Building wireless M2M & IoT sensor networks: issues and challenges -

Building wireless M2M & IoT sensor networks: issues and challenges


In the first of in a four part series on implementation of wireless sensor networks the authors of “Ad hoc wireless networks,” summarize the issues and challenges involved in the design of two different types, layers and clustered.

Sensor networks are highly distributed networks of small, lightweight wireless nodes, deployed in large numbers to monitor the environment or system by the measurement of physical parameters such as temperature, pressure, or relative humidity. Building sensors has been made possible by the recent advances in micro-electro mechanical systems (MEMS) technology[1].

Each node of the sensor network consists of three subsystems: the sensor subsystem which senses the environment, the processing subsystem which performs local computations on the sensed data, and the communication subsystem which is responsible for message exchange with neighboring sensor nodes.

While individual sensors have limited sensing region, processing power, and energy, networking a large number of sensors gives rise to a robust, reliable, and accurate sensor network covering a wider region. The network is fault-tolerant because many nodes are sensing the same events.

Further, the nodes cooperate and collaborate on their data, which leads to accurate sensing of events in the environment. The two most important operations in a sensor network are data dissemination, that is, the propagation of data/queries throughout the network, and data gathering, that is, the collection of observed data from the individual sensor nodes to a sink.

Sensor networks consist of different types of sensors such as seismic, thermal, visual, and infrared, and they monitor a variety of ambient conditions such as temperature, humidity, pressure, and characteristics of objects and their motion.

Sensor nodes can be used in military, health, chemical processing, and disaster relief scenarios. Some of the academic and industry-supported research programs on sensor networks include working on Smart Dust at the University of California, Berkeley (UCB), and wireless integrated network sensor (WINS) at the University of California, Los Angeles (UCLA).

Applications of Sensor Networks
Sensor nodes are used in a variety of applications which require constant monitoring and detection of specific events. The military applications of sensor nodes include battlefield surveillance and monitoring, guidance systems of intelligent missiles, and detection of attack by weapons of mass destruction, such as chemical, biological, or nuclear.

Sensors are also used in environmental applications such as forest fire and food detection, and habitat exploration of animals. Sensors can be extremely useful in patient diagnosis and monitoring. Patients can wear small sensor devices that monitor their physiological data such as heart rate or blood pressure.

The data collected can be sent regularly over the network to automated monitoring systems which are designed to alert the concerned doctor on detection of an anomaly.

Such systems provide patients a greater freedom of movement instead of their being conbined to a hospital. Sensor nodes can also be made sophisticated enough to correctly identify allergies and prevent wrong diagnosis.

Sensors will soon find their way into a host of commercial applications at home and in industries. Smart sensor nodes can be built into appliances at home, such as ovens, refrigerators, and vacuum cleaners, which enable them to interact with each other and be remote-controlled.

The home can provide a “smart environment” which adapts itself according to the user’s tastes. For instance, the lighting, music, and ambiance in the room can be automatically set according to the user’s preferences. Similar control is useful in office buildings too, where the airflow and temperature of different parts of the building can be automatically controlled.

Warehouses could improve their inventory control system by installing sensors on the products to track their movement. The applications of sensor networks are endless, limited only by the human imagination.

Comparison with Ad Hoc Wireless Networks
While both ad hoc wireless networks and sensor networks consist of wireless nodes communicating with each other, there are certain challenges posed by sensor networks. The number of nodes in a sensor network can be several orders of magnitude larger than the number of nodes in an ad hoc network.

Sensor nodes are more prone to failure and energy drain, and their battery sources are usually not replaceable or rechargeable. Sensor nodes may not have unique global identifiers, so unique addressing is not always feasible in sensor networks.

Sensor networks are data-centric, that is, the queries in sensor networks are addressed to nodes which have data satisfying some conditions. For instance, a query may be addressed to all nodes “in the south-east quadrant,” or to all nodes “which have recorded a temperature greater than 30 degrees Centigrade.””

On the other hand, ad hoc networks are address-centric, with queries addressed to particular nodes specified by their unique address. Hence, sensor networks require a different mechanism for routing and answering queries. Most routing protocols used in ad hoc networks cannot be directly ported to sensor networks because of limitations in memory, power, and processing capabilities in the sensor nodes and the non-scalable nature of the protocols.

An important feature of sensor networks is data fusion/aggregation, whereby the sensor nodes aggregate the local information before relaying. The main goals of data fusion are to reduce bandwidth consumption, media access delay, and power consumption for communication.

Issues and Challenges in Designing a Sensor Network
Sensor networks pose certain design challenges due to the following reasons:

1. Sensor nodes are randomly deployed and hence do not fit into any regular topology. Once deployed, they usually do not require any human intervention. Hence, the setup and maintenance of the network should be entirely autonomous.

2 . Sensor networks are infrastructure-less. Therefore, all routing and maintenance algorithms need to be distributed.

3. An important bottleneck in the operation of sensor nodes is the available energy. Sensors usually rely only on their battery for power, which in many cases cannot be recharged or replaced. Hence, the available energy at the nodes should be considered as a major constraint while designing protocols. For instance, it is desirable to give the user an option to trade off network lifetime for fault tolerance or accuracy of results.

4. Hardware design for sensor nodes should also consider energy efficiency as a primary requirement. The micro-controller, operating system, and application software should be designed to conserve power.

5. Sensor nodes should be able to synchronize with each other in a completely distributed manner, so that TDMA schedules can be imposed and temporal ordering of detected events can be performed without ambiguity.

6. A sensor network should also be capable of adapting to changing connectivity due to the failure of nodes, or new nodes powering up. The routing protocols should be able to dynamically include or avoid sensor nodes in their paths.

7. Real-time communication over sensor networks must be supported through provision of guarantees on maximum delay, minimum bandwidth, or other quality of service (QoS) parameters.

Provisions must be made for secure communication over sensor networks, especially for military applications which carry sensitive data. The protocols which have been designed to address the above issues have been classified in Figure 12.1 below.

Clickon image to enlarge.

Figure 12.1. Classification of sensor network protocols

Sensor Network Architectures
The design of sensor networks is influenced by factors such as scalability, fault tolerance, and power consumption [1]. The two basic kinds of sensor network architecture are layered and clustered.A layered architecture has a single powerful base station (BS), and the layers of sensor nodes around it correspond to the nodes that have the same hop-count to the BS. This is depicted in Figure 12.2 below.

Figure 12.2. Layered architecture

Layered architectures have been used with in-building wireless backbones, and in military sensor-based infrastructure, such as the multi-hop infrastructure network architecture (MINA) [2]. In the in-building scenario, the BS acts an an access point to a wired network, and small nodes form a wireless backbone to provide wireless connectivity.

The users of the network have hand-held devices such as PDAs which communicate via the small nodes to the BS. Similarly, in a military operation, the BS is a data-gathering and processing entity with a communication link to a larger network.

A set of wireless sensor nodes is accessed by the hand-held devices of the soldiers. The advantage of a layered architecture is that each node is involved only in short-distance, low-power transmissions to nodes of the neighboring layers.

Unified Network Protocol Framework.
UNPF [2] is a set of protocols for complete implementation of a layered architecture for sensor networks. UNPF integrates three operations in its protocol structure: network initialization and maintenance, MAC, and routing protocols.

Network Initialization and Maintenance Protocol. The network initialization protocol organizes the sensor nodes into different layers, using the broadcast capability of the BS. The BS can reach all nodes in a one-hop communication over a common control channel. The BS broadcasts its identifier (ID) using a known CDMA code on the common control channel.

All nodes which hear this broadcast then record the BS ID. They send a beacon signal with their own IDs at their low default power levels. Those nodes which the BS can hear form layer one since they are at a single-hop distance from the BS. The BS now broadcasts a control packet with all layer one node IDs. All nodes send a beacon signal again. The layer one nodes record the IDs which they hear, and these form layer two, since they are one hop away from layer one nodes.

In the next round of beacons, the layer one nodes inform the BS of the layer two nodes, which is then broadcast to the entire network. In this way, the layered structure is built by successive rounds of beacons and BS broadcasts. Periodic beaconing updates neighbor information and alters the layer structure if nodes die out or move out of range.

MAC Protocol. Network initialization is carried out on a common control channel. During the data transmission phase, the distributed TDMA receiver oriented channel (DTROC) assignment MAC protocol [3] is used. Each node is assigned a reception channel by the BS, and channel reuse is such that collisions are avoided. The node schedules transmission slots for all its neighbors and broadcasts the schedule.

This enables collision-free transmission and saves energy, as nodes can turn off when they are not involved in a send/receive operation. The two steps of DTROC are channel allocation (the assignment of reception channels to the nodes) and channel scheduling (the sharing of the reception channel among the neighbors). DTROC avoids hidden terminal and exposed terminal problems by suitable channel allocation algorithms.

Routing Protocol. Downlink from the BS is by direct broadcast on the control channel. The layered architecture enables multi-hop data forwarding from the sensor nodes to the BS. The node to which a packet is to be forwarded is selected considering the remaining energy of the nodes. This achieves a higher network lifetime. Existing ad hoc routing protocols can be simplified for the layered architecture, since only nodes of the next layer need to be maintained in the routing table.

A modification to the UNPF protocol set termed the UNPF-R [2] makes the sensor nodes adaptively vary their transmission range so that network performance can be optimized. While a very small transmission range could cause network partitioning, a very large transmission range will reduce the spatial reuse of frequencies. The optimal range is determined through an algorithm similar to simulated annealing. This is a centralized control algorithm in which the BS evaluates an objective function periodically.

The advantage of the UNPF-R is that it minimizes the energy delay metric, and maximizes the number of nodes which can connect to the BS. The minimization of the energy delay metric ensures that transmission should occur with minimum delay and with minimum energy consumption. The two conflicting objectives are together optimized by minimizing their product.

Clustered sensor architectures
A clustered architecture organizes the sensor nodes into clusters, each governed by a cluster-head. The nodes in each cluster are involved in message exchanges with their respective cluster-heads, and these heads send messages to a BS, which is usually an access point connected to a wired network. Figure 12.3 below represents a clustered architecture where any message can reach the BS in at most two hops. Clustering can be extended to greater depths hierarchically.

Figure 12.3. Clustered architecture.

The clustered architecture is particularly useful for sensor networks because of its inherent suitability for data fusion. The data gathered by all members of the cluster can be fused at the cluster-head, and only the resulting information needs to be communicated to the BS. Sensor networks should be self-organizing, hence the cluster formation and election of cluster-heads must be an autonomous, distributed process. This is achieved through network layer protocols such as the low-energy adaptive clustering hierarchy (LEACH) .

Low-Energy Adaptive Clustering Hierarchy . LEACH is a clustering-based protocol that minimizes energy dissipation in sensor networks. LEACH randomly selects nodes as cluster-heads and performs periodic reelection, so that the high-energy dissipation experienced by the cluster-heads in communicating with the BS is spread across all nodes of the network. Each iteration of selection of cluster-heads is called a round. The operation of LEACH is split into two phases: set-up and steady.

During the set-up phase, each sensor node chooses a random number between 0 and 1. If this is lower than the threshold for node n, T(n), the sensor node becomes a cluster-head. The threshold T(n)is calculated as

where P is the desired percentage of nodes which are cluster-heads, r is the current round, and G is the set of nodes that has not been cluster-heads in the past 1/P rounds. This ensures that all sensor nodes eventually spend equal energy. After selection, the cluster-heads advertise their selection to all nodes. All nodes choose their nearest cluster-head when they receive advertisements based on the received signal strength. The cluster-heads then assign a TDMA schedule for their cluster members.

The steady phase is of longer duration in order to minimize the overhead of cluster formation. During the steady phase, data transmission takes place based on the TDMA schedule, and the cluster-heads perform data aggregation/fusion through local computation. The BS receives only aggregated data from cluster-heads, leading to energy conservation. After a certain period of time in the steady phase,cluster-heads are selected again through the set-up phase.

To read Part 2 , go to: Sensor data dissemination
To read Part 3, go to: Sensor data gathering and location detection
To read Part 4 , go to:High quality and low power.

C. Siva Ram Murthy received a B.Tech degree in electronics and communications engineering from the National Institute of Technology, an M.Tech degree in computer engineering from the Indian Institute of Technology, and a Ph.D in computer science from the Indian Institute of Science. He has to his credit over 100 research papers in international journals and conference publications as well as author of several text books on parallel computing, real time systems and networks, and optical networks. His research interest include parallel and distributed computing, real time systems lightwave networks, and, of course, wireless sensor networks.

B.S. Manoj is the recipient of an M.Tech degree in Electronics and Communications engineering from the Institution of Engineers in India. His research interest include ad hoc wireless networks, next generation wireless architectures and wireless sensor networks.

This series of articles is from the book “Ad Hoc Wireless Networks ,” by C. Siva Ram Murthy and B.S. Manoj, Copyright 2011, used by permission of PearsonEducation, Inc.. Written permission from Pearson Education, Inc. is required forall other uses.

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