Title: SENSOR NETWORKS
1(No Transcript)
2SENSOR NETWORKS ARCHITECTURE
- Several thousand nodes
- Nodes are tens of feet of each other
- Densities as high as 20 nodes/m3
- I.F.Akyildiz, W.Su, Y. Sankarasubramaniam, E.
Cayirci, - Wireless Sensor Networks A Survey, Computer
Networks (Elsevier) Journal, March 2002.
3SENSOR NODE HARDWARE
- Small
- Low power
- Low bit rate
- High density
- Low cost (dispensable)
- Autonomous
- Adaptive
SENSING UNIT
PROCESSING UNIT
4MICA MotesBWN Lab _at_ GaTech
Processor/Radio Board MPR300CB
Speed 4 MHz
Flash 128K bytes
SRAM 4K bytes
EEPROM 4K bytes
Radio Frequency 916MHz or 433MHz (ISM Bands)
Data Rate 40 Kbits/Sec (Max)
Power 0.75 mW
Radio Range 100 feet (prog.)
Power 2 x AA batteries
Processor and Radio platform (MPR300CB) is based
on Atmel ATmega 128L low power Microcontroller
that runs TinyOs operating system from its
internal flash memory.
5 Examples for Sensor Nodes
6Examples for Sensor Nodes
7SENSOR NETWORKS FEATURES
- APPLICATIONS
- Military, Environmental, Health, Home,
Space Exploration, - Chemical Processing, Disaster Relief.
- SENSOR TYPES
- Seismic, Low Sampling Rate Magnetic,
Thermal, Visual, Infrared, - Acoustic, Radar
- SENSOR TASKS
- Temperature, Humidity, Vehicular, Movement,
Lightning Condition, - Pressure, Soil Makeup, Noise Levels,
Presence or Absence of Certain - Types of Objects, Mechanical Stress Levels
on Attached Objects, - Current Characteristics (Speed, Direction,
Size) of an Object .
8Factors Influencing Sensor Network Design
A. Fault Tolerance (Reliability) B.
Scalability C. Production Costs D. Hardware
Constraints E. Sensor Network Topology F.
Operating Environment G. Transmission Media H.
Power Consumption
9Sensor Networks Communication Architecture
- Used by sink and all sensor nodes
- Combines power and routing awareness
- Integrates data with networking protocols
- Communicates power efficiently through
- wireless medium and
- Promotes cooperative efforts.
10WHY CANT AD-HOC NETWORK PROTOCOLS BE USED HERE?
- 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 - Sensor nodes are limited in power, computational
capacities, and memory - May not have global ID like IP address.
- Need tight integration with sensing tasks.
11APPLICATON LAYER SMP Sensor Managament Protocol
- System Administrators interact with Sensors using
SMP. - TASKS
- Moving the sensor nodes
- Turning sensors on and off
- Querying the sensor network configuration and
the status of - nodes and re-configuring the sensor network
- Authentication, key distribution and security in
data - communication
- Time-synchronization of the sensor nodes
- Exchanging data related to the location finding
algorithms - Introducing the rules related to data
aggregation, - attribute-based naming and clustering to
the sensor nodes
12APPLICATON LAYER (Query Processing)
Users can request data from the network-gt
Efficient Query Processing User Query Types 1.
HISTORICAL QUERIES Used for analysis of
historical data stored in a storage area (PC),
e.g., what was the temperature 2 hours back in
the NW quadrant. 2. ONE TIME QUERIES
Gives a snapshot of the network, e.g., what is
the current temperature in the NW quadrant. 3.
PERSISTANT QUERIES Used to monitor the
network over a time interval with respect to some
parameters, e.g., report the temperature for the
next 2 hours.
13APPLICATON LAYER
- Sensor Query and Tasking Language (SQTL)
- (C-C Shen, et.al., Sensor Information Networking
Architecture and Applications, IEEE Personal
Communications Magazine, pp. 52-59, August
2001.) - SQTL is a procedural scripting language.
- It provides interfaces to access sensor
hardware - - getTemperature, turnOn
- for location awareness
- - isNeighbor, getPosition
- and for communication
- - tell, execute.
14APPLICATON LAYER
- Sensor Query and Tasking Language (SQTL)
- By using the upon command, a programmer can
create an event handling block for three types of
events - - Events generated when a message is received by
a sensor node, - - Events triggered periodically,
- - Events caused by the expiration of a timer.
- These types of events are defined by SQTL
keywords receive, every and expire, respectively.
15Simple Abtract Querying Example
Select task, time, location, distinct all,
amplitude, avg min max count
sum (amplitude) from any , every ,
aggregate m where power available ltgt PA
location in not in RECT
tmin lt time lt tmax task t
amplitude ltgt a group by
task based on time limit lt packet limit
lp resolution r region
xy
16Data Centric Query
- Attribute-based naming architecture
- Data centric protocol
- Observer sends a query and gets the response from
valid sensor node - No global ID
17APPLICATON LAYER Task Assignment and Data
Advertisement Protocol
- INTEREST DISSEMINATION
- Users send their interest to a sensor
node, - a subset of the nodes or the entire
network. - This interest may be about a certain
attribute - of the sensor field or a triggering
event. - ADVERTISEMENT OF AVAILABLE DATA
- Sensor nodes advertise the available data
to - the users and the users query the data
which - they are interested in.
18APPLICATON LAYER Sensor Query and Data
Dissemination Protocol
- Provides user applicatons with interfaces to
issue - queries, respond to queries and collect
incoming - replies.
- These queries are not issued to particular nodes,
instead - ATTRIBUTE BASED NAMING (QUERY)
- The locations of the nodes that sense
temperature - higher than 70F
- LOCATION BASED NAMING (QUERY)
- Temperatures read by the nodes in region A
19Interest Dissemination
- Interest dissemination is performed to assign
the sensing tasks to the sensor nodes. - Either sinks broadcast the interest or sensor
nodes broadcast an advertisement for - the available data and wait for a request
from the sinks.
Sink
Query Sensor nodes that read gt70oF temperature
20 Data Aggregation (Data Fusion)
- The sink asks the sensor nodes to report certain
conditions. - Data coming from multiple sensor nodes are
aggregated.
71
75
Query Sensor nodes that read gt70oF temperature
21 Location Awareness (Attribute Based Naming)
- Query an Attribute
- of the sensor field
Region A
Sink
Region C
Region B
Query Temperatures read by the nodes in Region A
- Important for broadcasting,
- multicasting, geocasting and anycasting
22APPLICATON LAYER RESEARCH NEEDS
- Sensor Network Management Protocol
- Task Assignment and Data Advertisement Protocol
- Sensor Query and Data Dissemination Protocol
- Sophisticated GUI
- (Graphical User Interface) Tool
23TRANSPORT LAYERReliable Multi-Segment Transport
(RMST) F. Stann and J. Heidemann, RMST
Reliable Data Transport in Sensor Networks, In
Proc. IEEE SNPA03, May 2003, Anchorage, Alaska,
USA
- RMST provides end-to-end data-packet
- transfer reliability
- Each RMST node caches the packets
- When a packet is not received before the
- so-called WATCHDOG timer expires, a
- NAK is sent backward
- The first RMST node that has the required
- packet along the path retransmits the
- packet
- RMST relies on Directed Diffusion scheme
RMST Node
Source Node
24Transport Layer PSFQ - Pump Slowly Fetch
QuicklyC. Y. Wan, A. T. Campbell and L.
Krishnamurthy, PSFQ A Reliable Transport
Protocol for Wireless Sensor Networks, In Proc.
ACM WSNA02, September 2002, Atlanta, GA
- Packets are injected slowly into the network
- Aggressive hop-by-hop recovery in case of packet
losses - PUMP performs controlled flooding and requires
each intermediate node to create and maintain a
data cache to be used for local loss recovery and
in-sequence data delivery. - Applicable only to strict sensor-sensor
guaranteed delivery - And for control and management of the end-to-end
reliability for the downlink from sink to sensors - Does not address congestion control
25Related Work
- Wireless TCP variants are NOT suitable for sensor
networks - Different notion of end-to-end reliability
- Huge buffering requirements
- ACKing is energy draining
- BOTTOMLINE Traditional end-to-end guaranteed
reliability (TCP solutions) cannot be applied
here.
? New Reliability Notion is required!!!
26Reliable EVENT Transport in WSN
- NEW NOTION Reliably Detect/Estimate EVENT
features from COLLECTIVE information - Challenges
- Significant energy and processing constraints,
multi-hop ad hoc communication - Network congestion
Need to address Congestion Control and
Reliability in Sensor Networks !
27Event-to-Sink Reliability
O. B. Akan, I. F. Akyildiz, and Y.
Sankarasubramaniam, ESRTEvent-to-Sink Reliable
Transport in Wireless Sensor Networks, in
Proceedings of ACM MOBIHOC 2003, pp. 177-188,
Annapolis, Maryland, USA, June 2003. Also to
appear in IEEE/ACM Transactions on Networking,
2004.
- Sensor networks are event-driven
- Multiple correlated data flows from event to sink
- Goal is to reliably detect/estimate event
features from collective information - Necessitates event-to-sink collective reliability
notion
28Event-to-Sink Reliability
- Sink decides about event features every ? time
units - Observed event reliability Di , the DISTORTION
observed in event estimation in the decision
interval i at the sink - Desired event reliability D ,the desired event
estimation distortion level for reliable event
detection - Application specific, known a priori at the sink
- Normalized reliability ? ?i D/ Di
- Reporting rate f packet transmissions rate at
source nodes
29Network States
State Description Condition
(NC,LR) (No Congestion, Low reliability) f lt fmax and ? lt 1 - ?
(NC,HR) (No Congestion, High reliability) f ? fmax and ? gt 1 ?
(C,HR) (Congestion, High reliability) f gt fmax and ? gt 1
(C,LR) (Congestion, Low reliability) f gt fmax and ? ? 1
OOR Optimal Operating Region f lt fmax and ? ? 1- ?, 1 ?
30ESRTProtocol Overview
- Determine reporting frequency f to achieve
desired reliability D with minimum resource
utilization - Source (Sensor nodes)
- Send data with reporting frequency f
- Monitor buffer level and notify congestion to the
sink - Sink
- Measures the observed event reliability Di at the
end of decision interval i - Performs congestion decision based on the
feedback from - the sources nodes (to determine f gtlt fmax).
- Updates f based on ?i D/ Di and f gtlt fmax
(congestion) to achieve desired event reliability
D
31ESRT Congestion Detection Mechanism
- ACK/NACK not suitable
- We use local buffer level monitoring in sensor
nodes
bk Buffer fullness level at the end of
reporting interval k Db Buffer length
increment B Buffer size f reporting
frequency
- Mark CN field in packet if congested
32ESRT OperationFrequency Update
State Frequency Update Comments
(NC,LR) fi1 fi / ?i Multiplicative increase, achieve desired reliability asap
(NC,HR) fi1 fi (?i 1) / 2?i Conservative decrease, no compromise on reliability
(C,HR) fi1 fi / ?i Aggressive decrease to state (NC,HR)
(C,LR) fi1 fi ?i Exponential decrease, relieve congestion asap
OOR fi1 fi Unchanged
33ESRT Performance
S0 (NC,LR)
S0 (NC,HR)
S0 (C,HR)
S0 (C,LR)
34NETWORK LAYER (ROUTING? BASIC KNOWLEDGE)
The constraints to calculate the routes 1.
Additive Metrics Delay, hop count,
distance, assigned costs (sysadmin preference),
average queue length...2. Bottleneck
Metrics Bandwidth, residual capacity and
other bandwidth related metrics. REMARK All
routing algorithms are based on the same
principle used as in Dijkstra's, which is used
to find the minimum cost path from source to
destination. Dikstra and Bellman solve the
SHORTEST PATH PROBLEM RIP (Distant Vector
Algorithm) -gt Bellman/Ford Algorithm OSPF (Open
Shortest Path Algorithm) ? Dikstra Algorithm
35 Routing Algorithms Constraints Regarding Power
Efficiency (Energy Efficient Routing)
E (PA1)
F (PA4)
- Maximum power available (PA) route
- Minimum hop route
- Minimum energy route
- Maximum minimum PA node
- route (Route along which the
- minimum PA is larger than the
- minimum PAs of the other routes
- is preferred, e.g., Route 3 is the
- most efficient Route 1 is the
- second).
D (PA3)
T
Sink
A (PA2)
B (PA2)
C (PA2)
Route 1 Sink-A-B-T (PA4) Route 2 Sink-A-B-C-T
(PA6) Route 3 Sink-D-T (PA3) Route 4
Sink-E-F-T (PA5)
36Why cant we use conventional routing algorithms
here?
- Global (Unique) addresses, local addresses.
-
- Unique node addresses cannot be used in many
sensor networks - sheer number of nodes
- energy constraints
- data centric approach
- Node addressing is needed for
- node management
- sensor management
- querying
- data aggregation and fusion
- service discovery
- routing
37NETWORK LAYER (ROUTING for SENSOR NETWORKS)
- Important considerations
- Sensor networks are mostly data centric
- An ideal sensor network has attribute based
addressing and location awareness - Data aggregation is useful unless it does not
hinder collaborative effort - Power efficiency is always a key factor
38Some Concepts
- Data-Centric
- Node doesn't need an identity
- What is the temp at node 27 ?
- Data is named by attributes
- Where are the nodes whose temp recently exceeded
30 degrees ? - How many pedestrians do you observe in region X?
- Tell me in what direction that vehicle in region
Y is moving? - Application-Specific
- Nodes can perform application specific data
aggregation, caching and forwarding
39 Taxonomy of Routing Protocols for Sensor
Networks
Categorization of Routing Protocols for Wireless
Sensor Networks (K. Akkaya, M. Younis, A
Survey on Routing Protocols for Wireless Sensor
Networks, Elsevier AdHoc Networks, 2004) 1. Data
Centric Protocols Flooding, Gossiping, SPIN,
SAR (Sequential Assignment Routing) ,
Directed Diffusion, Rumor Routing, Gradient Based
Routing, Constrained Anisotropic Diffused
Routing, COUGAR, ACQUIRE 2. Hierarchical
LEACH, TEEN (Threshold Sensitive Energy Efficient
Sensor Network Protocol), APTEEN, PEGASIS,
Energy Aware Scheme 3. Location Based MECN,
SMECN (Small Minimum Energy Com Netw), GAF
(Geographic Adaptive Fidelity), GEAR
40Conventional ApproachFLOODING
Broadcast data to all neighbor nodes
41ROUTING ALGORITHMS Gossiping
GOSSIPING Sends data to one randomly selected
neighbor. Example
42Problems of Flooding and Gossiping
PROBLEMS Although these techniques are simple
and reactive, they have some disadvantages
including Implosion (NOTE
Gossiping avoids this by selecting only one node
but this causes delays to
propagate the data through the network)
Overlap Resource Blindness
Power (Energy) Inefficient
43Problems
Data Overlap
r
- Resource Blindness
- No knowledge about the available power of
resources
44Gossiping
- Uses randomization to save energy
- Selects a single node at random and sends the
data to it - Avoids implosions
- Distributes information slowly
- Energy dissipates slowly
45The Optimum Protocol
- Ideal
- Shortest-path routes
- Avoids overlap
- Minimum energy
- Need global topology information
46SPIN Sensor Protocol for Information via
Negotiation(W.R. Heinzelman, J. Kulik, and H.
Balakrishan, Adaptive Protocols for Information
Dissemination in Wireless Sensor Networks,
Proc. ACM MobiCom99, pp. 174-185, 1999 )
- Two basic ideas
- Sensors communicate with each other about the
data that they already have and the data they
still need to obtain - to conserve energy and operate efficiently
- exchanging data about sensor data may be cheap
- Sensors must monitor and adapt to changes
- in their own energy resources
47SPIN
- Good for disseminating information to all sensor
nodes. - SPIN is based on data-centric routing where the
sensors broadcast an - advertisement for the available data and wait
for a request from - interested sinks
1.
1. ADV 2. REQ 3. DATA
2.
3.
48 SPIN
49ROUTING ALGORITHM (DIRECTED DIFFUSION)
- (C. Intanagonwiwat, R. Gowindan and D. Estrin,
Directed Diffusion A Scalable and Robust - Communication Paradigm for Sensor Networks,
Proc. ACM MobiCom00, pp. 56-67, 2000.) - This is a DATA CENTRIC ROUTING scheme!!!!
- The idea aims at diffusing data through sensor
nodes by using - a naming scheme for the data.
- The main reason behind this is to get rid off
unnecessary - operation of routing schemes to save Energy.
- Also Robustness and Scaling requirements need
to be considered.
50Directed Diffusion
Source
Sink
51Directed Diffusion
Features
- Sink sends interest, i.e., task descriptor, to
all sensor nodes. - Interest is named by assigning attribute-value
pairs.
source
source
sink
sink
Interest Propagation
Gradient Setup
Data Delivery
Drawbacks
Cannot change interest unless a new interest is
broadcast.
52LEACH
- Low Energy Adaptive Clustering Hierarchy (LEACH)
- (W. R. Heinzelman, A. Chandrakasan, and H.
Balakrishnan, Energy-Efficient Communication
Protocol for Wireless Microsensor Networks,''
IEEE Proceedings of the Hawaii International
Conference on System Sciences, pp. 1-10, January,
2000.) - LEACH is a clustering based protocol which
minimizes energy dissipation - in sensor networks.
- Idea
- Randomly select sensor nodes as cluster
heads, so the high energy - dissipation in communicating with the
base station is spread to all sensor - nodes in the sensor network.
- Forming clusters is based on the received
signal strength. - Cluster heads can then be used kind of
routers (relays) to the sink. -
53LEACH
- Optimum Number of Clusters ---????????
- - too few nodes far from cluster heads
- too many many nodes send data to SINK.
-
54Other Protocols
1. Energy Aware Routing R. Shah, J. Rabaey,
Energy Aware Routing for Low Energy Ad Hoc
Sensor Networks, IEEE WCNC02, Orlando,
March 2002. 2. Rumor Routing D. Braginsky,
D. Estrin, Rumor Routing Algorithm for Sensor
Networks, ACM WSNA02, Atlanta, October
2002. 3. Threshold sensitive Energy Efficient
sensor Network (TEEN) A. Manjeshwar, D.P.
Agrawal, TEEN A Protocol for Enhanced
Efficiency in Wireless Sensor Networks,
IEEE WCNC02, Orlando, March 2002. 4.
Constrained Anisotropic Diffusion Routing (CADR)
M. Chu, H.Hausecker, F. Zhao, Scalable
Information-Driven Sensor Querying and
Routing for Ad Hoc Heterogeneous Sensor
Networks, International Journal of High
Performance Computing Applications, Vol. 16, No.
3, August 2002.
55Other Protocols
5. Power Efficient Gathering in Sensor
Information Systems (PEGASIS) S.
Lindsey, C.S. Raghavendra, PEGASIS Power
Efficient Gathering in Sensor Information
Systems, IEEE Aerospace Conference, Montana,
March 2002. 6. Self Organizing Protocol L.
Subramanian, R.H. Katz, An Architecture for
Building Self Configurable Systems,
IEEE/ACM Workshop on Mobile Ad Hoc Networking and
Computing, Boston, August 2000. 7.
Geographic Adaptive Fidelity (GAF) Y. Yu, J.
Heideman, D. Estrin, Geography-informed Energy
Conservation for Ad Hoc Routing, ACM
MobiCom01, Rome, July 2001.
56Open Research Issues
- Store and Forward Technique
- that combines data fusion and aggregation.
- Routing for Mobile Sensors
- Investigate multi-hop routing techniques for
- high mobility environments.
- Priority Routing
- Design routing techniques that allow different
priority - of data to be aggregated, fused, and relayed.
- 3D Routing
57Medium Access Control (MAC) in WSN
- IEEE 802.11 1
- Originally developed for WLANs
- Per-node fairness
- High energy consumption due to idle listening
- S-MAC 2
- Aims to decrease energy consumption by sleep
schedules with virtual clustering - Redundant data are still sent with increased
latency due to sleep schedules
1 IEEE 802.11, Wireless LAN Medium Access
Control (MAC) and Physical Layer (PHY)
Specifications, 1999 2 W. Ye, J. Heidemann and
D. Estrin, An Energy Efficient MAC Protocol for
Wireless Sensor Networks, In Proc. ACM MOBICOM
01, pp.221 235, Rome, Italy 2001
58Related Work
- TRAMA3
- Based on time-slotted structure
- Information about every two-hop neighbor is used
for slot selection - High signaling overhead for high density networks
- High latency due to time-slotted structure
3 V. Rajendran, K. Obraczka, and J. J.
Garcia-Luna-Aceves, Energy-Efficient,
Collision-Free Medium Access Control for Wireless
Sensor Networks, in Proc. ACM SenSys 2003, Los
Angeles, California, November 2003.
59MAC for Sensor Networks
- WSN are characterized by dense deployment of
sensor nodes - MAC Layer Challenges
- Limited power resources
- Need for a self-configurable, distributed
protocol - Data centric approach rather than per-node
fairness
Exploit spatial correlation to reduce
transmissions in MAC layer !
60Collaborative MAC (CMAC) Protocol
M.C. Vuran, and I. F. Akyildiz, Spatial
Correlation-based Collaborative Medium Access
Control in Wireless Sensor Networks, submitted
for publication, Nov. 2003.
- If a node transmits data then all its correlation
neighbors have redundant information - Route-thru data has higher priority over
generated data
Filter out transmission of redundant data and
prioritize filtered data through the network!
61Collaborative MAC (CMAC) Protocol
- Source function Transmit event information
- Router function Forward packets from other nodes
in the multi-hop path to the sink - Two components
- Event MAC (E-MAC)
- Network MAC
- (N-MAC)
62Node Selections
- Choose representative nodes such that
- They are located as close to the event source as
possible - They are located as farther apart from each other
as possible.
63CMAC Performance
Medium Access Delay
Packet Drop Rate
64CMAC Performance
Avg. Energy Consumption
65Conclusions
- Spatial correlation in sensor networks is
exploited on both Transport and MAC layers - Redundant transmissions are suppressed
- Number of transmissions are reduced instead of
number of transmitted bits - Both protocols achieve low energy consumption
66 Research Needs for Sensor Networks
- An Analytical Framework for Sensor Networks
- ? Find a Basic Generic Architecture and
Protocol - development which can be tailored to
specific - applications.
- More theoretical investigations of the
Architecture and - Protocol developments
- Follow the TCP/IP Stack, i.e., keep the Strict
Layer - Approach ???
- Cross Layer Optimization
- Explore both Spatial-Temporal Correlations for
- Protocol development
-
67FURTHER OPEN RESEARCH ISSUES
- Research to integrate WSN domain into NGWI (Next
Generation Wireless Internet) - e.g., interactions of Sensor and AdHoc
Networks or Sensor and Satellite or any other
combinations - Explore the SENSOR/ACTOR NETWORKS
- Explore the SENSOR-ANTISENSOR NETWORKS
68Need for Realistic Applications
- Clear Demonstration of Testbeds and Realistic
Applications - Not only data or audio but also video ?
- Overall I ? Integrated Traffic.
- SOME OF OUR EFFORTS IN BWN LAB _at_ GaTech
- MAN ? for Meteorological Observations
- SpINet ? for Mars Surface
- Airport Security ? Sensors/Actors
- Sensor Wars
- Wide Area Multi-Campus Sensor Network
69MEDIUM ACCESS CONTROL (MAC) FURTHER RESEARCH NEEDS
- MAC for sensor networks must have inbuilt power
- management, mobility management and
failure recovery - strategies
- Need for a self-configurable, distributed
protocols - Data centric approach rather than per-node
fairness - Develop MACs which differentiate Multimedia
Traffic - Exploit Spatial Temporal Correlation
-
70Error Control
- Some sensor network applications like mobile
tracking - require high data precision
- Coding gain is generally expressed in terms of
the additional - transmit power needed to obtain the same BER
without coding - FEC is preferred over ARQ
- Since power consumption is crucial, we must take
into - account encoding and decoding energy
expenditures - Coding is profitable only if the encoding and
decoding - power consumption is less than the coding
gain. -
71ERROR CONTROL RESEARCH NEEDS
- Design of suitable FEC codes with minimal
encoding - and relatively higher decoding complexities
- Feasibility of ARQ schemes in multihop sensor
networks - (hop by hop ARQ instead of end-to-end). This
is needed for - reliable communications (data critical)
- Adaptive/Hybrid FEC/ARQ schemes
- Extension to Rayleigh/Rician fading conditions
with mobile - nodes
72Optimal Packet Size for Wireless Sensor
NetworksY. Sankarasubramaniam, I. F. Akyildiz,
S. McLaughlin, Optimal Packet Size for Wireless
Sensor Networks, IEEE SNPA, May 2003.
- Determining the optimal packet size for sensor
networks is necessary to operate at high energy
efficiencies. - The multihop wireless channel and energy
consumption characteristics are the two most
important factors that influence choice of
packet size.
Trailer (FEC) (gt3)
Payload (lt73)
Header (2)
73PHYSICAL LAYER
- New Channel Models (I/O/Underwater/Deep Space)
- Explore Antennae Techniques
- (e.g., Smart Antennaes)
- Software Radios??
- New Modulation Schemes
- SYNCH Schemes
- FEC Schemes on the Bit Level
- New Data Encryption
- Investigate UWB
74FINAL REMARKS
75Basic Research Needs
- An Analytical Framework for Sensor Networks
- ? Find a Basic Generic Architecture and
Protocol - Development which can be tailored to specific
- applications.
-
- More theoretical investigations of the
- Architecture and Protocol
- developments
- Network Configuration and Planning Schemes
-
76FURTHER OPEN RESEARCH ISSUES
- Research to integrate WSN domain into NGWI (Next
Generation Wireless Internet) - e.g., interactions of Sensor and AdHoc
Networks or Sensor and Satellite or any other
combinations - Explore the SENSOR/ACTOR NETWORKS
- Explore the SENSOR-ANTISENSOR NETWORKS
- SECURITY ISSUES
77Some Applications
- Clear Demonstration of Testbeds and Realistic
Applications - Not only data or audio but also video as well
as integrated - traffic.
- SOME OF OUR EFFORTS IN BWN LAB _at_ GaTech
- MAN ? for Meteorological Observations
- SpINet ? for Mars Surface
- Airport Security ? Sensors/Actors
- Sensor Wars
- Wide Area Multi-campus Sensor Network
78FURTHER CHALLENGESProtocol Stack
- Follow the TCP/IP Stack, i.e., keep the
- Strict Layer Approach ???
-
- Or Interleave the Layer functionalities???
- Cross Layer Optimization
- Standardization???
-
79Commercial Viability of WSN Applications
- Within the next few years, distributed sensing
and computing will be everywhere, i.e., homes,
offices, factories, automobiles, shopping
centers, super-markets, farms, forests, rivers
and lakes. - Some of the immediate commercial applications of
wireless sensor networks are - 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
80Commercial Viability of WSN Applications
- XSILOGY Solutions is a company which provides
wireless sensor network solutions for various
commercial applications such as tank inventory
management, stream distribution systems,
commercial buildings, environmental monitoring,
homeland defense etc. - http//www.xsilogy.com/home/main/index.html
- In-Q-Tel provides distributed data collection
solutions with sensor network deployment. - http//www.in-q-tel.com/tech/dd.html
- ENSCO Inc. invests in wireless sensor networks
for meteorological applications. - http//www.ensco.com/products/homeland/msis/msis_
rnd.htm - EMBER provides wireless sensor network
solutions for industrial automation, defense, and
building automation. - http//www.ember.com
81Commercial Viability of WSN Applications
- H900 Wireless SensorNet System(TM), the first
commercially available end-to-end, low-power,
bi-directional, wireless mesh networking system
for commercial sensors and controls is developed
by the company called Sensicast Systems. The
company targets wide range of commercial
applications from energy to homeland security. - http//www.sensicast.com
- The Sensor-based Perimeter Security product is
introduced by a company called SOFLINX Corp. (a
wireless sensor network software company) - http//www.soflinx.com
- XYZ On A Chip Integrated Wireless Sensor
Networks for the Control of the Indoor
Environment In Buildings is another commercial
application project currently performed by
Berkeley. - http//www.cbe.berkeley.edu/research/briefs-wirel
essxyz.htm
82Commercial Viability of WSN Applications
- The Crossbow wireless sensor products and its
environmental monitoring and other related
industrial applications of such as surveillance,
bridges, structures, air quality/food quality,
industrial automation, process control are
introduced. - http//www.xbow.com
- Japan's Omron Corp has two wireless sensor
projects in the US that it hopes to commercialize
in the near future. Omron's Hagoromo Wireless
Web Sensor project consists of wireless nodes
equipped with various sensing abilities for
providing security for major cargo-shipping ports
around the world. - http//www.omron.com
- Possible business opportunity with a big home
improvement store chain, Home Depot, with Intel
and Berkeley using wireless sensor networks - http//www.svbizink.com/otherfeatures/spotlight.a
sp?iid314
83Commercial Viability of WSN Applications
- Millennial Net builds wireless networks
combining sensor interface endpoints and routers
with gateways for industrial and building
automation, security, and telemetry - http//www.millennial.net
- CSEM provides sensing and actuation solutions
- http//www.csem.ch/fs/acuating.htm
- Dust Inc. develops the next-generation hardware
and software for wireless sensor networks - http//www.dust-inc.com
- Integration Associates designs sensors used in
medical, automotive, industrial, and military
applications to cost-effective designs for
handheld consumer appliances, barcode readers,
and wireless computer input devices - http//www.integration.com
84Commercial Viability of WSN Applications
- Melexis produces advanced integrated
semiconductors, sensor ICs, and programmable
sensor IC systems. - http//www.melexis.com
- ZMD designs, manufactures and markets high
performance, low power mixed signal ASIC and
ASSP solutions for wireless and sensor integrated
circuits. - http//www.zmd.biz
- Chipcon produces low-cost and low-power
single-chip 2.4 GHz ISM band transceiver design
for sensors. - http//www.chipcon.com
- ZigBee Alliance develops a standard for wireless
low-power, low-rate devices. - http//www.zigbee.com
85InterPlanetary Internet (Deep Space
Network)State-of-the-Art and Research
Challenges
- I.F. Akyildiz, O. Akan, C.Chen, J. Fang, W. Su,
InterPlanetary Internet - State-of-the-Art and Research Challenges,
Computer Networks Journal, Oct. 2003.
86InterPlaNetary Internet Architecture
- InterPlaNetary Backbone Network
- InterPlaNetary External Network
- PlaNetary Network
87PlaNetary Network Architecture
- PlaNetary Satellite Network
- PlaNetary Surface Network
88CHALLENGES
- Extremely long and variable propagation delays
- Asymmetrical forward and reverse link capacities
- Extremely high link error rates
- Intermittent link connectivity, e.g., Blackouts
- Lack of fixed communication infrastructure
- Effects of planetary distances on the signal
strength and the protocol design - Power, mass, size, and cost constraints for
communication hardware and protocol design - Backward compatibility requirement due to high
cost involved in deployment and launching
processes
89Planned InterPlaNetary Internet Missions
Mission Name Schedule Description/Objective
Galaxy Evolution Explorer 2003 To measure star formation 11 billion years ago with UV wavelengths.
Rosetta February 2004 Comet orbiter and lander to gather scientific data.
Messenger March 2004 To study the characteristics of Mercury, and to search for water ice and other frozen volatiles.
Deep Impact December 2004 To investigate the interior of the comet, the crater formation process, the resulting crater, and any outgassing from the nucleus.
Mars Reconnaissance Orbiter July 2005 To study Mars from orbit, perform high-resolution measurements and serve as communications relay for later Mars landers until 2010.
Venus Express November 2005 To study the atmosphere and plasma environment of Venus.
New Horizons January 2006 To fly by Pluto and its moon Charon and return scientific data/images.
Dawn May 2006 To study two of the largest asteroids, Ceres and Vesta.
Kepler October 2006 Search for terrestrial planets, i.e., similar to Earth.
Europa Orbiter 2008 To study the Jupiters Moon Europas icy surface.
LISA 2007 To probe the gravity waves emitted by dwarf stars and other objects sucked into black holes.
Mars 2007 Late 2007 To launch a remote sensing orbiter and four small Netlanders to Mars.
Mars 2009 Late 2009 Smart Lander, Long Range Rover and Communication Satellite.
BepiColombo January 2011 To study Mercurys form, interior structure, geology, composition, etc.
90Proposed Consultative Committee for Space Data
Systems (CCSDS) Protocol Stack
for Mars Exploration Mission Communications
91Proposed Delay Tolerant Networking (DTN) Protocol
Stack
92Transport Layer Issues
- Extremely High Propagation Delays
- High Link Error Rates
- Asymmetrical Bandwidth
- Blackouts
-
93Extremely Long Propagation Delays
Planet RTTmin RTTmax
Mercury 1.1 30.2
Venus 5.6 35.8
Mars 9 55
Jupiter 81.6 133.3
Saturn 165.3 228.4
Uranus 356.9 435.6
Neptune 594.9 646.7
Pluto 593.3 1044.4
94Performance of Existing TCP Protocols
- Window-Based TCPs are not suitable!!!
- For RTT 40 min ? 20B/s throughput on 1Mb/s
link !!
O. B. Akan, J. Fang, I. F. Akyildiz, Performance
of TCP Protocols in Deep Space Communication
Networks, IEEE Communications Letters, Vol. 6,
No. 11, pp. 478-480, November 2002.
95Space Communications Protocol Standards
Transport Protocol (SCPS-TP)
- Addresses link errors, asymmetry, and outages
- SCPS-TP Combination of existing TCP protocols
- Window-based
- Slow Start
- Retransmission timeout
- TCP-Vegas congestion control scheme variation
of the RTT value as an indication of congestion - SCPS-TP Rate-Based
- Does not perform congestion control
- Uses fixed transmission rate
New Transport Protocols are needed !!!
Space Communications Protocol
Specification-Transport Protocol (SCPS-TP)",
Recommendation for Space Data Systems Standards,
CCSDS 714.0-B-1, May 1999.
96 TP-PlanetO. B. Akan, J. Fang and I.F.
Akyildiz, TP-Planet A Reliable Transport
Protocol for InterPlaNetary Internet, to appear
in IEEE Journal of Selected Areas in
Communications (JSAC), early 2004.
Steady State
t2RTT
Initial State
tRTT
Immediate Start
FollowUP
Follow Up
- Objective To address challenges of
InterPlaNetary Internet - A New Initial State Algorithm
- A New Congestion Detection Algorithm in Steady
State - A New Rate-Based scheme instead of Window-Based
97Multimedia Transport in InterPlaNetary Internet
- Additional Challenges
- Bounded Jitter
- Minimum Bandwidth
- Smoothness
- Error Control
98RCP-Planet OverviewJ. Fang and I.F. Akyildiz,
RCP Planet A Rate Control Scheme for
Multimedia Traffic in InterPlaNetary Internet,
July 2003.
- Objective To Address the Challenges
- Framework
- A New Packet Level FEC
- A New Rate-Based Approach
- A New BEGIN State Algorithm
- A New Rate Control Algorithm in
OPERATIONAL State
99Transport LayerOpen Research Issues
- End-to-End Transport
- Feasibility of the end-to-end transport should be
investigated and new end-to-end transport
protocols should be devised accordingly. - Extreme PlaNetary Distances
- Deep Space links with extreme delays such as
Jupiter, Pluto have intermittent connectivity
even within an RTT. - Cross-layer Optimization
- The interactions between the transport layer and
lower/higher layers should be maximized to
increase network efficiency for scarce space link
resources.
100Network Layer Issues
- Naming and Addressing
- in the InterPlaNetary Internet
- Routing
- in the InterPlaNetary Backbone Network
- Routing
- in PlaNetary Networks
101Naming and Addressing
- Purpose To provide inter-operability between
different elements in the architecture - Influencing Factors
- What objects are named?
- (Typically nodes or data objects)
- Whether a name can be directly used by a data
router in order to determine the delivery path? - The method by which name/object binding is
managed?
102Domain Name System (DNS) Approach in Internet
- If an application on a remote planet needs to
resolve an Earth based name to an address - Problems
- If query an Earth-resident name server
- A significant delay of a round-trip time in
the commencement of communication - If maintain a secondary name server locally
State updates would dominate communication
channel utilization - If maintain a static list of host names and
addresses - Not scale well with systems growth
103Tiered Naming and Addressing
- Name Tuple region ID, entity ID
- Region ID identifies the entitys region and is
known by all regions in the InterPlaNetary
Internet - Entity ID is a name local to its entitys local
region and treated as opaque data outside this
region - ? The opacity of entity names outside their local
region - enforces Late Binding the entity ID of a
tuple is not interpreted outside its
local region - which avoids a universal name-to-address
binding space and preserves a significant amount
of autonomy within each region.
104An InterPlaNetary Internet Example and Host Name
Tuples
Host IPN regions Host name tuples
SRC earth.sol earth.sol, src.jpl.nasa.gov6769
GW1 earth.sol ipn.sol earth.sol, ipngw1.jpl.nasa.gov6769 ipn.sol, ipngw1.jpl.nasa.gov6769
GW2 ipn.sol mars.sol ipn.sol, ipngw2.jpl.nasa.gov6769 mars.sol, ipngw2.jpl.nasa.gov6769
DST mars.sol mars.sol, dst.jpl.nasa.gov6769
105ChallengesNetwork Layer
- Long and Variable Delays
- Without timely distribution of topology
information, routing computations fail to
converge to a common solution, resulting in route
inconsistency or oscillation - The node movement adds to the variability of
delays - Intermittent Connectivity
- Determine the predicted time and duration of
intermittent links and the degree of uncertainity - Obtain knowledge of the state of pending messages
- Schedule transmission of the pending messages
when links become available - SCPS-NP ? possible solution???
106Open Research IssuesNetwork Layer
- Distribution of Topology Information
- Combination of link state and distance vector
information exchange - Distribution of trajectory and velocity
information -
- Path Calculation
- Hop-by-hop routing is expected using incomplete
topology information and probabilistic estimation - Adaptive algorithms are needed for rerouting and
caching decisions - Interaction with Transport Layer Protocols
107ChallengesNetwork Layer (Planet)
- Extreme Power Constraints
- Space elements mainly depend on rechargeable
battery using solar energy - Frequent Network Partitioning
- The network can be partitioned due to harsh
environmental factors - Adaptive Routing through Heterogeneous Networks
- Fixed elements (e.g., landers)
- Satellites with scheduled movement
- Mobile elements with slow movement (e.g., rovers)
- Mobile elements with fast movement (e.g.,
spacecraft) - Low-power sensor nodes in clusters
108Medium Access Control InterPlaNetary Backbone
Network
- Challenges
- Very Long Propagation Delays
- Physical Design Change Constraints
- Topological Changes
- Power Constraints
109Medium Access Control InterPlaNetary Backbone
Network
- Vastly unexplored research field
- The suitability and performance evaluation of
fundamental MAC schemes, i.e., TDMA, CDMA, and
FDMA, should be investigated - Thus far, Packet Telecommand, and Packet
Telemetry standards developed by CCSDS are used
to address deep space link layer issues - (Virtual Channelization method!!!)
110Error ControlInterPlaNetary Backbone Network
- Deep space channel is generally modelled as
Additive White Gaussian Noise (AWGN) channel - Scientific space missions require bit-error rate
of 10-5 or better after physical link layer
coding - ? Error control at link layer is necessary
111Error ControlInterPlaNetary Backbone Network
- CCSDS Telemetry Standard (Telemetry Channel
Coding) - For Gaussian Channels ?
- ½ Rate Convolutional Code
- For Bandwidth-Constrained Channels ?
- Punctured Convolutional Codes
- For Further Constrained Channels ?
- Concatenated Codes (i.e.,Convolutional code as
the inner code and the RS code as the outer code) - Own Experience ? TORNADO CODES!!!
112Error ControlInterPlaNetary Backbone Network
- Advance Orbiting Systems Rec. by CCSDS ?
- Space Link (ARQ) Protocol (SLAP)
- Packet Telecommand Standard of CCSDS ?
- Command Operation Procedure (COP) (GoBack
N)
113Open Research IssuesLink Layer
- MAC for InterPlaNetary Backbone Network
- MAC for PlaNetary Networks
- Error Coding Schemes
- Cross-layer Optimization
- Optimum Packet Sizes
114Physical Layer Issues InterPlaNetary Backbone
Network
- Possible approach is to increase radiated RF
signal energy - Use of high power amplifiers such as travelling
wave tubes (TWT) or klystrons which can produce
output powers up to several thousand watts - This comes with an expense of increased antenna
size, cost and also power problems at remote
nodes - Current NASA DSN has several 70m antennas for
deep space missions - DSN operates in S-Band and X-Band (2GHz and 8GHz,
respectively) for spacecraft telemetry, tracking
and command - Not adequate to reach high data rates aimed for
InterPlaNetary Internet - New 34m antennas are being developed to operate
in Ka-Band (32 GHz) which will significantly
improve data rates
115Open Research IssuesPHYSICAL LAYER
- Signal Power Loss
- Powerful and size-, mass-, and cost-efficient
antennas and power amplifiers need to be
developed - Channel Coding
- Efficient and powerful channel coding schemes
should be investigated to achieve reliable and
very high rate bit delivery over the long delay
InterPlaNetary Backbone links - Optical Communications
- Optical communication technologies should be
investigated for possible deployment in
InterPlaNetary Backbone links - Hardware Design
- Low-power low-cost transceiver and antennas
should be developed - Modulation Schemes
- Simple and low-power modulation schemes should be
developed for PlaNetary Surface Network nodes.
Ultra-wide Band (UWB) could be explored for this
purpose
116Challenges in Deep Space Time Synchronization
- Variable and long transmission delays
- The long and variable delays may cause a
fluctuating offset to the clock - Variable transmission speed
- It may produce a fluctuating offset problem
- Variable temperature
- It may cause the clock to drift in different rate
- Variable electromagnetic interference
- This may cause the clock to drift or even
permanent damage to the crystal if the equipment
is not properly shielded
117Challenges in Deep Space Time Synchronization
(contd)
- Intermittent connectivity
- The situation may cause the clock offset to
fluctuate and jump - Impractical transmissions
- A time synchronization protocol can not depend on
message retransmissions to synchronize the
clocks, because the distance between deep space
equipments are simply too large - Distributed time servers
- Deep space equipments may require to synchronize
to their local time servers, and the time servers
have to synchronize among themselves
118Related Work
- Network Time Protocol
- Can not handle mobile servers and clients
(variable range and range rate with intermittent
connectivity) - Has time offset wiggles of few milliseconds of
amplitude - DSN Frequency and Time Subsystems
- Uses several atomic frequency standards to
synchronize the devices and provide references
for the three DSN sites, i.e., Goldstone, USA
Madrid, Spain Canberra, Australia - Recommendation for proximity-1 space link
protocol - Finds the correlation between the clocks of
proximity nodes. The correlation data and UTC
time are used to correct the past and project the
future UTC values
119Conclusions
- InterPlaNetary Internet will be the Internet of
next generation deep space networks. - There exist many significant challenges for the
realization of InterPlaNetary Internet. - Many researchers are currently engaged in
developing the required technologies for this
objective.
120FiNAL WORDS
- NASAs VISION
- to improve life here, to extend life to there,
to find - life beyond...
- NASAs MISSION
- to understand and protect our home planet, to
explore - the Universe and search for life, to inspire
- the next generation of explorers
- OUR AIM
- to point out the research problems and
inspire the - researchers worldwide to realize these
objectives!!!!!!!!!