Experimental evaluation of content distribution with NDN and HTTP

Yuan, Haowei; Crowley, Patrick

doi:10.1109/infcom.2013.6566771

Cited by 26 publications

(7 citation statements)

References 11 publications

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“…Yuan et al presented an early study between HTTP and CCNx (an incarnation of the Information Centric Networking concepts) [5]. The work compares HTTP and CCNx and shows that in networks with very high drop rates (10% or more) NDN outperforms HTTP.…”

Section: B Previous Workmentioning

confidence: 99%

Named Data Networking for Content Delivery Network Workflows

Thelagathoti

Mastorakis

Shah

et al. 2020

2020 IEEE 9th International Conference on Cloud Networking (CloudNet)

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In this work we investigate Named Data Networking's (NDN's) architectural properties and features, such as content caching and intelligent packet forwarding, in the context of Content Delivery Network (CDN) workflows. More specifically, we evaluate NDN's properties for PoP (Point of Presence) to PoP and PoP to device connectivity. We use the Apache Traffic Server (ATS) platform to create a CDN-like caching hierarchy in order to compare NDN with HTTPbased content delivery. Overall, our work demonstrates that several properties inherent to NDN can benefit content providers and users alike through in-network caching of content, fast retransmission, and stateful hop-by-hop packet forwarding. Our experimental results demonstrate that HTTP delivers content faster under stable conditions due to a mature software stack. However, NDN performs better in the presence of packet loss, even for a loss rate as low as 0.1%, due to packet-level caching in the network and fast retransmissions from close upstreams. We further show that the Time To First Byte (TTFB) in NDN is consistently lower than HTTP (~ 100ms in HTTP vs. ~ 50ms in NDN), a vital requirement for CDNs. Unlike HTTP, NDN also supports transparent failover to another upstream when a failure occurs in the network. Finally, we present implementation-agnostic (implementation choices can be Software Defined Networking, Information Centric Networking, or something else) network properties that can benefit CDN workflows.Named Data Networking (NDN) [1] is a future Internet architecture that focuses on content distribution and utilizes content names for most in-network operations such as packet forwarding and content caching. The synergy between CDNs and the NDN architecture is that both aim to optimize content delivery. Further, CDNs and NDN both utilize similar

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Section: B Previous Workmentioning

confidence: 99%

Named Data Networking for Content Delivery Network Workflows

Thelagathoti

Mastorakis

Shah

et al. 2020

2020 IEEE 9th International Conference on Cloud Networking (CloudNet)

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“…2) since HTTP is a name-centric protocol that is widely used to retrieve content named by URL [28]. Indeed, as HTTP has high affinity with NDN, some research efforts are de-270 rived from HTTP/NDN [29,30]. Yuan et al [31] defined NDN flow using a name, and each flow was maintained by the expiration time and a list of incoming faces.…”

Section: Conversion Of Http To Ndn Flowmentioning

confidence: 99%

The named data networking flow filter: Towards improved security over information leakage attacks

et al. 2020

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Named Data Networking (NDN) has the potential to create a more secure future Internet. It is therefore crucial to investigate its vulnerabilities in order to make it safer against information leakage attacks. In NDN, malware inside an enterprise can encode confidential information into Interest names and send it to the attacker. One of the countermeasures is to inspect a name in the Interest using a name filter and identify it as legitimate or anomalous. Although the name filter can dramatically decrease the information leakage throughput per Interest, it has a serious disadvantage: it does not consider a flow of Interests. This means that the malware can not only cause information leakage, but even improve the speed of the attack by aggressively producing massive flows of malicious Interests. This paper investigates such NDN flow attacks. Our contribution is twofold. First, we present a scheme that converts an HTTP flow into the corresponding NDN flow, as to date there is no publicly available dataset of the latter. Second, we propose an NDN flow filter based on support vector machines to classify the short-term activity of NDN consumers as legitimate or anomalous. In order to obtain legitimate and anomalous flows, we use a preprocessing anomaly detection step where we mark consumers based on their long-term activity. Our results clearly show that the flow filter improves the performance of the name filter by two orders of magnitude. Thus, we expect that our approach will drastically reduce the impact of this security attack in NDN.

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“…Even though NULL mode does not involve the process of segment authentication, it has a limited transmission performance. That is because in CCNx protocol execution content name encoding/decoding procedure is significantly time consuming [26,27]. TLDA with 1024-bit (resp., 2048-bit) key size provides the best performance of 76.506 Mbps (resp., 75.956 Mbps) when MHT size is 16 (resp., 64) while CCNx with 1024-bit (resp., 2048-bit) key size offers the best performance of 55.356 Mbps (resp., 40.571 Mbps) when MHT size is 32 (resp.…”

Section: Computational Performance and Overhead Analysismentioning

confidence: 99%

TLDA: An Efficient Two-Layered Data Authentication Mechanism for Content-Centric Networking

Seo

Youn

2018

Security and Communication Networks

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Content-Centric Networking (CCN) is a new networking paradigm for the future Internet, which shifts the communication paradigm from host-centric to data-centric. In CCN, contents are routed by their unique names and they are stored in network nodes by units of segment during transmission for future usage. Since contents are stored in network nodes in a distributed manner, security is built into CCN data packets by embedding a public key signature to enable any content requesters to verify authenticity and integrity of contents. However, the use of public key signatures for authenticating CCN data packets incurs significant overhead regarding computation and communication, which limits universal utilization of CCN. Furthermore, this can lead to a new kind of DDoS attacks. Even though CCN adopts an aggregate signature method based on Merkle Hash Tree (MHT) in its reference implementation, it still incurs large amount of overhead. This paper presents TLDA, an efficient Two-Layered Data Authentication mechanism, which can considerably reduce overhead of computation and communication for authenticating data segments in CCN. For efficiency of computation and communication, TLDA newly introduces the concept of authentication Meta part consisting of data segments' hash values. To a great extent TLDA not only reduces the computation and communication overhead compared with CCN's basic authentication method, but also provides robustness against transmission loss and out-of-order transmission.We have implemented TLDA and demonstrated that it provides 74.3% improved throughput and 36.557% reduced communication overhead compared to those of the original CCNx library developed by PARC when transmitting a 128Mbyte content in units of 1Kbyte segment with RSA-2048 and SHA-256 as its signature algorithm and hash algorithm, respectively.

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Experimental evaluation of content distribution with NDN and HTTP

Cited by 26 publications

References 11 publications

Named Data Networking for Content Delivery Network Workflows

Named Data Networking for Content Delivery Network Workflows

The named data networking flow filter: Towards improved security over information leakage attacks

TLDA: An Efficient Two-Layered Data Authentication Mechanism for Content-Centric Networking

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