2. Subjects
• Introduction
• Background
• WSN Design Issues: MAC Protocols, Routing Protocols, Transport Protocols
• Performance Modeling of WSNs: Performance Metrics, Basic Models,
Network Models
• Case Study: Simple Computation of the System Life Span
• Practical Example
3.
4. Introduction
• WSNs are collections of compact-size, relatively inexpensive
computational nodes that measure local environmental conditions or
other parameters and forward such information to a central point for
appropriate processing.
• The performance of WNSs is affected strongly by other parameters in
two groups: basic models and network models.
• Basic models form the elementary blocks based on which the network
models can be analyzed and the overall system performance studied.
5. Background
֍ WSNs usually consist of hundreds or thousands of sensor nodes
scattered in a geographical area and one or multiple sink(s) for
collecting information and transmitting it through wireless channels
(Figure 11.1).
֍ The special design and characteristics of sensors and their applications
make WSNs different from traditional networks.
֍ Most traffic in WSNs flows star like from sensor nodes to the sink. If
there are multiple sinks, multiple traffic flows will be generated between
sensor nodes and the sink.
6.
7. • The data related to the events are usually small, usually just a few bytes and in many
cases just a few bits. Therefore, it may be possible to transmit more than one event in a
single data unit if the application reporting frequency allows it.
• Other factors that affect WSN design are listed in (Table 11.1). These factors have a
direct impact on the system performance of WSNs.
8. The architecture of computer and communication networks is often structured in layers.
Each lower layer acts as a service provider to its immediate upper layer.
other higher
layers, including session, presentation, and
application
transport
network (or
internetworking)
data link
physical
9. WSN Design Issues
MAC Protocols
– The establishment of a multihop wireless network infrastructure for data transfer
requires the establishment of communication links between neighboring sensor
nodes.
– Communication in WNs is achieved in the form of electromagnetic signal
transmission through the air. This common transmission medium must therefore be
shared by all sensor network nodes in a fair manner. To achieve this goal, a medium
access control protocol must be utilized.
– The choice of the medium access control protocol is the major determining factor in
WSN performance.
10. • MAC affects the efficiency and reliability of hop-by-hop data transmission.
• Existing MAC protocols such as IEEE 802 series standard may not be
completely suitable for WSNs because of energy efficiency.
• MAC protocols for wireless sensor networks emphasize energy efficiency
through design of effective and practical approaches to deal with the foregoing
problems (i.e. S-MAC designs an adaptive algorithm to let sensor nodes sleep at
a certain time)
• Typical parameters used to measure performance of MAC protocols include
collision probability, control overhead, delay, and throughput.
11. WSN Design Issues
Routing Protocols
– Used for setting up one or more path(s) from sensor nodes to the sink.
– Since sensor nodes have limited resources, routing protocols should
have a small overhead, which may result from control message
interchange and caching.
– Therefore, the traditional address-centric routing protocols for
Internet (e.g. the routing information protocol, open shortest path
first, border gateway protocol) do not meet the requirements of
WSNs.
13. WSN Design Issues
Transport Protocols
– There are many factors should be considered carefully in the design of transport
protocols: a congestion control mechanism and especially, a reliability guarantee.
– Since most data streams are convergent toward the sink, congestion is likely to
occur at nodes around the sink.
– Although a MAC protocol can recover packet loss as a result of bit error, it has
no way to handle packet loss as a result of butter overflow. Therefore, transport
protocols should have mechanisms for loss recovery; to guarantee reliability,
mechanisms such as ACK and selective ACK used in the TCP would be helpful.
15. Sink Mobility
• In most applications, a WSN consists of two parts: one data collection unit (also
known as a sink or base station) and a large number of tiny sensor nodes.
• Sink mobility endues researchers with one more dimension in the design of
schemes and could potentially lead to a better solution. But it causes issues such as
link breakage or increased communication overheads. Thus, it needs to be managed
so that benefits it brings would outweigh damages it may cause.
• Sink mobility has long been recognized as an efficient method of improving system
performance in wireless sensor networks (WSNs), e.g. relieving traffic burden from
a specific set of nodes.
16. Performance analysis tests on some protocols
• The performance analysis tests are performed on Real Time and Reliable
Transport (RT2) protocol for Wireless Sensor, PETLP, CODA, ECODA,
and ESRT.
• In CODA, transport layer protocol is particularly developed to control the
congestion in WSNs.
• In ECODA, flexible queue scheduler and weighted fairness model are designed
to address the network traffic and local traffic with considering the static
priority and dynamic priority in order to serve the data traffic in better way.
17. • In PETLP, protocol describes the priority based reliability with congestion
detection mechanism. It functions in three modes: with priority, without and
distributed priority at intermediate node. It guarantees the congestion control, data
reliability and source data priority simultaneously.
• The RT2 protocol addresses the two major pending issues: application network
delay bound and heterogeneous reliability. The detection of physical phenomenon
and collaborative work are the main objectives of RT2 protocol.
• The ESRT protocol proposed to achieve the event reliability without any
intermediate storage requirements in wireless sensor networks. This protocol
basically runs and takes the decision on sink node, where actual processing of data
packets happens.
18. Performance modeling of WSNs
• Two important performance metrics, system lifetime and energy
efficiency.
• Both of these metrics relate to energy consumption.
• In WSNs, new models are required to capture special characteristics of
these networks which are different from the traditional networks.
19. Performance modeling of WSNs:
performance metrics
• System lifetime: This term can be defined in several ways:
(a) the duration of time until some node depletes all its energy;
(b) the duration of time until the QoS of applications cannot be guaranteed; or
(c) the duration of time until the network has been disjoined.
• Energy efficiency: Energy efficiency means the number of packets that
can be transmitted successfully using a unit of energy.
• Reliability: In WSNs, the event reliability is used as a measure to show
how reliable the sensed event can be reported to the sink.
20. • Coverage: Full coverage by a sensor network means the entire space
that can be monitored by the sensor nodes.
• Connectivity: For multihop WSNs, it is possible that the network
becomes disjointed because some nodes become dysfunctional.
• QoS metrics: Some applications in WSNs have real-time properties.
These applications may have QoS requirements such as delay, loss
ratio, and bandwidth.
21. Performance modeling of WSNs:
Basic Models
Basic
Models
Traffic
Model
Event-Based
Delivery
Continuous
Delivery
Query-Based
Delivery
Hybrid Delivery
Energy Models
Model for
Sensing
Model for
Communication
Model for
Computation
Node Model
22. Performance modeling of WSNs:
Network Models Network
Models
MAC
Model
Routing
Models
System
Model
Channel access is
controlled and
allocated by
MAC protocols.
energy consumed
for a generic
route P, P[E]
can be computed
as follows:
25. 1. All sensor nodes (N) in the network organize a two-tiered topology.
2. All sensor nodes are distributed equally and densely in a space for
monitoring events.
3. Each higher-layer node (leader node) receives data from other leader
nodes (k), its leaf nodes (c), as well as locally generated data.
4. There is a congestion and flow control mechanism between sink and
sensor nodes to guarantee that in steady-state congestion will not
occur;
5. Each sensor node has a maximum energy of E.
6. All nodes are stationary, and no adaptive power control would be
assumed.
26. Analysis
• Total Node Number:
• Average Number of Retransmissions: Let be and pe be bit-error
probability and packet error probability, respectively
So, the average number of retransmissions will be:
27. The number of
packets in
each reporting
instant
• Average Cost of Packet Forwarding in One Hop: In each hop, data
consume the following amount of energy: transceiver (et), MAC-layer
collision and idle and overhearing (em), and computation (ec).
• Therefore, the total energy consumed by forwarding a packet within one
hop is about:
• Converged Data Rate: For per-node fairness, each sensor node has the
same data rate, ri= npf ; therefore, rc is given as follows:
The
reporting
frequency
28. • System Lifetime: Let’s assume that all sensor nodes become active at time
t0 = 0 and let’s assume that at time t1 the energy of the highest node at level
1 is depleted first. System lifetime Tl can be approximately T1 = t1- t0. Here,
the effects of node mobility and/or power control have been ignored. The
quantity T1 can be used as the lower bound of the system lifetime.
• For per-node fairness,
• For max-min fairness,
30. The quantitative metrics are used to measure and evaluate the
performance of the simulated routing protocols.
31. Use simulators (e.g. TOSSIM, NS2, OPNET) to evaluate protocols
performance under specific conditions, for example:
The average radio range of transmission was a radius of 10 m.
The network setup consisted of 100 nodes dispersed in an area depicting
100m×100m.
The simulations are run on random networks model, where the nodes placements
are changed randomly in uniformly square area.
The sensors are deployed in a regular grid with random offsets.
The results of the simulation will be as follows:
