1 sensor networks and networked societies of artifacts jose rolim university of geneva
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Sensor Networks and Networked Societies of Artifacts
Jose RolimUniversity of Geneva
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Why sensor networks?
Invisible, everywhere computing Invisible computing:
• Tiny• Embedded• Attached …
Everywhere computing:• Wireless• Dynamic Configurable• Remote Access• Adapting …
Sensor Networks seems to be the typical example
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Definition
“Sensor networks are collections of wirelessly interconnected devices with sensing, computing and communication infrastructure that allow us to instrument, observe, and respond to phenomena in the natural environment and physical infrastructure.”
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Some Goals of Pervasive Computing
Invisible technology Integration of virtual and physical
worlds throughout desks, rooms, building, life, society Take the data out of the information,
leaving just an enhanced ability to act
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Situated Networking
Makes use of simple shared context: Space Time Proximity
Participation in the context: Physical Out here with us Many small and large places
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Difficulties of Pervasive Networking
Network explosion Impossibility of a centralized
management Network heterogeneity (not only
sensors but also laptops, servers, etc ..)
The use of adapted standard theoretical models, algorithms and protocols is impossible
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Why the Standard Approaches Fail
At the modeling level (ex: limited energy)
At the networking level (ex: scalability)
At the management level (ex: radically distributed)
At the service level (ex: situated nature)
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Our aim:
A communication system supporting millions of localized services in an networked society consisting of billions of heterogeneous nodes, intermittently connected and invisible
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Issues for sensor networking -1
Technology independent models of sensor networking
Dynamic models of sensor distributed computing
Self-organization in sensor networks Distributed cost sharing mechanisms Energy management, balancing and
complexity formulation Models of collaboration and competition for
resources
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Issues for sensor networking -2
Nature inspired control and adaptation mechanisms
Global impact of the local sensor interactions
Models of ad-hoc deployment Efficient approach to mobility
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Issues for sensor networking -3
Energy aware algorithms and protocols for: Self configuration, reconfiguration and
localization of sensors Long vs short range algorithms Resilience and robustness mechanisms Pervasive communication for routing,
interference and congestion control Achievement of global tasks via local,
event driven interactions
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How to tackle these issues?
Techniques from TCS Techniques from Game Theory Techniques from Natural Computing Techniques from Networking
Information Theory Techniques from Distributed
Computing Most importantly: integration among
those techniques
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Techniques from TCS
Examples:
Extended Random Graphs Models Geometric Approaches Probabilistic Algorithms Markov Chains
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Techniques from Game Theory
Examples: Nash Equilibrium Game Theoretic Methods for Enforcing
Cooperation Security Issues Evolutionary Game Theory Reputation Systems
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Techniques from Natural Computing
Examples: Adaptation by evolution Learning from experience Evolutionary genetics Biological networks Complex ecosystems Swarm intelligence
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Techniques from Distributed Computing
Examples: Approximate counting Randomized methods with noisy
information Manets mechanisms- mobility Obstacle avoidance Power saving schemes
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Example
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Example 2
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Ex
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Energy cost: Square of distance
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The Problem
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A distributed algorithm
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Illustration
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Stability
Markov Chain
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Mix of techniques
Theory Game Natural computing Network information Distributed computing Mix