Hash-routing has been proposed in the past as a mapping mechanism between object requests and cache clusters within enterprise networks.In this paper, we revisit hash-routing techniques and apply them to Information-Centric Networking (ICN) environments, where network routers have cache space readily available. In particular, we investigate whether hash-routing is a viable and efficient caching approach when applied outside enterprise networks, but within the boundaries of a domain.We design five different hash-routing schemes which efficiently exploit in-network caches without requiring network routers to maintain per-content state information.We evaluate the proposed hash-routing schemes using extensive simulations over real Internet domain topologies and compare them against various on-path caching mechanisms. We show that such schemes can increase cache hits by up to 31% in comparison to on-path caching, with minimal impact on the traffic dynamics of intra-domain links.
Abstract-Content Centric Networking (CCN) is a recently proposed information-centric Internet architecture in which the main network abstraction is represented by location-agnostic content identifiers instead of node identifiers. In CCN each content object is divided into packet-size chunks. When a content object is transferred, routers on the path can cache single chunks which they can use to serve subsequent requests from other users.Since content chunks in CCN may be retrieved from a number of different nodes/caches, implicit-feedback transport protocols will not be able to work efficiently, because it is not possible to set an appropriate timeout value based on RTT estimations given that the data source may change frequently during a flow.In order to address this problem, we propose in this paper a scalable, implicit-feedback congestion control protocol, capable of coping with RTT unpredictability using a novel anticipated interests mechanism to predict the location of chunks before they are actually served. Our evaluation shows that our protocol outperforms similar receiver-driven protocols, in particular when content chunks are scattered across network paths due to reduced cache sizes, long-tail content popularity distribution or the adoption of specific caching policies.
Information-Centric Networking (ICN) is a new networking paradigm proposing a shift of the main network abstraction from host identifiers to location-agnostic content identifiers. So far, several architectures have been proposed implementing this paradigm shift. A key feature, common to all proposed architectures, is the in-network caching capability, enabled by the locationagnostic, explicit naming of contents. This aspect, in particular, has recently received considerable attention by the research community. However, despite this wide interest, there is a shortage of publicly-available tools suitable for evaluating the performance of caching systems effectively. In fact, all available simulators or emulators are either bound to a specific architecture or cannot execute simulations at the scale required and within a reasonable time-frame. To address these issues, we present Icarus, a Python-based caching simulator for ICN. Icarus allows users to evaluate caching strategies for any ICN implementation and also provides modelling tools useful for caching research.
Arguably, one of the most cumbersome tasks required to run a network simulation is the setup of a complete simulation scenario and its implementation in the target simulator. This process includes selecting a topology, provision it with all required parameters and, finally, configure traffic sources or generate traffic matrices.Many tools exist to address some of these tasks. However, most of them do not provide methods for configuring network and traffic parameters, while others only support a specific simulator. As a consequence, a user often needs to implement the desired features personally, which is both time-consuming and error-prone.To address these issues, we present the Fast Network Simulation Setup (FNSS) toolchain. It provides capabilities for parsing topologies from datasets or generating them synthetically, assign desired configuration parameters and generate traffic matrices or event schedules. It also provides APIs for a number of programming languages and network simulators to easily deploy the simulation scenario in the target simulator. Categories and Subject Descriptors General TermsDesign, Performance, Experimentation Keywords network topology, network simulation, link capacity, modeling, traffic matrix * Source code, binaries and documentation of the FNSS toolchain is available at
In the immediate aftermath of a natural disaster, network infrastructure is likely to have suffered severe damages that challenge normal communications. In addition to that, traffic substantially increases as a result of people attempting to get in touch with friends, relatives or the rescue teams. To address such requirements of a challenged network, we propose a communication framework based on messages that exploits namebased replication of content and enables ad-hoc communications with spatial and temporal scoping and prioritisation of named messages. We evaluate our design against less sophisticated replication strategies and show that important messages (e.g., from first responders) get disseminated to more nodes than less important messages.
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