A first course in stochastic processes

https://www.cs.arizona.edu/~yic/paper/comcom-forwarding.pdf

A case for stateful forwarding plane

In Named Data Networking (NDN) architecture, packets carry data names rather than source or destination addresses. This change of paradigm leads to a new data plane: data consumers send out Interest packets, routers forward them and maintain the state of pending Interests, which is used to guide Data packets back to the consumers. NDN routers' forwarding process is able to detect network problems by observing the two-way traffic of Interest and Data packets, and explore multiple alternative paths without loops. This is in sharp contrast to today's IP forwarding process which follows a single path chosen by the routing process, with no adaptability of its own. In this paper we outline the design of NDN's adaptive forwarding, articulate its potential benefits, and identify open research issues.

/pdf/adaptive-forwarding-in-named-data-networking-3sius9lskr.pdf

Adaptive forwarding in named data networking

Content-Centric Networking (CCN) is an emerging networking paradigm being considered as a possible replacement for the current IP-based host-centric Internet infrastructure. In CCN, named content becomes a first-class entity. CCN focuses on content distribution, which dominates current Internet traffic and is arguably not well served by IP. Named-Data Networking (NDN) is an example of CCN. NDN is also an active research project under the NSF Future Internet Architectures (FIA) program. FIA emphasizes security and privacy from the outset and by design. To be a viable Internet architecture, NDN must be resilient against current and emerging threats. This paper focuses on distributed denial-of-service (DDoS) attacks; in particular we address interest flooding, an attack that exploits key architectural features of NDN. We show that an adversary with limited resources can implement such attack, having a significant impact on network performance. We then introduce Poseidon: a framework for detecting and mitigating interest flooding attacks. Finally, we report on results of extensive simulations assessing proposed countermeasure.

Poseidon: Mitigating Interest Flooding DDoS Attacks in Named Data Networking

Information-centric networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today’s Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, named data networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is intelligent transportation system realized through vehicular ad hoc network (VANET) where vehicles exchange information and content with each other and with the infrastructure. Up to date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community.

/pdf/named-data-networking-in-vehicular-ad-hoc-networks-state-of-1o0xpq761d.pdf

Named Data Networking in Vehicular Ad Hoc Networks: State-of-the-Art and Challenges

Name-based route lookup is a key function for Named Data Networking (NDN). The NDN names are hierarchical and have variable and unbounded lengths, which are much longer than IPv4/6 address, making fast name lookup a challenging issue. In this paper, we propose an effective Name Component Encoding (NCE) solution with the following two techniques: (1) A code allocation mechanism is developed to achieve memory-efficient encoding for name components, (2) We apply an improved State Transition Arrays to accelerate the longest name prefix matching and design a fast and incremental update mechanism which satisfies the special requirements of NDN forwarding process, namely to insert, modify, and delete name prefixes frequently. Furthermore, we analyze the memory consumption and time complexity of NCE. Experimental results on a name set containing 3,000,000 names demonstrate that compared with the character trie NCE reduces overall 30% memory. Besides, NCE performs a few millions lookups per second (on an Intel 2.8 GHz CPU), a speedup of over 7 times compared with the character trie. Our evaluation results also show that NCE can scale up to accommodate the potential future growth of the name sets.

/pdf/scalable-name-lookup-in-ndn-using-effective-name-component-12e201quww.pdf

Scalable Name Lookup in NDN Using Effective Name Component Encoding

Current Internet is reaching the limits of its capabilities due to its function transition from host-to-host communication to content dissemination. Named Data Networking (NDN) – an instantiation of Content-Centric Networking approach, embraces this shift by stressing the content itself, rather than where it locates. NDN tries to provide better security and privacy than current Internet does, and resilience to Distributed Denial of Service (DDoS) is a significant issue. In this paper, we present a specific and concrete scenario of DDoS attack in NDN, where perpetrators make use of NDN’s packet forwarding rules to send out Interest packets with spoofed names as attacking packets. Afterwards, we identify the victims of NDN DDoS attacks include both the hosts and routers. But the largest victim is not the hosts, but the routers, more specifically, the Pending Interest Table (PIT) within the router. PIT brings NDN many elegant features, but it suffers from vulnerability. We propose Interest traceback as a counter measure against the studied NDN DDoS attacks, which traces back to the originator of the attacking Interest packets. At last, we assess the harmful consequences brought by these NDN DDoS attacks and evaluate the Interest traceback counter measure. Evaluation results reveal that the Interest traceback method effectively mitigates the NDN DDoS attacks studied in this paper

/pdf/mitigate-ddos-attacks-in-ndn-by-interest-traceback-36x52tesj5.pdf

Mitigate DDoS attacks in NDN by interest traceback

This paper studies the name lookup issue with longest prefix matching, which is widely used in URL filtering, content routing/switching, etc. Recently Content-Centric Networking (CCN) has been proposed as a clean slate future Internet architecture to naturally fit the content-centric property of today's Internet usage: instead of addressing end hosts, the Internet should operate based on the identity/name of contents. A core challenge and enabling technique in implementing CCN is exactly to perform name lookup for packet forwarding at wire speed. In CCN, routing tables can be orders of magnitude larger than current IP routing tables, and content names are much longer and more complex than IP addresses. In pursuit of conquering this challenge, we conduct an implementation-based case study on wire speed name lookup, exploiting GPU's massive parallel processing power. Extensive experiments demonstrate that our GPU-based name lookup engine can achieve 63.52M searches per second lookup throughput on large-scale name tables containing millions of name entries with a strict constraint of no more than the telecommunication level 100µs per-packet lookup latency. Our solution can be applied to contexts beyond CCN, such as search engines, content filtering, and intrusion prevention/ detection.

https://www.usenix.org/system/files/conference/nsdi13/nsdi13-final32.pdf

Wire speed name lookup: a GPU-based approach

Complex name constitution plus huge-sized name routing table makes wire speed name lookup a challenging task in Named Data Networking. To overcome this challenge, we propose two techniques to significantly speed up the lookup process. First, we look up name prefixes in an order based on the distribution of prefix length in the forwarding table, which can find the longest match much faster than the linear search of current prototype CCNx. The search order can be dynamically adjusted as the forwarding table changes. Second, we propose a new near-perfect hash table data structure that combines many small sparse perfect hash tables into a larger dense one while keeping the worst-case access time of O(1) and supporting fast update. Also the hash table stores the signature of a key instead of the key itself, which further improves lookup speed and reduces memory use.

Fast name lookup for Named Data Networking

Per-flow measurement can provide fine-grained statistics for advanced network management and thus has been studied extensively. As network line rate continues its rapid growth, wire-speed per-flow measurement meets great challenges, for large numbers of statistics counters are required to record flow information at extremely high speed. Most of the previous efforts are committed to elaborate excellent sampling algorithms to make counters' memory occupation as small as possible, so as to fit into off-chip SRAM(s), but the throughput is rigidly bounded by the speed of SRAM. To break the wall, we explore a new path by proposing CASE: a cache-assisted stretchable estimator, which uses the on-chip memory as the fast cache of the off-chip SRAM. In this way, most of the accesses to the counters will happen on cache, thanks to the heavy-tailed distribution of Internet traffic. In this paper, we present CASE's design and derive strict mathematical proof to its relative error bound. Extensive experiments on real-world traces are conducted and the evaluation results indicate CASE can achieve up to 300Gbps throughput when using on-chip memory with 128K entries (equivalent to 1.125MB). Meanwhile CASE is more accurate and stretchable than uncached approaches.

CASE: Cache-assisted stretchable estimator for high speed per-flow measurement

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