Supporting Large Scale Communication Systems on Infrastructureless Networks Composed of Commodity Mobile Devices: Practicality, Scalability, and Security.

Infrastructureless Delay Tolerant Networks (DTNs) composed of commodity mobile devices have the potential to support communication applications resistant to blocking and censorship, as well as certain types of surveillance. In this thesis we study the utility, practicality, robustness, and security of these networks. We collected two sets of wireless connectivity traces of commodity mobile devices with different granularity and scales. The first dataset is collected through active installation of measurement software on volunteer users' own smartphones, involving 111 users of a DTN microblogging application that we developed. The second dataset is collected through passive observation of WiFi association events on a university campus, involving 119,055 mobile devices. Simulation results show consistent message delivery performances of the two datasets. Using an epidemic flooding protocol, the large network achieves an average delivery rate of 0.71 in 24 hours and a median delivery delay of 10.9 hours. We show that this performance is appropriate for sharing information that is not time sensitive, e.g., blogs and photos. We also show that using an energy efficient variant of the epidemic flooding protocol, even the large network can support text messages while only consuming 13.7% of a typical smartphone battery in 14 hours. We found that the network delivery rate and delay are robust to denial-of-service and censorship attacks. Attacks that randomly remove 90% of the network participants only reduce delivery rates by less than 10%. Even when subjected to targeted attacks, the network suffered a less than 10% decrease in delivery rate when 40% of its participants were removed. Although structurally robust, the openness of the proposed network introduces numerous security concerns. The Sybil attack, in which a malicious node poses as many identities in order to gain disproportionate influence, is especially dangerous as it breaks the assumption underlying majority voting. Many defenses based on spatial variability of wireless channels exist, and we extend them to be practical for ad hoc networks of commodity 802.11 devices without mutual trust. We present the Mason test, which uses two efficient methods for separating valid channel measurement results of behaving nodes from those falsified by malicious participants.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120779/1/liuyue_1.pd

A Learning-based Approach to Exploiting Sensing Diversity in Performance Critical Sensor Networks

Wireless sensor networks for human health monitoring, military surveillance, and disaster warning all have stringent accuracy requirements for detecting and classifying events while maximizing system lifetime. to meet high accuracy requirements and maximize system lifetime, we must address sensing diversity: sensing capability differences among both heterogeneous and homogeneous sensors in a specific deployment. Existing approaches either ignore sensing diversity entirely and assume all sensors have similar capabilities or attempt to overcome sensing diversity through calibration. Instead, we use machine learning to take advantage of sensing differences among heterogeneous sensors to provide high accuracy and energy savings for performance critical applications.;In this dissertation, we provide five major contributions that exploit the nuances of specific sensor deployments to increase application performance. First, we demonstrate that by using machine learning for event detection, we can explore the sensing capability of a specific deployment and use only the most capable sensors to meet user accuracy requirements. Second, we expand our diversity exploiting approach to detect multiple events using a distributed manner. Third, we address sensing diversity in body sensor networks, providing a practical, user friendly solution for activity recognition. Fourth, we further increase accuracy and energy savings in body sensor networks by sharing sensing resources among neighboring body sensor networks. Lastly, we provide a learning-based approach for forwarding event detection decisions to data sinks in an environment with mobile sensor nodes

On-the-Fly Establishment of Multi-hop D2D Communication based on Android Smartphones and Embedded Platforms: Implementation and Real-Life Experiments

Masteroppgave informasjons- og kommunikasjonsteknologi - Universitetet i Agder, 2015(Konfidensiell til/confidential until 01.07.2020

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Radio Frequency-Based Indoor Localization in Ad-Hoc Networks

The increasing importance of location‐aware computing and context‐dependent information has led to a growing interest in low‐cost indoor positioning with submeter accuracy. Localization algorithms can be classified into range‐based and range‐free techniques. Additionally, localization algorithms are heavily influenced by the technology and network architecture utilized. Availability, cost, reliability and accuracy of localization are the most important parameters when selecting a localization method. In this chapter, we introduce basic localization techniques, discuss how they are implemented with radio frequency devices and then characterize the localization techniques based on the network architecture, utilized technologies and application of localization. We then investigate and address localization in indoor environments where the absence of global positioning system (GPS) and the presence of unique radio propagation properties make this problem one of the most challenging topics of localization in wireless networks. In particular, we study and review the previous work for indoor localization based on radio frequency (RF) signaling (like Bluetooth‐based localization) to illustrate localization challenges and how some of them can be overcome

Underwater 3D positioning on smart devices

The emergence of water-proof mobile and wearable devices (e.g., Garmin Descent and Apple Watch Ultra) designed for underwater activities like professional scuba diving, opens up opportunities for underwater networking and localization capabilities on these devices. Here, we present the first underwater acoustic positioning system for smart devices. Unlike conventional systems that use floating buoys as anchors at known locations, we design a system where a dive leader can compute the relative positions of all other divers, without any external infrastructure. Our intuition is that in a well-connected network of devices, if we compute the pairwise distances, we can determine the shape of the network topology. By incorporating orientation information about a single diver who is in the visual range of the leader device, we can then estimate the positions of all the remaining divers, even if they are not within sight. We address various practical problems including detecting erroneous distance estimates, addressing rotational and flipping ambiguities as well as designing a distributed timestamp protocol that scales linearly with the number of devices. Our evaluations show that our distributed system running on underwater deployments of 4-5 commodity smart devices can perform pairwise ranging and localization with median errors of 0.5-0.9 m and 0.9-1.6

Lifenet: a flexible ad hoc networking solution for transient environments

In the wake of major disasters, the failure of existing communications infrastructure and the subsequent lack of an effective communication solution results in increased risks, inefficiencies, damage and casualties. Currently available options such as satellite communication are expensive and have limited functionality. A robust communication solution should be affordable, easy to deploy, require little infrastructure, consume little power and facilitate Internet access. Researchers have long proposed the use of ad hoc wireless networks for such scenarios. However such networks have so far failed to create any impact, primarily because they are unable to handle network transience and have usability constraints such as static topologies and dependence on specific platforms. LifeNet is a WiFi-based ad hoc data communication solution designed for use in highly transient environments. After presenting the motivation, design principles and key insights from prior literature, the dissertation introduces a new routing metric called Reachability and a new routing protocol based on it, called Flexible Routing. Roughly speaking, reachability measures the end-to-end multi-path probability that a packet transmitted by a source reaches its final destination. Using experimental results, it is shown that even with high transience, the reachability metric - (1) accurately captures the effects of transience (2) provides a compact and eventually consistent global network view at individual nodes, (3) is easy to calculate and maintain and (4) captures availability. Flexible Routing trades throughput for availability and fault-tolerance and ensures successful packet delivery under varying degrees of transience. With the intent of deploying LifeNet on field we have been continuously interacting with field partners, one of which is Tata Institute of Social Sciences India. We have refined LifeNet iteratively refined base on their feedback. I conclude the thesis with lessons learned from our field trips so far and deployment plans for the near future.MSCommittee Chair: Santosh Vempala; Committee Member: Ashok Jhunjhunwala; Committee Member: Michael Best; Committee Member: Nick Feamste