared with alternative system designs to help showcase its ability to aid implementers and analysts in making design choices with the simulation.

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Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that meets this criterion. To this end, a spline-based intrusion detection system has been pioneered as a solution. By combining clustering with spline-based general linear model classification, this knot flow classification method (KFC) allows for robust intrusion detection to occur. Due its design and the manner it is constructed, KFC holds great potential for implementation across a distributed system. The purpose of this thesis was to explain and extrapolate the afore mentioned IDS, highlight its effectiveness, and discuss the conceptual design of the distributed system for use in future research.