Delay Tolerant Networking over the Metropolitan Public Transportation

We discuss MDTN: a delay tolerant application platform built on top of the Public Transportation System (PTS) and able to provide service access while exploiting opportunistic connectivity. Our solution adopts a carrier-based approach where buses act as data collectors for user requests requiring Internet access. Simulations based on real maps and PTS routes with state-of-the-art routing protocols demonstrate that MDTN represents a viable solution for elastic nonreal-time service delivery. Nevertheless, performance indexes of the considered routing policies show that there is no golden rule for optimal performance and a tailored routing strategy is required for each specific case

Social-context based routing and security in delay tolerant networks

Delay Tolerant Networks (DTNs) were originally intended for interplanetary communications and have been applied to a series of difficult environments: wireless sensor networks, unmanned aerial vehicles, and short-range personal communications. There is a class of such environments in which nodes follow semi-predictable social patterns, such as wildlife tracking or personal devices. This work introduces a series of algorithms designed to identify the social patterns present in these environments and apply this data to difficult problems, such as efficient message routing and content distribution. Security is also difficult in a mobile environment. This is especially the case in the event that a large portion of the network is unreliable, or simply unknown. As the network size increases nodes have difficulty in securely distributing keys, especially using low powered nodes with limited keyspace. A series of multi-party security algorithms were designed to securely transmit a message in the event that the sender does not have access to the destinations public key. Messages are routed through a series of nodes, each of which partially decrypts the message. By encrypting for several proxies, the message can only be intercepted if all those nodes have been compromised. Even a highly compromised network has increased security using this algorithm, with a trade-off of reduced delivery ratio and increased delivery time -- Abstract, page iv

A Fog Computing Architecture for Disaster Response Networks

In the aftermath of a disaster, the impacted communication infrastructure is unable to provide first responders with a reliable medium of communication. Delay tolerant networks that leverage mobility in the area have been proposed as a scalable solution that can be deployed quickly. Such disaster response networks (DRNs) typically have limited capacity due to frequent disconnections in the network, and under-perform when saturated with data. On the other hand, there is a large amount of data being produced and consumed due to the recent popularity of smartphones and the cloud computing paradigm. Fog Computing brings the cloud computing paradigm to the complex environments that DRNs operate in. The proposed architecture addresses the key challenges of ensuring high situational awareness and energy efficiency when such DRNs are saturated with large amounts of data. Situational awareness is increased by providing data reliably, and at a high temporal and spatial resolution. A waypoint placement algorithm places hardware in the disaster struck area such that the aggregate good-put is maximized. The Raven routing framework allows for risk-averse data delivery by allowing the user to control the variance of the packet delivery delay. The Pareto frontier between performance and energy consumption is discovered, and the DRN is made to operate at these Pareto optimal points. The FuzLoc distributed protocol enables mobile self-localization in indoor environments. The architecture has been evaluated in realistic scenarios involving deployments of multiple vehicles and devices

Spreadable Connected Autonomic Networks (SCAN)

A Spreadable Connected Autonomic Network (SCAN) is a mobile network that automatically maintains its own connectivity as nodes move. We envision SCANs to enable a diverse set of applications such as self-spreading mesh networks and robotic search and rescue systems. This paper describes our experiences developing a prototype robotic SCAN built from commercial, off-the-shelf hardware, to support such applications. A major contribution of our work is the development of a protocol, called SCAN1, which maintains network connectivity by enabling individual nodes to determine when they must constrain their mobility in order to avoid disconnecting the network. SCAN1 achieves its goal through an entirely distributed process in which individual nodes utilize only local (2-hop) knowledge of the network's topology to periodically make a simple decision: move, or freeze in place. Along with experimental results from our hardware testbed, we model SCAN1's performance, providing both supporting analysis and simulation for the efficacy of SCAN1 as a solution to enable SCANs. While our evaluation of SCAN1 in this paper is limited to systems whose capabilities match those of our testbed, SCAN1 can be utilized in conjunction with a wide-range of potential applications and environments, as either a primary or backup connectivity maintenance mechanism

Design Experiences on Single and Multi Radio Systems in Wireless Embedded Platforms

The progress of radio technology has made several flavors of radio available on the market.Wireless sensor network platform designers have used these radios to build a variety of platforms. Withnew applications and different types of radios on wireless sensing nodes, it is often hard to interconnectdifferent types of networks. Hence, often additional radios have to be integrated onto existingplatforms or new platforms have to be built. Additionally, the energy consumption of these nodes have to be optimized to meetlifetime requirements of years without recharging.In this thesis, we address two issues of single and multi radio platform designfor wireless sensor network applications - engineering issues and energy optimization.We present a set of guiding principles from our design experiences while building 3 real life applications,namely asset tracking, burglar tracking and finally in-situ psychophysiological stress monitoring of human subjects in behavioral studies.In the asset tracking application, we present our design of a tag node that can be hidden inside valuable personal assets such asprinters or sofas in a home. If these items are stolen, a city wide anchor node infrastructure networkwould track them throughout the city. We also present our design for the anchor node.In the burglar tracking application, we present the design of tag nodes and the issueswe faced while integrating it with a GSM radio. Finally, we discuss our experiencesin designing a bridge node, that connects body worn physiological sensorsto a Bluetooth enabled mobile smartphone. We present the software framework that acts as middleware toconnect to the bridge, parse the sensor data, and send it to higher layers of the softwareframework.We describe 2 energy optimization schemes that are used in the Asset Tracking and the Burglar Tracking applications, that enhance the lifetime of the individual applications manifold.In the asset tracking application,we design a grouping scheme that helps increase reliability of detection of the tag nodes at theanchor nodes while reducing the energy consumption of the group of tag nodes travelling together.We achieve an increase of 5 times improvement in lifetime of the entire group. In the Burglar Tracking application, weuse sensing to determine when to turn the GSM radio on and transmit data by differentiatingturns and lane changes. This helps us reduce the number of times the GSM radio is woken up, thereby increasing thelifetime of the tag node while it is being tracked. This adds 8 minutes of trackablelifetime to the burglar tracking tag node. We conclude this thesis by observing the futuretrends of platform design and radio evolution

Algorithms to Find Two-Hop Routing Policies in Multiclass Delay Tolerant Networks

Most of the literature on delay tolerant networks (DTNs) focuses on optimal routing policies exploiting a priori knowledge about nodes mobility traces. For the case in which no a priori knowledge is available (very common in practice), apart from basic epidemic routing, the main approaches focus on controlling two-hop routing policies. However, these latter results commonly employ fluid approximation techniques, which, in principle, do not provide any theoretical bound over the approximation ratio. In our work, we focus on the case without a priori mobility knowledge and we provide approximation algorithms with theoretical guarantees that can be applied to cases where the number of hops allowed in the routing process is arbitrary. Our approach is rather flexible allowing us to address heterogeneous mobility patterns and transmission technologies, to consider explicitly the signaling and transmission costs, and to include also nodes discarding packets after a local timeout. We then provide a comprehensive performance evaluation of our algorithms, showing that two-hop routing provides the best tradeoff between delay and energy and that, in this case, they find solutions very close to the optimal ones with a low overhead. Finally, we compare our methods against some state-of-the-art approaches by means of a DTN simulation environment in realistic settings