3,379 research outputs found
Multidimensional content modeling and caching in D2D edge networks
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Future Internet is going to be shaped by networked multimedia services with exploding video traffic becoming the dominant payload. That evolution requires a remedial shift from the connection-oriented architecture to a content-centric one. Another technique to address this capacity crunch is to improve spectral utilization through new networking paradigms at the wireless network edge. To this end, Device-to-Device (D2D) communications has the potential for boosting the capacity and energy efficiency for content-centric networking. To design and implement efficient content-centric D2D networks, rigorous content modeling and in-network caching mechanisms based on such models are crucial. In this work, we develop a multidimensional content model based on popularity, chunking and layering, and devise caching schemes through this model. Our main motivation is to improve the system performance via our caching strategies. The numerical analysis shows the interplay among different system parameters and performance metrics: while our schemes perform slightly poorer in terms of system goodput, they also decrease the system energy expenditure. Overall, this improvement dominates the loss in the goodput, leading to greater energy efficiency compared to the commonly-used caching technique Least Recently Used (LRU)
Fog-enabled Edge Learning for Cognitive Content-Centric Networking in 5G
By caching content at network edges close to the users, the content-centric
networking (CCN) has been considered to enforce efficient content retrieval and
distribution in the fifth generation (5G) networks. Due to the volume,
velocity, and variety of data generated by various 5G users, an urgent and
strategic issue is how to elevate the cognitive ability of the CCN to realize
context-awareness, timely response, and traffic offloading for 5G applications.
In this article, we envision that the fundamental work of designing a cognitive
CCN (C-CCN) for the upcoming 5G is exploiting the fog computing to
associatively learn and control the states of edge devices (such as phones,
vehicles, and base stations) and in-network resources (computing, networking,
and caching). Moreover, we propose a fog-enabled edge learning (FEL) framework
for C-CCN in 5G, which can aggregate the idle computing resources of the
neighbouring edge devices into virtual fogs to afford the heavy delay-sensitive
learning tasks. By leveraging artificial intelligence (AI) to jointly
processing sensed environmental data, dealing with the massive content
statistics, and enforcing the mobility control at network edges, the FEL makes
it possible for mobile users to cognitively share their data over the C-CCN in
5G. To validate the feasibility of proposed framework, we design two
FEL-advanced cognitive services for C-CCN in 5G: 1) personalized network
acceleration, 2) enhanced mobility management. Simultaneously, we present the
simulations to show the FEL's efficiency on serving for the mobile users'
delay-sensitive content retrieval and distribution in 5G.Comment: Submitted to IEEE Communications Magzine, under review, Feb. 09, 201
Information Centric Networking in the IoT: Experiments with NDN in the Wild
This paper explores the feasibility, advantages, and challenges of an
ICN-based approach in the Internet of Things. We report on the first NDN
experiments in a life-size IoT deployment, spread over tens of rooms on several
floors of a building. Based on the insights gained with these experiments, the
paper analyses the shortcomings of CCN applied to IoT. Several interoperable
CCN enhancements are then proposed and evaluated. We significantly decreased
control traffic (i.e., interest messages) and leverage data path and caching to
match IoT requirements in terms of energy and bandwidth constraints. Our
optimizations increase content availability in case of IoT nodes with
intermittent activity. This paper also provides the first experimental
comparison of CCN with the common IoT standards 6LoWPAN/RPL/UDP.Comment: 10 pages, 10 figures and tables, ACM ICN-2014 conferenc
Content Delivery Latency of Caching Strategies for Information-Centric IoT
In-network caching is a central aspect of Information-Centric Networking
(ICN). It enables the rapid distribution of content across the network,
alleviating strain on content producers and reducing content delivery
latencies. ICN has emerged as a promising candidate for use in the Internet of
Things (IoT). However, IoT devices operate under severe constraints, most
notably limited memory. This means that nodes cannot indiscriminately cache all
content; instead, there is a need for a caching strategy that decides what
content to cache. Furthermore, many applications in the IoT space are
timesensitive; therefore, finding a caching strategy that minimises the latency
between content request and delivery is desirable. In this paper, we evaluate a
number of ICN caching strategies in regards to latency and hop count reduction
using IoT devices in a physical testbed. We find that the topology of the
network, and thus the routing algorithm used to generate forwarding
information, has a significant impact on the performance of a given caching
strategy. To the best of our knowledge, this is the first study that focuses on
latency effects in ICN-IoT caching while using real IoT hardware, and the first
to explicitly discuss the link between routing algorithm, network topology, and
caching effects.Comment: 10 pages, 9 figures, journal pape
Named data networking for efficient IoT-based disaster management in a smart campus
Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS
Modeling Data-Plane Power Consumption of Future Internet Architectures
With current efforts to design Future Internet Architectures (FIAs), the
evaluation and comparison of different proposals is an interesting research
challenge. Previously, metrics such as bandwidth or latency have commonly been
used to compare FIAs to IP networks. We suggest the use of power consumption as
a metric to compare FIAs. While low power consumption is an important goal in
its own right (as lower energy use translates to smaller environmental impact
as well as lower operating costs), power consumption can also serve as a proxy
for other metrics such as bandwidth and processor load.
Lacking power consumption statistics about either commodity FIA routers or
widely deployed FIA testbeds, we propose models for power consumption of FIA
routers. Based on our models, we simulate scenarios for measuring power
consumption of content delivery in different FIAs. Specifically, we address two
questions: 1) which of the proposed FIA candidates achieves the lowest energy
footprint; and 2) which set of design choices yields a power-efficient network
architecture? Although the lack of real-world data makes numerous assumptions
necessary for our analysis, we explore the uncertainty of our calculations
through sensitivity analysis of input parameters
Caching and D2D sharing for content delivery in software-defined UAV networks
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In cases of catastrophic events such as natural disasters or physical calamities, current network infrastructure can become inoperative. Furthermore, there are transient events leading to excessive demand surges where it is needed to deploy additional network capacity on-demand. In such cases, rapid network deployments become vital to establish communications and enable networked services. Unmanned Aerial Vehicle (UAV) networks are good candidates for this kind of operation. Software-defined networking and content-centric operation are promising technologies to enable agile control, network visibility and efficient content delivery via centralized optimization in these challenged systems. In this work, we consider an edge network which is composed of UAVs and serves in a content-centric mode with in-network caching and device-to-device (D2D) transmissions. We develop a cache placement and selection scheme for energy efficient operation. We also investigate how such a system performs under different operating conditions
Security for the Industrial IoT: The Case for Information-Centric Networking
Industrial production plants traditionally include sensors for monitoring or
documenting processes, and actuators for enabling corrective actions in cases
of misconfigurations, failures, or dangerous events. With the advent of the
IoT, embedded controllers link these `things' to local networks that often are
of low power wireless kind, and are interconnected via gateways to some cloud
from the global Internet. Inter-networked sensors and actuators in the
industrial IoT form a critical subsystem while frequently operating under harsh
conditions. It is currently under debate how to approach inter-networking of
critical industrial components in a safe and secure manner.
In this paper, we analyze the potentials of ICN for providing a secure and
robust networking solution for constrained controllers in industrial safety
systems. We showcase hazardous gas sensing in widespread industrial
environments, such as refineries, and compare with IP-based approaches such as
CoAP and MQTT. Our findings indicate that the content-centric security model,
as well as enhanced DoS resistance are important arguments for deploying
Information Centric Networking in a safety-critical industrial IoT. Evaluation
of the crypto efforts on the RIOT operating system for content security reveal
its feasibility for common deployment scenarios.Comment: To be published at IEEE WF-IoT 201
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