1,667 research outputs found
MIRAI Architecture for Heterogeneous Network
One of the keywords that describe next-generation wireless communications is "seamless." As part of the e-Japan Plan promoted by the Japanese Government, the Multimedia Integrated Network by Radio Access Innovation project has as its goal the development of new technologies to enable seamless integration of various wireless access systems for practical use by 2005. This article describes a heterogeneous network architecture including a common tool, a common platform, and a common access. In particular, software-defined radio technologies are used to develop a multiservice user terminal to access different wireless networks. The common platform for various wireless networks is based on a wireless-supporting IPv6 network. A basic access network, separated from other wireless access networks, is used as a means for wireless system discovery, signaling, and paging. A proof-of-concept experimental demonstration system is available
PEARL: a programmable virtual router platform
International audienceProgrammable routers supporting virtualization are a key building block for bridging the gap between new Internet protocols and their deployment in real operational networks. This article presents the design and implementation of PEARL, a programmable virtual router platform with relatively high performance. It offers high flexibility by allowing users to control the configuration of both hardware and software data paths. The platform makes use of fast lookup in hardware and software exceptions in commodity multicore CPUs to achieve highspeed packet processing. Multiple isolated packet streams and virtualization techniques ensure isolation among virtual router instances
Atomic-SDN: Is Synchronous Flooding the Solution to Software-Defined Networking in IoT?
The adoption of Software Defined Networking (SDN) within traditional networks
has provided operators the ability to manage diverse resources and easily
reconfigure networks as requirements change. Recent research has extended this
concept to IEEE 802.15.4 low-power wireless networks, which form a key
component of the Internet of Things (IoT). However, the multiple traffic
patterns necessary for SDN control makes it difficult to apply this approach to
these highly challenging environments. This paper presents Atomic-SDN, a highly
reliable and low-latency solution for SDN in low-power wireless. Atomic-SDN
introduces a novel Synchronous Flooding (SF) architecture capable of
dynamically configuring SF protocols to satisfy complex SDN control
requirements, and draws from the authors' previous experiences in the IEEE EWSN
Dependability Competition: where SF solutions have consistently outperformed
other entries. Using this approach, Atomic-SDN presents considerable
performance gains over other SDN implementations for low-power IoT networks. We
evaluate Atomic-SDN through simulation and experimentation, and show how
utilizing SF techniques provides latency and reliability guarantees to SDN
control operations as the local mesh scales. We compare Atomic-SDN against
other SDN implementations based on the IEEE 802.15.4 network stack, and
establish that Atomic-SDN improves SDN control by orders-of-magnitude across
latency, reliability, and energy-efficiency metrics
Toward incremental FIB aggregation with quick selections (FAQS)
Several approaches to mitigating the Forwarding Information Base (FIB)
overflow problem were developed and software solutions using FIB aggregation
are of particular interest. One of the greatest concerns to deploy these
algorithms to real networks is their high running time and heavy computational
overhead to handle thousands of FIB updates every second. In this work, we
manage to use a single tree traversal to implement faster aggregation and
update handling algorithm with much lower memory footprint than other existing
work. We utilize 6-year realistic IPv4 and IPv6 routing tables from 2011 to
2016 to evaluate the performance of our algorithm with various metrics. To the
best of our knowledge, it is the first time that IPv6 FIB aggregation has been
performed. Our new solution is 2.53 and 1.75 times as fast as
the-state-of-the-art FIB aggregation algorithm for IPv4 and IPv6 FIBs,
respectively, while achieving a near-optimal FIB aggregation ratio
GPU Accelerated protocol analysis for large and long-term traffic traces
This thesis describes the design and implementation of GPF+, a complete general packet classification system developed using Nvidia CUDA for Compute Capability 3.5+ GPUs. This system was developed with the aim of accelerating the analysis of arbitrary network protocols within network traffic traces using inexpensive, massively parallel commodity hardware. GPF+ and its supporting components are specifically intended to support the processing of large, long-term network packet traces such as those produced by network telescopes, which are currently difficult and time consuming to analyse. The GPF+ classifier is based on prior research in the field, which produced a prototype classifier called GPF, targeted at Compute Capability 1.3 GPUs. GPF+ greatly extends the GPF model, improving runtime flexibility and scalability, whilst maintaining high execution efficiency. GPF+ incorporates a compact, lightweight registerbased state machine that supports massively-parallel, multi-match filter predicate evaluation, as well as efficient arbitrary field extraction. GPF+ tracks packet composition during execution, and adjusts processing at runtime to avoid redundant memory transactions and unnecessary computation through warp-voting. GPF+ additionally incorporates a 128-bit in-thread cache, accelerated through register shuffling, to accelerate access to packet data in slow GPU global memory. GPF+ uses a high-level DSL to simplify protocol and filter creation, whilst better facilitating protocol reuse. The system is supported by a pipeline of multi-threaded high-performance host components, which communicate asynchronously through 0MQ messaging middleware to buffer, index, and dispatch packet data on the host system. The system was evaluated using high-end Kepler (Nvidia GTX Titan) and entry level Maxwell (Nvidia GTX 750) GPUs. The results of this evaluation showed high system performance, limited only by device side IO (600MBps) in all tests. GPF+ maintained high occupancy and device utilisation in all tests, without significant serialisation, and showed improved scaling to more complex filter sets. Results were used to visualise captures of up to 160 GB in seconds, and to extract and pre-filter captures small enough to be easily analysed in applications such as Wireshark
Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions
Traditional power grids are being transformed into Smart Grids (SGs) to
address the issues in existing power system due to uni-directional information
flow, energy wastage, growing energy demand, reliability and security. SGs
offer bi-directional energy flow between service providers and consumers,
involving power generation, transmission, distribution and utilization systems.
SGs employ various devices for the monitoring, analysis and control of the
grid, deployed at power plants, distribution centers and in consumers' premises
in a very large number. Hence, an SG requires connectivity, automation and the
tracking of such devices. This is achieved with the help of Internet of Things
(IoT). IoT helps SG systems to support various network functions throughout the
generation, transmission, distribution and consumption of energy by
incorporating IoT devices (such as sensors, actuators and smart meters), as
well as by providing the connectivity, automation and tracking for such
devices. In this paper, we provide a comprehensive survey on IoT-aided SG
systems, which includes the existing architectures, applications and prototypes
of IoT-aided SG systems. This survey also highlights the open issues,
challenges and future research directions for IoT-aided SG systems
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