441 research outputs found
Packet Transactions: High-level Programming for Line-Rate Switches
Many algorithms for congestion control, scheduling, network measurement,
active queue management, security, and load balancing require custom processing
of packets as they traverse the data plane of a network switch. To run at line
rate, these data-plane algorithms must be in hardware. With today's switch
hardware, algorithms cannot be changed, nor new algorithms installed, after a
switch has been built.
This paper shows how to program data-plane algorithms in a high-level
language and compile those programs into low-level microcode that can run on
emerging programmable line-rate switching chipsets. The key challenge is that
these algorithms create and modify algorithmic state. The key idea to achieve
line-rate programmability for stateful algorithms is the notion of a packet
transaction : a sequential code block that is atomic and isolated from other
such code blocks. We have developed this idea in Domino, a C-like imperative
language to express data-plane algorithms. We show with many examples that
Domino provides a convenient and natural way to express sophisticated
data-plane algorithms, and show that these algorithms can be run at line rate
with modest estimated die-area overhead.Comment: 16 page
Accessing wireless sensor networks via dynamically reconfigurable interaction models
The Wireless Sensor Networks (WSNs) technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce. Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs.publishersversionpublishe
Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models
The Wireless Sensor Networks (WSNs) technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce.
Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs
A Complementary Resistive Switch-based Crossbar Array Adder
Redox-based resistive switching devices (ReRAM) are an emerging class of
non-volatile storage elements suited for nanoscale memory applications. In
terms of logic operations, ReRAM devices were suggested to be used as
programmable interconnects, large-scale look-up tables or for sequential logic
operations. However, without additional selector devices these approaches are
not suited for use in large scale nanocrossbar memory arrays, which is the
preferred architecture for ReRAM devices due to the minimum area consumption.
To overcome this issue for the sequential logic approach, we recently
introduced a novel concept, which is suited for passive crossbar arrays using
complementary resistive switches (CRSs). CRS cells offer two high resistive
storage states, and thus, parasitic sneak currents are efficiently avoided.
However, until now the CRS-based logic-in-memory approach was only shown to be
able to perform basic Boolean logic operations using a single CRS cell. In this
paper, we introduce two multi-bit adder schemes using the CRS-based
logic-in-memory approach. We proof the concepts by means of SPICE simulations
using a dynamical memristive device model of a ReRAM cell. Finally, we show the
advantages of our novel adder concept in terms of step count and number of
devices in comparison to a recently published adder approach, which applies the
conventional ReRAM-based sequential logic concept introduced by Borghetti et
al.Comment: 12 pages, accepted for IEEE Journal on Emerging and Selected Topics
in Circuits and Systems (JETCAS), issue on Computing in Emerging Technologie
Low-power emerging memristive designs towards secure hardware systems for applications in internet of things
Emerging memristive devices offer enormous advantages for applications such as non-volatile memories and in-memory computing (IMC), but there is a rising interest in using memristive technologies for security applications in the era of internet of things (IoT). In this review article, for achieving secure hardware systems in IoT, low-power design techniques based on emerging memristive technology for hardware security primitives/systems are presented. By reviewing the state-of-the-art in three highlighted memristive application areas, i.e. memristive non-volatile memory, memristive reconfigurable logic computing and memristive artificial intelligent computing, their application-level impacts on the novel implementations of secret key generation, crypto functions and machine learning attacks are explored, respectively. For the low-power security applications in IoT, it is essential to understand how to best realize cryptographic circuitry using memristive circuitries, and to assess the implications of memristive crypto implementations on security and to develop novel computing paradigms that will enhance their security. This review article aims to help researchers to explore security solutions, to analyze new possible threats and to develop corresponding protections for the secure hardware systems based on low-cost memristive circuit designs
Flexibility Support for Homecare Applications Based on Models and Multi-Agent Technology
In developed countries, public health systems are under pressure due to the increasing percentage of population over 65. In this context, homecare based on ambient intelligence technology seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and help optimize medical resources. Thus, current technological developments make it possible to build complex homecare applications that demand, among others, flexibility mechanisms for being able to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node failure (availability). The solution proposed in this paper copes with these flexibility requirements through the whole life-cycle of the target applications: from design phase to runtime. The proposed domain modeling approach allows medical staff to design customized applications, taking into account the adaptability needs. It also guides software developers during system implementation. The application execution is managed by a multi-agent based middleware, making it possible to meet adaptation requirements, assuring at the same time the availability of the system even for stateful applications.This work was financed in part by the University of the Basque Country (UPV/EHU) under project UFI 11/28, by the Regional Government of the Basque Country under Project IT719-13, and by the MCYT&FEDER under project DPI 2012-37806-C02-01
Memristive Computing
Memristive computing refers to the utilization of the memristor, the fourth
fundamental passive circuit element, in computational tasks.
The existence of the memristor was theoretically predicted in 1971 by
Leon O. Chua, but experimentally validated only in 2008 by HP Labs. A
memristor is essentially a nonvolatile nanoscale programmable resistor —
indeed, memory resistor — whose resistance, or memristance to be precise,
is changed by applying a voltage across, or current through, the device.
Memristive computing is a new area of research, and many of its fundamental
questions still remain open. For example, it is yet unclear which
applications would benefit the most from the inherent nonlinear dynamics
of memristors. In any case, these dynamics should be exploited to allow
memristors to perform computation in a natural way instead of attempting
to emulate existing technologies such as CMOS logic. Examples of such
methods of computation presented in this thesis are memristive stateful logic
operations, memristive multiplication based on the translinear principle, and
the exploitation of nonlinear dynamics to construct chaotic memristive circuits.
This thesis considers memristive computing at various levels of abstraction.
The first part of the thesis analyses the physical properties and the
current-voltage behaviour of a single device. The middle part presents memristor
programming methods, and describes microcircuits for logic and analog
operations. The final chapters discuss memristive computing in largescale
applications. In particular, cellular neural networks, and associative
memory architectures are proposed as applications that significantly benefit
from memristive implementation. The work presents several new results on
memristor modeling and programming, memristive logic, analog arithmetic
operations on memristors, and applications of memristors.
The main conclusion of this thesis is that memristive computing will
be advantageous in large-scale, highly parallel mixed-mode processing architectures.
This can be justified by the following two arguments. First,
since processing can be performed directly within memristive memory architectures,
the required circuitry, processing time, and possibly also power
consumption can be reduced compared to a conventional CMOS implementation.
Second, intrachip communication can be naturally implemented by
a memristive crossbar structure.Siirretty Doriast
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