Wireless sensor network

Wireless Sensor Network
Routing
Routing challenges and design issues in WSN:
 Node deployment
 Energy consumption without losing accuracy
 Data Reporting Model
 Node/Link Heterogeneity
 Fault Tolerance
 Scalability
 Network Dynamics
 Transmission Media
 Connectivity
 Coverage
 Data Aggregation
 Quality of Service
Routing Protocols
 The protocols can be divided into Flat-based routing, hierarchical based routing and
location based routing depending on the network structure.
 In flat based routing, all nodes are typically assigned equal roles of functionalities.
 In hierarchical based routing, each node will play different roles.
 In location based routing, sensor nodes’ positions are exploited to route data in the
network.
 A routing protocol is considered adaptive if certain system parameters can be
controlled in order to adapt to the current network conditions and available energy
levels.
 The protocols can be further divided into multipath-based, query based, negotiation
based, QoS based, or coherent based routing techniques depending upon the protocol
operations.
 Apart from all the above classifications of the routing protocols, the routing protocol
can be further classified into three categories: proactive, reactive and hybrid
depending upon how the source finds a route to the destination.
 In proactive protocols, all the routes are computed before they are really needed.
 In reactive protocols, the routes are computed on demand, and hybrid protocols uses
the functionality of both these ideas.
 When the sensor nodes are static, it is preferable to have table driven routing
protocols instead of having reactive protocols.
 Another class of routing protocol is called the cooperative routing protocol. In this,
the data is aggregated at a central node where the aggregated node may be further
processed leading to reduction of routes cost in terms of energy consumed.

1. Network Structure Protocol
1.1 Flat Routing: The first category of routing protocol is the multi-hop flat routing
protocols. In flat networks, each node typically plays the same role and sensor nodes
collaborate together to perform the sensing task. Due to large number of such nodes, it is not
feasible to assign a global identifier to each node. This consideration has led to data centric
routing, where the base station sends queries to certain regions and waits for data from
the sensor located in the selected regions. Since data is being requested through queries,
attributes based naming is necessary to specify the properties of data.
Early works on data centric routing e.g. SPIN and Directed Diffusion, were shown to save
energy through data negotiation and eliminating the redundant data. These two protocols
motivated the design of many other protocols which follow a similar concept. Some of the
flat routing protocols are mentioned below:
 Sensor Protocols for Information via Navigation (SPIN)
 Directed Diffusion (DD)
 Rumor Routing
 Minimum Cost Forwarding Algorithm (MCFA)
 Gradient Based Routing
 Information Driven Sensor Querying (IDSQ) and Constrained Anisotropic Diffusion
Routing (CADR)
Directed Diffusion
 The directed diffusion protocol is useful in scenarios where the sensor nodes
themselves generate requests/queries for data sensed by other nodes.
 Each sensor node names its data with one or more attributes.
 Each sensor node expresses their interest depending on these attributes.
 Each path is associated with an interest gradient, while positive gradient make the
data flow along the path, negative gradient inhibit the distribution data along a
particular path.
Routing Protocols in WSN
Network Structure
Flat
Netowrk
Routing
Hierarchical
Network
Routing
Location
Based
Routing
Protocol Operation
Negotiation
BAsed
Rouing
multi-Path
Based
Routing
Query
Based
Routing
QoS Based
Routing
Coherent
Based
Routing

– Example : two path formed with gradient 0.4 and 0.8, the source may twice as
much data along the higher one
– Suppose the sink wants more frequent update from the sensor which have
detected an event => send a higher data-rate requirement for increasing the
gradient of that path.
Sensor protocol for Information Negotiation (SPIN)
 SPIN use negotiation and resource adaptation to address the disadvantage of flooding.
 Reduce overlap and implosion, and prolong network lifetime.
 Use meta-data instead of raw data.
 SPIN 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.
Fig: SPIN Protocol
1.2 Hierarchical Network Routing: hierarchical or cluster based routing, originally
proposed in wireless network, are well known techniques with special advantages related to
scalability and efficient communication. As such the concept of hierarchical routing is also
utilized to perform energy efficient routing in WSNs. In hierarchical architecture, higher
energy nodes can be used to process and send the information while the low energy nodes can
be used to perform the sensing in the proximity of the target. This means, creation of
clusters and assigning special tasks to cluster heads leading to greatly contributing
towards the overall system scalability, lifetime and energy efficiencies.
Hierarchical routing is an efficient way of lower energy consumption within a cluster and by
performing data aggregation and fusion in order to decrease the number of transmitted
messages to the base station. Hierarchical routing is mainly two layers routing where one
layer is used to select the cluster heads and the other layer is used for routing.
Some of the hierarchical routing protocols are:
 LEACH Protocol
 PEGASIS
 TEEN and APTEEN

 Small Minimum Energy Communication Network (MECN)
 Self-Organizing Protocol
 Sensor Aggregate Routing
 Virtual Grid Architecture Routing (VGA)
 Hierarchical Power Aware Routing
 Two-Tier Data Dissemination
Difference between hierarchical vs Flat routing
Hierarchical Routing Flat Routing
Reservation based scheduling Contention based scheduling
Collision avoided Collision overhead present
Reduced duty cycle due to periodic sleeping Variable duty cycle by controlling sleep time
of nodes
Data aggregation by cluster heads Node on multi-hop path aggregates incoming
data from neighbours.
Simple but not optimal routing Routing can be made optimal but with an
added complexity
Requires global and local synchronization Links formed on the fly without
synchronization
Energy dissipation is uniform Energy dissipation depends on traffic
patterns
Energy dissipation cannot be controlled Energy dissipation adapts to traffic pattern
Fair channel allocation Fairness not guaranteed.
Overhead of the cluster formation throughout
the network
Routes formed only in regions that have data
for transmission.
Hierarchical Routing Protocol
 It is natural way of routing to scale: Size, Network administration and Governance.
 It exploits the address aggregation and allocation.
 It allows multiple metrics at different levels of the hierarchy.
 The following are the hierarchical routing protocols:
Low Energy Adaptive Clustering Hierarchy (LEACH)
Fig: LEACH protocol

 LEACH protocol is a self-organizing adaptive clustering.
 Cluster heads elect themselves in a manner random round robin manner. In future, it
could be done in with a power based probability.
 The cluster head is always on and nodes die in random. The base station is stationary.
The coordination between the nodes is done in a localised manner.
 Data fussion
 (aggregation) takes place.
 It suffers from HOT-SPOT problem: nodes on a path from an event-congested area to
the sink may drain
 It is in adequate for time critical applications.
 Basic algorithm assumes any node can communicate with sink – possible to a scale.
 In LEACH, sink makes all the decisions. Thus, too much power is consumed in
computation at the sink.
 LEACH works in round and each round consist of set-up phase (short) and steady
phase (long)
 Set up phase:
o Advertisement: a cluster head decides itself as a cluster head
o Cluster set-up: nodes included in a cluster declares themselves
o Schedule creation: slots are allotted to nodes for data transmission
 Steady state phase:
o Data is transmitted using TDMA
o Everyone uses same channel
o Different cluster use different CDMA code
o Code selection is done in a random manner
o The cluster heads communicates with the base station or the cluster head in
higher hierarchy.
Time Line Showing LEACH Operation
Threshold Sensitive Energy Efficient Sensor Network Protocol (TEEN)
 At every cluster change time, the cluster-head broadcasts to its members
o Hard Threshold (HT)

 This is a threshold value for the sensed attribute.
 It is the absolute value of the attribute beyond which, the node sensing
this value must switch on its transmitter and report to its cluster head.
o Soft Threshold (ST)
 This is a small change in the value of the sensed attribute which
triggers the node to switch on its transmitter and transmit.
 It uses LEACH based clustering. It uses smart data transmission to save power. It is
suited for time-critical applications.
 The cluster heads needs to listen continuously. It leads to wasted time slots.
 In this protocol, it cannot distinguish between dead nodes.
 Node transmit in timeslot only if both:
o Value greater then a Hard Threshold (HT)
o Value differs from last transmitted value (TV ) by more than a Soft Threshold
(ST)
 After transmission, TV is reset
Adaptive periodic Threshold-sensitive Energy Efficient Sensor Network (APTEEN)
 It is similar to TEEN but a better version of TEEN. It has more flexible logic and
timeslots.
 It uses multi type of queries: historical, one-time and persistent.
 It can also distinguish between dead and alive nodes.
 Node transmit in timeslot only if both:
o Value greater then a Hard Threshold (HT)
o Value differs from last transmitted value (SV ) by more than a Soft Threshold
(ST)
o Or If did not transmit for a max time (TC )
o Or if queried by some sink
 After transmission SV is reset
Power Efficient Gathering in Sensor Information System (PEGASIS)
 The key idea in PEGASIS is to form a chain among the sensor nodes so that each
node will receive from and transmit to a close neighbor
 The nodes will be organized to form a chain, which can either be accomplished by the
sensor nodes themselves using a greedy algorithm starting from some node.
 When a node dies, the chain is reconstructed in the same manner to bypass the dead
node.
 The main idea in PEGASIS is for each node to receive from and transmit to close
neighbors and take turns being the leader for transmission to the BS.
 Nodes take turns transmitting to the BS, and we will use node number i mod N (N
represents the number of nodes) to transmit to the BS in round i.

Power Efficient Data Gathering and Aggregation protocol (PEDAP)
 It is a tree-based routing protocol. The objective of PEDAP is to maximize the
network lifetime, which is defined by the number transmission rounds.
 The minimum energy cost tree is uses to data transmission.
 This tree is constructed by a centralized manner using Prim’s minimum spanning
tree algorithm.
 Initially, the sink is defined as the root of the tree. After that, we select the
minimum weighted edge, one vertex of which is in the tree and another vertex is not
in the tree. Such an edge is added to the tree. This process lasts until all nodes are
merged into the tree.
 The total energy consumption in each communication round is achieved by
computing a minimum spanning tree with link cost, which is related to data volume
and transmission distance.
 In order to achieve load balancing among all nodes, the residual energy of the nodes
is taken into account during the course of data aggregation. When data transmission is
performed, the root of the tree structure acts as the CH.
 Each node receives data from its child nodes, aggregates the data with its own and
delivers it to its parent node. This process continues until the aggregated data reaches
the CH. Ultimately, the data is delivered from the CH to the sink.
 PEDAP can cut down the total energy dissipation in each communication round
by computing a minimum spanning tree with link cost calculation.
 Moreover, the residual energy is considered. This can contribute to load balancing to
some extent. In addition, the transmission delay is lessened because the tree formation
mechanism can reduce the path length. However, in large-scale networks, the
energy cost calculation is a difficult task.
 So PEDAP suffers from the scalability problem. Furthermore, the robustness of
PEDAP is very limited due to its centralized nature which requires the global
knowledge of the location of all nodes at the sink.
Types of Hierarchical routing protocol: LEACH, PEGASIS, TEEN, APTEEN, PEDAP-PA

Performance Parameters LEACH TEEN APTEEN PEGASIS PEDAP-PA
Energy Efficiency Poor Moderate Moderate Good Best
Network Lifetime Shortest Long Long Longer Longest
Self-Organisation Capability High High Low High Low
Network Quality Maintenance Poor Moderate Moderate Good Best
Throughput Low Low High Low High
Latency High Low Moderate High Moderate
Generally Hierarchical Routing Protocol are designed to provide scalability to WSNs while
maintaining high energy efficiency
1.3 Location Based Routing: In this kind of routing, sensor nodes are addressed by means
of their locations. The distance between neighbouring nodes can be estimated on the basis of
incoming signal strengths. Relative coordinates of neighbouring nodes can be obtained by
exchanging such information between neighbours. Alternatively, the location of nodes may
be available directly by communicating with a satellite, using GPS (Global Positioning
System), if nodes are equipped with a small low power GPS receiver. To save energy,
some location based schemes demand that nodes should go to sleep if there is no activity.
More energy savings can be obtained by having as many sleeping nodes in the network as
possible. The problem of designing sleep period schedules for each node in a localized
manner was addressed in. some of the location based routing protocols are given below:
 Geographic adaptive fidelity (GAF)
 Geographic and Energy Aware Routing
 Most forward Within Radius (MFR)
 Geographic Distance Routing (GEDIR)
ENERGY EFFICIENT ROUTING
Power Aware Routing
Transmission Power Control Approach
OMM – Online Max-min
PLR – Power Aware Localized Routing
MER – Minimum Energy Routing
COMPOW – Common Power
PAAODV – Power Aware Adhoc on Demand Distance Vector Routing
Load Distribution
LEAR – Localized Energy Aware Routing
CMMBCR – Conditional Max-Min Battery Capacity Routing
Power Management
PAMAS – Power Aware Multi Access
PDTORA – Power and Delay Aware on Demand Routing for Adhoc Networks

Sleep/Power Down Mode
SPAN -
GAF
Transmission power Control Approach:
 This approach can be achieved with the help of topology control of a MANET. The
transmission power determines the range over which the signal can be coherently
received, and is therefore crucial in determining the performance of the network.
 Power aware routing protocols based on transmission power control finds best route
that minimizes the total transmission power between a source and a destination.
 It is equivalent to graph optimization problem where each link is weighted with
the link cost corresponding to the required transmission power. Finding the most
power efficient route from source to destination is equivalent to finding the least
cost path in the weighted graph.
 There are some of the protocols for transmission power control approach, of which
OMM is explained here.
 Online Max-Min (OMM)
o This protocol uses two different metrics of the nodes in the network:
minimizing power consumption (min-power) and maximizing the minimal
residual power (max-min).
o Max-min metric is helpful in preventing the occurrence of overloaded nodes.
o OMM protocol uses Djkstra’s algorithm to find the optimal path between
source-destination pair. This min-power path consumes the minimal power
(Pmin)
o In order to optimise the second metric, the OMM protocol obtains multiple
near optimal min-power paths that do not deviate much from the optimal
value.
o In order to obtain the max-min path among those three path candidates, the
node with the minimal residual power in each path must be compared.
Fig:
o In the next figure, node A has residual energy of 25 but it will drop to 13 if
that path is used to transfer the data packets from node S to node D.
o Similarly node B and node C will have residual energy of 6 and 20
respectively.
o Therefore, the max-min path among the three min-power path is SCD.
o The major advantage of OMM protocol is that without requiring the
information regarding the data transmission sequence or data generation rate,

the protocol makes a routing decision that optimizes the two different metrics
in the nodes of the network.
o The disadvantage of using OMM protocol is that the data transmission
sequence or data generation rate is not usually known in advance. This graph
optimization algorithm based on global information such as data generation
rate may not be practical because each node is provided with only the local
information.
Load distribution:
 The specific objective of load distribution approach is to balance the energy usage of
all mobile nodes by selecting a route with underutilized nodes rather than the
shortest route. This may result in longer routes, but packets are routed only through
energy rich intermediate nodes.
 Protocols based on this approach do not necessarily provide the lowest energy route,
but prevent certain nodes from being overloaded and thus, ensures longer lifetime.
 Localized Energy Aware Routing (LEAR) Protocol
o The LEAR routing protocol is based on DSR which modifies the route
discovery procedure for balanced energy consumption.
o LEAR is a distributed algorithm where each node makes its routing
decisions based on local information such as Er and Thr.
o In DSR, when a node receives a route request message, it appends its identity
in the message’s header and forwards it toward the destination. Thus, an
intermediate node always relays messages if the corresponding route is
selected.
o However, in LEAR, a node determines whether to forward the route request
message or not depending on its residual battery Power (Er ). When Er is
higher than a threshold value Thr, the node forwards the Route-request
message; otherwise, it drops the message and refuses to participate in relaying
packets.
o Therefore, the destination node will receive a route-request message only
when all intermediate nodes along a route have good battery power levels, and
nodes with low battery levels can conserve their battery power.
o LEAR is a distributed algorithm where each node makes its routing decision
based only on local information, such as Er and Thr. As Er decreases in time,
the value of Thr must also be decreased adaptively in order to identify energy-
rich and energy-hungry nodes in a relative sense.
Basic LEAR Algorithm
Node Steps
Source Node Broadcast a ROUTE_REQ;
Wait for the first arriving ROUTE_REPLY;
Select the source route contained in the message;

Ignore all later replies
Intermediate
Node
If the message is not the first trial and Er < Thr adjust Thr by d;
If Er > Thr, broadcast the ROUTE_REQ and ignore all later requests
Otherwise, drop the message
Destination
Node
Upon receipt the first arriving ROUTE_REQ send a ROUTE_REPLY to
the source with the source route contained in the message
Power Management:
 Power management approach helps in reducing the system power consumption and
hence prolonging the battery life of mobile nodes.
 Furthermore, it improves the end-to-end network throughput as compared to
other ad-hoc networks in which all mobile nodes use the same transmit power.
The improvement is due to the achievement of a trade-off between minimizing
interference ranges, reduction in the average number of hops to reach a
destination, the probability of having isolated clusters, and the average number
of transmissions (including retransmissions due to collisions) and also due to the
fact that as the power gets higher, and the connectivity range increases, each
node would reach almost all other nodes in a single hop.
 The protocols would dynamically determine first an optimal connectivity range
wherein they adapt their transmit powers so as to only reach a subset of the nodes in
the network. The connectivity range would then be dynamically changed in a
distributed manner so as to achieve the near optimal throughput.
 Minimal power routing is used to further enhance performance. As power
management approach increases the throughput of the network this approach is better
in terms of throughput as compared to the previous 2 approaches.
 Power Aware Multiple Access (PAMAS):
o PAMAS saves energy by turning off radios when the nodes are not in use. It
uses a new routing cost model to discourage the use of nodes running low on
battery power.
o The lifetime of the network is improved significantly. There is a trivial
negative effect on packet delivery fraction and delay, except at high traffic
scenarios, where both actually improve due to reduced congestion.
o Routing load, however, is consistently high, more at low traffic scenarios. For
the most part, PAMAS demonstrates significant benefits at high traffic and
not-so high mobility scenarios.
o Although, it was implemented on the AODV protocol, the technique used is
very standard and can be used with any on-demand protocol. The energy-
aware protocol works only in the routing layer and exploits only routing-
specific information
o In this protocol, the node can be in any of the six following different states:
 Idle state - A node goes to idle state if it is not transmitting or
receiving a packet or does not have any packets to transmit or does
have packets to transmit but cannot transmit because a neighbour is
receiving a transmission.

 Await CTS state - Whenever a node gets a packet to transmit it
transmits a RTS and enters the Await CTS state.
 BEB (Binary Exponential Backoff) state-If the awaited CTS state
does not arrive the node goes into BEB (Binary Exponential Backoff)
state.
 Transmit Packet state-If a CTS arrives it begins transmitting the
packet and enters the Transmit Packet state.
 Await Packet state-This state comes into picture when the intended
receiver transmits the CTS.
 Receive Packet state-If the packet begins arriving, it transmits a busy
tone over the signalling channel and enters the Receive Packet state
otherwise enters to the idle state.
Sleep/Power-Down Approach
 The sleep/power-down mode approach focuses on inactive time during
communication. Since most radio hardware supports a number of low power states, it
is desirable to put the radio subsystem into the sleep state or simply turn it off to save
energy. However, when all the nodes in a MANET sleep and do not listen, packets
cannot be delivered to a destination node.
 One possible solution is to elect a special node, called a master, and let it coordinate
the communication on behalf of its neighbouring slave nodes. Now, slave nodes can
safely sleep most of time thereby saving battery power. Each slave node periodically
wakes up and communicates with the master node to find out if it has data to receive
or not and it sleeps again if it is not addressed.
 SPAN Protocol:
o SPAN protocol is a power saving mechanism that reduces power consumption
of nodes by retaining the capacity and coordinating with the underlying MAC
layer.
o SPAN tries to exploit MAC layers power saving features
o The routing layer uses information SPAN provides for power aware routing.
o Advantages of the SPAN protocol is that the master nodes play an important
role in routing by providing a routing backbone and control traffic as well as
channel contention is reduced because the routing backbone helps to avoid the
broadcast flooding of route request messages.
o Other benefits of SPAN protocol are that this technique not only preserves
network connectivity, it also preserves capacity, decreases latency and
provides significant power savings.
o Drawback of SPAN protocol is that the amount of power saving increases
slightly as density decreases
o To select master nodes in a dynamic configuration, the SPAN protocol
employs a distributed master eligibility rule so that each node independently
checks if it should become a master or not. The rule is that if two of its

neighbours cannot reach each other either directly or via one or two masters, it
should become a master.
o Non-master nodes also periodically determine if they should become a master
or not based on the master eligibility rule.
o In Figure below, nodes B, C and D become masters. Node B is eligible to
become master since its two neighbours A and F cannot communicate directly.
Node D is eligible to become master since its two neighbours C and E cannot
communicate directly. Node C is not eligible to become master since its
neighbours B and F can communicate with each other directly. Node C is also
eligible to become master since its neighbours B and D cannot communicate
directly.
Fig: Master Eligibility Rule in SPAN protocol
o So, if any one of the nodes B and D do not elect itself as a master, node C is
eligible to be the master.
o Thus, the master selection process is not deterministic. This rule does not yield
the minimum number of master nodes, but it provides robust connectivity with
substantial energy savings.
o However, the master nodes are easily overloaded. To prevent this and to
ensure fairness, each master periodically checks if it should withdraw as a
master and gives other neighbour nodes a chance to become a master. Non-
master nodes also periodically determine if they should become a master or
not based on the master eligibility rule
2. Protocol Operation
2.1 Multipath Routing Protocol:
These are the routing protocol that uses multiple paths rather than a single path in order to
enhance the network performance. The fault tolerance (resilience) of a protocol is
measured by the likelihood that an alternate path exist between a source and a
destination when the primary path fails. This can be increased by maintaining multiple
paths between a source and a destination at the expense of an increased energy
consumption and traffic generation. These alternate paths are kept alive by sending
periodic messages. Hence, network reliability can be increased at the expense of increased
overhead of maintaining the alternate paths.

2.2 Query Based Routing:
In this kind of routing, the destination node propagates a query for data from a node through
a network and a node having this data sends the data which matches the query back to the
node which initiates the query. Usually these queries are described in a natural language or
in a high level query language. All the nodes have tables consisting of a sensing task queries
that they receive and send data which matches these tasks when they receive it.
2.3 Negotiation Based Routing:
These protocols use high level data descriptors in order to eliminate redundant data
transmission through negotiation. Communication decisions are also taken based on the
resources that are available to them.
2.4 QoS Based Routing:
In QoS based routing protocol, the network has to balance between energy consumption and
data quality. In particular, the network has to satisfy certain QoS matrices e.g. delay, energy,
bandwidth, etc. when delivering data to base station. Sequential assignment routing (SAR) is
one of the first WSN routing protocol that talks about the QoS in routing decisions.
2.5 Coherent Based Routing:
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.
Design of Wireless Sensor Network
Wireless sensor networks (WSNs) are networks of tiny sensing devices for wireless
communication, actuation, control, and monitoring. Given the potential benefits offered by
these networks, as, e.g., simple deployment, low installation cost, lack of cabling, and
mobility, they are specially appealing for control applications in home and industrial
automation. The variety of application domains and theoretical challenges for WSNs has
attracted research efforts for more than one decade. Nevertheless, a lively research and
standardization activity is ongoing and there is not yet a widely accepted protocol stack for
WSNs for control applications. The lack of efficient protocol solutions is due to that the
protocols for control applications face complex control and communication requirements.
Traditional control applications are usually designed by a top-down approach from a protocol
stack point of view, whereby most of the essential aspects of the network and sensing
infrastructure that has to be deployed to support control applications are ignored.
Here, packet losses and delays introduced by the communication network are considered as
non-idealities and uncertainties and the controllers are tuned to cope with them without
having any influence on them. The top-down approach is limited for two reasons: 1) it misses

the essential aspect of the energy efficiency that is usually required to WSNs, and 2) it can be
quite conservative and therefore inefficient, because the controllers are built by presuming
worst case wireless channel conditions that may be rarely experienced in the reality. On the
other side, protocols for WSNs are traditionally designed to maximize the reliability and
minimize the delay. This is a bottom-up approach, where controller specifications are not
explicitly considered even though the protocols are used for control. This approach is energy
inefficient because high reliability and low latency may demand significant energy
consumption. Therefore, it follows that there is the essential need of a new design approach.
Traditional WSNs applications (e.g., monitoring) need a high probability of success in the
packet delivery (reliability). In addition to reliability, control applications ask also for timely
packet delivery (latency). If reliability and latency constraints are not met, the correct
execution of control decisions may be severely compromised, thus creating unstable control
loops. High reliability and low latency may demand significant energy expenditure, thus
reducing the WSN lifetime. Controllers can usually tolerate a certain degree of packet losses
and delay: For example, the stability of a closed loop control system may be ensured by high
reliable communications and large delays, or by low delays when the packet loss is high. In
contrast to monitoring applications, for control applications there is no need to maximize the
reliability. A trade-off between latency, packet losses, and stability requirements can be
exploited for the benefit of the energy consumption, as proposed by the system level design
approach. Therefore, we claim that the protocol design for control needs a system-level
approach whereby the need of a parsimonious use of energy and the typical requirements of
the control applications are jointly taken into account and control and WSNs protocols are co-
designed. Exploiting such a trade-off poses extra challenges when designing WSNs protocols
for control applications when compared to more traditional communication networks,
namely:
 Reliability: Sensor information must be sent to the sink of the network with a given
probability of success, because missing these data could prevent the correct execution
of control actions or decisions concerning the phenomena sensed. However,
maximizing the reliability may increase substantially the network energy
consumption. Hence, the network designers need to consider the tradeoff between
reliability and energy consumption.
 Latency: Sensor information must reach the sink within some deadline. A
probabilistic delay requirement must be considered instead of using average packet
delay since the delay jitter can be too difficult to compensate for, especially if the
delay variability is large. Retransmission of old data to maximize the reliability may
increase the delay and is generally not useful for control application.
 Energy efficiency: The lack of battery replacement, which is essential for affordable
WSN deployment, requires energy-efficient operations. Since high reliability and low
delay may demand a significant energy consumption of the network, thus reducing the
WSN lifetime, the reliability and delay must be flexible design parameters that need
to be adequate for the requirements. Note that controllers can usually tolerate a certain
degree of packet losses and delay. Hence, the maximization of the reliability and
minimization of the delay are not the optimal design strategies for the control
applications we are concerned within this chapter.

 Adaptation: The network operation should adapt to application requirement changes,
varying wireless channel and network topology. For instance, the set of control
application requirements may change dynamically and the communication protocol
must adapt its design parameters according to the specific requests of the control
actions. To support these changing requirements, it is essential to have an analytical
model describing the relation between the protocol parameters and performance
indicators (reliability, delay, and energy consumption).
 Scalability: Since the processing resources are limited, the protocol procedures must
be computationally light. These operations should be performed within the network,
to avoid the burden of too much communication with a central coordinator. This is
particularly important for large networks. The protocol should also be able to adapt to
size variation of the network, as, for example, caused by moving obstacles, or
addition of new nodes.

Wireless sensor network

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Wireless sensor network