TagNet: a scalable tag-based information-centric network

The Internet has changed dramatically since the time it was created. What was originally a system to connect relatively few remote users to mainframe computers, has now become a global network of billions of diverse devices, serving a large user population, more and more characterized by wireless communication, user mobility, and large-scale, content-rich, multi-user applications that are stretching the basic end-to-end, point-to-point design of TCP/IP. In recent years, researchers have introduced the concept of Information Centric Networking (ICN). The ambition of ICN is to redesign the Internet with a new service model more suitable to today's applications and users. The main idea of ICN is to address information rather than hosts. This means that a user could access information directly, at the network level, without having to first find out which host to contact to obtain that information. The ICN architectures proposed so far are based on a "pull" communication service. This is because today's Internet carries primarily video traffic that is easy to serve through pull communication primitives. Another common design choice in ICN is to name content, typically with hierarchical names similar to file names or URLs. This choice is once again rooted in the use of URLs to access Web content. However, names offer only a limited expressiveness and may or may not aggregate well at a global scale. In this thesis we present a new ICN architecture called TagNet. TagNet intends to offer a richer communication model and a new addressing scheme that is at the same time more expressive than hierarchical names from the viewpoint of applications, and more effective from the viewpoint of the network for the purpose of routing and forwarding. For the service model, TagNet extends the mainstream "pull" ICN with an efficient "push" network-level primitive. Such push service is important for many applications such as social media, news feeds, and Internet of Things. Push communication could be implemented on top of a pull primitive, but all such implementations would suffer for high traffic overhead and/or poor performance. As for the addressing scheme, TagNet defines and uses different types of addresses for different purposes. Thus TagNet allows applications to describe information by means of sets of tags. Such tag-based descriptors are true content-based addresses, in the sense that they characterize the multi-dimensional nature of information without forcing a partitioning of the information space as is done with hierarchical names. Furthermore, descriptors are completely user-defined, and therefore give more flexibility and expressive power to users and applications, and they also aggregate by subset. By their nature, descriptors have no relation to the network topology and are not intended to identify content univocally. Therefore, TagNet complements descriptors with locators and identifiers. Locators are network-defined addresses that can be used to forward packets between known nodes (as in the current IP network); content identifiers are unique identifiers for particular blocks of content, and therefore can be used for authentication and caching. In this thesis we propose a complete protocol stack for TagNet covering the routing scheme, forwarding algorithm, and congestion control at the transport level. We then evaluate the whole protocol stack showing that (1) the use of both push and pull services at the network level reduces network traffic significantly; (2) the tree-based routing scheme we propose scales well, with routing tables that can store billions of descriptors in a few gigabytes thanks to descriptor aggregation; (3) the forwarding engine with specialized matching algorithms for descriptors and locators achieves wire-speed forwarding rates; and (4) the congestion control is able to effectively and fairly allocate all the bandwidth available in the network while minimizing the download time of an object and avoiding congestion

Information-Centric Design and Implementation for Underwater Acoustic Networks

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 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\u27s paradigm shift from traditional TCP/IP architecture to improve data handling and enhance network efficiency. By utilizing some of ICN\u27s techniques, such as data naming hierarchy, we can reevaluate each component of the network\u27s 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 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. 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

Delay-Tolerant ICN and Its Application to LoRa

Connecting long-range wireless networks to the Internet imposes challenges due to vastly longer round-trip-times (RTTs). In this paper, we present an ICN protocol framework that enables robust and efficient delay-tolerant communication to edge networks. Our approach provides ICN-idiomatic communication between networks with vastly different RTTs. We applied this framework to LoRa, enabling end-to-end consumer-to-LoRa-producer interaction over an ICN-Internet and asynchronous data production in the LoRa edge. Instead of using LoRaWAN, we implemented an IEEE 802.15.4e DSME MAC layer on top of the LoRa PHY and ICN protocol mechanisms in RIOT OS. Executed on off-the-shelf IoT hardware, we provide a comparative evaluation for basic NDN-style ICN [60], RICE [31]-like pulling, and reflexive forwarding [46]. This is the first practical evaluation of ICN over LoRa using a reliable MAC. Our results show that periodic polling in NDN works inefficiently when facing long and differing RTTs. RICE reduces polling overhead and exploits gateway knowledge, without violating ICN principles. Reflexive forwarding reflects sporadic data generation naturally. Combined with a local data push, it operates efficiently and enables lifetimes of >1 year for battery powered LoRa-ICN nodes.Comment: 12 pages, 7 figures, 2 table

Implementation and Evaluation of an NoC Architecture for FPGAs

The Networks-on-Chip (NoC) approach for designing Systems-on-Chip (SoC) is currently emerging as an advanced concept for overcoming the scalability and efficiency problems of traditional bus-based systems. A great deal of theoretical research has been done in this area that provides good insight and shows promising results. There is a great need for research in hardware implementation of NoC-based systems to determine the feasibility of implementing various topologies and protocols, and also to accurately determine what design tradeoffs are involved in NoC implementation. This thesis addresses the challenges of implementing an NoC-based system on FPGAs for running real benchmark applications. The NoC used a mesh topology and circuit-switched communication protocol. An experimental framework was developed that allowed implementation of NoC-based system from a high level specification, using the Celoxica Handel-C hardware description language. Two test applications: charged couple device (CCD) and JPEG were developed in Handel-C to be used as our benchmark applications. Both benchmarks are computational expensive and require large quantities of data transfer that will test the NoC system. Implementation results show that the NoC-based system gives superior area utilization and speed performance compared to the bus-based system, running the same benchmarks

Clustering algorithm for D2D communication in next generation cellular networks : thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Auckland, New Zealand

Next generation cellular networks will support many complex services for smartphones, vehicles, and other devices. To accommodate such services, cellular networks need to go beyond the capabilities of their previous generations. Device-to-Device communication (D2D) is a key technology that can help fulfil some of the requirements of future networks. The telecommunication industry expects a significant increase in the density of mobile devices which puts more pressure on centralized schemes and poses risk in terms of outages, poor spectral efficiencies, and low data rates. Recent studies have shown that a large part of the cellular traffic pertains to sharing popular contents. This highlights the need for decentralized and distributive approaches to managing multimedia traffic. Content-sharing via D2D clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. Different studies have established that D2D communication in clusters can improve spectral and energy efficiency, achieve low latency while increasing the capacity of the network. To achieve effective content-sharing among users, appropriate clustering strategies are required. Therefore, the aim is to design and compare clustering approaches for D2D communication targeting content-sharing applications. Currently, most of researched and implemented clustering schemes are centralized or predominantly dependent on Evolved Node B (eNB). This thesis proposes a distributed architecture that supports clustering approaches to incorporate multimedia traffic. A content-sharing network is presented where some D2D User Equipment (DUE) function as content distributors for nearby devices. Two promising techniques are utilized, namely, Content-Centric Networking and Network Virtualization, to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multi-factor clustering algorithm is proposed for grouping the DUEs sharing a common interest. Various performance parameters such as energy consumption, area spectral efficiency, and throughput have been considered for evaluating the proposed algorithm. The effect of number of clusters on the performance parameters is also discussed. The proposed algorithm has been further modified to allow for a trade-off between fairness and other performance parameters. A comprehensive simulation study is presented that demonstrates that the proposed clustering algorithm is more flexible and outperforms several well-known and state-of-the-art algorithms. The clustering process is subsequently evaluated from an individual user’s perspective for further performance improvement. We believe that some users, sharing common interests, are better off with the eNB rather than being in the clusters. We utilize machine learning algorithms namely, Deep Neural Network, Random Forest, and Support Vector Machine, to identify the users that are better served by the eNB and form clusters for the rest of the users. This proposed user segregation scheme can be used in conjunction with most clustering algorithms including the proposed multi-factor scheme. A comprehensive simulation study demonstrates that with such novel user segregation, the performance of individual users, as well as the whole network, can be significantly improved for throughput, energy consumption, and fairness

Fair-RTT-DAS: A robust and efficient dynamic adaptive streaming over ICN

To sustain the adequate bandwidth demands over rapidly growing multimedia traffic and considering the effectiveness of Information-Centric Networking (ICN), recently, HTTP based Dynamic Adaptive Streaming (DASH) has been introduced over ICN, which significantly increases the network bandwidth utilisation. However, we identified that the inherent features of ICN also causes new vulnerabilities in the network. In this paper, we first propose a novel attack called as Bitrate Oscillation Attack (BOA), which exploits fundamental ICN characteristics: in-network caching and interest aggregation, to disrupt DASH functionality. In particular, the proposed attack forces the bitrate and resolution of video received by the attacked client to oscillate with high frequency and high amplitude during the streaming process. To detect and mitigate BOA, we design and implement a reactive countermeasure called Fair-RTT-DAS. Our solution ensures efficient bandwidth utilisation and improves the user perceived Quality of Experience (QoE) in the presence of varying content source locations. For this purpose, Fair-RTT-DAS consider DASH\u2019s two significant features: round-trip-time (RTT) and throughput fairness. In the presence of BOA in a network, our simulation results show an increase in the annoyance factor in user\u2019s spatial dimension, i.e., increase in oscillation frequency and amplitude. The results also show that our countermeasure significantly alleviates these adverse effects and makes dynamic adaptive streaming friendly to ICN\u2019s implicit features