Exploring Computing Continuum in IoT Systems: Sensing, Communicating and Processing at the Network Edge

As Internet of Things (IoT), originally comprising of only a few simple sensing devices, reaches 34 billion units by the end of 2020, they cannot be defined as merely monitoring sensors anymore. IoT capabilities have been improved in recent years as relatively large internal computation and storage capacity are becoming a commodity. In the early days of IoT, processing and storage were typically performed in cloud. New IoT architectures are able to perform complex tasks directly on-device, thus enabling the concept of an extended computational continuum. Real-time critical scenarios e.g. autonomous vehicles sensing, area surveying or disaster rescue and recovery require all the actors involved to be coordinated and collaborate without human interaction to a common goal, sharing data and resources, even in intermittent networks covered areas. This poses new problems in distributed systems, resource management, device orchestration,as well as data processing. This work proposes a new orchestration and communication framework, namely CContinuum, designed to manage resources in heterogeneous IoT architectures across multiple application scenarios. This work focuses on two key sustainability macroscenarios: (a) environmental sensing and awareness, and (b) electric mobility support. In the first case a mechanism to measure air quality over a long period of time for different applications at global scale (3 continents 4 countries) is introduced. The system has been developed in-house from the sensor design to the mist-computing operations performed by the nodes. In the second scenario, a technique to transmit large amounts of fine-time granularity battery data from a moving vehicle to a control center is proposed jointly with the ability of allocating tasks on demand within the computing continuum

INDIGO: a generalized model and framework for performance prediction of data dissemination

According to recent studies, an enormous rise in location-based mobile services is expected in future. People are interested in getting and acting on the localized information retrieved from their vicinity like local events, shopping offers, local food, etc. These studies also suggested that local businesses intend to maximize the reach of their localized offers/advertisements by pushing them to the maxi- mum number of interested people. The scope of such localized services can be augmented by leveraging the capabilities of smartphones through the dissemination of such information to other interested people. To enable local businesses (or publishers) of localized services to take in- formed decision and assess the performance of their dissemination-based localized services in advance, we need to predict the performance of data dissemination in complex real-world scenarios. Some of the questions relevant to publishers could be the maximum time required to disseminate information, best relays to maximize information dissemination etc. This thesis addresses these questions and provides a solution called INDIGO that enables the prediction of data dissemination performance based on the availability of physical and social proximity information among people by collectively considering different real-world aspects of data dissemination process. INDIGO empowers publishers to assess the performance of their localized dissemination based services in advance both in physical as well as the online social world. It provides a solution called INDIGO–Physical for the cases where physical proximity plays the fundamental role and enables the tighter prediction of data dissemination time and prediction of best relays under real-world mobility, communication and data dissemination strategy aspects. Further, this thesis also contributes in providing the performance prediction of data dissemination in large-scale online social networks where the social proximity is prominent using INDIGO–OSN part of the INDIGO framework under different real-world dissemination aspects like heterogeneous activity of users, type of information that needs to be disseminated, friendship ties and the content of the published online activities. INDIGO is the first work that provides a set of solutions and enables publishers to predict the performance of their localized dissemination based services based on the availability of physical and social proximity information among people and different real-world aspects of data dissemination process in both physical and online social networks. INDIGO outperforms the existing works for physical proximity by providing 5 times tighter upper bound of data dissemination time under real-world data dissemination aspects. Further, for social proximity, INDIGO is able to predict the data dissemination with 90% accuracy and differently, from other works, it also provides the trade-off between high prediction accuracy and privacy by introducing the feature planes from an online social networks

Fabricate

Bringing together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation, Fabricate is a triennial international conference, now in its third year (ICD, University of Stuttgart, April 2017). Each year it produces a supporting publication, to date the only one of its kind specialising in Digital Fabrication. The 2017 edition features 32 illustrated articles on built projects and works in progress from academia and practice, including contributions from leading practices such as Foster + Partners, Zaha Hadid Architects, Arup, and Ron Arad, and from world-renowned institutions including ICD Stuttgart, Harvard, Yale, MIT, Princeton University, The Bartlett School of Architecture (UCL) and the Architectural Association

Reports to the President

A compilation of annual reports for the 1999-2000 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

Erkennung und Vermeidung von Fehlverhalten in fahrzeugbasierten DTNs

Delay- and Disruption-Tolerant Networks (DTNs) are a suitable technology for many applications when the network suffers from intermittent connections and significant delays. In current vehicular networks, due to the high mobility of vehicles, the connectivity in vehicular networks can be highly unstable, links may change or break soon after they have been established and the network topology varies significantly depending on time and location. When the density of networked vehicles is low, connectivity is intermittent and with only a few transmission opportunities. This makes forwarding packets very difficult. For the next years, until a high penetration of networked vehicles is realized, delay-tolerant methods are a necessity in vehicular networks, leading to Vehicular DTNs (VDTNs). By implementing a store-carry-forward paradigm, VDTNs can make sure that even under difficult conditions, the network can be used by applications. However, we cannot assume that all vehicles are altruistic in VDTNs. Attackers can penetrate the communication systems of vehicles trying their best to destroy the network. Especially if multiple attackers collude to disrupt the network, the characteristics of VDTNs, without continuous connectivity, make most traditional strategies of detecting attackers infeasible. Additionally, selfish nodes may be reluctant to cooperate considering their profit, and due to hard- or software errors some vehicles cannot send or forward data. Hence, efficient mechanisms to detect malicious nodes in VDTNs are imperative. In this thesis, two classes of Misbehavior Detection Systems (MDSs) are proposed to defend VDTNs against malicious nodes. Both MDSs use encounter records (ERs) as proof to document nodes' behavior during previous contacts. By collecting and securely exchanging ERs, depending on different strategies in different classes of MDSs, a reputation system is built in order to punish bad behavior while encouraging cooperative behavior in the network. With independently operating nodes and asynchronous exchange of observations through ERs, both systems are very well suited for VDTNs, where there will be no continuous, ubiquitous network in the foreseeable future. By evaluating our methods through extensive simulations using different DTN routing protocols and different realistic scenarios, we find that both MDS classes are able to efficiently protect the system with low overhead and prevent malicious nodes from further disrupting the network.In Netzwerken mit zeitweisen Unterbrechungen oder langen Verzögerungen sind Delay- and Disruption-Tolerant Networks (DTNs) eine geeignete Technologie für viele Anwendungen. Die Konnektivität in Fahrzeugnetzen ist bedingt durch die hohe Mobilität und die geringe Verbreitung von netzwerkfähigen Fahrzeugen oft instabil. Bis zur flächendeckenden Verbreitung von netzwerkfähigen Fahrzeugen ist es daher zwingend notwendig auf Methoden des Delay Tolerant Networking zurückzugreifen um die bestmögliche Kommunikation zu gewährleisten. In diesem Zusammenhang wird von Vehicular Delay Tolerant Networks (VDTNs) gesprochen. Durch das Store-Carry-Forward-Prinzip kann ein VDTN Kommunikation für Anwendungen ermöglichen. Allerdings ist davon auszugehen, dass sich nicht alle Fahrzeuge altruistisch verhalten: Angreifer können Fahrzeuge übernehmen und das Netzwerk attackieren oder Knoten sind aus egoistischen Motiven oder auf Grund von Defekten unkooperativ. Verfahren, die Fehlverhalten in stabilen Netzen durch direkte Beobachtung erkennen können, sind in VDTNs nicht anwendbar. Daher sind Methoden, die Fehlverhalten in VDTNs nachweisen können, zwingend erforderlich. In dieser Arbeit werden zwei Klassen von Misbehavior Detection Systems (MDSs) vorgestellt. Beide Systeme basieren auf Encounter Records (ERs): Nach einem Kontakt tauschen zwei Knoten kryptografisch signierte Meta-Informationen zu den erfolgten Datentransfers aus. Diese ERs dienen bei darauffolgenden Kontakten mit anderen Netzwerkteilnehmern als vertrauenswürdiger Nachweis für das Verhalten eines Knotens in der Vergangenheit. Basierend auf der Auswertung gesammelter ERs wird ein Reputationssystem entwickelt, das kooperatives Verhalten belohnt und unkooperatives Verhalten bestraft. Dauerhaft unkooperative Knoten werden aus dem Netzwerk ausgeschlossen. Durch den asynchronen Austausch von Informationen kann jeder Knoten das Verhalten seiner Nachbarn selbstständig und unabhängig evaluieren. Dadurch sind die vorgestellten MDS-Varianten sehr gut für den Einsatz in einem VDTN geeignet. Durch umfangreiche Evaluationen wird gezeigt, dass sich die entwickelten MDS-Verfahren für verschiedene Routingprotokolle und in unterschiedlichen Szenarien anwenden lassen. In allen Fällen ist das MDS in der Lage das System mit geringem Overhead gegen Angreifer zu verteidigen und eine hohe Servicequalität im Netzwerk zu gewährleisten

Fabricate 2017

Bringing together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation, Fabricate is a triennial international conference, now in its third year (ICD, University of Stuttgart, April 2017). Each year it produces a supporting publication, to date the only one of its kind specialising in Digital Fabrication. The 2017 edition features 32 illustrated articles on built projects and works in progress from academia and practice, including contributions from leading practices such as Foster + Partners, Zaha Hadid Architects, Arup, and Ron Arad, and from world-renowned institutions including ICD Stuttgart, Harvard, Yale, MIT, Princeton University, The Bartlett School of Architecture (UCL) and the Architectural Association

Reports to the President

A compilation of annual reports for the 1990-1991 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans