sensor network overview taekyoung kwon [email protected]
TRANSCRIPT
For starters
• The problems of engineering education– Problem solving– English– Communication skills
For starters
• What you can achieve by taking this course– Problem solving
• Problem definition– Topics in the wireless/sensor network
• Idea• Verify/evaluate
– sensor network • Ubiquitous computing• standardization
Evolution (size and number)
Confluence of technologies
Ubiquitous computing
• 21st century computers– Embedded in our world (ubiquitous, pervasive)
• They weave themselves into the fabric of everyday life until they are indistinguishable from it
[Mark Weiser, 1991]• The anti-thesis of “virtual reality”• Like motor technology, embedding computers
everywhere and having them “disappear in the background” is easy
Wired vs. wireless
• Bandwidth
• Reliability
• CSMA/CD vs CSMA/CA
Wireless networks
• Wireless network ad hoc network
• Ad hoc network sensor network?
• Wireless WAN: Cellular
• Wireless MAN: IEEE 802.16
• Wireless LAN: IEEE 802.11 series
• Wireless PAN: IEEE 802.15 family
What is sensor?
• Sensor: a transducer that converts a physical, chemical, or biological parameter into an electrical signal
• Actuator: a transducer that accepts an electrical signal and converts it into a physical, chemical, or biological action
• Transducer: a device converting energy from one domain into another. The device may either be a sensor or an actuator
Sensor network
• Tens of thousand nodes– Densely deployed
Internet, Internet, Satellite, Satellite, etcetc
Sink
Sink
TaskManager
Sensor node hardware
Power UnitPower Unit
Sensor ADCProcessorProcessor
MemoryMemoryTransceiverTransceiver
Location Finding SystemLocation Finding System MobilizerMobilizer• Small
• Low power
• Low bit rate
• High density
• Low cost (dispensable)
• Autonomous
• Adaptive
Sensor network• Power constraint
– Battery powered mains powered– Energy harvest
• Light(solar), vibration, temperature
• Tradeoff between energy and QoS– Prolong network lifetime by sacrificing application
requirements• Delay, throughput, reliability, data fidelity,…
– Still QoS is attractive• Deterministic or probabilistic bound
Sensor network• Traffic type: streaming, periodic, event• Low cost, Low bit rate, low duty cycle• IEEE 802.15.4: 250Kbps
Application LayerApplication Layer
Transport LayerTransport Layer
Network LayerNetwork Layer
Data Link LayerData Link Layer
Physical LayerPhysical Layer
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Ad hoc vs. sensor• Number of sensor nodes can be several orders of
magnitude higher• Sensor nodes are densely deployed and are prone to
failures• The topology of a sensor network changes very
frequently due to node mobility and node failure• May leverage broadcasting than point-to-point
communications• May operate in aggregate fashion• In-network processing• Sensor nodes are limited in power, computational
capacities, and memory• May not have global ID like IP address• Need tight integration with sensing tasks
Design issues• Fault tolerance
– Battlefield application
• Scalability– Node density: (NR^2)/A (transmission)
• Production costs• Hardware constraints• Topology
– Deployment phase– Post-deployment phase
• Environment• Transmission media: ISM, IR• Power consumption: sensing, processing,
communication
PHY layer
• Sync• Self-organization
– Beacon scheduling (periodic)
• Directional/smart antenna• Ultra-wideband (UWB)• Transmit-only device
– pros: cost, energy– Cons: uncontrollable, communications/networking
overhead
MAC layer• TDMA vs. CSMA
– TDMA: inter-cluster, scalability– CSMA: idle listening, overhearing
• Sleep cycle• Coordination
– Spatial correlation– Clustering (MAC vs NWK)
• Additional control channel– FDMA or TDMA
• Location awareness– Exposed terminal problem
network layer
• Attribute-based addressing– Information-centric delivery
• Routing– Route discovery
• Data aggregation/coordination• Location awareness
– Directional antenna (AOA)– UWB (distance measure via signal flight time)– GPS
routing
• Route discovery (AODV, DSR,…)– Route selection metric: hop count– Metric can be generalized to cost
• Hierarchical tree routing
• Gradient routing: data broadcasting
Transport layer
• Goodput decreases drastically as the offered traffic exceeds the network capacity
• Flow control vs. Congestion control– open loop vs closed loop– Proactive vs. reactive
Transport layer
• Reliability concept should be relaxed– Event-to-sink reliability
• Not all event-sensing nodes need to report• N reception among M transmission might be
OK (M > N)
• Hop-by-hop approaches
Middleware/Language/Appl.
• query/advertisement – Publish/subscribe
• nesC, Mate, SQTL – Declarative rather than procedural– TEDS (IEEE 1451)
Some of the commercial applications
– Industrial automation (process control)
– Defense (unattended sensors, real-time monitoring)
– Utilities (automated meter reading),
– Weather prediction
– Security (environment, building etc.)
– Building automation (HVAC controllers).
– Disaster relief operations
– Medical and health monitoring and instrumentation
What to consider: application requirements
• Energy-saving• QoS
– Throughput/Goodput– Reliability– timeliness
• Traffic/application scenario– Amdahl’s law– Every possible case
• Self-organization
What to consider: enabling technologies
• Directional (smart, MIMO) antenna– Multi-hop reachability– AoA– Hidden node problem
• Heterogeneous node type– E.g., Transmit-only device
• GPS: too costly• UWB (distance measurement)
– Location aware
• Energy harvesting device• Additional (separate) control channel
Possible approaches• Conservative vs. aggressive• Pessimistic vs. opportunistic vs. optimistic• Proactive (a priori) vs reactive (on demand)• Information amount vs. performance (better
control/decision)– History– Neighbors within some hops
• Deterministic (e.g. threshold) vs. probabilistic– N * p = 1?
• Reservation vs. random access• Heterogeneous functionalities
– E.g, cluster head, member
Possible enhancements:
• Flexibility vs. efficient – adaptivity
• Stability vs. throughput (utilization)– Goodput
• Reliable vs. fault-tolerant vs. error-resilient vs. robust
• fairness• Legacy-system support, standard-compliant,
backward compatibility
Final goal
• Tradeoff
• Quantitative trend
• Qualitative feature
• How to verify?– Analysis– Simulation – Implementation
analysis
• assumptions
• Whole system vs key element
• Steady state probability
• Upper/lower bound
• Worst/average case
• Complexity: O()– Temporal vs. spatial
Simulation
• Arbitrary level of detail
• Still too many ambiguities– Follow the norm, other reference
• How to emphasize the strength?
• Also show the weakness
Implementation
• Most time and energy consuming
• Good luck!
Leverage other techniques
• Algorithm • Combination theory• AI
– e.g., self-learning
• Operations Research– optimization
• Network Flow, scheduling theory• Probability
– Queuing theory
Let’s make team!