Wireless Sensor Networks

Hebron University
College of Information Technology
Student Name: Abdullah I Roomi
Student No: 21410051
Subject: Wireless Sensor Networks
Dr: Khalil al-Masri

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Introduction
Today, smart grid, smart homes, smart water networks, intelligent transportation, are
infrastructure systems that connect our world more than we ever thought possible.
The common vision of such systems is usually associated with one single concept, the
internet of things (IoT), where through the use of sensors, the entire physical
infrastructure is closely coupled with information and communication technologies;
where intelligent monitoring and management can be achieved via the usage of
networked embedded devices. In such a sophisticated dynamic system, devices are
interconnected to transmit useful measurement information and control instructions
via distributed sensor networks. A wireless sensor network (WSN) is a network
formed by a large number of sensor nodes where each node is equipped with a sensor
to detect physical phenomena such as light, heat, pressure, etc. WSNs are regarded as
a revolutionary information gathering method to build the information and
communication system which will greatly improve the reliability and efficiency of
infrastructure systems. Compared with the wired solution, WSNs feature easier
deployment and better flexibility of devices. With the rapid technological
development of sensors, WSNs will become the key technology for IoT.

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Characteristic features of WSNs
A WSN can generally be described as a network of nodes that cooperatively sense and
control the environment, enabling interaction between persons or computers and the
surrounding environment. WSNs nowadays usually include sensor nodes, actuator
nodes, gateways and clients. A large number of sensor nodes deployed randomly
inside of or near the monitoring area (sensor field), form networks through self-
organization. Sensor nodes monitor the collected data to transmit along to other
sensor nodes by hopping. During the process of transmission, multiple nodes to get to
gateway node after multihop routing, and finally reach the management node through
the internet or satellite may handle monitored data. It is the user who configures and
manages the WSN with the management node; publish monitoring missions and
collection of the monitored data. As related technologies mature, the cost of WSN
equipment has dropped dramatically, and their applications are gradually expanding
from the military areas to industrial and commercial fields. Meanwhile, standards for
WSN technology have been well developed, such as Zigbee
2. Sensor nodes
The sensor node is one of the main parts of a WSN. The hardware of a sensor node
generally includes four parts: the power and power management module, a sensor, a
microcontroller, and a wireless transceiver, see Figure 3-3. The power module offers
the reliable power needed for the system. The sensor is the bond of a WSN node,
which can obtain the environmental, and equipment status. A sensor is in charge of
collecting and transforming the signals, such as light, vibration and chemical signals,
into electrical signals and then transferring them to the microcontroller. The
Figure 1-1 | Wireless sensor networks

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microcontroller receives the data from the sensor and processes the data
accordingly. The Wireless Transceiver (RF module) then transfers the data, so that
the physical realization of communication can be achieved. It is important that the
design of the all parts of a WSN node consider the WSN node features of tiny size
and limited power.
2.1 Miniaturization technology of sensor based on MEMS
The miniaturization technology of WSN nodes based on microelectromechanical
systems (MEMS) has made remarkable progress in recent years. The core technology
of MEMS is to realize the combination of microelectronics technology,
micromachining technology and the packaging technology. Different levels of 2D and
3D micro sensitive structures can be produced based on microelectronics and micro-
machining technology, which can be the miniature sensing elements. These
miniature sensing elements, associated power supply and signal conditioning circuits
can be integrated and packaged as a miniature MEMS sensor
At present, there are already many types of miniature MEMS sensors in the market,
which can be used to measure a variety of physical, chemical and biomass signals,
including displacement, velocity, acceleration, pressure, stress, strain, sound, light,
electricity, magnetism, heat, pH value, etc. In 2003, researchers at the University Of
California Berkeley (UCB) developed a WSN sensor node (mote) with a micro sensor.
The actual size of its MEMS sensing module was only 2.8 mm × 2.1 mm.
2.2 Ambient energy harvesting technology
Hardware structure of a WSN sensor node

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Nodes need an energy source, and ambient energy harvesting from external sources
are used to power small autonomous sensors such as those based on MEMS
technology. These systems are often very small and require little power; however,
their applications are limited by the reliance on battery power. Ambient energy
harvesting cannot only be realized by conventional optical cell power generation, but
also through miniature piezoelectric crystals, micro oscillators, thermoelectric power
generation elements, or electromagnetic wave reception devices [12] [13]. Some
companies have begun to commercialize sensor network applications using energy
acquisition devices. For example, the German company EnOcean has provided light
energy harvesting devices, vibration energy harvesting devices and temperature-
based energy harvesting devices for smart building lighting and air monitoring
applications. For equipment and construction health monitoring applications, a
variety of piezoelectric vibration energy harvesting products have entered the
market. The British company of Perpetuum provides a series of products that
converts mechanical vibration into electrical energy used to perpetually power
autonomous, maintenance-free industrial wireless sensor nodes. For these sensor
nodes, the energy of vibration made by your fingers knocking the desk can support
the sensor node sending 2 kB data to 100 m away every 60 seconds. For the
monitoring applications of piping systems, a large number of products based on
temperature difference energy harvesting have been developed. Nextreme
Company’s products can produce 0.25 W of power by a temperature difference of 60
°C in an area of 3.2 mm × 1.6 mm energy harvesting materials. Figures 3-4 and 3-5
show some sensor nodes configured with ambient energy harvesting devices.
Sensor nodes configured with ambient energy harvesting devices

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3. Access network technologies the access network, whose length ranges from a few
hundred meters to several miles, includes all the devices between the backbone
network and the user terminals. It is thus aptly called “the last mile”. Because the
backbone network usually uses optical fiber structure with a high transmission rate,
the access network has become the bottleneck of the entire network system. As
shown in Figure 3-6, due to the open property of wireless channels, conflicts will
happen in time, space or frequency dimension when the channel is shared among
multiple users. The function of access network technologies is to manage and
coordinate the use of channels resources to ensure the interconnection and
communication of multiple users on the shared channel. According to the distance
and speed of access, existing access technologies can be classified into four
categories: wireless local area network (WLAN), wireless metropolitan area network
(WMAN), wireless personal area network (WPAN) and wireless wide area network
(WWAN). However, the overall developing trend of high transmission rates is not
suitable for the application requirements of WSNs. The main reasons are as follows:
§ In terms of reliability, the working environment of WSNs is usually rather severe.
The bad environment with narrow-band multi-frequency noise, interference and
multi-path effects makes the reliable communication based on the rare channel
resources an urgent problem, which needs to be resolved.
In terms of real-time capability, applications for WSN and IoT have stricter real-time
requirements than the others. A tiny latency may lead to a major mishap. Therefore,
hard real-time communication has to be guaranteed in many applications. § In terms
of energy efficiency, low energy consumption is the key to support the long flow of
independent battery-powered devices and to reduce maintenance cost. This is also
another requirement for WSNs and IoT applications, especially for the devices with
batteries difficult to be replaced. According to the current specific requirements for
WSN applications, the development of access network technology has already made
significant progresses. The representative access technologies that are more
systematic and noteworthy are Bluetooth 4.0 oriented towards medical WSN; IEEE
802.15.4e oriented towards industrial WSN; and WLAN IEEE 802.11™ in view of the
IoT. These technologies are described further in Annex A.
Access technologies

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4. Topology
Generally, a WSN consists of a number of sensor network nodes and a gateway for
the connection to the internet. The general deployment process of a WSN is as
follows (see Figure 3-8): firstly, the sensor network nodes broadcast their status to
the surroundings and receive status from other nodes to detect each other.
Secondly, the sensor network nodes are organized into a connected network
according to a certain topology (linear, star, tree, mesh, etc.). Finally, suitable paths
are computed on the constructed network for transmitting the sensing data.
Batteries usually provide the power of sensor network nodes, so the transmission
distance of WSN nodes is short. The transmission distance can be up to 800 to 1 000
meters in the open outdoor environment with line of sight. It will sharply decline in
the case of a sheltered indoor environment to an estimated few meters. In order to
expand the coverage of a network, the sensor network uses multi-hop transmission
mode. That is to say, the sensor network nodes are both transmitter and receiver.
The first sensor network node, the source node, sends data to a nearby node for
data transmission to the gateway. The nearby node forwards the data to one of its
nearby nodes that are on the path towards the gateway. The forwarding is repeated
until the data arrives at the gateway, the destination. The protocols and some
implementation techniques of WSNs can be adapted to the mature architecture and
technologies of wireless and wired computer networks. However, the features of
Developing trends of access technologies

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WSNs are self-organization, self-adaption, limited nodes energy, and unstable
transmission links.
4.1 Self-organizing and reliable networking technology
The positions of WSN nodes are random, and the nodes can be moved, sheltered
and interfered with. The topology of mesh networks have great advantages in
flexibility and reliability compared with other network topologies. The self-organizing
management approach of network nodes can greatly improve the robustness of the
network, resulting in a smart mesh networking technology, as shown in Figure 3-9. In
smart mesh ad hoc networking technology, the node first monitors the neighbour
nodes and measures the signal strength, and then it selects the appropriate
neighbour node for time synchronization and sends a joining request. Then the
neighbour node delivers the request to the gateway. The gateway receives the
request and assigns network resources for the node. Based on the mesh network,
the sensor network nodes can be assigned with two or more transmission paths to
improve the reliability of network. Time synchronized mesh protocol (TSMP)
network [19] of the dust network can support self-organizing network and maintain
a network consisted of one hundred nodes.
4.2 Low cost IP interconnection technology
the design of early sensor networks commonly used internal addresses to manage
the sensor network nodes. The address length was relatively short and suitable for
Organizing and transmitting process of WSNs

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implementing in low-power embedded sensor network nodes. However, the internal
address management method is not compatible with the IP method of the internet,
which increased the difficulty of interacting between the sensor network nodes and
the traditional IP network nodes. Therefore, there is a need to resolve
The connectivity problem of WSN and IP network. Traditional IPv4 addresses have
been gradually depleted, and the new IPv6 technology has an enormous address
resource, which is suitable for a wide range of sensor network deployment. As a
result, 6LoWPAN low-power wireless technology based on IPv6 has emerged [20].
6LoWPAN has generally implemented a simplified IPv6 protocol above the link layer
of the IEEE 802.15.4 protocol. Header compression and packet fragmentation
reloading is implemented by adding an adaptation layer between the IP layer and
the link layer, which is a reliable method to achieve protocol adaptive between IPv6
network and the sensor network, as shown in Figure 3-10. The sensor network
products of Sensinode Company based on Nano Stack and of TI Company based on
CC-6LoWPAN [22] all use 6LoPAN technology to provide the capability of scalability,
seamless and reliable interconnection between sensor network and IP network.
Mesh self-organizing network

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6LoWPAN protocol stack
6LoWPAN improved header compression example

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4.3 Self-adaptive flow control technology
One of the differences between WSNs and traditional wired networks is the
instability of wireless communication. In WSNs, the communication between nodes
is susceptible to interference and occlusion, resulting in signal transmission failure.
The traditional network is a stable wired network, which data will only be lost due to
congestion. The principle of flow control is that the data sender adjusts the sending
traffic according to the loss situation of data transmission. When data loss occurs,
the sender decreases the transmission rate. And when the data is not lost, the
sender increases the transmission rate. Such flow control mechanisms are no longer
suitable for WSNs, because the data loss in sensor networks is mostly caused by
congestion, interference and occlusion. Purely decreasing the transmission rate
cannot solve the problem, but only lowers the network performance. In order to
solve the network performance degradation problem in unstable transmission
conditions, adaptive flow control is proposed. Adaptive flow control checks the
reason for packet loss and adjusts the transmission flow. Meanwhile, according to
the quality of the link and the number of transmission errors, the best transmission
rate for the data transmission between nodes is prioritized to obtain good network
stability while considering the transmission distance and throughput.
5. Data aggregation
In the energy-constrained sensor network environments, it is unsuitable in
numerous aspects of battery power, processing ability, and storage capacity and
communication bandwidth, for each node to transmit data to the sink node. This is
because in sensor networks with high coverage, the information reported by the
neighbouring nodes has some degree of redundancy, thus transmitting data
separately in each node while consuming bandwidth and energy of the whole sensor
network, which shortens lifetime of the network. To avoid the above-mentioned
problems, data aggregation techniques have been introduced. Data aggregation is
the process of integrating multiple copies of information into one copy, which is
effective and able to meet user needs in middle sensor nodes. The introduction of
data aggregation benefits both from saving energy and obtaining accurate
information. The energy consumed in transmitting data is much greater than that in
processing data in sensor networks. Therefore, with the node’s local computing and
storage capacity, data aggregating operations are made to remove large quantities
of redundant information, so as to minimize the amount of transmission and save
energy. In the complex network environment, it is difficult to ensure the accuracy of
the information obtained only by collecting few samples of data from the distributed
sensor nodes. As a result, monitoring the data of the same object requires the
collaborative work of multiple sensors that effectively improves the accuracy and the
reliability of the information obtained. The performance of data aggregation
protocol is closely related to the network topology. It is then possible to analyze
some data aggregation protocols according to star, tree, and chain network could

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save energy and improve information accuracy, while sacrificing performance in
other areas. On one hand, in the data transfer process, looking for aggregating
nodes, data aggregation operations and waiting for the arrival of other data are
likely to increase in the average latency of the network. On the other hand,
compared to conventional networks, sensor networks have higher data loss rates.
Data aggregation could significantly reduce data redundancy but lose more
information inadvertently, which reduces the robustness of the sensor network.
Three kinds of WSN topologies: star, tree, chain

Wireless Sensor Networks

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