On the throughput capacity of information-centric networks

Nowadays, Internet is mostly used to access content and users are also interested in content, instead of location. Information-Centric Networking (ICN) has drawn substantial consideration over past few years because its appearance introduced a new potential Internet architecture (deploying extensive cache structure to distribute and deliver information). Though ICN has undoubtedly become a promising Future Internet architecture to solve current host-centric Internet problems, conventional ICN design still has its own drawbacks. These include caching, routing, etc., particularly mobility issue and energy-efficiency problem due to additional energy consumption for Content Routers’ caching capability. In order to address the energy flaw and enhance the mobility performance of ICNArchitecture, in this article, we have designed, evaluated and proposed a wireless Information Centric Networking (ICN) based access model within the context of Intelligent Transport System (ITS) for ICN standardization procedure. We take into consideration the fact that number of mobile devices increases rapidly day by day as well as the public transportation (e.g. train, bus, etc) becomes more popular nowadays. Besides, mobile users may ask for different content interests via Internet during the period of time when they are on public transport vehicle. We then propose a wireless communication topology in ICN for the ITS by utilizing the smart scheduling algorithm with proactive-caching based strategy to deal with possible and practical situations of commuters (mobile content users). In our scheme, the dedicated content provider proactively sends appropriate segments of requested content (based on chunk-level structure of content) to expected proximity Aggregation content nodes located at neighbor stations (future attachment points) on the moving path of public transportation vehicle. This working scheme substantially enhances the mobile user’s quality of experience and network performance in ICN. Moreover, the proposed ICN based system adapts the network nodes to their optimized network utilization values according to content popularity by conducting cross-layer optimization. This mechanism provides mobile users more reliable and effective Green Information and Communication Systems (ICS) when they travel with public transportation. Therefore, the proposal integrates Green networking into ICN by combining the benefits of innovated rate-adaptivity and proactive-caching based schemes for achieving highly scalable, reliable and energy-efficient network performance in future transportation Information-centric communication system with data-awareness. In addition, we identify that there are currently various ICN-based models and emphasize the need of an official ICN international standard for wireless communication in general and transportation system in particular. Following, by evaluating the proposal, we show that the proposed cross-layer wireless content access model in ICN for ITS is a promising and feasible contribution for the standardization process of ICN.

With the rapid growth of internet traffic, the traditional host-to-host TCP/IP architecture is subject to many service limitations faced with content-oriented applications. Various novel network architectures have been proposed to solve these limitations, among which Information-Centric Networking (ICN) is one of the most prominent. ICN features the decoupling of content (service) from the physical devices storing (providing) it through location-independent naming, and offers inherent enhancement to network performance, such as multicast and in-network caching. ICN in-network caching has been extensively studied, and we believe that it may also be the main incentive for ISPs to deploy ICN. A CDN (content delivery network) is a typical content-oriented network paradigm that aims to provide the fast delivery of content. In this paper, we leverage the advantages of the in-network caching of ICN to enhance the content delivery efficiency of CDN by integrating ICN as a service. First, we present our design of a content delivery network enhanced with ICN, called IECDN. Additionally, we formulate a mathematical model to optimize the performance of our proposed design and conduct a series of evaluations. The results indicate that our proposed design provides significant performance gains while reducing bandwidth consumption and shows better resilience to traffic surge.

In-network content caching is a key feature of Information Centric Network (ICN), which facilitates efficient content distribution with reduced bandwidth consumption, less network congestion, and improved content retrieval latency. However, this ubiquitous caching of ICN is vulnerable to side-channel timing attack, where the adversary takes advantage of the response time difference between the cached and un-cached contents from the router, to detect if a privacy-sensitive object is cached, or even infer which user requested the object. To mitigate this type of privacy risk in ICN, we propose a differential defense mechanism against distributed timing attack in this paper. Specifically, we design an algorithm based on differential privacy to determine whether a cache-hit or cache-miss is returned for a certain request, which effectively hide the actual cache hit with differential privacy guarantee. Furthermore, a differential delay algorithm for artificial cache miss is implemented based on Laplace mechanism of differential privacy. Performance analysis and simulation results show that our scheme is more effective against distributed timing attack and incurs less impact on caching efficiency and delay performance compared with existing defense schemes for ICN.

As devices for the Internet of Things (IoT) are typically battery-powered, energy efficiency is a major challenge for IoT networks. In this paper, we leverage the in-network caching of Information-Centric Networking (ICN) to propose a novel cooperative caching scheme, based on the IoT data lifetime and user request rate, to improve the energy efficiency of IoT networks. By caching IoT data at different nodes (such as content routers, base stations, etc.), IoT devices can stay in sleep mode for a larger portion of time and therefore reduce the overall energy consumption. With the help of an auto- configuration mechanism, the proposed IoT data Lifetime-based Cooperative Caching (LCC) scheme can dynamically adapt to the change of request rate. Extensive evaluations were performed and the simulation results show that LCC outperforms existing schemes in terms of total energy consumption reduction (up to 40%) and the reduction in the average number of hops traversed along the path (up to 20%), which is also directly related to the response time. Keywords- Internet of Things (IoT), Cooperative Caching, Information-Centric Network (ICN).

In Information-Centric Networks (ICNs), caching decisions are mostly driven by request-centric mechanisms. Fluctuations in request rates and cache capacities typically have the most impact on where content would be cached. However, as ICNs expand in scale, producers may prefer certain nodes to cache their contents based on favorable properties, such as topological centrality, closeness of cache locations with respect to consumers, security measures, and service up-time. These factors would impact the valuation of caching nodes. Nevertheless, maximizing cache utilization via dynamic cache valuation is a challenging task in ICNs, largely due to inter-dependencies in model parameters. In this paper, we propose a novel caching model where content producers aim to dynamically valuate cache nodes to optimize caching. The model is built on a value-based utility function that considers dynamic and topological attributes of cache nodes, enabling a dynamic novel caching scheme named Max-Node Utility that aims to maximize caching utility. Simulation results demonstrate that Max-Node Utility outperforms current state-of-the art caching schemes by providing better caching utility, reducing access delay and increasing cache hit ratios across varying cache sizes and popularity skewness values. An outlook on the premise of producer-driven caching schemes is presented in the conclusion, to emphasize future directions in similar caching models.

In this paper, we model the random multi-user multi-channel access network by using the well known occupancy problem from probability theory. Furthermore, we combine this with a network interference model in order to derive the achievable throughput capacity of such networks. The mathematical developments and results are illustrated through various simulations results. The proposed model is particularly relevant in analyzing the performance of networks where the users are not synchronized neither in time nor in frequency as it is often the case in various Internet of Things (IoT) applications.

We quantify the throughput capacity of wireless multi-hop networks with several medium access schemes. We analyze pure ALOHA scheme where simultaneous transmitters are dispatched according to a uniform Poisson distribution and exclusion schemes where simultaneous transmitters are dispatched according to an exclusion rule such as node coloring and carrier sense based schemes. We consider both no-fading and standard Rayleigh fading channel models. Our results show that, under no-fading, slotted ALOHA can achieve at least one-third (or half under Rayleigh fading) of the throughput capacity of node coloring scheme whereas carrier sense based scheme can achieve almost the same throughput capacity as node coloring.

We present the first unified modeling framework for the computation of the throughput capacity of random wireless ad hoc networks in which information is disseminated by means of unicast routing, multicast routing, broadcasting, or different forms of anycasting. We introduce (n,m, k)-casting as a generalization of all forms of one-to-one, one-to-many and many-to-many information dissemination in wireless networks. In this context, n, m, and k denote the total number of nodes in the network, the number of destinations for each communication group, and the actual number of communication-group members that receive information (i.e., k lesm), respectively. We compute upper and lower bounds for the (n, m, k)- cast throughput capacity in random wireless networks. When m = k = ominus(1), the resulting capacity equals the well-known capacity result for multi-pair unicasting by Gupta and Kumar. We demonstrate that ominus(1/radic(mnlogn)) bits per second constitutes a tight bound for the capacity of multicasting (i.e., m = k < n) when m les ominus (n/(log n)). We show that the multicast capacity of a wireless network equals its capacity for multi-pair unicasting when the number of destinations per multicast source is not a function of n. We also show that the multicast capacity of a random wireless ad hoc network is ominus (1/n), which is the broadcast capacity of the network, when m ges ominus(n/ log n). Furthermore, we show that ominus (radicm/(kradic(n log n))),ominus(1/(k log n)) and ominus(1/n) bits per second constitutes a tight bound for the throughput capacity of multicasting (i.e., k < m < n) when ominus(1) les m les ominus (n/ log n), k les ominus(n / log n) les m les n and ominus (n/ log n) les k les m les n respectively.

Information-Centric Networking (ICN) is an emerging networking paradigm where named and routable data (content) is the focal point. Users send explicit requests (interests) which specify content by name, and the network handles routing these interests to some entity capable of satisfying them with the appropriate data response (producer). One key feature of ICN is opportunistic in-network content caching. This property facilitates efficient content distribution by reducing bandwidth consumption, lessening network congestion, and improving the content retrieval latency by users (consumers). Unfortunately, the same feature is also detrimental to privacy of content consumers and producers. Simple to implement, and difficult to detect, timing attacks can exploit ICN routers as “oracles” and allow an adversary to learn whether a nearby consumer recently requested certain content. The attack leverages a timing side channel that relies on router caches and is implemented by requesting a few packets from each piece of content being probed. Similarly, probing attacks that target content producers can be used to discover whether certain content has been recently distributed. After analyzing the scope and feasibility of such attacks, we propose and evaluate some efficient countermeasures that offer quantifiable privacy guarantees while retaining the benefits of ICN.

We study the throughput capacity of wireless networks which employ (asynchronous) random-access scheduling as opposed to deterministic scheduling. The central question we answer is: how should we set the channel-access probability for each link in the network so that the network operates close to its optimal throughput capacity? We design simple and distributed channel-access strategies for random-access networks which are provably competitive with respect to the optimal scheduling strategy, which is deterministic, centralized, and computationally infeasible. We show that the competitiveness of our strategies are nearly the best achievable via random-access scheduling, thus establishing fundamental limits on the performance of random- access. A notable outcome of our work is that random access compares well with deterministic scheduling when link transmission durations differ by small factors, and much worse otherwise. The distinguishing aspects of our work include modeling and rigorous analysis of asynchronous communication, asymmetry in link transmission durations, and hidden terminals under arbitrary link-conflict based wireless interference models.

Information-centric networking (ICN) is of high interest to the Internet of Things (IoT) community, since the dissemination of massive data continuously produced by IoT devices can be easily handled by ICN’s data naming scheme and inherent multipath delivery. Providing optimal multipath-oriented transmission control is crucial for ICN-IoT data delivery, but yet remains challenging because of the randomness of request arrival, dynamic link condition, and on-path caching. More prominently, the resource limitation and scalability issues in IoT require the control scheme to be lightweight and distributed. In this paper, we propose a distributed stochastic optimization framework for multipath transmission control in ICN-IoT. The transmission control, including request scheduling and data rate regulation, is formulated as a stochastic concave optimization problem, which aims to accommodate the randomness, unpredictability, and multipath delivery of ICN-IoT and maximize the overall throughput. This problem is linearly separated into two subproblems: 1) a request scheduling problem and 2) a data rate control problem, which can be individually solved per time slot. A distributed alternating descent method (DADM) is designed to optimally control the transmission by solving the aforementioned problems at client sides. DADM enables each client to sequentially update the request schedule and rate regulation via communicating the links and providers they use, which asymptotically converges to optimality while allowing low-complexity and decentralized implementation. Validated by simulations, our DADM significantly improves throughput, delay reduction, and energy efficiency, in comparison with other state-of-the-art solutions.

In this chapter, we explore techniques for capacity estimation and throughput maximization in multi-hop wireless networks. The specific problem we investigate is the following: how can we characterize the set of all feasible end-to-end connection throughput rate vectors which can be supported by the network (i.e., what is the network capacity), and how can we design cross-layer algorithms at the scheduling, routing, and transport layers which are guaranteed to operate the network close to its capacity? We approach this problem from three distinct perspectives which have greatly influenced research in this field: (1) throughput scaling in random geometric graphs whose nodes are distributed uniformly in space, (2) geometric packing and linear programming-based techniques for arbitrary networks, and (3) the dynamic back-pressure scheme based on queueing theoretic principles for achieving network stability. A recurring theme throughout this chapter is the role of geometric insights into the design and analysis of provably good algorithms for multi-hop wireless networks. We also include a brief survey of related developments in the field of cross-layer algorithms for multi-hop wireless networks.

A formal framework is presented for the characterization of cache allocation models in Information-Centric Networks (ICN). The framework is used to compare the performance of optimal caching everywhere in an ICN with opportunistic caching of content only near its consumers. This comparison is made using the independent reference model adopted in all prior studies, as well as a new model that captures non-stationary reference locality in space and time. The results obtained analytically and from simulations show that optimal caching throughout an ICN and opportunistic caching at the edge routers of an ICN perform comparably the same. In addition caching content opportunistically only near its consumers is shown to outperform the traditional on-path caching approach assumed in most ICN architectures in an unstructured network with arbitrary topology represented as a random geometric graph.

Deploying the active queue management (AQM) algorithm on a router is an effective way to avoid packet loss caused by congestion. In an information-centric network (ICN), routers not only play a role of packets forwarding but are also content service providers. Congestion in ICN routers can be further summarized as the competition between the external forwarding traffic and the internal cache response traffic for limited bandwidth resources. This indicates that the traditional AQM needs to be redesigned to adapt to ICN. In this paper, we first demonstrated mathematically that allocating more bandwidth for the upstream forwarding flow could improve the quality of service (QoS) of the whole network. Secondly, we propose a novel AQM algorithm, YELLOW, which predicts the bandwidth competition event and adjusts the input rate of request and the marking probability adaptively. Afterwards, we model YELLOW through the totally asymmetric simple exclusion process (TASEP) and deduce the approximate solution of the existence condition for each stationary phase. Finally, we evaluated the performance of YELLOW by NS-3 simulator, and verified the accuracy of modeling results by Monte Carlo. The simulation results showed that the queue of YELLOW could converge to the expected value, and the significant gains of the router with low packet loss rate, robustness and high throughput.

The throughput capacity of arbitrary wireless networks under the physical Signal to Interference Plus Noise Ratio (SINR) model has received much attention in recent years. In this paper, we investigate the question of how much the worst-case performance of uniform and non-uniform power assignments differ under constraints such as a bound on the area where nodes are distributed or restrictions on the maximum power available. We determine the maximum factor by which a non-uniform power assignment can outperform the uniform case in the SINR model. More precisely, we prove that in one-dimensional settings the capacity of a non-uniform assignment exceeds a uniform assignment by at most a factor of O(logL max ) when the length of the network is L max . In two-dimensional settings, the uniform assignment is at most a factor of O(logP max ) worse than the non-uniform assignment if the maximum power is P max . We provide algorithms that reach this capacity in both cases. Due to lower bound examples in previous work, these results are tight in the sense that there are networks where the lack of power control causes a performance loss in the order of these factors. As a consequence, engineers and researchers may prefer the uniform model due to its simplicity if this degree of performance deterioration is acceptable.