An Analysis Of Lifetime Of Wireless Sensor Network

Published Date: 02 Nov 2017

Abstract

The advancement in last decade in electronics & communication, computer science and information technology domain has resulted in the new computing and communication era, known as Wireless Sensor Networks. . In the past the wired sensors were implemented in limited applications in industries. However, wireless implementation makes the wide deployment of sensor nodes more feasible than before. There has been much research regarding the great potential capabilities of wireless sensor networks (WSNs) in applications such as environmental monitoring, habitat study, military surveillance in the battlefield and home automation. With sharp decreases in cost and tangible improvements in storage and processing capabilities of sensor nodes, the integrated presence of sensor nodes in human everyday-life, as the connector of the physical environment with virtual digital world, will be dominant in near future. This paper survey Wireless Sensor Networks (WSN) and their technologies, routing and applications.

KEYWORDS

Sensor networks, virtual coordinates ad hoc routing.

INTRODUCTION.

Wireless Sensor Networks (WSNs) employ a large number of miniature disposable autonomous devices known as sensor nodes to form the network without the aid of any established infrastructure. In a WSN, the individual nodes are capable of sensing the environments, processing the information locally, or sending it to one or more collection points through a wireless link. Wireless sensor nodes or sensors are hardware devices that are small in size, consume extremely low energy, operate in high volumetric densities, are autonomous and operate unattended, and is adaptive to the environment. Sensors produce a measurable response to a change in a physical condition like temperature or pressure. The continual analog signal produced by the sensors is digitized by an analog-to-digital converter and sent to controllers for further processing.

Sensors are classified into three categories: passive, omni-directional sensors; passive, narrow-beam sensors; and active sensors. Passive sensors sense the data without actually manipulating the environment by active probing. They are self powered; that is, energy is needed only to amplify their analog signal. Active sensors actively probe the environment, for example, a sonar or radar sensor, and they require continuous energy from a power source. Narrow-beam sensors have a well-defined notion of direction of measurement, similar to a camera. Omni-directional sensors have no notion of direction involved in their measurements.

WSNs work with passive, omni-directional sensors. Each sensor node has a certain area of coverage for which it can reliably and accurately report the particular quantity that it is observing. Several sources of power consumption in sensors are: signal sampling and conversion of physical signals to electrical ones, signal conditioning, and analog-to-digital conversion. Spatial density of sensor nodes in the field may be as high as 20 nodes per cubic meter.

WSN Architecture

The architecture of WSN is different for a single node and the network as a whole. The main objectives of sensor node architecture are energy efficiency, small size and low cost. The architecture for network as a whole is a set of principles that guide where functionality should be implemented along with a set of interfaces, functional units, protocols, and physical hardware that follows those guidelines.

The figure 1[1] shows the functional block diagram of a sensor node.

Figure 1: Block diagram of WSN [1]

A wireless sensor node or node is also known as mote and is made up of the following four functional components: sensing unit, processing unit, transceiver, and power unit.

Sensing Unit

It consists of an array of sensors that can measure the physical characteristics of its environment.

Processing Unit

A sensor node uses a microcontroller instead of a microprocessor. The controller performs task, processes data and controls the functionality of other components in the sensor node. A microcontroller is often used in many embedded systems such as sensor nodes because of its low cost, flexibility to connect to other devices, ease of programming, and low power consumption. A general purpose microprocessor generally has higher power consumption than a microcontroller; therefore it is often not considered a suitable choice for a sensor node.

From an energy perspective, the most relevant kinds of memory are the on-chip memory of a microcontroller and flash memory. Flash memories are used due to their cost and storage capacity. Memory requirements are very much application dependent. Two categories of memory based on the purpose of storage are: user memory used for storing application related or personal data, and program memory used for programming the device. Program memory also contains identification data of the device if present.

Transceiver

Transceiver is used to send and receive messages wirelessly. The functionality of both transmitter and receiver are combined into a single device known as a transceiver. In WSN any node has to "converse" with other nodes. Nodes are constrained by limited energy. A transceiver must provide an adequate balance between a low data rate and small energy consumption. This enables the node to live for an extended period of time.

Sensor nodes generally make use of ISM band, which gives free radio, spectrum allocation and global availability. The possible choices of wireless transmission media are radio frequency (RF), optical communication (laser) and infrared. Lasers require less energy, but need line-of-sight for communication and are sensitive to atmospheric conditions. Infrared, like lasers, needs no antenna but it is limited in its broadcasting capacity. Radio frequency-based communication is the most relevant that fits most of the WSN applications. WSNs tend to use license-free communication frequencies: 173, 433, 868, and 915 MHz; and 2.4 GHz. Radio frequency communication is ideal for WSNs in most cases since it is not limited by line of sight. The current technology allows implementation of low-power radio.

Energy consumption of the transceiver is far greater than the energy consumption of the microcontroller. Hence sensor nodes must do in-network processing as possible.

After the appearance in 2003 of the IEEE 802.15.4 standard for low-rate wireless personal area networks (PANs), most sensor nodes use transceivers that comply with this standard. Transceivers lack unique identifiers. The operational states of transceiver are transmitting, receiving, idling, and sleeping. Most transceivers operating in idle mode have power consumption almost equal to the power consumed in receive mode. Thus, it is better to completely shut down the transceiver rather than leave it in the idling mode when it is not transmitting or receiving. A significant amount of power is consumed when switching from sleep mode to transmit mode in order to transmit a packet.

Power source

Power source provides the energy required by all components. A wireless sensor node is a popular solution when it is difficult or impossible to run a mains supply to the sensor node. However, since the wireless sensor node is often placed in a hard-to-reach location, changing the battery regularly can be costly and inconvenient. An important aspect in the development of a wireless sensor node is ensuring that there is always adequate energy available to power the system. The sensor node consumes power for sensing, communicating and data processing. More energy is required for data communication than any other process. Power is stored either in batteries or capacitors. Batteries, both rechargeable and non-rechargeable, are the main source of power supply for sensor nodes. Current sensors are able to renew their energy from solar sources, temperature differences, or vibration.

Operating Systems for WSN

WSNs are composed of large numbers of tiny-networked devices that can communicate. Operating systems are the basis of the sensor node architecture. The requirements of operating system architecture in WSNs are:

Extremely small footprint,

Extremely low system overhead, and,

Extremely low power consumption.

When designing or selecting operating systems for WSN, the main goal is to reduce memory size and system overheads because of the resource constraints in WSN hardware platform. According to [2] and [3] three classifications of operating system architectures are described for wireless sensor nodes. They are monolithic, modular/micro and virtual machine.

TinyOS[4] is one of the first operating system specially designed for WSNs. TinyOS has a component-based architecture which enables rapid innovation and implementation along with minimizing code size necessary due to sever memory constraints in WSNs. TinyOS’s component library includes network protocols, distributed services, sensor drivers, and data acquisition tools - all of which can be further refined for custom application. TinyOS is an open source OS based on an event-driven programming model. Contiki [5] is another open source OS specifically designed for WSNs. The Contiki kernel is event-driven, like TinyOS, but the system supports multithreading on a per-application basis. Contiki provides IP communication, both for IPv4 and IPv6. Many key mechanisms and ideas from Contiki have been widely adopted within the industry. SOS (SOS Embedded Operating System) [6] is an event-driven OS for mote-class sensor nodes that adopts a more dynamic point on the design spectrum. The prime feature of SOS is its support for loadable modules. LiteOS [7] is an open source, interactive, UNIX-like operating system designed for WSNs. With the tools that come from LiteOS, it is possible to operate one or more WSNs in a Unix-like manner. It is also possible to develop programs for nodes, and wirelessly distribute such programs to sensor nodes.

According to [3], [8], [9] and [10] there are a total of thirty nine operating systems identified for WSNs.

Topologies for WSN

Wireless sensor nodes are typically organized in one of three types of network topologies:

Star topology: Each node connects directly to a gateway.

Cluster tree topology: Each node connects to a node higher in the tree and then to the gateway, and data is routed from the lowest node on the tree to the gateway.

Mesh networks: Nodes can connect to multiple nodes in the system and pass data through the most reliable path available. It offers increased reliability.

Lifecycle of WSN

Characteristically, there are four phases in the lifecycle of a wireless sensor network (the implementation phase is omitted because the sensor code is frequently reused) [7]. Researchers are usually involved in the planning and deployment phase, while the final customers are more interested in monitoring and control the WSN.

Planning WSNs Planning phase usually involves the inspection of the deployment area and the selection of the correct locations to position the sensors in a way that accomplishes the intended goal.

Deploying WSNs In the deployment phase, sensor nodes continually send their wireless connection quality and route to the base.

Monitoring WSNs In this phase, the user interest is mainly focuses on the values read by network sensors.

Controlling WSNs The application can also be used to control WSNs by sending commands to the network. These commands can tell the network devices to stop sending messages, increase the time between messages or even reset the network (restart the Multi-Hop algorithm). In future, WSNs could be controlled via a web interface or a handheld device, being easier to stop and restart the network as needed.

Node Deployment in WSN

WSN is deployed to measure environment parameters in Region of Interest (ROI) and to send it to a controller node or base station. In WSNs deployment of node is basically application specific and totally dependent on environment. The node deployment option affects the performance of routing protocol basically in terms of energy consumptions. Basically there are three ways in which tiny sensor nodes can be deployed in a wireless sensor network environment:

• Regular Deployment - Sensor nodes can be deployed in a well planned, fixed manner; not necessarily geometric structure, but that is often a convenient assumption. In this type of deployment data is routed through a predefined path.

Area of Use: Medical and health, Industrial sector, Home networks, etc.

• Random Deployment – Sensor nodes are scattered over finite area. When the deployment of nodes is not predefined optimal positioning of cluster head becomes a critical issue to enable energy efficient network operation. Random deployment is generally used in rescue operations.

Area of Use: Environmental and Habitual monitoring, etc.

• Sensor Nodes with Mobility – Nodes can move to compensate for deployment shortcomings. They can be passively moved around by some external force such as wind, water, vehicle etc. or can actively seek out "interesting" areas.

Area of Use: Battle field surveillances, Emergency situations (Fire, Volcano, Tsunami), etc.

Routing in WSN

Routing is a process of determining a path between source and destination for data transmission. Routing in WSN is very challenging due to the inherent characteristics that distinguish these networks from other wireless networks like mobile ad hoc networks or cellular networks. In WSN the routing protocols [11] [12] are application specific, data centric, capable of aggregating data and capable of optimizing energy consumption. The important characteristics of a good routing protocol for WSN are simplicity, energy awareness, adaptability and scalability due to limited energy supply, limited computation power, limited memory and limited bandwidth of WSN [13][14][15]. The main design goal of WSNs is to carry out data communication while trying to prolong the lifetime of the network. The design of routing protocol in WSNs is influenced by many challenging factors as summarized below:

Node deployment: Node deployment in WSN is application dependent and affects the performance of the routing protocol. The deployment is either deterministic (manual) or self-organizing (random).

Network dynamics: Most of the network architectures assume that sensor nodes are stationary, because there are very few setups that utilize mobile sensors. Route stability becomes an important optimization factor, in addition to energy, bandwidth etc. as communication from moving nodes is more challenging. Further, the sensed event can also be either dynamic or static depending on the application.

Energy Conservation: During the creation of an infrastructure, the process of setting up the routes is greatly influenced by energy considerations [16] [17] [18]. Multi-hop routing will consume less energy than direct communication. However, multi-hop routing introduces significant overhead for topology management and medium access control. Direct routing would perform well enough if all the nodes were very close to the sink. Most of the time, sensors are scattered randomly over an area of interest and multi-hop routing becomes unavoidable.

Fault Tolerance: If sensor nodes fail, MAC and routing protocols must accommodate formation of new links so that sensor node failure should not affect the overall task of the sensor network.

Scalability: The number of sensor node in the target area may be on the order of hundreds or thousands, or more so protocols should be able to scale to such high degree and take advantage of the high density of such networks.

Production Costs: The cost of a single node must be low.

Hardware Constraint: All subunits of sensor node, that is sensing, processing, communication, power, location finding system and mobilize, must consume extremely low power [19] and be contained within an extremely small volume.

Sensor network topology: It must be maintained even with very high node density.

Environment: Nodes should be operating in inaccessible location because of hostile environment.

Transmission Media: Generally, transmission media is wireless (RF or Infrared), which is affected by fading and high error rate and affect the operation of WSNs.

Data delivery models: Data delivery model to the sink can be continuous, event driven, query-driven and hybrid, depending on the application of the sensor network.

Quality of Service (QoS): Quality service required by the application, involves: length of life time, data reliability, energy efficiency, location awareness, collaborative-processing, etc. QoS factors will affect the selection of routing protocols for a particular application.

Security: Security concerns needs special attention in current era where data stealing and data diddling becomes major issue.

Node capabilities: Depending on the application, a node can be dedicated to a particular special function such as relaying, sensing and aggregation since engaging the three functionalities at the same time on a node may quickly drain the energy of that node.

Data aggregation/fusion: Data aggregation is the combination of data from different sources by using functions such as suppression (eliminating duplicates), min, max and average. Similar packets from multiple nodes can be aggregated to reduce the transmission.

Byte Overhead [20]: Byte overhead means the total number of bytes in the routing control messages needed to find a route to the sink. For flooding, byte overhead means the total number of bytes in the extra messages flooded throughout the network. In both cases the bytes in the data packets transmitted by nodes along the route from the originating node to the sink node are not counted as overhead.

All systems, processes and communication protocols for sensors and sensor networks must minimize power consumption. Each sensor node in WSN coordinates with its neighbor nodes in forwarding their packets towards destination. Placements of nodes in improper places and difficulty in charging or recharging batteries have made researchers to do investigations on reduction of energy consumption [21]. The limited power of sensor nodes mandates the design of energy-efficient communication protocol [22]. In order to effectively use the limited energy available, computation costs which are much smaller than the communications cost, is utilized to minimize the amount of information that actually has to be sent [23, 24]. The communication cost can be reduced significantly by using cluster based communication as compared to one without clustering. The clustering protocol supports in-network aggregation which is used to aggregate information from various sensors and to summarize that information before communicating and passing it on to the other nodes. This increases the life span of WSNs. The clustering protocols have other advantages like scalable, energy efficient in finding routes and easy to manage.

Applications of WSN

In the recent past, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics [25]. WSNs can be applied in a wide range of areas, such as: habitat monitoring and tracking, disaster relief, emergency rescue operation, home networks, detecting chemical/biological /radiological /nuclear/explosive material, monitoring patents and elderly people, asset and warehouse management, building monitoring and control, fleet monitoring, military battlefield awareness and surveillance, security and surveillance, environmental monitoring, pipeline corrosion monitoring, homeland security, monitoring conditions of buildings and bridges, industrial process monitoring and control, machine health monitoring, healthcare applications, home automation, traffic control, etc.

The table 1 below summarizes some applications for different areas.

Area

Applications

Military

• Military situation awareness [26].

• Sensing intruders on basis. [27]

• Detection of enemy unit movements on land and sea [27].

• Battle field surveillances[28]

Emergency

situations

• Disaster management [29].

• Fire/water detectors.[ 27]

• Hazardous chemical level and fires [30].

Physical world

• Environmental monitoring of water and soil [31].

• Habitual monitoring [31].

• Observation of biological and artificial systems [31].

• Marginal Farming.

Medical and health

• Sensors for blood flow, respiratory rate, ECG (electrocardiogram), pulse oxymeter, blood pressure and oxygen measurement [32].

• Monitoring people’s location and health condition.

Industry

• Factory process control and industrial automation [26].

• Monitoring and control of industrial equipment [30].

• Machine health monitoring [33].

Home networks

• Home appliances, location awareness (blue tooth).

• Person locator.

Automotive

• Tire pressure monitoring [30,34].

• Active mobility [35].

• Coordinated vehicle tracking [26].

Area monitoring

• Detecting enemy intrusion [26]

• Geo-fencing of gas or oil pipelines [27].

• Detecting the presence of vehicles [26].

8. Conclusion

This paper carries out a survey on Wireless Sensor Networks (WSN) based on their technologies, routing and applications. WSNs consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. In comparison with the traditional Mobile Ad hoc Network, WSNs have different characteristics and poses different design challenges. In WSNs the solutions are primarily application-specific.

The flexibility, fault tolerance, high sensing dependability, low cost, and swift deployment characteristics of sensor networks create many new and exciting application areas for remote sensing. In the future, this wide range of application areas will make sensor networks an integral part of our lives. However, realization of sensor networks needs to satisfy the constraint introduced by factors such as fault tolerance, scalability, cost, hardware, topology change, location, and power utilization.