Ruting Protocol for Wsn

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    ROUTINGPROTOCOLS FOR

    WSN

    1

    UNIT V

    Created by : Neha Birla

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    2

    Data Dissemination and Gathering

    Dissemination = The act of spreading something,

    spreading, distribution.

    Gathering = Assemble or collect

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    1. Data Dissemination

    3

    Process of Distribution of data.

    Information flow from one sensor node to another.

    The originator of data is known as Source Nodeand

    Receiver of the data is calledSink nodeorGateway.

    The Sink registers itsinterestto receive the data from

    source. The Source reports the data information to the

    Sink. The information thus reported is calledevent.

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    Process of Data Dissemination

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    The node that is interested in some events, like temperature

    or air humidity, broadcasts its interests to its neighbors

    periodically. Interests are then propagated through the

    whole sensor network.

    Nodes that have requested data, send back data after

    receiving the request.

    Intermediate nodes in the sensor network also keep a cache

    of received interests and data.

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    Data Dissemination Methods

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    Flooding

    Gossiping

    SPIN

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    1.1 Flooding

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    Each node which receives a packet (queries/data) broadcasts it if

    the maximum hop-count of the packet is not reached and the node

    itself is not the destination of the packet.

    Advantage

    No costly topology maintenance or route discovery

    Disadvantages

    Implosion

    Overlapping

    Resource Blindness

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    Implosion : This is the situation When duplicate messages are

    send to the same node. This occurs when a node receives copies

    of the same messages from many of its neighbors

    7

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    Overlap : Overlap is another problem which occurs when using

    flooding. If two nodes share the same observation region both nodes

    will witness an event at the same time and transmit details of this

    event.

    Resource blindness : the flooding protocol does not consider the

    available energy at the nodes and results in many redundant

    transmissions. Hence, it reduces the network lifetime.

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    1.2 Gossiping

    Modified version of flooding

    The nodes do not broadcast a packet, but

    send it to a randomly selected neighbor.

    Avoid the problem of implosion by making

    one copy of each message at any node

    It takes a long time for message to propagate

    throughout the network.

    The hop count can become quite large due to

    the protocols random nature

    9

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    1.3 Sensor Protocols for Information via

    Negotiation

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    SPIN use negotiation and resource adaptation to address the

    disadvantage of flooding and Use meta-data instead of raw data.

    Reduce overlap and implosion, and prolong network lifetime.

    SPIN-1 has three types of messages: ADV, REQ, and DATA.

    SPIN-2 using an energy threshold to reduce participation. A node

    may join in the ADV-REQ-DATA handshake only if it has

    sufficient resource above a threshold.

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    11

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    2. Data Gathering

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    The objective of the data gathering problem is to transmit the

    sensed data from each sensor node to a BS.

    The goal of algorithm which implement data gathering is

    maximize the lifetime of network

    Minimum energy should be consumed

    The transmission occur with minimum delay

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    Difference between Data Dissemination

    and Gathering

    13

    Data Dissemination Data Gathering

    1 Any node can request the

    data along with base station.

    All data is transmitted to the

    base station

    2 Data is always transmitted

    on demand

    Data can be transmitted

    periodically

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    Data Gathering Approaches

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    Direct Transmission

    Power-Efficient Gathering for Sensor Information Systems

    Binary Scheme

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    2.1 Direct Transmission

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    All sensor nodes transmit their data directly to the BS.

    It cost expensive when the sensor nodes are very far from the BS.

    Nodes must take turns while transmitting to the BS to avoid

    collision, so the media access delay is also large. Hence, this

    scheme performs poorly with respect to the energy x delay metric.

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    2.2 Power-Efficient Gathering for Sensor

    Information Systems

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    PEGASIS based on the assumption that all sensor nodes know the

    location of every other node.

    Any node has the required transmission range to reach the BS in

    one hop, when it is selected as a leader.

    The goal of PEGASIS are as following

    Minimize the distance over which each node transmit

    Minimize the broadcasting overhead

    Minimize the number of messages that need to besent to the BS

    Distribute the energy consumption equally across all nodes

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    To construct a chain of sensor nodes, starting from the node

    farthest from the BS. At each step, the nearest neighbor which has

    not been visited is added to the chain.

    This algorithm uses greedy algorithm for chain construction.

    Before first round of communication chain formation is done

    During formation of chain care must be taken so that nodes

    already in chain should not revisited

    It is reconstructed when nodes die out.

    At every node, data fusion or aggregation is carried out.

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    A node which is designated as the leader finally transmits one

    message to the BS.

    Leadership is transferred in sequential order.

    The delay involved in messages reaching the BS is O(N)

    18

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    Figure 5 : Data gathering with PEGASIS

    19

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    2.3 Binary Scheme

    This is a chain-based scheme like PEGASIS, which classifies

    nodes into different levels.

    This scheme is possible when nodes communicate using CDMA,

    so that transmissions of each level can take place simultaneously.

    The delay is O(log2N)

    20

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    Advantages

    Low delay of only O(log2N), where the N is the amountof

    nodes.

    Disadvantages

    Non equal distribution of energy consumption, nodes that are

    active on several levels consume more energy than nodes that

    are only active at the first level. This might lead to the

    situation where some of sensor nodes die earlier than others.

    Transmission distances may become long in high levels,

    which leads to a high power consumption

    21

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    Routing Challenges and Design

    Issues in WSN

    The design of routing protocols in WSNs is influenced bymany challenging factors. These factors must be overcome

    before efficient communication can be achieved in WSNs.

    Node deployment Energy considerations

    Data delivery model

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    Node/link heterogeneity Fault tolerance

    Scalability

    Network dynamics

    Transmission media

    Connectivity

    Coverage

    Data aggregation/converge cast

    Quality of service

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    Node Deployment

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    Node deployment in WSNs isapplication dependent and affects

    the performance of the routing protocol.

    The deployment can be eitherdeterministicorrandomized.

    In deterministic deployment, the sensors are manually placed and

    data is routed through pre-determined paths.

    In random node deployment, the sensor nodes are scattered

    randomly creating an infrastructure in an ad hoc manner.

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    Energy Considerations

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    Sensor nodes can use up their limited supply of energy performing

    computations and transmitting information in a wireless

    environment. Energy conserving forms of communication and

    computation are essential.

    In a multi-hop WSN, each node plays a dual role asdata sender

    and data router. The malfunctioning of some sensor nodes due to

    power failure can cause significant topological changes and might

    require rerouting of packets and reorganization of the network.

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    Data Delivery Model

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    Time-driven (continuous)

    Suitable for applications that require periodic data monitoring

    Event-driven

    React immediately to sudden and drastic changes

    Query-driven

    Respond to a query generated by the BS or another node in the

    network

    Hybrid

    The routing protocol is highly influenced by the data reporting method

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    Node/Link Heterogeneity

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    Depending on the application, a sensor node can have a

    different role or capability.

    The existence of aheterogeneous set of sensors raises many

    technical issues related to data routing.

    Even data reading and reporting can be generated from these

    sensors at different rates, subject to diverse QoS constraints,

    and can follow multiple data reporting models.

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    Fault Tolerance

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    Some sensor nodes may fail or be blocked due to lack of power,

    physical damage, or environmental interferences

    It may require actively adjusting transmission powers and

    signaling rates on the existing links to reduce energy

    consumption, or rerouting packets through regions of the

    network where more energy is available

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    Scalability

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    The number of sensor nodes deployed in the sensing area may

    be on the order of hundreds or thousands, or more.

    Any routing scheme must be able to work with this huge

    number of sensor nodes.

    In addition, sensor network routing protocols should be

    scalable enough to respond to events in the environment.

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    Network Dynamics

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    Routing messages from or to moving nodes is more

    challenging since route and topology stability become

    important issuesMoreover, the phenomenon can be mobile (e.g., a

    target detection/ tracking application).

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    Transmission Media

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    In general, the required bandwidth of sensor data will be low,

    on the order of 1-100 kb/s. Related to the transmission media is

    the design of MAC.TDMA (time-division multiple access)

    CSMA (carrier sense multiple access)

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    Connectivity

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    High node density in sensor networks precludes them from

    being completely isolated from each other.

    However, may not prevent the network topology from being

    variable and the network size from shrinking due to sensor

    node failures.

    In addition, connectivity depends on the possibly random

    distribution of nodes.

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    Coverage

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    In WSNs, each sensor node obtains a certain view of theenvironment.

    A given sensors view of the environment is limited in both

    range and accuracy.

    It can only cover a limited physical area of the environment.

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    Data Aggregation/Convergecast

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    Since sensor nodes may generate significant redundant data,

    similar packets from multiple nodes can be aggregated to

    reduce the number of transmissions.

    Data aggregation is the combination of data from different

    sources according to a certain aggregation function.

    Converge casting is collecting information upwardsfrom the

    spanning tree after a broadcast.

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    Quality of Service

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    In many applications,conservation of energy, which is directly

    related to network lifetime.

    As energy is depleted, the network may be required to reduce

    the quality of results in order to reduce energy dissipation in

    the nodes and hence lengthen the total network lifetime.

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    Routing Protocols in WSNs: A taxonomy

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    Network Structure Protocol Operation

    Flat routing SPIN

    Directed Diffusion (DD)

    Hierarchical routing LEACH

    PEGASIS

    TTDD

    Location based routing GEAR GPSR

    Negotiation based routing SPIN

    Multi-path network routing DD

    Query based routing DD, Data centric routing

    QoS based routing TBP, SPEED

    Coherent based routing DD

    Aggregation Data Mules, CTCCAP

    Routing protocols in WSNs

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    Routing Strategies inWSN

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    Routing Strategies

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    Aim to make communication more efficient

    Trade-off between routing overhead and datatransmission cost

    Strategies incur differing levels of communicationand storage overhead

    Hybrid approaches are possible

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    Proactive and Reactive Routing

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    Proactive routing Routes created and maintained in advance

    E.g : LEACH protocol

    Does not scale to large networks

    Reactive routing

    Routes created and cached as required

    E.g : TEEN protocol

    Dynamic delays

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    Geographic and Energy Aware Routing

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    Motivation: Reduce overhead of interest and low rate data flooding in directed

    diffusion

    Basic ideas: Leverage geographical information to restrict flooding, and

    recursively disseminate data inside the target region.

    Extend overall network lifetime using local techniques tobalanceenergy usage

    Reuse routing information across multiple user queries.

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    Geographic and Energy Aware Routing

    Forward the packets towards thetarget region: Greedy mode: minimizing cost

    function (f=mix function of distanceand energy)

    Route around communicationholes with energy aware neighborestimation

    Disseminate the packet within thetarget region:

    Geographic Recursive Forwarding recursively re-send packets to sub-

    regions of the original geographicregion

    41

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    Geographic and Energy Aware Routing

    Each node has a learned cost(historical cost) and anestimated cost (present statecost) to decide the next

    forwarding node Learned cost

    Estimated cost

    min min( , ) ( , ) ( , )h N R h N R C N N

    ( , ) ( , ) (1 ) ( )i i i

    c N R d N R e N

    42

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    G P S R : G R E E D Y P E R I M E T E R S T A T E L E S S

    R O U T I N G F O R W I R E L E S S N E T W O R K S

    43

    Geographic Routing

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    Motivation

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    A sensor net consists of hundreds or thousands of nodes Scalability is the issue

    Existing ad hoc net protocols, e.g., DSR, AODV, ZRP, require nodesto cache e2e route information

    Dynamic topology changes Mobility

    Reduce caching overhead

    Hierarchical routing is usually based on well defined, rarely changingadministrative boundaries

    Geographic routing

    Use location for routing

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    Scalability metrics

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    Routing protocol msg cost How many control packets sent?

    Per node state

    How much storage per node is required?

    E2E packet delivery success rate

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    Assumptions

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    Every node knows its location Positioning devices like GPS

    Localization

    A source can get the location of the destination

    802.11 MAC

    Link bidirectionality

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    Geographic Routing: Greedy Routing

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    SD

    Closest to D

    A

    - Find neighbors who are the closer to the destination

    - Forward the packet to the neighbor closest to the destination

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    Benefits of GF

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    A node only needs to remember the location info ofone-hop neighbors

    Routing decisions can be dynamically made

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    Greedy Forwarding does NOT always work

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    If the network is dense enough that each interiornode has a neighbor in every 2/3 angular sector,GF will always succeed

    GF fails

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    Energy-Aware Routing

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    Maximise network lifetime (no accepted definition) Communication is the most expensive activity Possible goals include:

    Shortest-hop (fewest nodes involved) Lowest energy route Route via highest available energy Distribute energy burden evenly Lowest routing overhead

    Distributed algorithms cost energy Changing component state costs energy

    NOTE: Read Routing Strategies PPTs after this

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    Energy-Aware Routing

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    A destination-initiated reactive protocol

    It maintains a set of paths

    Choosing paths by means of certain probability

    depending on how low the energy consumption is

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    Energy-Aware Routing

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    Setup Phase

    Controller

    Sensor

    Directional flooding

    10 nJ

    30 nJ

    p1= 0.75

    p2= 0.25

    Local Rule

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    Energy-Aware Routing

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    Data Communication Phase

    1.0 1.0

    0.6

    0.4

    Controller

    Sensor0.3

    0.7

    Each node makes

    a local decision

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    Attribute-based routing

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    Data-centric approach: Not interested in routing to a particular node or a particular location

    Nodes desiring some information need to find nodes that have thatinformation

    Attribute-value event record, and associated query

    type animal

    instance horse

    location 35,57

    time 1:07:13

    type animal

    instance horse

    location 0,100,100,200

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    Directed diffusion

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    Sinks: nodes requesting information Sources: nodes generating information

    Interests: records indicating A desire for certain types of information

    Frequency with which information desired

    Key assumption: Persistence of interests

    Approach:

    Learn good paths between sources and sinks

    Amortize the cost of finding the paths over period of use [IGE00]

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    Diffusion of interests and gradients

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    Interests diffuse from the sinks through the sensornetwork

    Nodes track unexpired interests

    Each node maintains an interest cache Each cache entry has a gradient

    Derived from the frequency with which a sink requests repeateddata about an interest

    Sink can modify gradients (increase or decrease) depending on

    response from neighbors

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    Attribute based Routing

    Directed Diffusion

    Rumor Routing

    Geographic hash table

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