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Routing Protocols for Sensor Networks. Agenda. General Properties Architectures and Requirements Routing Protocols Classification 10 Suggested Routing Protocols: . LEACH PEGASIS TEEN APTEEN SPIN . DD MCF TTDD RW RR. Acknowledgements. E. Magistretti (U. Bologna Italy)

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Routing Protocols for Sensor Networks

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Routing ProtocolsforSensor Networks


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


Acknowledgements

  • E. Magistretti (U. Bologna Italy)

  • J. Kulik (MIT; BBN Co.)

  • R. R. Choudhury, P. Kyasanur & N. Vaidya (UIUC)

  • P. Desai (UFL)

  • D. Braginsky and D. Estrin (UCLA)

  • S. Hazarika, W. Chen, Y. Gong & X. Liu (UMASS)

  • T. Kwon & Mjnam (SNU Korea)

  • R. Peterson & D. Rus (Dartmouth C.)

  • H.C. Chung, K. Ghoshal & J. Krishna (TAMU)

  • C. Tavoularis (Cornell )

  • G. Dong (Virginia U.)


WSN

Dartmouth College


Concepts


Application:Military

From UMASS


Environmental

From UMASS


Circulatory Net

Future Health


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


General Properties (1)

  • Mainly for Information Collection

  • Single Owner

  • Up to Hundreds of Thousands of Nodes

  • Disposable Nodes

  • Cheap Nodes

  • Security Concerns


General Properties (2)

  • Bounded Directed Stream (from/to Sink)

  • Somewhat Limited Computation Capability

  • Limited Communication Capability

  • Limited Power Resources

  • Node may not have Unique ID

  • Common case - Stationary Nodes


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


General Architecture (1)

Sensor Network Node Main Components

  • Sensor Unit

  • ADC – Analog Digital Converter

  • CPU – Central Processing Unit

  • Power Unit

  • Communication Unit


General Architecture (2)


General Requirements (1)

  • Varying Network Size

  • Inexpensive Nodes Equipment

  • Long Lifetime (Power) Þ Load-Balancing

  • Self-Organization

  • Re-tasking and Querying Capability


General Requirements (2)

  • Sensible Data Aggregation

  • Consolidation of Redundant Data

  • Application Awareness

    Þ Tradeoff Communication for Computation

  • Possible Mobility


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


Protocol Classification (1)

  • Proactive – First Compute all Routes;Then Route

  • Reactive – Compute Routes On-Demand

  • Hybrid – First Compute all Routes;Then Improve While Routing


Protocol Classification (2)

  • Direct – Node and Sink Communicate Directly(Fast Drainage; Small Scale)

  • Flat (Equal) – Random Indirect Route(Fast Drainage Around Sink; Medium Scale)

  • Clustering (Hierarchical) – Route Thru Distinguished Nodes


Protocol Classification (3)

  • Location Aware – Nodes knows where they are

  • Location-Less – Nodes location is unimportant

  • Mobility Aware – Nodes may move – Sources; Sinks; All


Protocol Classification (4)

  • Unicast – One-to-One Message Passing

  • Multicast (actually Local Broadcast) – Node-to-Neighbors Message Passing

  • Broadcast – Full-Mesh – Source to Everyone


Protocol Classification (5)

Query Models:

  • Historical Queries: Analysis of historical data“What was the watermark 2h ago in the southeast?”

  • One-time Queries:Snapshot view“What is the watermark in the southeast?”

  • Persistent Queries:Monitoring over time“Report the watermark in the southeast for the next 4h”


Protocol Classification (6)


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


Low Energy Adaptive Clustering Hierarchy

1 - LEACH – Discussed …

  • Self-Organizing – Adaptive Clustering

  • Cluster-Heads elect themselves – Now – “Random Round-Robin”Future – Power-Based Probability

  • Nodes die in random

  • Stationary Sink

  • Localized Coordination

  • Data Fusion

Protocol Highlights


Low Energy Adaptive Clustering Hierarchy

1 - LEACH (2)

  • “Hot Spot” Problem(Nodes on a path from an event-congested area to the sink may drain)

  • Inadequate for Time-Critical Applications

  • Stationary Sink – Maybe Unpractical

  • Basic Algorithm assumes any node can communicate with sink – limited scale

Main Drawbacks


Low Energy Adaptive Clustering Hierarchy

1 - LEACH (3)

  • Works in Rounds, each with Set-Up (Short) and Steady-State (Long)

  • Set-Up Phase - subdivided:

    • Advertisement (I am a Cluster-Head)

    • Cluster Set-Up (I am in your Cluster)

    • Schedule Creation (This is your slot)

  • Steady-State Phase:

    • Data Transmission using TDMA

Main Procedures


Low Energy Adaptive Clustering Hierarchy

1 - LEACH (4)

  • Everyone uses the same channel

  • Different clusters use different CDMA codes

  • Code chosen in random

  • Cluster-Head communicate with Sink

  • Can be extended to Hierarchical Clustering

Main Procedures


Low Energy Adaptive Clustering Hierarchy

1 - LEACH (5)

Illustrations


Low Energy Adaptive Clustering Hierarchy

1 - LEACH (6)

Illustrations


Power-Efficient Gathering in Sensor Information Systems

2 - PEGASIS (1)

  • Token-Passing Chain-Based

  • Considered Near-Optimal (in a sense)

  • Nodes die in random

  • Stationary Nodes and Sink

  • Every node have a global network map

  • Data Fusion

  • Greedy chain construction

Protocol Highlights


Power-Efficient Gathering in Sensor Information Systems

2 - PEGASIS (2)

  • Stationary Nodes

  • Global Information

    Limited Scale:

  • Information travels many nodes

  • Assumes any node can communicate with sink

Main Drawbacks


Power-Efficient Gathering in Sensor Information Systems

2 - PEGASIS (3)

  • 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 i

  • Nodes passes token thru the chain to leader from both sides

  • Each node fuse its data with the rest

  • Leader transmit to sink

Main Procedures


Power-Efficient Gathering in Sensor Information Systems

2 - PEGASIS (4)

Illustrations


Power-Efficient Gathering in Sensor Information Systems

2 - PEGASIS (5)

Rounds Until Death

Illustrations


Threshold sensitive Energy Efficient Sensor Network

3 - TEEN (1)

  • LEACH based Clustering

  • Smart data transmission (Saves Power)

  • Nodes dynamic reconfiguration ability

  • Suits for Time-Critical applications

Protocol Highlights


Threshold sensitive Energy Efficient Sensor Network

3 - TEEN (2)

  • “Hot Spot” Problem

  • Cluster-Heads need to listen constantly

  • Wasted time-slots

  • Can’t distinguish dead nodes

  • Other LEACH problems…

Main Drawbacks


Threshold sensitive Energy Efficient Sensor Network

3 - TEEN (3)

  • LEACH Proactive Clustering

  • Node transmit in timeslot only if both:

    • Value greater then a Hard Threshold (HT)

    • Value differs from last transmitted value (SV ) by more then a Soft Threshold (ST)

  • After transmission SV is reset

Main Procedures


Threshold sensitive Energy Efficient Sensor Network

3 - TEEN (4)

Illustrations


Adaptive Periodic Threshold-sensitive Energy Efficient Sensor Network

4 - APTEEN (1)

  • Improved (Adaptive - Hybrid) TEEN

  • All TEEN Features

  • More flexible logic and timeslots

  • Multi-type Queries:

    • Historical (What was the temp. then?)

    • One-time (What’s the temp. now?)

    • Persistent (Tell me the temp for 2 hours)

  • Can distinguish dead nodes

Protocol Highlights


Adaptive Periodic Threshold-sensitive Energy Efficient Sensor Network

4 - APTEEN (2)

  • LEACH problems…

  • Complex logic

Main Drawbacks


Adaptive Periodic Threshold-sensitive Energy Efficient Sensor Network

4 - APTEEN (3)

  • LEACH Proactive Clustering

  • Node transmit in timeslot only if both:

    • Value greater then a Hard Threshold (HT)

    • Value differs from last transmitted value (SV ) by more then a Soft Threshold (ST)

      Or If did not transmit for a max time (TC )

      Or if queried by some sink

  • After transmission SV is reset

Main Procedures


Adaptive Periodic Threshold-sensitive Energy Efficient Sensor Network

4 - APTEEN (4)

Power Consumption:

  • As could be expected – APTEEN is better the LEACHbut not as good as TEEN

Illustrations


Sensor Protocol for Information via Negotiation

5 - SPIN (1)

  • Network-wide Broadcast Limited by Negotiation and using Local Communication

  • Flooding problems solved:

    • Implosion – same data from many neighbors

    • Detection of overlapping regions

    • Excessive resources consumption (Blindness)

  • Needs only Localized Information

  • Data Fusion

  • Two main protocols SPIN-PP & SPIN-BC

Protocol Highlights


Sensor Protocol for Information via Negotiation

5 - SPIN (2)

  • Broadcast - Limited Scale – every node handles O(n) messages

  • Data is updated throughout network – unnecessary in many cases

  • Network lifetime - not clear

  • High degree nodes = High power needs

Main Drawbacks


Sensor Protocol for Information via Negotiation

5 - SPIN (3)

SPIN-PP (Point-to-Point Communication)

  • Data is described by meta-data ADV msg.

  • Node has data Þsends ADV to neighbors

  • If neighbor do not have data Þ sends REQ

  • Node responds by sending the DATA

  • This process continues around the network

  • Nodes may aggregate their data to ADV

  • In a Lossy Network ADV may be repeated periodically and REQ if not answered

Main Procedures


Sensor Protocol for Information via Negotiation

5 - SPIN (4)

SPIN-BC (Local Broadcast Communication)

  • ADV and DATA sending like PP (but in B.C.)

  • Since only one REQ answer is needed, any node waits a random interval and B.C. REQ only if none was received yet.

  • The rest – like SPIN-PP

Main Procedures


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

ADV

Illustrations

SPIN-PP

Node with data advertises to all its neighbors


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

REQ

Illustrations

SPIN-PP

Neighbor requests for data and it is sent


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

DATA

Illustrations

SPIN-PP

Node with data advertises to all its neighbors


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

ADV

Illustrations

SPIN-PP

Receiving node sends ADV to neighbors


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

Already has data

(or dead)

Illustrations

REQ

SPIN-PP

Receiving neighbors requests for data.


Sensor Protocol for Information via Negotiation

5 - SPIN (5)

Node with data

Illustrations

DATA

SPIN-PP

Receiving node sends ADV to neighbors


Directed Diffusion

6 - DD (1)

  • Hybrid Data Centric Routing – Looking for Named Data

  • Query–Response Model

  • Performs Better than Flooding

  • Robust and Fault Tolerant (bypass faults)

  • Localized Interactions

  • Data Fusion - Application Specific Filters

Protocol Highlights


Directed Diffusion

6 - DD (2)

  • “Hot Spot” Problem near sink

  • Periodic Broadcasts of “Interest” Reduces Network Lifetime

  • Trade-off: Energy Efficiency vs.Robustness and Scalability

  • Complex Data Aggregation - may Lead to Expensive Node

Main Drawbacks


Directed Diffusion

6 - DD (3)

  • A Query (Interest) is Broadcasted by a node (sink)

  • Query Reaches Relevant Sensor Sources

  • This Sets-Up Exploratory Gradients

  • Once Data is Available in a Source it is Sent Back via Reinforced Path

  • Failing Links / Nodes are being Gradually Bypassed

Main Procedures


Directed Diffusion

CLASS_KEY IS INTEREST_CLASS

LONGITUDE_KEY GE 10

LONGITUDE_KEY LE 50

LATITUDE_KEY GE 100

LATITUDE_KEY LE 120

SENSOR EQ MOVEMENT

INTENSITY GE 0.6

CONFIDENCE GE 0.7

INTERVAL IS 10

EXPIRE_TIME IS 100

Source

Sink

Interest = Interrogation

Gradient = Who is interested

6 - DD (4)

Illustrations


Directed Diffusion

FilterAttrVec

CLASS_KEY EQ DATA_CLASS

SENSOR EQ MOVEMENT

INTENSITY GE 0.7

Source

3. addFilter (FilAttrVec, FilterCallback)

1. subscribe (InterestAttrVec, Callback)

2. subscribe (AttrVec, ApplCallback)

InterestAttrVec

CLASS_KEY EQ INTEREST_CLASS

LONGITUDE_KEY IS 35

LATITUDE_KEY IS 110

SENSOR IS MOVEMENT

Sink

Interest = Interrogation

Gradient = Who is interested

6 - DD (4)

Illustrations


Directed Diffusion

6 - DD (4)

Interests Setting up gradients

Source

Illustrations

Sink

Interest = Interrogation

Gradient = Who is interested


Directed Diffusion

6 - DD (4)

Sending data …

Source

Illustrations

4. h = publish (SensedAttrVec)

5. send (h, SensedAttrVec)

Sink

SensedAttrVec

CLASS_KEY IS DATA_CLASS

LONGITUDE_KEY IS 35

LATITUDE_KEY IS 110

SENSOR IS MOVEMENT

INTENSITY IS 0.8

CONFIDENCE IS 0.7

Low rate event


Directed Diffusion

m1a

6. FilterCallback.recv (Message m1)

m1b

m2

m2

CLASS_KEY IS DATA_CLASS

LONGITUDE_KEY IS 35

LATITUDE_KEY IS 110

SENSOR IS MOVEMENT

INTENSITY IS 0.8

CONFIDENCE IS 0.8

m2

7. sendMessage (Message new)

6 - DD (4)

Source

Illustrations

Low rate event


Directed Diffusion

6 - DD (4)

Source

8. ApplCallback.recv (NRAttrVec)

Illustrations

Sink

Low rate event


Directed Diffusion

6 - DD (4)

… and Reinforcing the best path

CLASS_KEY IS INTEREST_CLASS

LONGITUDE_KEY GE 10

LONGITUDE_KEY LE 50

LATITUDE_KEY GE 100

LATITUDE_KEY LE 120

SENSOR EQ MOVEMENT

INTENSITY GE 0.6

CONFIDENCE GE 0.7

INTERVAL IS 1

EXPIRE_TIME IS 90

Source

Illustrations

Sink

Low rate event

Reinforcement = Increased interest


Directed Diffusion

6 - DD (5)

Source

Illustrations

Sink

Recovering

from node failure

Low rate event

Reinforcement

High rate event


Directed Diffusion

6 - DD (5)

Source

Illustrations

Sink

Stable path

Low rate event

High rate event


Directed Diffusion

6 - DD (6)

Source

Illustrations

Sink

Recovering

from link failure

Low rate event

Reinforcement

High rate event


Directed Diffusion

6 - DD (6)

Source

Illustrations

Sink

Stable path

Low rate event

Reinforcement

High rate event

Use: “Interests set up gradients drawing down data”


Minimum Cost Forwarding

7 - MCF (1)

  • Cost-Field min Cost from Node to Sink on Optimal Path

  • Slop-Down the Cost-Fields to Get to Sink

  • Minimize Multiple Transmissions using Back-Off Algorithm Based on Node Cost

  • Localized Communication

Protocol Highlights


Minimum Cost Forwarding

7 - MCF (2)

  • High Time Complexity (due to back-off)

  • Many Sinks – Large Cost Tables

  • Cost Field Set-Up Time O(N)

  • No Load-Balancing

Main Drawbacks


Minimum Cost Forwarding

7 - MCF (3)

  • Broadcast ADV msg. and get Answers from all Sinks ÞCreate Cost-Fields

  • Calculate Back-Off Timer Proportional to Cost per each Sink

  • Needed Information Sent thru Slop

  • If no ACK until Timer Expires – Resend ADV

Main Procedures


Minimum Cost Forwarding

7 - MCF (4)

Illustrations

Cost

A

B

C

Timeline


Minimum Cost Forwarding

7 - MCF (5)

A=150

110

Illustrations

B = 120

S = 200

C = 90

130

50

100

60

90

Sink = 0


Two-Tier Data Dissemination

8 - TTDD (1)

  • Grid Structure Clustering

  • Stationary Location-Aware Nodes

  • Mission Aware – Infrequent Changes

  • Greedy Geographical Forwarding – Building Grid

  • Localized Communication

Protocol Highlights


Two-Tier Data Dissemination

8 - TTDD (2)

  • No Mobile Sensors

  • Requires Location Information

  • Grid Nodes may Drain

Main Drawbacks


Two-Tier Data Dissemination

8 - TTDD (3)

  • Grid Build using Greedy Algorithm and Location Awerness

  • Node Floods Messages to Dissemination Nodes

  • Dissemination Nodes Forward to Sink

  • If a Node Fails – Grid is Fixed

Main Procedures


Two-Tier Data Dissemination

Source

Sink

8 - TTDD (4)

TTDD Basics

Dissemination Node

Illustrations

Data Announcement

Data

Query

Immediate

Dissemination

Node


Two-Tier Data Dissemination

Source

Sink

Trajectory

Forwarding

8 - TTDD (5)

TTDD Mobile Sinks

Dissemination Node

Trajectory

Forwarding

Illustrations

Data Announcement

Immediate

Dissemination

Node

Data

Immediate

Dissemination

Node


Two-Tier Data Dissemination

Source

TTDD Multiple Mobile Sinks

8 - TTDD (6)

Dissemination Node

Trajectory

Forwarding

Illustrations

Data Announcement

Immediate

Dissemination

Node

Data


Random Walks

9 - RW (1)

  • Finding a Random Walk over a Grid

  • Multi-path Routing

  • Load Balancing

  • Large Scale Networks

  • Nodes Assumed to be Mostly Stationary

  • No Location Information Needed

  • Little State Information

  • Localized Communication

Different Routes

at Different Times

Protocol Highlights


Random Walks

9 - RW (2)

  • Topology may not be Practical(Nodes are Assumed to be Located at Cubic Grid Junctions)

Main Drawbacks


Random Walks

9 - RW (3) - RSG

Regular Static Graphs

  • Find coordinates differences (Dx, Dy) using Distributed Bellman Ford (local comm.)

  • For every node compute probability of moving on X and Y (By the diagonal to the destination)

  • On each node move to a adjacent one on X or Y using that probability. Adjust near end.

    All Paths together draws a straight “Banana”

Main Procedures


Random Walks

9 - RW (4) - ISG

Irregular Static Graphs (Some dead nodes)

  • Same as RSG but…

  • If one adjacent node is missing – go to the other (with p=1).

  • If both are missing – go to a neighbor whose B-F distance to the destination is strictly smaller than the current node(This will create a detour).

  • (Could optimize by not getting to that node…).

Main Procedures


Random Walks

9 - RW (5) - DG

Dynamic Graphs (Nodes may sleep and wake)

  • Same as ISG but…

  • When a node changes state: the one-hop neighbors change B-F labels and possibly trigger further label (distances) changes

  • Concerns:

    • Delays in propagating updates

    • Sensitivity to inaccuracies in labels

Main Procedures


Random Walks

9 - RW (6) - RSG

Illustrations


Random Walks

9 - RW (7) – RSG vs. ISG

Illustrations

ISG

ISG


Random Walks

9 - RW (8) – RSG vs. ISG

A Random walk by flipping a fair coin

Illustrations

RSG (DG Similar)

ISG

Load Distribution -Narrow


Random Walks

9 - RW (9) – RSG vs. ISG

A Random walk by RSG/ISG algorithms

Illustrations

RSG (DG Similar)

ISG

Load Distribution - Flat


Rumor Routing

10 - RR (1)

  • Observation: for many application any arbitrary path will do – No Need for a Shortest Path

  • Nodes are Densely Distributed

  • Bidirectional Links

  • Localized Communication

  • Stationary Nodes

  • Meet Trails of Queries and Events

Protocol Highlights


Rumor Routing

10 - RR (2)

  • Attractive only when the ratio between events and queries is inside a threshold where it is not attractive to flood neither.

  • Optimal parameters depend heavily on topology (but can be adaptively tuned)

  • Does not guarantee delivery

Main Drawbacks


Rumor Routing

10 - RR (3)

  • Movement on the net is done by several agents, trying (randomly) to walk straight.

  • Every node maintains lists of neighbors and events (how to get to the reporting node).

  • An agent coming from and event is updating nodes it visits.

  • An agent coming from a query is searching for ways to the reporting nodes.

  • High probability the lines will intersect.

Main Procedures


Rumor Routing

10 - RR (4)

Illustrations

Event 1

Knows Event 1

Agent

Event 2

Knows Event 2

Knows Both Event


Rumor Routing

10 - RR (5)

Very

Theoretical

Execution

Event

Source

Illustrations

Query

Source


Agenda

  • General Properties

  • Architectures and Requirements

  • Routing Protocols Classification

  • 10 Suggested Routing Protocols:

Done!!!

  • LEACH

  • PEGASIS

  • TEEN

  • APTEEN

  • SPIN

  • DD

  • MCF

  • TTDD

  • RW

  • RR


Conclusions

  • WSN will spread to many applications

  • Properties and Requirements are bothUnique and Diversified

  • Routing Protocol choice is and probably will continue to beApplication Driven

  • More Analysis, Simulations and newIdeas are needed for every category


References (1)

  • Q. Jiang, D. Manivannan, Routing Protocols for Sensor Networks, IEEE Consumer Communications and Networking Conference (CCNC'04), 2004.

  • R. Jurdak, C. V. Lopes, P. Baldiy, A Framework for Modeling Sensor Networks, 19th Annual ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA'04), 2004.

  • W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, IEEE Proceedings of the IEEE International Conference on System Sciences, 2000.

  • S. Lindsey, C. S. Raghavendra, PEGASIS: Power Efficient GAthering in Sensor Information Systems, IEEE Aerospace Conference, 2002.


References (2)

  • A. Manjeshwar and D. P. Agrawal, TEEN: A Protocol for Enhanced Efficiency in Wireless Sensor Networks, Proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing (with IPDPS'01), 2001.

  • A. Manjeshwar and D. P. Agrawal, APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks, Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS'02), 2002.

  • J. Kulik, W. Heinzelman, and H. Balakrishnan, Negotiation-Based Protocols for Disseminating Information in Wireless Sensor Networks, Wireless Networks, Vol. 8, pp. 169-185, 2002.

  • C. Intanagonwiwat, R. Govindan, D. Estrin, J. S. Heidemann, and F. Silva, Directed Diffusion for Wireless Sensor Networking, IEEE/ACM Transactions on Networking, vol. 11, no. 1, pp. 2-16, 2003.


References (3)

  • F. Ye, A. Chen, S. Lu, L. Zhang, A Scalable Solution to Minimum Cost Forwarding in Large Sensor Networks, Proceedings of the 10th IEEE International Conference on Computer Communications and Networks (ICCCN'01), 2001.

  • F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, A Two-Tier Data Dissemination Model for Large-scale Wireless Sensor Networks, ACM International Conference on Mobile Computing and Networking (MOBICOM'02), 2002.

  • S. D. Servetto, G. Barrenechea, Constrained Random Walks on Random Graphs: Routing Algorithms for Large Scale Wireless Sensor Networks, In the Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002.

  • D. Braginsky, D. Estrin, Rumor Routing Algorithm For Sensor Networks, In the Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002.


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