RAPEL: Robust and Adaptive method for PIT Entry Lifetime in Wireless Content-Centric Networks

As a key component in implementing Named Data Networking (NDN), Pending Interest Table (PIT) requires an efficient exact-matching algorithm for a scalable and fast PIT lookup. A Bloom filter (BF) is a memory-efficient data structure for performing exact matching operations. In this paper, three different BF-based PIT architectures are proposed: PIT using functional Bloom filters (FBF-PIT), PIT using counting Bloom filters with return values (rCBF-PIT), and a refined rCBF-PIT with signatures (R-rCBF-PIT). The proposed BF-based PITs incrementally allocate a new BF for storing multiple incoming faces of Interest packets with the same content name. For a Data packet lookup, the proposed PIT architectures simultaneously access every BF structure to find matching faces and delete the faces (i.e., matching Interest packet information). The functional Bloom filter (FBF) used in an FBF-PIT is a key-value data structure that stores values only without keys. However, because the number of non-reusable conflict cells in the FBF increases as the number of stored packets increases in the FBF-PIT, the indeterminable rate increases. To decrease the indeterminable rate, we propose the rCBF-PIT, which uses counting Bloom filters with return values (rCBFs), allowing reusable conflict cells. False positives for Interest packets lead to incorrect deletions that can cause false negatives for incoming Data packets. Because most of the false positives occur in the first BF structure, we finally propose the R-rCBF-PIT, in which the first rCBF is replaced with an rCBF with a signature field. The proposed PITs also provide an aging mechanism using a valid bit and a hit bit for entry expiration. Simulation results show that rCBF-PIT and R-rCBF-PIT both reduce the indeterminable rate by more than 81% compared with FBF-PIT. The results also show that R-rCBF-PIT resolves false negatives caused by incorrect deletions by including the signature fields in the first rCBF.

Today’s Internet is no longer fit for the user traffic patterns that it is serving. To remedy this cognitive mismatch between the service platform and the traffic it serves, several future Internet architectures such as Content-Centric Networking (CCN) have been proposed recently with the aim of re-engineering the Internet towards supporting content-oriented communication. With the mechanisms to transform the Internet from being host-centric to becoming content-centric well spelt-out in the CCN standard, the problem of how to manage congestion and control traffic flows in CCN is still left open. Existing congestion control mechanisms for the current Internet have been shown to be ill-suited for CCN making the case for a clean-slate design of congestion control and traffic management mechanisms for CCN. In this thesis, we identify the fact that congestion in CCN can take place not only in the transmission buffer but also in the pending interest table (PIT), a data structure that keeps track of all requests received from downstream nodes and forwarded to upstream nodes. Keeping this in mind, we make three contributions in this thesis: First, we characterize the PIT occupancy distribution using a 2-dimensional continuous-time Markov chain model to study the impact of PIT entry timeout and interest retransmission on the interest blocking probability. Second, given the dependence of the PIT occupancy on the PIT entry timeout and interest retransmission, we investigate the performance of two types of routers in lossy networks: no-rtx routers that do not retransmit pending interests upon timeout, and rtx routers that do retransmit pending interests periodically. Based on this, we further introduce a novel adaptive method to estimate the PIT entry timer that relies on the data chunk response delays to replace the currently used fixed-value method introduced in CCN. Finally, identifying that content requesters should be responsible for retransmitting timeout requests and that estimates of the retransmission timeout should reflect the network load conditions, we propose a novel congestion control mechanism for CCN that takes into account both the PIT and the transmit buffer. Using the PIT occupancy as a good estimator for the data flight size to arrive to the node in the near future, we design a congestion avoidance mechanism that adjusts the request rate based on anticipated congestion.

<p class="JESTECAbstract">Content Centric Networking (CCN) is a modern architecture that got wide attention in the current researches as a substitutional for the current IP-based architecture. Many studies have been investigated on this novel architecture but only little of them focused on Pending Interest Table (PIT) which is very important component in every CCN router. PIT has fundamental role in packet processing in both upstream process (Interest packets) and downstream process (Data packets). PIT must be fast enough in order to not become an obstruction in the packet processing and also it must be big enough to save a lot of incoming information. In this paper, we suggest a new PIT design and implementation named CF-PIT for CCN router. Our PIT design depends on modifying and utilizing an approximate data structure called Cuckoo filter (CF). Cuckoo filter has ideal characteristics like: high insertion/query/deletion performance, acceptable storage demands and false positive probability which make it with our modification convenient for PIT implementation. The experimental results showed that our CF-PIT design has high performance in different side of views which make it very suitable to be implemented on CCN routers.</p>

Vehicular Content-Centric Networks (VCCN) has been proposed and emerged as an upcoming Internet technology for the Vehicular Ad-hoc Networks (VANETs). However, VCCN architecture faces many challenges including Consumer/Provider mobility, Flooding, Interest/Data packet forwarding, Forwarding selection and Congestion control. Consumer vehicle broadcasts (i.e., requests) the interest packet. Relay nodes vehicles receiving this interest packet and performs search (Content Storage, Pending Interest Table and Forward Interest Base) operations on it and then rebroadcasts the interest message in case of no content match. These search (Content Storage, Pending Interest Table, and Forward Interest Base) operations cause delay and duplication's of interest packets. In our paper, we propose a routing protocol scheme named Intersection Based Forwarder Selection (IBFS) to mitigate the interest broadcast storm and disconnected link within the network. In IBFS, each vehicle shares its trajectory information with its neighboring vehicles. All vehicles store/save trajectory information in its Neighbor Table (NT), which helps to select the best interest relay/forwarder vehicle on the basis of matching trajectory information with the consumer vehicle. We have also considered the other metrics i.e. velocity and hop count. IBFS protocol overcomes the end-to-end delay (low latency), ISD (Interest Satisfaction Delay), communication overheads and minimum number of interest forwarded with the reliable interest and data packet transmission.

Radient: Scalable, memory efficient name lookup algorithm for named data networking

The large expansion in network services and applications seen in the last few years requires new network architectures to satisfy an increasing number of users and enhance content delivery. Named Data Networking (NDN) has recently appeared as a new paradigm to solve many shortcomings in the current TCP/IP architecture. Its main characteristics like stateful forwarding and in-network caching made NDN networks an efficient environment for data delivery where the data is retrieved based on content names rather than IP addresses. The NDN, by its nature, defends against the well-known Distributed Denial of Service (DDoS) attacks that take place in the traditional TCP/IP architecture. However, a special kind of DoS attack called Collusive Interest Flooding Attack (CIFA) has appeared to overwhelm the resources of NDN routers by filling their Pending Interest Tables (PIT) with long-lasting malicious entries. The network throughput and consumer satisfaction rate are highly affected by CIFA. A lightweight yet efficient stateless CIFA detection algorithm is proposed in this research utilizing the non-parametric CUSUM algorithm; a change point detection approach that detects the point in time when a transition occurs in the network. The proposed algorithm is characterized by its low computational overhead, highly accurate detection, and quick response. To detect the malicious name prefixes and eliminate the CIFA effect, a mitigation algorithm that uses the average response time vales of all name prefixes is proposed in this research. Experimental results show that this approach detects CIFA after 199.5 ms from when an attack is launched in the large-scale topology. In addition, the mitigation approach effectively reduces the PIT utilization and increases the average consumer satisfaction rate.

Content-centric networking (CCN) is an innovative network architecture that is being considered as a successor to the Internet. In recent years, CCN has received increasing attention from all over the world because its novel technologies (e.g., caching, multicast, aggregating requests) and communication based on names that act as addresses for content have the potential to resolve various problems facing the Internet. To implement these technologies, however, requires routers with performance far superior to that offered by today's Internet routers. Although many researchers have proposed various router components, such as caching and name lookup mechanisms, there are few router-level designs incorporating all the necessary components. The design and evaluation of a complete router is the primary contribution of this paper. We provide a concrete hardware design for a router model that uses three basic tables — forwarding information base (FIB), pending interest table (PIT), and content store (CS) — and incorporates two entities that we propose. One of these entities is the name lookup entity, which looks up a name address within a few cycles from content-addressable memory by use of a Bloom filter; the other is the interest count entity, which counts interest packets that require certain content and selects content worth caching. Our contributions are (1) presenting a proper algorithm for looking up and matching name addresses in CCN communication, (2) proposing a method to process CCN packets in a way that achieves high throughput and very low latency, and (3) demonstrating feasible performance and cost on the basis of a concrete hardware design using distributed content-addressable memory.

A density-aware probabilistic interest forwarding method for content-centric vehicular networks

Named Data Networking (NDN) is one of the most promising future Internet architectures, which supports communications based on content names but not the content locations. Clients can retrieve content only by sending an Interest packet, which includes the content name. However, independent Interest packets will cause heavy loads on the routers, particularly in the Internet of Things (IoT) scenarios which will induce huge number of small-sized content exchanges. The proposed scheme enables clients to retrieve many different contents by sending an aggregated Interest packet. In addition, the Data packet can also be aggregated by the intermediate routers to improve the efficiency of NDN communications.

Named Data Network (NDN) is a next-generation network architecture that shifts the traditional data communications paradigm Unlike conventional networks that rely on IP addresses, NDN delivers content based on data names rather than specific locations. In NDN, consumers express their requests by sending interest packets containing content names. These names are then propagated through the network nodes, which forward them to the appropriate destinations. The forwarding strategy in an NDN network plays a crucial role in ensuring efficient data delivery. This strategy includes a set of rules that determine the next hop for each interest packet. These rules are designed to optimize the forwarding process, minimizing delays and improving network efficiency. However, if the forwarding strategy is implemented without accurately identifying the appropriate face (i.e., the network interface) to forward interests toward the producer or the nearest cache node, it can lead to significant delays and packet drops. This, in turn, negatively impacts Quality of Service (QoS) parameters and the overall performance of the NDN network. This study applies supervised learning to classify consumer-requested interests to overcome this issue. This technique leverages several related variables to accurately classify these interests. The outcomes of the conducted research demonstrated that raw data from the mini-NDN output can be processed and transformed into a usable dataset. This data is then utilized to train a classification model with supervised learning. In a scenario with 9 NDN nodes and varying numbers of interests, distributed both uniformly and according to Zipf's law, the Random Forest model performs effectively, achieving an accuracy rate of 86.2% with an error rate of 14.8%.

Content centric networking (CCN) has attracted a great deal of attention as a network that can efficiently deliver content. In CCN, content is delivered using the content name, instead of the host IP address, from cache memory implemented at routers. The nodes sending content are not explicitly indicated, and content is delivered from routers that have copies of content on the routes where the Interest packets are transmitted. Therefore, as a result of introducing CCN in ISP networks, the pattern of traffic exchanges among ISPs will change considerably. Customer ISPs normally pay a transit fee to transit ISPs based on the traffic volume transmitted on the transit links. Therefore, the introduction of CCN by ISPs will affect the profit of ISPs. CCN is introduced and operated by ISPs based on their business judgment, so it is important to estimate how CCN affects ISP profit in order to investigate the likelihood of CCN spreading among many ISPs. In this paper, we formalize the profit of ISPs when implementing CCN, assuming a hierarchical topology of ISPs in three levels and investigate the likelihood of CCN spreading through numerical evaluation.

SummaryThe Vehicular Ad‐hoc Network (VANET) is one of the emerging research areas in recent days, in which accomplishing the robustness and security are the demanding tasks. To obtain these objectives, various offloading‐based techniques are developed in the traditional works. Still, it remains with the limitations of high mobility, no assurance for data acceptance, and limited applicability for multiple data exchange units. Thus, this paper aims to develop a Data Centric Dispatcher Selection (DCDS) algorithm based on data offloading for a secure information exchange in VANET. It aims to enable the cellular‐based VANET connection by using the application layer protocol without taking the Pending Interest (PI)‐based information. Also, the Content Centric Network (CCN) concept is utilized to exchange the data between for upcoming internet. In this environment, the position of own vehicle and neighboring vehicle are known to each vehicle by using the Global Positioning System (GPS) and security messages. Moreover, the communication does not depend on the device's name, but it depends on the content name in CCN. Because of the availability of multiple interfaces in CCN, there is no content loss in the network. During simulation, various performance measures are used to evaluate the performance of the proposed technique, which includes throughput, packet loss rate, average end‐to‐end delay, total Satisfied Interest Packet (SIP), Forwarded Interest Packet (FIP), and average Interest Satisfactory Delay (ISD). Also, the superiority of this paper is proved by comparing it with some existing techniques such as Internet Protocol Television Quality of Service (IPTV‐QoS), Michael Oche (MO), and RobUst Forwarder Selection (RUFs).

Recently, Content-Centric Networking (CCN) has been extensively studied by networking researchers as one of the promising network architectures for realizing information-centric networks. CCN adopts a fundamentally different communication paradigm from that of the conventional Internet Protocol (IP). Therefore, advanced transport protocols developed for IP cannot be directly used in CCN. In this paper, we propose a packet loss detection mechanism called Interest ACKnowledgement (ACK). Interest ACKs provides information on the history of successful Interest packet receptions at a repository (i.e., content provider), this information is conveyed to the corresponding entity (i.e., content consumer) via the header of Data packets. Interest ACKs enable the entity to quickly and accurately detect Interest and Data packet losses in the network. We conduct simulations to investigate the effectiveness of Interest ACKs in a rather simple network topology. Our results show that Interest ACKs are effective for improving the adaptability, stability, and fairness of CCN with window-based flow control and that packet losses at the repository can be reduced by 10%–20%.

As content distribution over the Internet become more and more popular and important, future Internet architecture requires highly scalable infrastructures to distribute content efficiently. Information-Centric Networks (ICN) was proposed as a kind of important future Internet architecture to facilitate the contents distribution. ICN uses content name as the routing locator has been proposed for efficient contents distribution. In ICN, content is dynamically cached in routers, which is different from traditional content distribution networks that still use IP address as routing locator and cache content at distributed servers, and caching has been identified as a critical component for ICN. This paper proposes a time-based caching mechanism for Service Providers (SPs) to monetize caching. The SPs cache contents of Contents Providers (CPs) for a certain mount of time, depending on the payment from CPs.

Evolutionary multi-path routing for network lifetime and robustness in wireless sensor networks