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PhD Defense – Robert Martin

March 26, 2018 @ 3:00 pm - 4:00 pm UTC-5

Title: Information-Centric Design and Implementation for Underwater Acoustic Networks

Major Advisor: Dr. Sanguthevar Rajasekaran

Associate Advisors: Dr. Song Han, Dr. Reda A. Ammar

Date: March 26, 2018 at 3:00 PM

Location: HBL Class of 1947 Conference Room


Over the past decade, Underwater Acoustic Networks (UANs) have received extensive attention due to their vast benefits in academia and industry alike. However, due to the overall magnitude and harsh characteristics of underwater environments, standard wireless sensor network techniques will fail because current technology and energy restrictions limit underwater devices due to delayed acoustic communications. To help manage these limitations we utilize Information-Centric Networking (ICN). More importantly, we look at ICN’s paradigm shift from traditional TCP/IP architecture to improve data handling and enhance network efficiency. By utilizing some of ICN’s techniques, such as data naming hierarchy, we can reevaluate each component of the network’s protocol stack given current underwater limitations to study the vast solutions and perspectives Information-Centric architectures can provide to UANs.


First, we propose a routing strategy used to manage and route large data files in a network prone to high mobility. Therefore, due to UANs limited transmitting capability, we passively store sensed data and adaptively find the best path. Furthermore, we introduce adapted Named Data Networking (NDN) components to improve upon routing robustness and adaptiveness. Beyond naming data, we use tracers to assist in tracking stored data locations without using other excess means such as flooding. By collaborating tracer consistency with routing path awareness our protocol can adaptively manage faulty paths or high mobility nodes. Through this incorporation of varied NDN techniques, we are able to see notable improvements in routing efficiency.


Second, we analyze the effects of Denial of Service (DoS) attacks on upper layer protocols. Since UANs are typically resource restrained, malicious users can advantageously create fake traffic to burden the already constrained network. While ICN techniques only provide basic DoS restriction we must expand our detection and restriction technique to meet the unique demands of UANs. To provide enhanced security against DoS we construct an algorithm to detect and restrict against these types of attacks while adapting to meet acoustic characteristics. To better extend this work we incorporate three node behavior techniques using probabilistic, adaptive, and predictive approaches for detecting malicious traits. Furthermore, we apply these proposed models in advanced DoS attacker scenarios to further restrict malicious user effects on UANs.


Thirdly, to depict and test protocols in UANs, simulators are commonly used due to their accessibility and controlled testing aspects. For this section, we review Aqua-Sim, a discrete event-driven open-source underwater simulator. To enhance the core aspect of this simulator we first rewrite the current architecture and transition Aqua-Sim to the newest core simulator, NS-3. Following this, we clean up redundant features spread out between the various underwater layers. Additionally, we fully integrate the diverse NS-3 API within our simulator. By revamping previous code layout we are able to improve architecture modularity and child class expandability. New features are also introduced including localization and synchronization support, busy terminal problem support, multi-channel support, transmission range uncertainty modules, external noise generators, channel trace-driven support, security module, and an adapted NDN module. Additionally, we provide extended documentation to assist in user development. Simulation testing shows improved memory management and continuous validity in comparison to other underwater simulators and past iterations of Aqua-Sim.




March 26, 2018
3:00 pm - 4:00 pm UTC-5
Event Category:


HBL Class of 1947 Conference Room
UConn Library, 369 Fairfield Way, Unit 1005
Storrs, CT 06269 United States
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(860) 486-2518
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