Wsn routing protocol

WSN – Routing Protocols
Dr.N.Suganthi
Assistant Professor
Dept. of CSE

Routing challenges and design issues in WSN –
Data dissemination and Gathering – Flooding –
Flat based routing – SAR – Directed diffusion –
MCFA coherent processing – non coherent
processing – Hierarchical routing – LEACH,
TEEN, APTEEN,PEGASIS – Query based
routing – Negotiation based routing –
Geographical based routing – routing protocol
simulation in Contiki OS – RPL objective
function – RPL for Low-power and Lossy
network

Routing challenges and design issues
in WSN
• Although WSNs share many commonalities with wired and
ad hoc networks, they also exhibit a number of unique
characteristics which set them apart from existing networks.
• These unique characteristics bring to sharp focus new
routing design requirements that go beyond those typically
encountered in wired and wireless ad hoc networks.
• Meeting these design requirements presents a distinctive
and unique set of challenges.
• These challenges can be attributed to multiple factors,
including severe energy constraints, limited computing and
communication capabilities, the dynamically changing
environment within which sensors are deployed, and unique
data traffic models and application-level quality of service
requirements.

in WSN
• Network Scale and Time-varying characteristics
• Sensor nodes operate with limited computing, storage, and
communication capabilities under severe energy constraints.
• the densities of the WSNs may vary widely, ranging from very sparse
to very dense.
• in many applications, the sensor nodes, are deployed in an ad hoc and
often unsupervised manner over wide coverage areas.
• In these networks, the behavior of sensor nodes is dynamic and highly
adaptive,
• need to self-organize and conserve energy forces sensor nodes to adjust
their behavior constantly in response to their current level of activity.
• Furthermore, sensor nodes may be required to adjust their behavior in
response to the erratic and unpredictable behavior of wireless
connections caused by high noise levels and radio-frequency
interference, to prevent severe performance degradation of the
application supported.

in WSN
• Resource Constraints
• Energy is a key concern in WSNs, which must achieve a long
lifetime while operating on limited battery reserves.
• Multihop packet transmission over wireless networks is a major
source of power consumption.
• Reducing energy consumption can be achieved by dynamically
controlling the duty cycle of the wireless sensors.
• The energy management problem, however, becomes especially
challenging in many mission-critical sensor applications. The
requirements of these applications are such that a predetermined
level of sensing and communication performance constraints must
be maintained simultaneously.
• Therefore, a question arises as to how to design scalable routing
algorithms that can operate efficiently for a wide range of
performance constraints and design requirements.
• The development of these protocols is fundamental to the future of
WSNs.

in WSN
• Sensor Applications Data Models
• The data model describes the flow of information between the sensor nodes
and the data sink. These models are highly dependent on the nature of the
application in terms of how data are requested and used.
• Several data models have been proposed to address the data-gathering needs
and interaction requirements of a variety of sensor applications.
• A class of sensor applications requires data collection models that are based on
periodic sampling or are driven by the occurrence of specific events.
• In other applications, data can be captured and stored, possibly processed and
aggregated by a sensor node, before they are forwarded to the data sink.
• Some class of sensor applications requires bidirectional data models in which
two-way interaction between sensors and data sinks is required .
• The need to support a variety of data models increases the complexity of the
routing design problem.
• Optimizing the routing protocol for an application’s specific data requirements
while supporting a variety of data models and delivering the highest
performance in scalability, reliability, responsiveness, and power efficiency
becomes a design and engineering problem of enormous magnitude.

Data Dissemination and Gathering
• Methods to communicate data between base station(sink node)
and sensor node
– Single hop
– Multi hop

• Single hop
– Node exchange data directly with base station
– It is costly, as nodes that are farther away from the
base station may deplete their energy reserves quickly,
thereby severely limiting the lifetime of the network.
– Cases
– WSNs deployed to cover large geographical area.
- sensor nodes are mobile and hence move away from
base station

• Multi hop
• data exchange between the sensors and the base stations is usually
carried out using multihop packet transmission over short
communication radius.
• leads to significant energy savings and reduces considerably
communication interference between sensor nodes competing to
access the channel, particularly in highly dense WSNs.
• In response to queries issued by the sinks or when specific events
occur within the area monitored, data collected by the sensors are
transmitted to the base station using multihop paths.
• In a multihop WSN, intermediate nodes must participate in
forwarding data packets between the source and the destination.
• Determining which set of intermediate nodes is to be selected to
form a data-forwarding path between the source and the destination
is the principal task of the routing algorithm.

Flooding
• Flooding is a common technique frequently used for path
discovery and information dissemination in wired and
wireless ad hoc networks.
• Flooding uses a reactive approach whereby each node
receiving a data or control packet sends the packet to all its
neighbors.
• After transmission, a packet follows all possible paths.
Unless the network is disconnected, the packet will
eventually reach its destination.
• Furthermore, as the network topology changes, the packet
transmitted follows the new routes.
• flooding in its simplest form may cause packets to be
replicated indefinitely by network nodes.

Flooding
• To prevent a packet from circulating indefinitely in the network,
• Hop Count
– a hop count field is usually included in the packet.
– Initially, the hop count is set to approximately the diameter of the network.
– As the packet travels across the network, the hop count is decremented by one
for each hop that it traverses.
– When the hop count reaches zero, the packet is simply discarded.
• time-to-live field,
– which records the number of time units that a packet is allowed to live within
the network.
– At the expiration of this time, the packet is no longer forwarded.
• Flooding can be further enhanced by identifying data packets uniquely,
forcing each network node to drop all the packets that it has already
forwarded.
• Such a strategy requires maintaining at least a recent history of the traffic,
to keep track of which data packets already been forwarded.

Flooding
• flooding suffers several deficiencies when used in WSNs.
• The first drawback of flooding is its susceptibility to traffic implosion.
• This undesirable effect is caused by duplicate control or data packets being
sent repeatedly to the same node.

Flooding
• The second drawback naive of flooding is overlap problem.
• Overlapping occurs when two nodes covering the same region send packets
containing similar information to the same node.

Flooding
• The third and most severe drawback of
flooding is resource blindness.
• The simple forwarding rule that flooding uses
to route packets does not take into
consideration the energy constraints of the
sensor nodes.
• As such, the node’s energy may deplete
rapidly, reducing considerably the lifetime of
the network.

Flooding
• To address the shortcomings of flooding, a derivative approach, referred to
as gossiping, has been proposed.
• Similar to flooding, gossiping uses a simple forwarding rule and does not
require costly topology maintenance or complex route discovery
algorithms.
• Contrary to flooding, where a data packet is broadcast to all neighbors,
gossiping requires that each node sends the incoming packet to a randomly
selected neighbor.
• Upon receiving the packet, the neighbor selected randomly chooses one of
its own neighbors and forwards the packet to the neighbor chosen.
• This process continues iteratively until the packet reaches its intended
destination or the maximum hop count is exceeded.
• Gossiping avoids the implosion problem by limiting the number of packets
that each node sends to its neighbor to one copy.
• The latency that a packet suffers on its way to the destination may be
excessive, particularly in a large network.

Negotiation Based Routing
• Sensor Protocols for Information via Negotiation (SPIN) is a family of negotiation-
based, data-centric, and time-driven flooding protocols.
• However, compared to classic flooding, SPIN nodes rely on two key techniques to
overcome the deficiencies of flooding.
• To address the problems of implosion and overlap, SPIN nodes negotiate with their
neighbors before they transmit data, allowing them to avoid unnecessary
communications.
• To address the problem of resource blindness, each SPIN node uses a resource
manager to keep track of actual resource consumption, allowing them to adapt
routing and communication behavior based on resource availability.
• SPIN uses meta-data to succinctly and completely describe the data collected by
sensor nodes. To ensure that the meta-data is useful for SPIN, a key requirement is
that if x describes the meta-data for some sensor data X, the size of x (in bytes) must
be less than the size of X.
• Further, two identical pieces of sensor data should have the same meta-data
representation. Similarly, if two pieces of sensor data differ, their meta-data
representations should differ too.

SPIN -PP
• SPIN-PP, is optimized for networks using point-to point
transmission media, where two nodes can communicate exclusively
with each other without interference from other nodes.
• In SPIN-PP, data is flooded in three steps via a 3-way handshake
protocol.
• First, when new data arrives, a node advertises this event using an
advertisement message (ADV) to its neighbors via the data’s meta-
data.
• Upon receiving an advertisement, a node checks whether it has
already received the described sensor data. If not, the node responds
with a request for data (REQ) message, indicating its desire to
receive the advertised data.
• Finally, the sender node responds to the REQ message with a DATA
message, containing the advertised data.

SPIN -PP
• A key strength of this protocol is its simplicity and nodes only need
to know their single-hop neighbors to run this protocol.
• While this protocol has been designed for lossless environments
with symmetric communication links, nodes could compensate for
lost ADV messages by periodically readvertising their data and for
lost REQ and DATA messages by rerequesting data of interest if
such data does not arrive within certain timeout intervals.
• As an alternative, the protocol could be modified to use explicit
acknowledgments.
• For example, REQ messages could contain explicit lists of data that
a node wants or does not want to receive. Based on the list, a node
can identify if previous advertisements were successfully received
by the neighbor.

SPIN - EC
• A variation of SPIN-PP protocol, called SPIN-EC, adds a simple
heuristic to add energy conservation to the SPIN-PP protocol.
• As long as all nodes have sufficient energy, they participate in the
three-way handshake of the SPIN-PP protocol.
• However, once the energy of a node approaches a specific low-
energy threshold, it becomes more selective in its participation in the
protocol. That is, a node should only participate in the three-way
handshake if it believes that it can complete all stages of the
protocol without falling below the energy threshold.
• Therefore, a node replies to an advertisement only if it has sufficient
energy to transmit the request and receive the requested data.
• Similarly, a node initiates the three-way handshake with its
neighbors only if it believes that it can complete the protocol even if
all neighbors request a copy of the data.

SPIN - BC
• SPIN-BC uses the characteristics of broadcast transmission. In broadcast transmission,
every message sent by a sender will be received by all nodes within the sender’s radio
range.
• SPIN-BC uses cheap, one-to-many communications and nodes can coordinate their
resource-conserving efforts more effectively because they are able to overhear all
transactions within their radio ranges.
• The SPIN-BC uses a three-way handshake consisting of ADV, REQ, and DATA
messages, but with three central differences compared to the approaches taken by SPIN-
PP:
1. All messages are directed to the broadcast message, that is, all nodes within a sender’s
transmission range will receive a copy of the message.
2. Upon receiving an ADV message, a node checks whether it wishes to receive a copy of
the advertised data, and if so, sets a random timer, uniformly chosen from a
predetermined interval. Only after the timer expires, the node issues the REQ message,
again to the broadcast address (specifying the identity of the sender of the ADV message
in the message header). When a node overhears the REQ message before its own timer
expires, the node cancels its timer and does not send its own REQ message.
3. The advertiser transmits the advertised data to the broadcast address only once, that is,
it will ignore duplicate REQ messages for the same data.
• The random timer is necessary to avoid collisions of REQ messages from different
neighbors and to allow nodes to avoid REQ transmissions when another node has already
transmitted an REQ.
• The consequence of this approach is that the number of transmissions can be significantly
reduced, for example, for each transmission, a node needs only to transmit a single ADV
message and a single copy of the DATA message.

SPIN-RL
• The final variant of the SPIN protocol is SPIN-RL, a reliable version
of SPIN-BC, addressing packet loss and asymmetric
communications.
• First, each node keeps track of overheard REQ messages and if it
does not receive a corresponding DATA message within a certain
timeout interval, it assumes that either the REQ message or the
DATA message did not arrive.
• In this case, the node rerequests the data by broadcasting an REQ
message, specifying the identity of a randomly selected node among
the nodes that previously advertised this data in the message header.
• In addition, SPIN-RL limits the frequency with which DATA
messages are sent out. That is, once a node sends a DATA message,
it will wait a predetermined time before responding to any other
requests for the same data.

Directed Diffusion
• Directed diffusion is another data-centric data
dissemination protocol that is also application-
aware in that data generated by sensor nodes is
named by attribute-value pairs.
• The main idea of directed diffusion is that nodes
request data by sending interests for named data.
• This interest dissemination sets up gradients
within the network that are used to direct sensor
data toward the recipient, and intermediate nodes
along the data paths can combine data from
different sources to eliminate redundancy and
reduce the number of transmissions.

Directed Diffusion
• Directed diffusion does not rely on globally valid node identifiers,
but instead uses attribute-value pairs to describe a sensing task and
to steer the routing process.
• For example, a description for a simple vehicle-tracking application
could be:
type = vehicle // detect vehicle location
interval = 20 ms // send data every 20 ms
duration = 10 s // perform task for 10 s
rect = [-100,-100,200,200] // from sensors within rectangle
• That is, a task description expresses a node’s desire (or interest) to
receive data matching the provided attributes.
• The data sent in response to such interests is also named in the same
manner, that is, using attribute-value pairs.

Directed Diffusion
• A sink node periodically broadcasts an interest message to its
neighbors, which continue to broadcast the message throughout the
network.
• Each node establishes a gradient toward the sink node, where a
gradient is a reply link toward the neighbor from which the interest
was received. As a consequence, using interests and gradients, paths
between event sources and sinks can be established.
• Once a source begins to transmit data, it can use multiple paths for
transmission toward the sink. The sink can then reinforce one
particular neighbor based on some data-driven local rule.
• The concept of reinforcement is used to update a node’s interest
along a particular path. For example, suppose the sink wants more
frequent updates from the sensors, which have detected an event. It
reinforces the path by sending an interest with a higher data-rate
requirement, in effect increasing the gradient of that path. On the
other hand, if the sink needs only fewer updates, it applies negative
reinforcement by sending an interest of lower required data-rate.

Directed Diffusion
• Directed diffusion differs from SPIN in that queries
(interests) are issued on demand by the sinks and not
advertised by the sources as in SPIN.
• Based on the process of establishing gradients, all
communication is neighbor-to-neighbor, removing the need
for addressing schemes and allowing each node to perform
aggregation and caching of sensor data, both of which can
contribute to reduced energy consumption.
• Finally, directed diffusion is a query-based protocol, which
may not be a good choice for certain sensor network
applications, particularly where continuous data transfers
are required (e.g., environmental monitoring applications).

Sequential Assignment Routing
• One of the first routing protocols to explicitly consider Quality-of-
Service is the Sequential Assignment Routing (SAR) protocol,
which is also an example of a multipath routing approach.
• The sequential assignment routing (SAR) algorithm creates multiple
trees, where the root of each tree is a one-hop neighbor of the sink.
• Each tree grows outward from the sink and avoids nodes with low
throughput or high delay.
• At the end of the procedure, most nodes belong to multiple trees.
• The trees rooted at A and B , two of the one-hop neighbors of the
sink, are shown.
• Node C belongs to both trees, and has path lengths of 3 and 5,
respectively, to the sink, using the two trees.
• Each sensor node records two parameters about each path through it:
the available energy resources on the path and an additive QoS
metric such as delay.

Sequential Assignment Routing
• This allows a node to choose one path from among many to relay its
message to the sink.
• The SAR algorithm chooses a path with high estimated energy
resources, and provisions can be made to accommodate packets of
different priorities.
• A weighted QoS metric is used to handle prioritized packets, which
is computed as a product of priority level and delay. The routing
ensures that the same weighted QoS metric is maintained.
• Thus, higher priority packets take lower delay paths, and lower
priority packets have to use the paths of greater delay. For example,
if node C generates a packet of priority 3, it follows the longer path
along tree B , and a packet of priority 5 (higher priority) will follow
the shorter path along tree A , so that the priority °ø delay QoS
metric is maintained.
• SAR minimizes the average weighted QoS metric over the lifetime
of the network.
• The sink periodically triggers a metric update to reflect the changes
in available energy resource after some transmissions.

Minimum Cost Forwarding Algorithm
• The MCFA algorithm exploits the fact that the direction of routing is
always known, that is, towards the fixed external base-station.
• Hence, a sensor node need not have a unique ID nor maintain a
routing table. Instead, each node maintains the least cost estimate
from itself to the base-station.
• Each message to be forwarded by the sensor node is broadcast to its
neighbors.
• When a node receives the message, it checks if it is on the least cost
path between the source sensor node and the base-station.
• If this is the case, it re-broadcasts the message to its neighbors. This
process repeats until the base-station is reached.

Minimum Cost Forwarding Algorithm
• In MCFA, each node should know the least cost path estimate from itself to the
base-station.
• This is obtained as follows.
• The base-station broadcasts a message with the cost set to zero while every node
initially set its least cost to the base-station to infinity.
• Each node, upon receiving the broadcast message originated at the base-station,
checks to see if the estimate in the message plus the link on which it is received is
less than the current estimate.
• If yes, the current estimate and the estimate in the broadcast message are updated.
• If the received broadcast message is updated, then it is re-sent; otherwise, it is
purged and nothing further is done.
• However, the previous procedure may result in some nodes having multiple updates
and those nodes far away from the base-station will get more updates from those
closer to the base-station.
• To avoid this, the MCFA was modified to run a backoff algorithm at the setup
phase.
• The backoff algorithm dictates that a node will not send the updated message until a
* lc time units have elapsed from the time at which the message is updated, where a
is a constant and lc is the link cost from which the message was received.

Coherent and non-coherent Data
Processing
• Data processing is a major component in the operation of wireless
sensor networks.
• Hence, routing techniques employ different data processing
techniques. In general, sensor nodes will cooperate with each other
in processing different data flooded in the network area.
• Two examples of data processing techniques proposed in WSNs are
coherent and non-coherent data processing-based routing.
• In non-coherent data processing routing, nodes will locally process
the raw data before being sent to other nodes for further processing.
The nodes that perform further processing are called the
aggregators.
• In coherent routing, the data is forwarded to aggregators after
minimum processing. The minimum processing typically includes
tasks like time stamping, duplicate suppression, etc.
• To perform energy-efficient routing, coherent processing is normally
selected.

Coherent and non-coherent Data
Processing
• Non-coherent functions have fairly low data traffic loading. On the
other hand, since coherent processing generates long data streams,
energy efficiency must be achieved by path optimality.
• In non-coherent processing, data processing incurs three phases:
• (1) Target detection, data collection, and preprocessing
• (2) Membership declaration, and
• (3) Central node election.
• During phase 1, a target is detected, its data collected and
preprocessed. When a node decides to participate in a cooperative
function, it will enter phase 2 and declare this intention to all
neighbors. This should be done as soon as possible so that each
sensor has a local understanding of the network topology.
• Phase 3 is the election of the central node. Since the central node is
selected to perform more sophisticated information processing, it
must have sufficient energy reserves and computational capability.

Rumor Routing
• While the classic flooding approach can be described as event flooding (i.e.,
a source propagates its sensor data via an event throughout the network),
query flooding describes the process used to propagate queries to all nodes
in the network when no localization information is available to steer the
query toward the appropriate sensors.
• In rumor routing, each node maintains a list of its neighbors and an event
table that contains forwarding information to all known events.
• Once a node witnesses an event (i.e., a phenomenon in the physical world),
the event is added to this table (including a distance of zero) and an agent is
generated with a certain probability (i.e., not all events may result in an
agent generation).
• This agent is a long-lived packet that travels the network to propagate
information about this event and other events encountered along its route to
remote nodes.
• Once an agent arrives at a node, the node can use the agent’s content to
update its own table.

Rumor Routing
• For example, in Figure (a) , the table for node A pointing toward events E1 and E2
is shown, before the arrival of an agent originating at node E.
• When the agent arrives at node A (via node G), A sees that E1 can be reached via
neighbor G using a shorter route than currently stored in its table. It therefore
updates its table with the newly obtained information from E’s agent.

Rumor Routing
• When a node wants to issue a query targeted at a specific event, it first
checks whether it has a route toward the target event.
• If so, it forwards the query to the neighbor indicated by the event’s table
entry.
• If there is no route, a random neighbor is selected and the query is passed to
this neighbor.
• This process is continued on each node, where the query message collects a
list of recently seen nodes to avoid revisiting them.
• Both agent and query messages use a time-to-live (TTL) counter value that
is decremented at each hop and a message is only forwarded if this counter
value is greater than zero.
• Note that even though a node may not know the direction of the target
event, by forwarding it to a random neighbor, the query may be able to
come to a node that has an entry for the desired event.
• Since it is possible that the query may not reach the target event, the
querying node can use another technique, for example, flooding the query,
when no response is received after a certain timeout value (which depends
on the TTL value).

Rumor Routing
• Rumor routing uses a query-based approach, it
attempts to route queries to only the nodes that
have observed a particular event rather than
flooding the entire network.
• Rumor routing is not concerned with latency,
instead a nonoptimal route is satisfactory.
• Further, a node’s table size grows with the
number of events it is aware of, therefore, in
networks with many events, the cost of storing
and maintaining such tables may pose a problem.

Hierarchical Routing
• LEACH (Low Energy Adaptive Clustering
Hierarchy)
• PEGASIS(Power Efficient Gathering in Sensor
Information Systems)
• TEEN(Threshold-sensitive Energy Efficient sensor
Network protocol)
• APTEEN(Adaptive Periodic Threshold-sensitive
Energy Efficient sensor Network protocol)

LEACH
• Low-energy adaptive clustering hierarchy
(LEACH) is a routing algorithm designed to
collect and deliver data to the data sink, typically
a base station.
• The main objectives of LEACH are:
– Extension of the network lifetime
– Reduced energy consumption by each network sensor
node
– Use of data aggregation to reduce the number of
communication messages

LEACH
• LEACH adopts a hierarchical approach to organize the network into a set
of clusters.
• Each cluster is managed by a selected cluster head. The cluster head
assumes the responsibility to carry out multiple tasks.
• The first task consists of periodic collection of data from the members of
the cluster. Upon gathering the data, the cluster head aggregates it in an
effort to remove redundancy among correlated values.
• The second main task of a cluster head is to transmit the aggregated data
directly to the base station. The transmission of the aggregated data is
achieved over a single hop.
• The third main task of the cluster head is to create a TDMA-based schedule
whereby each node of the cluster is assigned a time slot that it can use for
transmission.
• The cluster head advertises the schedule to its cluster members through
broadcasting.
• To reduce the likelihood of collisions among sensors within and outside the
cluster, LEACH nodes use a code-division multiple access–based scheme
for communication.

LEACH
• The basic operations of LEACH are organized in
two distinct phases.
• The first phase, the setup phase, consists of two
steps, cluster-head selection and cluster
formation.
• The second phase, the steady-state phase, focuses
on data collection, aggregation, and delivery to
the base station.
• The duration of the setup is assumed to be
relatively shorter than the steady-state phase to
minimize the protocol overhead.

LEACH
• At the beginning of the setup phase, a round of cluster-head
selection starts.
• The cluster-head selection process ensures that this role rotates
among sensor nodes, thereby distributing energy consumption
evenly across all network nodes.
• To determine if it is its turn to become a cluster head, a node, n,
generates a random number, v, between 0 and 1 and compares it to
the cluster-head selection threshold.
• The node becomes a cluster head if its generated value, v, is less
than threshold.
• The cluster-head selection threshold is designed to ensure with high
probability that a predetermined fraction of nodes, P, is elected
cluster heads at each round.
• Further, the threshold ensures that nodes which served in the last 1/P
rounds are not selected in the current round.

LEACH
• At the completion of the cluster-head selection process, every node that
was selected to become a cluster head advertises its new role to the rest of
the network.
• Upon receiving the cluster-head advertisements, each remaining node
selects a cluster to join. The selection criteria may be based on the received
signal strength, among other factors. The nodes then inform their selected
cluster head of their desire to become a member of the cluster.
• Upon cluster formation, each cluster head creates and distributes the
TDMA schedule, which specifies the time slots allocated for each member
of the cluster.
• Each cluster head also selects a CDMA code, which is then distributed to
all members of its cluster. The code is selected carefully so as to reduce
intercluster interference.
• The completion of the setup phase signals the beginning of the steady-state
phase.
• During this phase, nodes collect information and use their allocated slots to
transmit to the cluster head the data collected. This data collection is
performed periodically.

LEACH
• LEACH suffers several shortcomings.
• The assumption that all nodes can reach the base station in one hop
may not be realistic, as capabilities and energy reserves of the nodes
may vary over time from one node to another.
• Furthermore, the length of the steady-state period is critical to
achieving the energy reduction necessary to offset the overhead
caused by the cluster selection process.
• A short steady-state period increases the protocol’s overhead,
whereas a long period may lead to cluster head energy depletion.
• Several algorithms have been proposed to address these
shortcomings.
• The extended LEACH (XLEACH) protocol takes into consideration
the node’s energy level in the cluster-head selection process.

LEACH
• LEACH exhibits several properties which enable the protocol to reduce
energy consumption.
• Energy requirement in LEACH is distributed across all sensor nodes, as
they assume the cluster head role in a round-robin fashion based on their
residual energy.
• LEACH is a completely distributed algorithm, requiring no control
information from the base station.
• The cluster management is achieved locally, which obliterates the need for
global network knowledge.
• Furthermore, data aggregation by the cluster also contributes greatly to
energy saving, as nodes are no longer required to send their information
directly to the sink.
• It has been shown using simulation that LEACH outperforms conventional
routing protocols, including direct transmission and multihop routing,
minimum-transmission-energy routing, and static clustering–based routing
algorithms.

PEGASIS
• PEGASIS - Power-Efficient Gathering in Sensor
Information Systems.
• PEGASIS is a routing and information gathering
protocol used in WSN.
• The main objectives of PEGASIS are twofold.
• First, the protocol aims at extending the lifetime
of a network by achieving a high level of energy
efficiency and uniform energy consumption
across all network nodes.
• Second, the protocol strives to reduce the delay
that data incur on their way to the sink.

PEGASIS
• The network model assumes a homogeneous set of nodes
deployed across a geographical area. Nodes are assumed to
have global knowledge about other sensors’ positions.
• Furthermore, they have the ability to control their power to
cover arbitrary ranges. The nodes may also be equipped with
CDMA-capable radio transceivers.
• The nodes’ responsibility is to gather and deliver data to a
sink, typically a wireless base station.
• The goal is to develop a routing structure and an aggregation
scheme to reduce energy consumption and deliver the
aggregated data to the base station with minimal delay while
balancing energy consumption among the sensor nodes.
• Contrary to other protocols, which rely on a tree structure or
a cluster-based hierarchical organization of the network for
data gathering and dissemination, PEGASIS uses a chain
structure.

PEGASIS
• Based on the chain structure, nodes communicate with their
closest neighbors.
• The construction of the chain starts with the farthest node
from the sink. Network nodes are added to the chain
progressively, starting from the closest neighbor to the end
node.
• Nodes that are currently outside the chain are added to the
chain in a greedy fashion, the closest neighbor to the top
node in the current chain first, until all nodes are included.
• To determine the closest neighbor, a node uses the signal
strength to measure the distance to all its neighboring
nodes.
• Using this information, the node adjusts the signal strength
so that only the closest node can be heard.

PEGASIS
• Data aggregation in PEGASIS is achieved along the chain.
• The aggregation process can be performed sequentially as follows.
• First, the chain leader issues a token to the last node in the right end of
the chain.
• Upon receiving the token, the end node transmits its data to its
downstream neighbor in the chain toward the leader.
• The neighboring node aggregates the data and transmits them to its
downstream neighbor. This process continues until the aggregated data
reach the leader.
• Upon receiving the data from the right side of the chain, the leader
issues a token to the left end of the chain, and the same aggregation
process is carried out until the data reach the leader.
• Upon receiving the data from both sides of the chain, the leader
aggregates the data and transmits them to the data sink.
• Although simple, the sequential aggregation scheme may result in long
delays before the aggregated data are delivered to the base station.
• Such a sequential scheme, however, may be necessary if arbitrarily close
simultaneous transmission cannot be carried out without signal
interference.

PEGASIS
• A potential approach to reduce the delay required to deliver
aggregated data to the sink is to use parallel data aggregation
along the chain.
• A high degree of parallelism can be achieved if the sensor
nodes are equipped with CDMA-capable transceivers.
• The added ability to carry out arbitrarily close transmissions
without interference can be used to ‘‘overlay’’ a hierarchical
structure onto the chain and use the embedded structure to
perform data aggregation.
• At each round, nodes at a given level of the hierarchy
transmit to a close neighbor in the upper level of the
hierarchy.
• This process continues until the aggregated data reach the
leader at the top level of the hierarchy. The latter transmits
the final data aggregate to the base station.

PEGASIS
• It is assumed that all nodes have global knowledge of the network
and employ a greedy algorithm to construct the chain.
• Furthermore, it is assumed that nodes take turns in transmitting to
the base station such that node i mod N, where N represents the total
number of nodes, is responsible for transmitting the aggregate data
to the base station in round i.
• Based on this assignment, node 3, in position 3 in the chain, is the
leader in round 3.
• All nodes in an even position must send their data to their neighbor
to the right. At the next level, node 3 remains in an odd position.
• Consequently, all nodes in an even position aggregate their data and
transmit them to their right neighbors.
• At the third level, node 3 is no longer in an odd position. Node 7, the
only node beside node 3 to rise to this level, aggregates its data and
sends them to node 3.
• Node 3, in turn, aggregates the data received with its own data and
sends them to the base station.

PEGASIS
• The sequential scheme and the CDMA-based fully parallel scheme
constitute two endpoints of the design spectrum.
• A third scheme, which does not require the node transceivers to be
equipped with CDMA capabilities, strikes a balance between the two
extreme schemes and achieves some level of parallelism.
• The basic idea of the scheme is to restrict simultaneous transmission to
nodes that are spatially separated.
• Based on this restriction, hierarchical PEGASIS creates a three-level
hierarchy in which the total number of network nodes is divided into
three groups.
• Data are aggregated simultaneously within each group and exchanged
between groups. The data aggregated eventually reach the leader, which
delivers them to the data sink.
• simultaneous transmission must be carefully scheduled to avoid
interference.
• Furthermore, the three-level hierarchy must be restructured properly to
allow leadership rotation among group nodes.
• The simulation results of the hierarchical extension of PEGASIS show
considerable improvement over schemes such as LEACH.

TEEN
• TEEN (Threshold-sensitive Energy Efficient sensor Network protocol)
• In TEEN, sensor nodes sense the medium continuously, but the data
transmission is done less frequently.
• A cluster head sensor sends its members a hard threshold, which is the
threshold value of the sensed attribute and a soft threshold, which is a
small change in the value of the sensed attribute that triggers the node
to switch on its transmitter and transmit.
• Thus the hard threshold tries to reduce the number of transmissions by
allowing the nodes to transmit only when the sensed attribute is in the
range of interest.
• The soft threshold further reduces the number of transmissions that
might have otherwise occurred when there is little or no change in the
sensed attribute.
• When cluster-heads are to change, new values for the above parameters
are broadcast.
• The main drawback of this scheme is that, if the thresholds are not
received, the nodes will never communicate, and the user will not get
any data from the network at all.

TEEN
• The nodes sense their environment continuously.
• The first time a parameter from the attribute set reaches its hard
threshold value, the node switches its transmitter on and sends the
sensed data. The sensed value is stored in an internal variable, called
Sensed Value (SV).
• The nodes will transmit data in the current cluster period only when the
following conditions are true:
• (1) The current value of the sensed attribute is greater than the hard
threshold
• (2) The current value of the sensed attribute differs from SV by an
amount equal to or greater than the soft threshold.
• Important features of TEEN include its suitability for time critical
sensing applications.
• Also, since message transmission consumes more energy than data
sensing, so the energy consumption in this scheme is less than the
proactive networks.
• The soft threshold can be varied. At every cluster change time, a fresh
parameters are broadcast and so, the user can change them as required.

APTEEN
• APTEEN (Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network
protocol)
• APTEEN, is a hybrid protocol that changes the periodicity or threshold values used in
the TEEN protocol according to the user needs and the type of the application.
• In APTEEN, the cluster-heads broadcasts the following parameters :
• 1. Attributes (A): this is a set of physical parameters which the user is interested in
obtaining information about.
• 2. Thresholds: this parameter consists of the Hard Threshold (HT) and the Soft
Threshold (ST).
• 3. Schedule: this is a TDMA schedule, assigning a slot to each node.
• 4. Count Time (CT): it is the maximum time period between two successive reports sent
by a node.
• The node senses the environment continuously, and only those nodes which sense a data
value at or beyond the hard threshold transmit. Once a node senses a value beyond HT, it
transmits data only when the value of that attribute changes by an amount equal to or
greater than the ST.
• If a node does not send data for a time period equal to the count time, it is forced to
sense and retransmit the data.
• A TDMA schedule is used and each node in the cluster is assigned a transmission slot.
Hence, APTEEN uses a modified TDMA schedule to implement the hybrid network.

APTEEN
• The main features of the APTEEN scheme include the following.
• It combines both proactive and reactive policies.
• It offers a lot of flexibility by allowing the user to set the count-time
interval (CT), and the threshold values for the energy consumption
can be controlled by changing the count time as well as the
threshold values.
• The main drawback of the scheme is the additional complexity
required to implement the threshold functions and the count time.
• Simulation of TEEN and APTEEN has shown that these two
protocols outperform LEACH. The experiments have demonstrated
that APTEENs performance is somewhere between LEACH and
TEEN in terms of energy dissipation and network lifetime.
• TEEN gives the best performance since it decreases the number of
transmissions.
• The main drawbacks of the two approaches are the overhead and
complexity associated with forming clusters at multiple levels, the
method of implementing threshold-based functions, and how to deal
with attribute-based naming of queries.

Geographical Based Routing
• Location routing is based on the position of nodes rather than
its network address. In this, a source node knows the
geographic location of the destination and sends a message to
the destination therefore is also known as geographical routing.
• Nodes do not have the location information of entire network. It
does not require flooding and hence reduces the control
overhead.
• It only knows the location of its direct neighbors to forward the
packet. Route discovery and packet forwarding is based on the
location information.
• Location of the nodes is available through various methods
(GPS, received radio signal strength etc). GPS (Global
Positioning System) can be used to get the location information
directly through satellite.
• The distance between the neighboring nodes can be estimated
on the basis of incoming signal strengths and by exchanging
such information between neighbors, relative coordinates of the
neighboring nodes can be obtained.

Geographical Based Routing
• Advantages
• It reduces control overhead as this scheme does not
require flooding.
• It saves the energy consumption through various
techniques.
• The cost of route setup is reduced as it is based on the
location of destination.
• It requires less memory as there is no need to store the
entire network information.
• It is scalable i.e. any number of nodes can join the
network.
• It also needs less maintenance.

Forwarding Strategies
• The goal of greedy forwarding is to move a packet closer to the destination with
each hop. Each node makes such a forwarding decision based on local
information only.
• However, a variety of forwarding strategies have been explored that all meet
this requirement, but potentially lead to different resource requirements and
paths.
• Common strategies for forwarding in location-based protocols include:
• 1. Greedy: This common technique chooses a neighbor that minimizes the
distance to the destination in each hop. In Figure, this would be node E. The
goal of the greedy approach is to minimize the number of hops required to reach
the destination.
• 2. Nearest with Forwarding Progress (NFP): This strategy chooses the nearest
neighbor of all neighbors that make a positive progress (in terms of geographic
distance to the destination) toward the destination. (e.g., node A in Figure).
• 3. Most Forwarding Progress within Radius (MFR): The MFR strategy selects
the neighbor that makes the greatest positive progress towards the destination,
where progress is defined as the distance between the source and its neighbor
node projected onto a line drawn from the source to the destination (e.g., node
B in Figure).
• 4. Compass Routing: This strategy chooses the neighbor with the smallest angle
between a line drawn from the source to the neighbor and the line connecting
the source and the destination . node C in Figure.

GAF (GEOGRAPHIC ADAPTIVE FIDELITY)
• GAF is a location based and an energy aware routing protocol.
• Earlier it was proposed for Ad-hoc networks but now WSNs can
also use this protocol. It is based on the idea that all neighboring
nodes are equivalent from the view of routing.
• In GAF, the whole network is divided into a virtual grid. The
size of grid is based on the concept that any node can
communicate with other node present in the neighboring grid.
• A cell is assigned to each node of the network and only one
node per cell is in the active state.
• An active node is selected by analyzing the highest remaining
energy of a node.
• To associate itself within the grid, each node uses the GPS based
location information.
• This is a location based protocol but also used as a hierarchical
protocol, in which clusters are formed on the basis of location
information.

• In GAF, three transition states are defined: discovery, active and sleep
state.
• Td is a discovery time, Ta is an active time and Ts is a sleeping time.
• Only an active node will participate in monitoring as well as sending
data to the sink.
• Active node is said to be in an active state and all other nodes which are
inactive at that time are in a sleep state.
• When a node wants to select an active node it sends the discovery
messages to all the neighboring nodes present in the grid.
• After Td, a node with the highest energy becomes an active node for a
specific time.
• After Ta, node again enters into the discovery state and starts
discovering another node to enter into an active state.
• Sleeping nodes wake up before the leaving time of the active node
expires and anyone of them will become active.
• Hence it increases the lifetime of network by lowering the energy
consumption.

GEAR (GEOGRAPHICAL AND
ENERGY AWARE ROUTING)
• GEAR is an energy aware routing protocol which selects the neighbor for
routing the queries towards the target region.
• It sends the packet to the target region rather than a particular node as
shown in Figure.
• As it is a location based protocol, it uses GIS (Global Information System)
or localization system to find the position information. GEAR minimizes
delay and increases the lifetime by balancing energy.

• Each node in GEAR keeps an estimated cost and a learning
cost of reaching the destination through its neighbors.
• The estimated cost is a combination of residual energy and
distance to destination.
• The learned cost is a refinement of the estimated cost that
accounts for routing around holes in the network.
• A hole occurs when a node does not have any closer
neighbor to the target region than itself. If there are no
holes, the estimated cost is equal to the learned cost.
• It works in two steps.
– First, route packets towards destination region.
– Second, spread the information within that region.

• When a packet reaches its destination area then to
spread the information in that region a recursive
geographic forwarding and restricted flooding methods
are used.
• Figure shows the recursive geographic forwarding. In
this, a data when reached to a target region then to
spread a data to all the nodes, a region is further divided
into sub regions.
• A destination node (D) makes the duplicate copies of
received data and forwards it to all the sub regions.
• Figure shows the restricted flooding. This is used in a
low density network while recursive geographic
forwarding is used in high density networks.

Recursive Geographic
Forwarding Restrictive Flooding

RPL
• RPL - Routing Protocol for Low Power and Lossy Networks.
• Created in February 2008, the Routing over Low-power and Lossy networks (RoLL)
working group initially defined the routing requirements for urban LLNs , industrial
LLNs, home automation LLNs, and building automation LLNs.
• In parallel to the definition of the routing requirements, the RoLL working group
initiated a study to verify whether the IETF standard routing protocols could supply
the identified requirements.
• Through the first conclusions, the RoLL detected that the existent routing solutions
could not satisfy the requirements of LLNs. Since then, the working group has
studied new routing solutions to provide the specific requirements of several types
of LLN applications.
• In March 2012, the RoLL working group defined the IPv6 Routing Protocol for
LLNs (RPL) as the standard routing protocol for LLN.
• Presented in the RFC 6550, RPL is a proactive tree-based routing protocol that
builds a directed acyclic graph between the leaf nodes and the border route (sink
node).
• Although considered as the standard routing protocol for IoT networks, since its
creation, RPL has presented several drawbacks, and new solutions have been
emerging to solve them.

Routing Requirement for Low Power
Network
• The routing requirements of IoT/LLN networks
may vary according to the specificities of
applications.
• The routing requirements for Urban LLNs (U-
LLN).
– This kind of LLN provides the network structure for
applications executed in urban environments such as
smart-metering, pollution and meteorological
monitoring, and general purposes for smart cities.
– routers have the function of prolonging the network’s
lifetime, balancing energy consumption, building the
sensing infrastructure, and providing links to the
Internet.

Network
• The routing requirements for Industrial LLNs.
• Security, monitoring, and control in industrial environments
are some examples of applications supported by this group
of LLNs.
• Thus, wireless devices should provide easy installation and
maintenance, low power, and high reliability.
• It is expected that critical alarm packets can be delivered
with lower latency than normal messages. Hence, the
routing protocol must support different routing metrics,
including link quality and throughput.
• Further, industrial LLN applications can require the sending
of messages for specific groups of nodes or more than one
base station. In this case, multicast forwarding support
becomes a critical routing requirement for these networks.

Network
• The routing requirements for Home Automation LNNs (HA-LLN).
• Home automation scenarios encompass a great set of applications such as energy
conservation and consumption optimization, window shade control, and
healthcare.
• a routing protocol able to support all HA-LLN applications must be ready to
provide constraint-based routing and support to mobility, scalability, convergence
time, manageability, and stability.
• The routing requirements for Building Automation LLNs (BA-LLNs).
• BA applications include the monitoring of several aspects such as fire alarms,
elevator systems, control access, and intrusion detection systems.
• A complete Building Management Systems (BMS) can be composed from
different, smaller applications executed in several subnetworks that are connected
through a backbone.
• Both the traffic pattern and the device density, as well as several other network
peculiarities can diverge for each subnetwork.
• Therefore, the routing protocols must provide a self-organizing structure with zero-
configuration to make the installation and replacement of devices accessible.
• Further, it must also provide scalability and support resource-constrained devices,
mobility, addressing, manageability, dynamic route selection, and security.

RPL
• RPL is a tree-based routing protocol created by the RoLL
working group and defined by IETF as the standard routing
protocol for LLNs.
• RPL organizes the network topology in a Destination-
Oriented Graph (DAG), which is composed of one or more
Destination-Oriented Directed Acyclic Graphs (DODAG).
• Each DODAG represents a routing tree created by a root
node, also known as a sink node or LBR (LLN Border
Router).
• To construct the DODAG, RPL uses the Objective
Functions (OF) that adopt routing metrics to calculate the
best path between nodes and the DODAG root.
• Thus, the routing structure created by the RPL is a logical
topology built on a physical topology according to the used
OF.

RPL
• In the RPL operation, the network nodes initially build the DODAG.
Thus, in this first step, the root node starts the process of DODAG
construction, sending a DIO (DODAG Information Object) message to
its neighbors.
• This message carries various relevant information, such as node rank,
mode of operation, OF, and metrics.
• Each node that receives a DIO message should process it and decide
whether or not to join the DODAG according to the used OF .
• If a node chooses to join the DODAG, it has an upward path to the root
node. At this moment, the node computes its rank, refreshes its
neighbor table, and chooses its preferred parent, which will be used to
forward messages to the DODAG root.
• Usually, the preferred parent is the neighbor with the lowest rank
computed according to the OF.
• Some nodes may be configured to provide routes to other nodes. If a
node is set to be a router, it should update and resend the DIO
messages to its neighbors.
• If the node does not resend DIO, it is defined as a leaf in the routing
tree.

RPL
• RPL permits a new node to join the network at
any time.
• In this case, the new node uses a DIS
(DODAG Information Solicitation) message to
request a DIO message of a node already
incorporated in the DODAG.
• Through the reception of the DIO message, the
new node selects its preferred parent according
to the OF.

RPL
• RPL allows both upward (from the node to its parent)
and downward (from the node to its children) routes.
• Upward routes are naturally created during the initial
process of DIO sending.
• However, the use of downward routes requires the
handling of DAO (Destination Advertisement Object)
messages.
• The DODAG nodes process the DAO messages
according to the RPL Mode Of Operations (MOP).
• Independent of the MOP used, DAO messages may
require reception confirmation, which should be done
using DAO-ACK messages.

RPL
• Although it is designed for the Multipoint-to-Point (MP2P) traffic pattern,
RPL also admits the data forwarding using Point-to-Multipoint (P2MP) and
Point-to-Point (P2P).
• In MP2P, the nodes send data messages to the root, creating an upward
flow (Figure 1a).
• In P2MP, sometimes termed as multicast, the root sends data messages to
the other nodes, producing a downward flow (Figure 1b).
• In P2P, a node sends messages to the other node (non-root) of DODAG;
thus, both upward and downward forwarding may be required (Figure 1c).

RPL
• RPL defines four MOPs that should be used considering the traffic
pattern required by the application and the computational capacity of the
nodes.
• In the first, MOP 0, RPL does not maintain downward routes; thus,
consequently, only MP2P traffic is enabled.
• In non-storing MOP (MOP 1), downward routes are supported, and the
use of P2P and MP2P is allowed. However, all downward routes are
maintained in the root node. Thus, the total downward traffic should be
initially sent to the DODAG root and subsequently be forwarded to its
destination as shown in Figure 2a.
• In storing without multicast MOP (MOP 2), downward routes are also
supported, but are different from MOP 1; the nodes maintain,
individually, a routing table constructed using DAO messages to provide
downward traffic. Hence, downward forwarding occurs without the use
of the root node, as illustrated in Figure 2b.
• Storing with multicast MOP (MOP 3) has a functioning similar to MOP
2 plus the possibility of multicast data sending. This type of transmission
permits the non-root node to send messages to a group of nodes formed
using multicast DAOs.

RPL – Objective Function
• In RPL, the whole process of DODAG construction is highly
dependent on the OF considered by the network.
• Furthermore, the network performance is directly linked to the
process of route selection. According to the metrics and constraints
applied to select the best path between a node and a root, it is
possible to increase or decrease the network performance.
• Furthermore, as already explained, some applications require
different performance of the routing protocol. Thus, different types
of applications can require different OFs.
• To fulfill the application requirements, each OF should contemplate
metrics or constraints that better attend to these conditions.
• Based on the information of OFs, the node computes the weight of
each path to the root. Hence, the selection of preferred parent and
the rank calculation are performed according to OF.
• IETF defines, as the standard, two different objective functions:
– Objective Function zero (OF0) and
– Minimum Rank with Hysteresis Objective Function (MRHOF).

RPL – Objective Function 0
• Objective Function zero (OF0) is defined in the RFC 6552
and is designed to find the shortest path to the root.
• Using the DOI message information, OF0 knows the rank of
each candidate neighbor. OF0 selects, as the preferred parent,
the candidate neighbor with the best rank (the shortest).
• Additionally, OF0 stores a backup feasible successor to use as
an alternative to the preferred parent.
• All the upward traffic received by the node is routed to the
root using the preferred parent or the backup successor,
according to the link conditions. OF0 does not attempt to
perform any load balancing.
• The backup successor is used to forward a packet to the root
node when it is not possible to use the preferred parent.
• The rank of a node is obtained through the sum of the rank of
its preferred parent and the value of rank_Increase, which is
computed using a specific equation and predefined variables.

MRHOF
• The Minimum Rank with Hysteresis Objective Function
(MRHOF) was developed to select the path with the lowest
path cost without promoting excessive changes of the
preferred parent.
• Thus, MRHOF uses two mechanisms to fulfill this purpose.
• The first seeks to find the path with minimum cost, while
the second performs the hysteresis.
• Using the hysteresis mechanism, a candidate parent is
selected as the preferred parent only when it has a path cost
smaller than the current preferred parent, minus a given
threshold.
• Nevertheless, the preferred parent selection process is
executed just when the path cost for a neighbor is refreshed
or a new neighbor is inserted in the neighbors’ table.

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