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The need for Data Dissemination and Fusion

Energy efficiency is an essential factor; therefore, short-range hop-by-hop communication is preferred over direct long-range communicationto the destination

Since sensor network contains large amount of data for the end user,methods of combining or aggregating data into small set of informationis necessary and contributes to energy savings

Data aggregation (aka data fusion) can combine unreliable datareadings to produce accurate signal by improving the common signaland reducing the noise

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LEACH is a clustering-based protocol that utilizes the randomized rotationof local cluster base stations to evenly distribute the energy load within thenetwork of sensors

It is a distributed, does not require any control information from base station(BS) and the nodes do not need to have knowledge of global network forLEACH to function

The energy saving of LEACH is achieved by combining compression withdata routing

Key features of LEACH include:

Localized coordination and control of cluster set-up and operation

Randomized rotation of the cluster base stations or clusterheads and theirclusters

Local compression of information to reduce global communication

Energy-Efficient Communication Protocol Architecture forWireless Microsensor Networks (LEACH Protocol) [Heinzelman+ 2000, 2002]

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Considered microsensor network has the following characteristics:

The base station is fixed and located far from the sensors

All the sensor nodes are homogeneous and energy constrained

Communication between sensor nodes and the base station is expensive and nohigh energy nodes exist to achieve communication

By using clusters to transmit data to the BS, only few nodes need to transmit forlarger distances to the BS while other nodes in each cluster use small transmitdistances

LEACH achieves superior performance compared to classical clustering algorithmsby using adaptive clustering and rotating clusterheads ; assisting the total energy of

the system to be distributed among all the nodes By performing load computation in each cluster, amount of data to be transmitted to

BS is reduced. Therefore, large reduction in the energy dissipation is achievedsince communication is more expensive than computation

LEACH

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Algorithm Overview

The nodes are grouped into local clusters with one node acting as the local basestation (BS) or clusterhead (CH)

The CHs are rotated in random fashion among the various sensors

Local data fusion is achieved to compress the data being sent from clusters to the

BS; resulting the reduction in the energy dissipation and increase in the networklifetime

Sensor elect themselves to be local BSs at any any given time with a certainprobability and these CHs broadcast their status to other sensor nodes

Each node decided which CH to join based on the minimum communication energy

Upon clusters formation, each CH creates a schedule for the nodes in its clustersuch that radio components of each non-clusterhead node need to be turned OFFalways except during the transmit time

The CH aggregates all the data received from the nodes in its cluster beforetransmitting the compressed data to BS

LEACH

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Algorithm Overview

The transmission between CH and BS requires high energy transmission

In order to evenly distribute energy usage among the sensor nodes, clusterheadsare self-elected at different time intervals

The nodes decides to become a CH depending on the amount of energy it has left

The decisions to become CH are made independently of the other nodes The system can determine the optimal number of CHs prior to election procedure

based on parameters such as network topology and relative costs of computationvs. communication (Optimal number of CHs considered is 5% of the nodes)

It has been observed that nodes die in a random fashion

No communication exists between CHs Each node has same probability to become a CH

LEACH

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Algorithm Details

The operation of LEACH is achieved by rounds

Each round begins with a set-up phase (clusters are selected) followed by steady-state phase (data transmission to BS occurs)

1. Advertisement Phase: Initially, each node need to decide to become a CH for the current round based

on the suggested percentage of CHs for the network (set prior to this phase)and the number times the node has acted as a CH

The node (n) decides by choosing a random number between 0 and 1

If this random number is less than T(n), the nodes become a CH for this round The threshold is set as follows:

LEACH

1P

P1 P * (r mod )

0 OtherwiseT(n) =

If n C G P = desired percentage of CHsr = current roundG = set of nodes that have not

been CHs in the last 1/P rounds

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Algorithm Details

1. Advertisement Phase:

Assumptions are (i) each node starts with the same amount of energy and (ii)each CHs consumes relatively same amount of energy for each node

Each node elected as CH broadcasts an advertisement message to the rest

During this clusterhead -advertisement phase, the non-clusterhead nodeshear the ads of all CHs and decide which CH to join

A node joins to a CH in which it hears with its advertisement with the highest signal strength

2. Cluster Set-Up Phase:

Each node informs its clusterhead that it will be member of the cluster

3. Schedule Creation:

Upon receiving all the join messages from its members, CH creates a TDMAschedule about their allowed transmission time based on the total number ofmembers in the cluster

LEACH

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Algorithm Details

4. Data Transmission:

Each node starts data transmission to their CH based on their TDMA schedule

The radio of each cluster member nodes can be turned OFF until theirallocated transmission time comes; minimizing the energy dissipation

The CH nodes must keep its receiver ON to receive all the data

Once all the data is received, the CH compresses the data to send it to BS

Multiple Clusters

In order to minimize the radio interference between nearby clusters, each CH

chooses randomly from a list of spreading CDMA codes and it informs itscluster members to transmit using this code

The neighboring CHs radio signals will be filtered out to avoid corruption in thetransmission

LEACH

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LEACH

Disadvantages:

How to decide the percentage of cluster heads for a network? The topology,density and number of nodes of a network could be different from other networks

No suggestions about when the re-election needs to be invoked

The clusterheads farther away from the base station will use higher power and die

more quickly than the nearby ones

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LEACH

Suggestions/Improvements/Future Work:

Extensions can be included to have hierarchical clustering where each CHwill communicate with super -clusterhead until the top layer of hierarchy inwhich the data needs to be sent to BS

The degree and remaining energy of a node may be considered as

parameters to decide a clusterhead in a round. If a clusterhead with a limitedpower used up its power in a round, the data to be transmitting may be lost

Since TDMA schedule is used, a large delay may be introduced betweenevent detection and notification at base station. Therefore, the protocol is notsuitable for a real-time application

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Motivated by scaling, robustness and energy efficiency requirements Directed diffusion is data-centric in that all communication is for named data

Data generated by sensor nodes is named using attribute-value pairs

All nodes in the network are application-aware

A node requests data by sending interests for named data A sensing task is disseminated via sequence of local interactions throughout

the sensor network as an interest for named data

Nodes diffusing the interest sets up their own caches and gradients within the

network to which channel the delivery of data

During the data transmission, reinforcement and negative reinforcement areused to converge to efficient distribution

Intermediate nodes fuse interests, aggregate, correlate or cache data

Directed Diffusion [Intanagonwiwat+ 2000]

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Assumes that sensor networks are task-specific the task types are known at the

time the sensor network is deployed

An essential feature of directed diffusion is that interest, data propagation and

data aggregation are determined by local interactions

Focused on design of dissemination protocols for tasks and events

Naming

Task descriptions are named (specifies an interest for data matching the list ofattribute-value pairs) and also called as interest

Example task: Every I ms, for the next T seconds, send me a location of anyfour-legged animal in subregion R of the sensor field.

task = four-legged animal // detect animal location

interval = 20 ms // send back events every 20 ms

duration = 10 seconds // for the next 10 seconds

rect = [-100, 100, 200, 400] // from sensors within rectangle

Directed Diffusion

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Naming

A sensor detecting an animal may generate the following data:task = four-legged animal // type of animal seen

instance = horse // instance of this type

location = [150, 200] // node location

intensity = 0.5 // signal amplitude measure

confidence = 0.85 // confidence in the match

timestamp = 01:30:45 // event generation time

Interests and Gradients

Interest is generally given by the sink node

For each active task, sink periodically broadcasts an interest message to each ofits neighbors (including rect and duration attributes)

Sink periodically refreshes each interest by sending re-sending the same interestwith monotonically increasing timestamp attribute for reliability purposes

Directed Diffusion

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Every node maintains an interest cache where each item in the cachecorresponds to a distinct interest (different type , interval attributes with disjointrect attributes)

Interest entries in the cache do not contain information about the sink

In some cases, definition of distinct interests allows interest aggregation

The interest entry contains several gradient fields, up to one per neighbor

When a node receives an interest, it determines if the interest exists in the cache

1. If no matching exist, the node creates an interest entry

This entry has single gradient towards the neighbor from which theinterest was received with specified data rate

Individual neighbors can be distinguished by locally unique identifiers

2. If the interest entry exists, but no gradient for the sender of interest

Node adds a gradient with the specified value

Updates the entrys timestamp and duration fields

Directed Diffusion

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3. If there exists both entry and a gradient,The node updates the entrys timestamp and duration fields

When a gradient expires, it is removed from its interest entry

When all gradients for an interest entry have expired, the interest entry isremoved from the cache

After receiving an interest, a node may re-send the interest to subset of itsneighbors

To the neighbors, it may seem that interest originated from the sending nodeeven though it may have been generated a distant sink. This represents a localinteraction

This way, interest diffuse throughout the network and not each interest have beensent to all the neighbors if a node sent matching interest recently

Gradient specifies data rate (value) and a direction in directed diffusion, whereasthe values can be used to probabilistically forward data in different paths in othersensor networks

Directed Diffusion

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Data propagation

Data message is unicast individually to the relevant neighbors

A node receiving a data message from its neighbors checks to see if matchinginterest entry in its cache exists according the matching rules described

1. If no match exist, the data message is dropped

2. If match exists, the node checks its data cache associated with thematching interest entry

If a received data message has a matching data cache entry, the datamessage is dropped

Otherwise, the received message is added to the data cache and thedata message is re-sent to the neighbors

Data cache keeps track of the recently seen data items, preventing loops

By checking the data cache, a node can determine the data rate of the receivedevents

Directed Diffusion

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Reinforcement

After the sink starts receiving low data rate events, it reinforces one neighbor inorder to draw down higher quality (higher data rate) events

This is achieved by data driven local rules

To enforce a neighbor, the sink may re-send the original interest with higher datarate

task = four-legged animal // detect animal locationinterval = 20 ms // send back events every 20 msduration = 10 seconds // for the next 10 seconds

rect = [-100, 100, 200, 400] // from sensors within rectangle

When the data rate is higher than before, the node must also reinforce at leastone neighbor

Reinforcement can be carried out from neighbors to other neighbors in aparticular path (i.e., if a path delivers an event faster than others, sink attempts touse this path to draw down high quality data)

In Summary, reinforce one path, or part of it, based on observed losses, delayvariances, and so on

Negative reinforce certain paths because resource levels are low

Directed Diffusion

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Directed Diffusion Advantages:

Data-centric dissemination

Robust multi-path delivery

Reinforcement-based adaptation to the empirically best network path

Energy savings with in-network data aggregation and caching

Gives designers the freedom to attach different semantics to gradient values

Reinforcement can be triggered not only by sources but also by intermediatenodes


Exploration of possible naming schemes

Disadvantages:

It may consume memory since all the attribute list is being sent

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Avg. dissipated energy/packt Vs. Nw size

DD compared with flooding

NW SIZE NW SIZE

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SPIN (Sensor Protocols for Information via Negotiation) is a family of

negotiation-based information dissemination protocols which is designed to

address the deficiencies of classic flooding by negotiation and resource-

adaptation

SPIN disseminates each sensor readings to all sensors in the network,

treating all sensors as potential sink nodes

Nodes using SPIN protocols names their data using high-level data

descriptors, called meta-data and usage of meta-data negotiations

eliminate transmission of redundant data in the network Communication decisions can be based upon both application-specific

knowledge of the data and knowledge of the resources available to nodes

Negotiation-Based Protocols for Disseminating Informationin Wireless Sensor Networks (SPIN Protocols) [Kulik+ 2002]

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SPIN has two basic ideas:

Operate efficiently and conserve energy: communicate with each otherabout the sensor data received already and the data needed still

Monitor and adapt changes in their own energy resources: extend thelifetime of the system

Four difference SPIN protocols:

SPIN-PP

SPIN-EC

SPIN-BC

SPIN-RL

Meta Data

Used to uniquely and completely describe the data being collected by sensors

If two pieces of actual data are distinguishable, then their meta-data should alsobe distinguishable

Since the format of meta-data is application-specific, each application needs tointerpret and synthesize its own meta-data

SPIN

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The Problem

In conventional classic flooding, the source nodes sends data to all its neighborsand the neighbors check their record of already sent data to see if they haveforwarded the data to their neighbors. If not, they forward the data and updatethe record

This requires small amount of protocol state at any node, disseminates dataquickly in the network where neither the bandwidth is scarce and the links areerror prone

The problems include: implosion , overlap and resource blindness

Implosion: A node always sends data to its neighbors without being concerned about

if the same data has been received by the neighbors from other nodes

Overlap: The nodes waste energy and bandwidth by sending the overlapping data

Resource Blindness: Nodes do not make decisions based on the energy available

SPIN

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The Solution

SPIN provides solution to the problems of implosion and overlap by negotiatingwith each other before transmitting data eliminates the transmission ofredundant data

Nodes poll their resources before transmitting or processing data by probing theresource manager which keeps track of the resource consumption

Nodes can make efficient decisions based on the available energy level The use meta-data descriptors eliminates the possibility of overlap since the

nodes can name the part of the data the nodes are interested in receiving

Resource-awareness of local resources allow sensors to make meaningfuldecisions to extend longevity

SPIN

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SPIN Protocols

1. SPIN-PP: A Three stage handshake protocol for point-to-point media

This protocol works in three stages (ADV-REQ-DATA) with each stagecorresponding to one of the messages

The node sends ADV message to its neighbors

Neighbors check to see if they already have received or requested this data

If not, the neighbors respond by sending REQ message to the sender

The sender responds to the REQ message sent by sending the actual DATA tothe neighbors requesting the data

If the neighbor already has the advertised data, it does not send any message

Simplicity is the main strength, meaning that nodes make simple decisions,resulting in usage of small energy in computation

Each node only needs to know about its one hop neighbors

SPIN

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SPIN Protocols

2. SPIN-EC: SPIN-PP with low-energy threshold

Adds simple energy-conservation heuristic to the SPIN-PP protocol

When energy is abundant, SPIN-EC acts as SPIN-PP protocol

Whenever energy comes close to low-energy threshold, it adapts by reducing itsparticipation

The node will only participate in the full protocol if it believes that it has enoughenergy to complete the protocol without reaching below the threshold value

It does not prevent nodes from receiving messages such as ADV or REQ belowits low-energy threshold, but prevents the nodes to handle a DATA messagebelow the threshold

SPIN

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SPIN Protocols

3. SPIN-BC: A Three stage handshake protocol for broadcast media

Improves upon SPIN-PP for broadcast networks by using cheap, one-to-manycommunications, meaning that all messages are sent to broadcast address andprocessed by all the nodes that are within transmission range of the sender

This approach is often called broadcast-message-suppression

SPIN-BC has three main differences from SPIN-PP are:All SPIN-BC nodes send their messages to the broadcast address such that all nodeswithin the transmission range of sender will receive message

Upon receiving ADV message, each node checks to see if they already have the data.If not, node sets a random timer to expire, uniformly chosen from a predetermined

interval. After timer expires, the node sends an REQ message to the broadcastaddress, including the original advertiser in the header of message. When the nodeswho are not original advertiser receive the REQ, they cancel their own request timers,preventing from sending out redundant copies of the same REQ

The nodes will send out the requested data to the broadcast address only once to getthe data all its neighbors. It will not respond to multiple requests of the same data

SPIN

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SPIN Protocols

4. SPIN-RL: SPIN-BC for lossy networks

Reliable version of SPIN-BC which disseminates data through a broadcastnetwork even in the cases of network loses packets or communication isasymmetric

Adds two adjustments to SPIN-BC to achieve reliability:

Each node maintains a record of which advertisements it hears from whichnodes, and if does not receive the data within a set time after request, nodererequests the data

Nodes limit the frequency with which they will resend the data, meaningthat it will wait for a set time before responding to any additional requests

for the same data

SPIN

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SPIN Advantages:

Meta-data negotiation and resource adaptation Maintains only local information about the nearest neighbors

Suitable for mobile sensors since the nodes base their forwarding decisionson local neighborhood information


Study SPIN protocols in mobile wireless network models

Develop more sophisticated resource-adaptation protocols to use availableenergy well

Design protocols that make adaptive decisions based not only on the cost ofcommunicating data, but also the cost of synthesizing it

Disadvantages: It cannot isolate the nodes that do not want to receive information;

unnecessary power may be consumed

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References[Heinzelman+ 2002] W. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, An Application-Specific

Protocol Architecture for Wireless Microsensor Networks, IEEE Transactions on Wireless

Communications, Vol. 1, No. 4, October 2002, pp. 660-670.

[Heinzelman+ 2000] W. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, IEEE Proceedings of the HawaiiInternational Conference on System Sciences, January 4-7, 2000, Maui, Hawaii.

[Intanagonwiwat + 2000] C. Intanagonwiwat, R. Govindan and D. Estrin, Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks, In Proceedings of the Sixth AnnualInternational Conference on Mobile Computing and Networks (MobiCOM 2000), August 2000,Boston, Massachusetts

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

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