Chapter 6 Design and Implementation of an Ultra-Low Power Wireless Sensor Node
6.2 Challenges in Wireless Sensor Nodes and Networks
A wireless sensor node is a small device that combines the sensing, processing, storage, communication and power supply in it. It collects information about the surroundings and environment and sends it to a base station or sink node directly or via other nodes. At least one sink node and a number of sensor nodes form a wireless sensor network. Sometimes, these nodes are deployed in remote and difficult to reach areas. Once deployed, these sensor nodes are usually unattended and expected to work autonomously. However, there are various challenges faced by the researchers and engineers while designing and implementing a wireless sensor network. Therefore, it is essential to understand the existing challenges in this technology. Some of the major challenges are briefly described below:
Limited Resources: A sensor node typically has low processing capability and limited amount of memory. As a result, the data processing, storage and information transferring capability of an individual sensor node is very limited. Therefore, the algorithms and protocols should be designed to make the best use of the limited resources. In addition, a wireless sensor network can consist of thousands of nodes. Therefore, it is desirable that an individual node is cheap.
Limited Energy: A sensor node needs energy for data sensing, processing and communicating. Most of the wireless sensor nodes are powered by batteries that have finite energy. Once the energy is consumed, they have to changed or recharged which
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can be difficult, expensive and cumbersome. This limited energy of the storage poses a significant challenge in the design process of a WSN. It is crucial that both the hardware design and software protocols are energy efficient.
Lifespan: The lifespan of a node is mainly restricted by limited energy. The lifespan of a sensor node can be shortened by the lifespan of the energy storage element. Ambient energy harvesting with a rechargeable storage element is the most popular solution for a wireless sensor node. However, a rechargeable energy storage element can go through a finite number of charging-discharging cycles before it can no longer meet the expected quality of service. This process can be delayed with reduced energy consumption. Therefore, the overall power consumption of a sensor node needs to be minimized in order to extend the lifespan.
Lack of Common Standards: Currently there are different solutions such as ZigBee, Z-Wave, Insteon and Wavenis for implementing a wireless sensor network. This presents a challenge to large-scale deployment, as there is no direct communication between these various standards without using gateway or proxies. However, with the implementation of Internet Protocol (IP) based standard, it would be possible to connect all smart objects and sensors via the Internet. This is vital to make the Internet of Things into a reality. The ZigBee Alliance has already embraced this solution with ZigBee IP, which is an IPv6 based solution.
Data Management: Data collection is the primary objective of a sensor node. With the ever-increasing number of devices connected to a wireless sensor network, handling of the large volume of generated data would be one of the main challenges in near future. It will be necessary to increase the memory storage and processing capability of each sensor node in the network.
Security and Interference: Data integrity, confidentiality and authenticity has to be maintained to ensure the target node receives the exact data send by the source node and the data has not been intercepted or altered by anyone in middle. It is also essential to verify that a trusted sender has sent the data. With increasing number of treats and various kinds of attacks, security is a very challenging and complex issue in a wireless sensor networks.
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6.2.1 Focus of this Work
The focus of the design and implementation of the WSN in this thesis is addressing the issue of limited energy. The work involves reduction of power consumption as well as using energy harvesting and storage to achieve autonomous operation. There has been extensive research to make the wireless sensor nodes to be highly energy efficient and self-sustaining. The issue with power consumption has been primarily addressed in the literature in two ways. The first is implementing energy- efficient communication protocols medium access control [6.4], routing [6.5], data gathering [6.6] and topology management [6.7].
The second approach is by managing power consumption to avoid wasteful and inefficient activities. The work in this thesis adapts the latter approach by reducing the power consumption during idle time by implementing a wake-up receiver (WuR). The process is described in Section 6.3.4. Besides reduced power consumption, energy harvesting and storage are equally important to address the limited available energy in a WSN. The ability of a WSN to generate electricity by ambient energy harvesting has drawn particular attention. A “direct-use” energy harvesting architecture [6.8] must generate more power than the minimum requirement at all times which is inconvenient in most situations. A WSN powered by a rechargeable battery using the harvested power from ambient energy resources is the most effective and viable solution to achieve long lifetime and low maintenance cost. This is also one of the vital features for an autonomous WSN. Several energy sources such as mechanical vibration [6.9] - [6.12], thermal [6.13], [6.14], radio frequency [6.15] - [6.18], wind [6.19] - [6.21] and light [6.22], [6.23] have been explored.
Table 6.1: A comparison of various ambient energy sources in terms of available and harvested powers [6.24]
Source Available Power
Harvested Power Efficiency Ambient Light Indoor 0.1 mW/cm2 10 µW/cm2 5-30% [6.25] Outdoor 100 mW/cm2 10 mW/cm2 Vibration /Motion Human 1 m/s0.5 m@1Hz 2@50Hz 4 µW/cm 2 1-10% [6.25] Industrial 10 m/s1 m@5Hz 2@1kHz 100 µW/cm 2 Thermal Energy Human 20 mW/cm2 30 µW/cm2 0.15% Industrial 100 mW/cm2 1-10 mW/cm2 1-10% Radio
Frequency Cell Phone 0.3 µW/cm2 0.1 µW/cm
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Table 6.1 shows a comparison of various ambient energy sources reported in literature for WSNs in terms of available and harvested power. Amongst these various sources, outdoor light is the best energy source with highest power density. It is evident from Table 6.1 that under indoor conditions, light is the best energy source considering both power density and efficiency. However, the power available is typically less than 100 µW, therefore micro-scale energy harvesting systems [6.26], [6.27] with ultra-low power circuits with maximum power point tracking (MPPT) have been proposed. Light energy harvesters have the disadvantage of being able to produce energy only in the presence of adequate light. Hybrid combination of energy sources [6.28] has been proposed to overcome this limitation. Wireless sensor nodes such as the one in this work can also solely depend on the storage element to operate in the dark or poor light conditions.