1,460 research outputs found
A Hypothesis for Ad-Hoc Routing Algorithm Improvement
In this article, a new approach to reducing the complexity of routing algorithms is discussed to improve routing in ad hoc networks. To avoid duplicating the routing process for each data transfer, nodes create binary matrices for each base station and update them when the routing is complete. Routing may be made much simpler using the method given here
A Taxonomy of Self-configuring Service Discovery Systems
We analyze the fundamental concepts and issues in service
discovery. This analysis places service discovery in the context of distributed
systems by describing service discovery as a third generation
naming system. We also describe the essential architectures and the
functionalities in service discovery. We then proceed to show how service
discovery fits into a system, by characterizing operational aspects.
Subsequently, we describe how existing state of the art performs service
discovery, in relation to the operational aspects and functionalities, and
identify areas for improvement
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 framework for proving the self-organization of dynamic systems
This paper aims at providing a rigorous definition of self- organization, one
of the most desired properties for dynamic systems (e.g., peer-to-peer systems,
sensor networks, cooperative robotics, or ad-hoc networks). We characterize
different classes of self-organization through liveness and safety properties
that both capture information re- garding the system entropy. We illustrate
these classes through study cases. The first ones are two representative P2P
overlays (CAN and Pas- try) and the others are specific implementations of
\Omega (the leader oracle) and one-shot query abstractions for dynamic
settings. Our study aims at understanding the limits and respective power of
existing self-organized protocols and lays the basis of designing robust
algorithm for dynamic systems
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