BIONETS: Bio-Inspired Networking for Pervasive Communication Environments

Carreras, Iacopo; Chlamtac, I.; Pellegrini, Francesco De; Miorandi, Daniele

doi:10.1109/tvt.2006.883762

Cited by 48 publications

(23 citation statements)

References 20 publications

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“…Packets are routed under the probabilistic guidance of the learned pheromone tables. In the BIONETS project [7,17], bioinspired techniques are used for autonomic self-evolving network services in an environment of a huge number of low-cost sensors nodes with heterogeneous capabilities and mobility. BIONETS considers evolutionary paradigms to drive the adaptation process of autonomic services (e.g., natural selection), and social paradigms for the provisioning of the necessary cooperation mechanisms.…”

Section: Simulation Resultsmentioning

confidence: 99%

Bio-inspired multi-agent data harvesting in a proactive urban monitoring environment

Lee¹,

Magistretti

Gerla³

et al. 2009

Ad Hoc Networks

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Section: Simulation Resultsmentioning

confidence: 99%

Bio-inspired multi-agent data harvesting in a proactive urban monitoring environment

Lee¹,

Magistretti

Gerla³

et al. 2009

Ad Hoc Networks

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“…No traditional routing protocol is used by either type of node, they do not even have a notion of addressing. The group has also developed a theoretical model of their system to show its feasibility for effective data transport under high-mobility conditions [78].…”

Section: Bionetsmentioning

confidence: 99%

A taxonomy of biologically inspired research in computer networking

2010

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a b s t r a c tThe natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the inherent challenges of surviving in such a world, biological organisms evolve, self-organize, self-repair, navigate, and flourish. Generally, they do so with only local knowledge and without any centralized control. Our computer networks are increasingly facing similar challenges as they grow larger in size, but are yet to be able to achieve the same level of robustness and adaptability. Many research efforts have recognized these parallels, and wondered if there are some lessons to be learned from biological systems. As a result, biologically inspired research in computer networking is a quickly growing field. This article begins by exploring why biology and computer network research are such a natural match. We then present a broad overview of biologically inspired research, grouped by topic, and classified in two ways: by the biological field that inspired each topic, and by the area of networking in which the topic lies. In each case, we elucidate how biological concepts have been most successfully applied. In aggregate, we conclude that research efforts are most successful when they separate biological design from biological implementation -that is to say, when they extract the pertinent principles from the former without imposing the limitations of the latter.

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“…1 left). A number of approaches exist for coordinated emergence of sensing networks [2,15,3,10] and autonomous composition [14,24] and evolution [21,5,20] of services. Autonomous self-organization according to the sensing mission results in a goal-oriented sensing ensemble providing the relevant information to the mobile system from wearable or ambient sensors.…”

Section: Opportunistic Sensingmentioning

confidence: 99%

OPPORTUNITY: Towards opportunistic activity and context recognition systems

Roggen

Förster

Calatroni

et al. 2009

2009 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks &Amp; Workshops

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Opportunistic sensing allows to efficiently collect information about the physical world and the persons behaving in it. This may mainstream human context and activity recognition in wearable and pervasive computing by removing requirements for a specific deployed infrastructure. In this paper we introduce the newly started European research project OPPORTUNITY within which we develop mobile opportunistic activity and context recognition systems. We outline the project's objective, the approach we follow along opportunistic sensing, data processing and interpretation, and autonomous adaptation and evolution to environmental and user changes, and we outline preliminary results.

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BIONETS: Bio-Inspired Networking for Pervasive Communication Environments

Cited by 48 publications

References 20 publications

Bio-inspired multi-agent data harvesting in a proactive urban monitoring environment

Bio-inspired multi-agent data harvesting in a proactive urban monitoring environment

A taxonomy of biologically inspired research in computer networking

OPPORTUNITY: Towards opportunistic activity and context recognition systems

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