Research issues in wireless Sensor networks

1

• Research issues in wireless Sensor networks
• Presented by Brajendra Kumar Singh
• Course Wireless Communications Systems
• 88-563 Winter 2007 Semester
• Instructor Dr. Kemal E. Tepe
• Department of electrical and computer engineering
• University of Windsor,
• Windsor, Ontario, Canada

2
Introduction

• Wireless sensor network
• Massively distributed, untethered, and unattended
  systems to cover spatially distributed phenomena
  in natural obstructed environments
• A sensor node is a Single-chip systems with
• Low-power CPU and less memory,
• Radio or optical communication
• MEMs-based on-chip sensors
• Referred to as motes or smart dust
• Mote applications are deeply tied to hardware
• Each mote runs a single application at a time.
• Driven by interaction with environment
• Event arrival and data processing are concurrent
  activities
• Reliability
• It must collect data without human interaction
  for months at a time. No real recovery mechanism
  in the field except for automatic reboot.
• In-network processing
• Self configuring system

3
Sensor nodes scattered in a sensor field
The components of a sensor node
Source Ref1
4
Example of some sensors
Source Ref4
5
OS and Programming

• TinyOS
• designed for network embedded systems.
• the core OS requires 400 bytes of code and data
  memory, combined.
• a component-based architecture,
• a simple event-based concurrency model
• nesC
• nesC is an extension of C
• Whole-program analysis
• nesC is a static language
• nesC supports and reflects TinyOSs design
• two types of components in nesC modules and
  configurations.
• Simulators
• Tossim
• Emstar
• Others Shawn, VisualSense, J-Sim etc.

6
Group of sensor nodes in action
Source Ref6
7
Base Station
Sensors on field
Source Ref6
8
Sensor Network Challenges

• Tight resource constraints
• Energy
• Communications range, bandwidth
• Computation, storage (but not as constrained as
  energy and communications computation is often
  used to reduce communication)
• Dynamically changing network topology
• Battery depletion
• Node failure
• Node mobility
• Unreliable links (noise, jamming)
• Dynamically changing bandwidth, range, and
  computation power Interactions
• Computation constraints lead to uneven power
  depletion which leads to network topology changes
• Correlated bursts of traffic across neighboring
  nodes
• not a collection of independent point-to-point
  flows
• violating the design assumptions of common media
  access protocols
• Wireless transmission is unreliable

9
Factors influencing design of WSN

• Fault tolerance,
• Scalability,
• Production costs,
• Operating environment,
• Sensor network topology,
• Hardware constraints,
• Transmission media,
• Power consumption
• Data Management
• Geographic routing challenges
• Monitor and Maintenance

10
Sensor network model
11
THE PHYSICAL LAYER

• OPEN RESEARCH ISSUES
• Modulation schemes
• Simple and low-power modulation schemes needed
• can be either baseband or passband
• Solution Strategy
• overcome signal propagation effects
• Hardware design
• Tiny, low-power, low-cost transceiver, sensing,
  and processing units needed
• Power-efficient hardware management strategies
• Solution Strategy
• managing frequencies of operation
• reducing switching power
• predicting work load in processors

12
DATA LINK LAYER

• OPEN RESEARCH ISSUES
• MAC for mobile sensor networks
• Self-Organizing Medium Access Control for Sensor
  Networks (SMACS) and the Eavesdrop-And-Register
  (EAR) Algorithm perform well for mainly static
  sensor networks. It is assumed in the connection
  schemes that a mobile node has many static nodes
  as neighbors.
• In CSMA-based scheme, the mobility issues and
  carrier sensing mechanisms remain largely
  unexplored.
• Determination of lower bounds on the energy
  required for sensor network self-organization
• Error control coding schemes
• Convolution coding effects have been explored.
  The feasibility of other error control schemes in
  sensor networks needs to be explored.
• Power-saving modes of operation
• a sensor node must enter into periods of reduced
  activity when running low on battery power. The
  enumeration and transition management for these
  nodes is open to research.

13
NETWORK LAYER

• OPEN RESEARCH ISSUES
• Existing protocols need to be improved or new
  protocols developed to address
• higher topology changes
• higher scalability

An overview of network layer schemes
14
NETWORK LAYERContinued..
Open Research Issues for routing

• Exploit Redundancy
• Tiered Architectures
• Exploit spatial diversity and density of sensor
  networks
• Achieve desired global behavior with adaptive
  localized algorithms
• Leverage data processing inside the network and
  exploit computation near data sources
• Time and location synchronization
• Self-configuration
• Secure routing
• Source Ref5

Fruits are not so low in the Routing research area
15
TRANSPORT LAYER

• OPEN RESEARCH ISSUES
• Acknowledgments are too costly (As needed in
  TCP/IP)
• Split the end-to-end communication
• UDP-type protocols are used in the sensor network
  
• traditional TCP/UDP protocols in the Internet or
  satellite network

16
THE APPLICATION LAYER

• Open research issues
• Three possible protocols
• Sensor Management Protocol (SMP),
• Task Assignment and Data Advertisement Protocol
  (TADAP)
• Sensor Query and Data Dissemination Protocol
  (SQDDP)
• SQDDP is explored a lot, but SMP and TADAP are
  still open for research.

17
Open Research Areas - 1

• Routing Algorithms with secure foundations
• Optimize Secure Data Management Algorithms
  (Aggregation)
• Social and Network privacy
• Mobile nodes, Mobile Base Stations
• Delegation of privileges
• Tolerate the lack of physical security
• Intrusion Detection techniques, integrated IDS
• Efficient Data Dissemination Protocols
• Reliable Transport Protocols
• Congestion Control and Avoidance Techniques
• Sensor Network Measurements

18
Open Research Areas - 2

• Programming models, architectures, tools
• Programming abstractions, service architecture,
  resource mgmt
• Computing with uncertainties
• Uncertainties about environment and system itself
• Models of reliability, resource-aware and
  task-oriented computation, software architectures
• Consider both application and networking
• Simultaneously Vs Separately
• Quality of service guarantees built in to the
  network protocols
• Real-time support in sensor networks
• - Network support for classes of traffic not
  for specific applications
• - Precise network provisioning not realistic in
  sensor networks
• Innovative applications
• In areas such as security, transportation,
  healthcare

19
Open Research Areas - 3

• Scheduling Challenges
• Uncertainty
• nondeterministic processing algorithms,
• communication noise
• Dynamics
• robustness to topology and resource changes
• Deep, multi-hop data flows
• Scale
• Providing decision-theoretic objective tradeoffs
• Some Approaches to Handling Scheduling Problems
• Static schedules that are robust to uncertainty
  and time-varying constraints
• Network provisioning for redundant paths
• On-line scheduling
• - Not practical in tight computation nodes
• - Introduces latency
• Off-line construction of conditional schedules
  that adapt to sensor feedback, topology changes,
  and task changes

20
Open Research Areas - 4

• Integrated Communication and Computation
  Scheduling Problem (Load balancing problem)
• Parallel, distributed computation
• Sensor processing
• Task data flow, e.g. aggregation, in-network
  processing
• Communication
• Broadcast links interference, range
• Synchronization of computation and communication
  to satisfy task Objective Function
• Minimize computation convergence time
• Minimize latency in responding to new sensor data
• Minimize total energy consumed
• Balance distribution of energy consumed

21
Sensor Applications

• Just the tip of the iceberg
• A Wireless Sensor Network for Structural
  Monitoring
• For monitoring health of power lines
• Smart paint
• Wireless Sensor Networks for Habitat
  Monitoring
• Biomedical Sensors
• Military surveillance

22
Conclusion

• Optimize, Optimize, Optimize!
• (memory constraints, energy usage)

23
References

• Ian Akyildiz., W. Su, Y. Sankarasubramaniam, E.
  Cayirci, "A Survey on Sensor Networks", IEEE
  Communications Magazine, August 2002
• David Culler, Deborah Estrin, and Mani
  Srivastava, "Overview of Sensor Networks", IEEE
  Computer, August 2004
• Chee.-Yee. Chong and Kumar, S.P., "Sensor
  Networks Evolution, Opportunities, and
  Challenges," Proc IEEE, August 2003
• David Gay, Phil Levis, Rob von Behren, Matt
  Welsh, Eric Brewer, and David Culler, "The nesC
  Language A Holistic Approach to Networked
  Embedded Systems", Programming Language Design
  and Implementation (PLDI) 2003, June 2003
• Al-Karaki, J.N. Kamal, A.E., Routing techniques
  in wireless sensor networks a survey, Wireless
  Communications, Volume 11, Issue 6, Dec. 2004
• Deepak Ganesan , Alberto Cerpa , Wei Ye , Yan Yu
  ,Jerry Zhao , Deborah Estrin, "Networking Issues
  in Wireless Sensor Networks" Slides Slides
  internet, 2005

24
Thanks
Questions and suggestions?
25
Some facts

• TinyDB a sensor network query processing engine,
• Mate a small virtual machine that allows rapid
  reprogramming of sensor networks.
• nesC Vs C C does have significant
  disadvantages it provides little help in writing
  safe code or in structuring applications. nesC
  addresses safety through reduced expressive power
  and structure through components.

26

• Differences between sensor networks and ad hoc
  networks are
• The number of sensor nodes in a sensor network
  can be several orders of magnitude higher than
  the nodes in an ad hoc network.
• Sensor nodes are densely deployed.
• Sensor nodes are prone to failures.
• The topology of a sensor network changes very
  frequently.
• Sensor nodes mainly use a broadcast communication
  paradigm, whereas most ad hoc networks are based
  on point-to-point communications.
• Sensor nodes are limited in power, computational
  capacities, and memory.
• Sensor nodes may not have global identification
  (ID) because of the large amount of overhead and
  large number of sensors.

27
Transmission media

• based on RF circuit design
• The uAMPS wireless sensor node uses a
  Bluetooth-compatible 2.4 GHz transceiver with an
  integrated frequency synthesizer.
• The low-power sensor device uses a single-channel
  RF transceiver operating at 916 MHz.
• based on infrared.
• Infrared communication is license-free
• robust to interference from electrical devices.
• cheaper and easier to build.
• Smart Dust mote computing
• Both infrared and optical require a line of sight
  between the sender and receiver.

28
Power Consumption

• A limited power source (lt 0.5 Ah, 1.2 V).
• Power-aware protocols and algorithms for sensor
  networks.
• The main task of a sensor node
• detect events,
• perform quick local data processing
• transmit the data
• Power consumption can hence be divided into three
  domains
• sensing
• communication
• data processing

29
Embaded Network Sensing Research focus
30
(No Transcript)
31
(No Transcript)