1,532 research outputs found
Fault-tolerant sub-lithographic design with rollback recovery
Shrinking feature sizes and energy levels coupled with high clock rates and decreasing node capacitance lead us into a regime where transient errors in logic cannot be ignored. Consequently, several recent studies have focused on feed-forward spatial redundancy techniques to combat these high transient fault rates. To complement these studies, we analyze fine-grained rollback techniques and show that they can offer lower spatial redundancy factors with no significant impact on system performance for fault rates up to one fault per device per ten million cycles of operation (Pf = 10^-7) in systems with 10^12 susceptible devices. Further, we concretely demonstrate these claims on nanowire-based programmable logic arrays. Despite expensive rollback buffers and general-purpose, conservative analysis, we show the area overhead factor of our technique is roughly an order of magnitude lower than a gate level feed-forward redundancy scheme
Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence
IEEE Access
Volume 3, 2015, Article number 7217798, Pages 1512-1530
Open Access
Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article)
Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc
a Department of Information Engineering, University of Padua, Padua, Italy
b Department of General Psychology, University of Padua, Padua, Italy
c IRCCS San Camillo Foundation, Venice-Lido, Italy
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Abstract
In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network
A Gossip-based optimistic replication for efficient delay-sensitive streaming using an interactive middleware support system
While sharing resources the efficiency is substantially degraded as a result
of the scarceness of availability of the requested resources in a multiclient
support manner. These resources are often aggravated by many factors like the
temporal constraints for availability or node flooding by the requested
replicated file chunks. Thus replicated file chunks should be efficiently
disseminated in order to enable resource availability on-demand by the mobile
users. This work considers a cross layered middleware support system for
efficient delay-sensitive streaming by using each device's connectivity and
social interactions in a cross layered manner. The collaborative streaming is
achieved through the epidemically replicated file chunk policy which uses a
transition-based approach of a chained model of an infectious disease with
susceptible, infected, recovered and death states. The Gossip-based stateful
model enforces the mobile nodes whether to host a file chunk or not or, when no
longer a chunk is needed, to purge it. The proposed model is thoroughly
evaluated through experimental simulation taking measures for the effective
throughput Eff as a function of the packet loss parameter in contrast with the
effectiveness of the replication Gossip-based policy.Comment: IEEE Systems Journal 201
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