Biblio

Named Data Networking (NDN) is one of the future internet architectures, which is a clean-slate approach. NDN provides intelligent data retrieval using the principles of name-based symmetrical forwarding of Interest/Data packets and innetwork caching. The continually increasing demand for rapid dissemination of large-scale scientific data is driving the use of NDN in data-intensive science experiments. In this paper, we establish an intercontinental NDN testbed. In the testbed, an NDN-based application that targets climate science as an example data intensive science application is designed and implemented, which has differentiated features compared to those of previous studies. We verify experimental justification of using NDN for climate science in the intercontinental network, through performance comparisons between classical delivery techniques and NDN-based climate data delivery.

Named Data Networks provide a clean-slate redesign of the Future Internet for efficient content distribution. Because Internet of Things are expected to compose a significant part of Future Internet, most content will be managed by constrained devices. Such devices are often equipped with limited CPU, memory, bandwidth, and energy supply. However, the current Named Data Networks design neglects the specific requirements of Internet of Things scenarios and many data structures need to be further optimized. The purpose of this research is to provide an efficient strategy to route in Named Data Networks by constructing a Forwarding Information Base using Iterated Bloom Filters defined as I(FIB)F. We propose the use of content names based on iterative hashes. This strategy leads to reduce the overhead of packets. Moreover, the memory and the complexity required in the forwarding strategy are lower than in current solutions. We compare our proposal with solutions based on hierarchical names and Standard Bloom Filters. We show how to further optimize I(FIB)F by exploiting the structure information contained in hierarchical content names. Finally, two strategies may be followed to reduce: (i) the overall memory for routing or (ii) the probability of false positives.

Autonomous vehicles must communicate with each other effectively and securely to make robust decisions. However, today's Internet falls short in supporting efficient data delivery and strong data security, especially in a mobile ad-hoc environment. Named Data Networking (NDN), a new data-centric Internet architecture, provides a better foundation for secure data sharing among autonomous vehicles. We examine two potential threats, false data dissemination and vehicle tracking, in an NDN-based autonomous vehicular network. To detect false data, we propose a four-level hierarchical trust model and the associated naming scheme for vehicular data authentication. Moreover, we address vehicle tracking concerns using a pseudonym scheme to anonymize vehicle names and certificate issuing proxies to further protect vehicle identity. Finally, we implemented and evaluated our AutoNDN application on Raspberry Pi-based mini cars in a wireless environment.

NDN is a promising protocol that can help to reduce congestion at Internet scale by putting content at the center of communications instead of hosts, and by providing each node with a caching capability. NDN can also natively authenticate transmitted content with a mechanism similar to website certificates that allows clients to assess the original provider. But this security feature comes at a high cost, as it relies heavily on asymmetric cryptography which affects server performance when NDN Data are generated. This is particularly critical for many services dealing with real-time data (VOIP, live streaming, etc.), but current tools are not adapted for a realistic server-side performance evaluation of NDN traffic generation when digital signature is used. We propose a new tool, NDNperf, to perform this evaluation and show that creating NDN packets is a major bottleneck of application performances. On our testbed, 14 server cores only generate \textbackslashtextasciitilde400 Mbps of new NDN Data with default packet settings. We propose and evaluate practical solutions to improve the performance of server-side NDN Data generation leading to significant gains.

In content-based security, encrypted content as well as wrapped access keys are made freely available by an Information Centric Network: Only those clients which are able to unwrap the encryption key can access the protected content. In this paper we extend this model to computation chains where derived data (e.g. produced by a Named Function Network) also has to comply to the content-based security approach. A central problem to solve is the synchronized on-demand publishing of encrypted results and wrapped keys as well as defining the set of consumers which are authorized to access the derived data. In this paper we introduce "content-attendant policies" and report on a running prototype that demonstrates how to enforce data owner-defined access control policies despite fully decentralized and arbitrarily long computation chains.

The Internet of Things (IoT) is an emerging architecture that seeks to interconnect all of the "things" we use on a daily basis. Whereas the Internet originated as a way to connect traditional computing devices in order to share information, IoT includes everything from automobiles to appliances to buildings. As networks and devices become more diverse and disparate in their communication methods and interfaces, traditional host-to host technologies such as Internet Protocol (IP) are challenged to provide the level of data exchange and security needed to operate in this new network paradigm. Named Data Networking (NDN) is a developing Internet architecture that can help implement the IoT paradigm in a more efficient and secure manner. This paper introduces the NDN architecture in comparison to the traditional IP-based architecture and discusses several security concepts pertaining to NDN that make this a powerful technology for implementing the Internet of Things.

Named Data Networking (NDN), a clean-slate data oriented Internet architecture targeting on replacing IP, brings many potential benefits for content distribution. Real deployment of NDN is crucial to verify this new architecture and promote academic research, but work in this field is at an early stage. Due to the fundamental design paradigm difference between NDN and IP, Deploying NDN as IP overlay causes high overhead and inefficient transmission, typically in streaming applications. Aiming at achieving efficient NDN streaming distribution, this paper proposes a transitional architecture of NDN/IP hybrid network dubbed Centaur, which embodies both NDN's smartness, scalability and IP's transmission efficiency and deployment feasibility. In Centaur, the upper NDN module acts as the smart head while the lower IP module functions as the powerful feet. The head is intelligent in content retrieval and self-control, while the IP feet are able to transport large amount of media data faster than that if NDN directly overlaying on IP. To evaluate the performance of our proposal, we implement a real streaming prototype in ndnSIM and compare it with both NDN-Hippo and P2P under various experiment scenarios. The result shows that Centaur can achieve better load balance with lower overhead, which is close to the performance that ideal NDN can achieve. All of these validate that our proposal is a promising choice for the incremental and compatible deployment of NDN.