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Mobile & Wireless Computing 1 Kemal Akkaya
Department of Computer ScienceSouthern Illinois University Carbondale
Mobile & Wireless Computing
Routing Protocols for Sensor NetworksHierarchical & Location-based and QoS Protocols
Dr. Kemal AkkayaE-mail: [email protected]
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Hierarchical Protocols When sensor density increases single tier networks
cause Sink overloading Increased latency Large energy consumption
Clustered Network allow coverage of large area of interest and additional load without degrading the performance
Hierarchical clustering schemes are the most suitable for wireless sensor networks Uses Multi - hop communication within a cluster Performs data aggregation and fusion on data to reduce number of
transmitted messages to the sink Maintain the energy reserves of nodes efficiently
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Hierarchical Routing
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LEACH
LEACH (Low Energy Adaptive Clustering Hierarchy) is the first hierarchical routing protocol for sensor networks
W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-efficient communication protocol for wireless sensor networks," in the Proceeding of the Hawaii International Conference System Sciences, Hawaii, January 2000.
Self-Organizing, adaptive clustering protocol Even distribution of energy load among the sensors Nodes organize themselves into clusters Cluster-heads communicate data with the base station
(sink)
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LEACH Dynamic cluster formation - Cluster-heads are not fixed
They rotate at each round randomly
Data-fusion at each cluster– reduces energy dissipation and enhances lifetime
Cluster-heads at time t Cluster-heads at time t + d
Dynamic Clustering
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LEACH uses First Order Radio ModelTransmit k-bit message a distance d using the radio model
Fig 1: First Order Radio Model
ETx-elec = Energy dissipated/bit at Transmitter
ERx-elec = Energy dissipated/bit at Receiver
Єamp = Amplification factor
Energy equation at the Transmitter:
Energy equation at the Receiver:
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LEACH Algorithm
Algorithm is broken into rounds, and each rounds consists of following 4 phases:
Advertisement phase Each node decides whether or not to become cluster-head Advertises itself as cluster-head
Cluster Set-up phase Each node decides to which cluster it belongs Notification to the cluster-head
Schedule Creation Cluster-head creates a TDMA schedule notifying each node when it
can transmit
Data transmission Each node send data during their allotted time
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Simulation Results
Energy dissipation System Lifetime
Direct: Direct Transmission to the Sink MTE: Minimum Transmission Energy
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Sensor Lifetimes
System life time after 1200 rounds
Live nodes (circled)
Dead nodes (dotted)
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What about MTE & Direct Communication?
No of rounds: 180 Alive (circles); Dead (dots)
Direct Communication MTE
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LEACH Summary
Factor of 7 reduction in energy dissipation as compared to Direct Communication
Uniform distribution of energy-usage in the network Doubles the system lifetime compared to other
methods Nodes die essentially in random fashion, thus maintain
the network coverage Completely distributed, no network knowledge required Problems:
Nodes use single-hop communication Not good for large domains
Cluster-head change overhead
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PEGASIS Power Efficient GAthering in Sensor Information Systems Improvement to LEACH
Form chains rather than clusters S. Lindsey and C. S. Raghavendra, "PEGASIS: Power
Efficient GAthering in Sensor Information Systems," in the Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, March 2002.
Token-Passing Chain-Based Considered Near-Optimal Nodes die in random Stationary Nodes and Sink Every node have a global network map Data Fusion Greedy chain construction
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Main Procedures
Greedy Algorithm Construct Chain –Start at a node far from sink and gather everyone neighbor by neighbor
Node i (mod N) is the leader in round iNodes passes token through the chain to
leader from both sidesEach node fuse its data with the restLeader transmit to sink
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PEGASIS - Illustration
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Comparison
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Summary Outperforms LEACH by eliminating clustering overhead Global Information assumed Limited Scale:
Information travels many nodesExcessive delay for far nodes
Assumes any node can communicate with sink Hierarchical PEGASIS
Extension of PEGASIS Decrease the delay for the packets during transmission to the base
station Simultaneous transmissions of data messages Avoid collisions and possible signal interference
Signal Coding (e.g. CDMA) Spatially separated nodes can transmit at the same time
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Hierarchical PEGASIS
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Location-based Protocols If the locations of the sensor nodes are known, the
routing protocols can use this information to reduce the latency and energy consumption of the sensor network. Distance between two nodes is calculated using location information Energy consumption can be estimated
Efficient energy utilization
Location of a node can be determined using Global Positioning System (GPS) Ultrasonic Systems using trilateration Beacons
Although GPS is not envisioned for all types of sensor networks, it can still be used if stationary nodes with large amount of energy are allowed.
Location based protocols assume that each node knows its location in the network
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GAF (Geographic Adaptive Fidelity) GAF designed for both ad hoc and sensor networks Y. Xu, J. Heidemann, and D. Estrin, "Geography-informed
energy conservation for ad hoc routing," in the Proceedings of the 7 th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom’01), Rome, Italy, July 2001.
Forms a virtual grid of the covered area Each node associates itself with a point in the grid based
on its location Nodes associated with same point in grid are considered
equivalent Some nodes in an area are kept sleeping to conserve
energy Nodes change state from sleeping to active for load
balancing
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Routing in GAF
Sink
Representative Node for the subregion
Virtual Grid
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States in GAF Nodes use GPS to
associate itself to the grid A node remains active for
time Ta Ta of a node in the grid is
broadcasted to other equivalent nodes
The sleeping time of a node is adjusted depending on Ta
In the discovery state each node broadcasts discovery messages periodically (Td)
Handles mobility
Three States•Discovery: Determining neighbors•Active: Does routing•Sleep: Turn off radio
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GAF Summary
Increase the lifetime of the network significantly Works for MANETs as well
Handles mobility
Also considered to be hierarchical protocol Each sub-region is a cluster Representative node is the cluster-head
But does not perform any data aggregation
Not very scalable. As the network size increases distance to the sink increases
Overhead of forming the grid Only the active nodes sense and report data.
Hence data accuracy is not very high.
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AA
BB
Connection A requires less energy than Connection A requires less energy than connection B because the power required connection B because the power required to transmit between a pair of nodes to transmit between a pair of nodes increases as the nincreases as the nthth power of the distance power of the distance between them (n>=2).between them (n>=2).
Minimum Energy Communication Minimum Energy Communication Network (MECN)Network (MECN)
L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless Networks Revisited”. Proc. of IEEE Int. Conf. on Networks Revisited”. Proc. of IEEE Int. Conf. on Communications (ICC’01), Helsinki, Finland, June 2001.Communications (ICC’01), Helsinki, Finland, June 2001.
Uses graph theory:Uses graph theory: Each node knows its exact locationEach node knows its exact location Network is represented by a graph G’, and it is assumed that the Network is represented by a graph G’, and it is assumed that the
resulting graph is connected resulting graph is connected
A sub-graph G of G’ is computed. A sub-graph G of G’ is computed. G connects all nodes with minimum energy cost.G connects all nodes with minimum energy cost.
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QoS Routing In WSN QoS-aware protocols consider end-to-end delay
requirements while setting up paths End-to-end delay is the most common Bandwidth
Video or image sensors
Real-time routing in Disaster management Fire detection Tsunami alerts etc.
QoS in WSN is very challenging Already have constraints such as bandwidth and energy QoS routing will bring a lot of overhead
QoS in WSN is still in very early stages May require redefinition of QoS for WSN
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SPEED
A real-time routing protocol for WSN T. He et al., “SPEED: A stateless protocol for real-time
communication in sensor networks,” in the Proceedings of International Conference on Distributed Computing Systems, Providence, RI, 2003.
Each node maintains info about its neighbors and uses geographic forwarding to find the paths
Tries to ensure a certain speed for each packet in the network
Congestion avoidance
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Energy-aware QoS Routing Protocol K. Akkaya and M. Younis,
"Energy-aware routing of time-constrained traffic in wireless sensor networks," in the International Journal of Communication Systems, Vol. 17(6), pp. 663-687, 2004.
Finds least cost and energy efficient paths that meet the end-to-end delay during connection Energy reserve, transmission energy
WFQ (Weighted Fair Queuing) packet scheduling model used to support best-effort and real-time traffic WFQ can provide upper delay bound
Used with constant data rate
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Summary of Protocols for WSN