Basic Architecture of Wireless Sensor Network

Software Architecture Design of Wireless Sensor Networks
John Henkel
Department of Software Engineering
University of Wisconsin Platteville
henkelj@uwplatt.edu

Abstract
Wireless sensor networks compose a large area of current research due to advances to enabling
advances in hardware and software. The structure and concept behavior of these networks poses
a challenge in terms of software development, and requires novel programming techniques and
technologies. In particular, the dynamic topology of a wireless sensor network and use of
cooperative processing for distributed software eliminates classical methods of network
communications and organization. This document examines the characteristics of wireless
sensor networks with respect to the effective of system requirements on the resulting software
architecture.

I.

INTRODUCTION

W

IRELESS sensor networks (WSNs) are just one of the presently hot research topics.
Both civilian and military oriented institutions have diverted a great deal of funding to
research on WSNs as advances in software and hardware provide the means to make WSNs.
Wireless sensor networks are aggregates of numerous small sensor nodes. Each node can send
messages through the network to the information sink – or ultimate controlling device. The
nodes can also forward messages from other nodes, perform network organization tasks, and a
variety of other functions.
The applications of WSNs vary widely. WSNs could be used in industrial settings for machine
control and environment monitoring. Other applications could be medical – monitoring a
patient’s health from a variety of perspectives. The military is highly interested in sensor
networks for intelligence gathering, while WSNs have possible applications in aerospace for the
structural integrity of planes.
A great deal of research has already been performed on WSNs, and a number of possible
implementations and architectures suggested. The University of California - Berkley has
remained at the forefront of research, creating smart-dust, WEbS, and PicoRadio [1]. Through
all prior research, it has been shown that WSNs require unique software architecture to solve
inherent difficulties [1]. Section II of this paper examines the characteristics of a WSN for
robust operation. Section III discusses the basic components of a service oriented architecture,
while Section IV examines and compares two proposed software architectures. Section V briefly

discusses some aspects of the software development process for sensor node applications.
Section VI concludes the paper.

II.

WSN CHARACTERISTICS

The concept of wireless sensor networks implies a number of WSN characteristics which
heavily influence the software architecture. Specifically, WSNs must be self organizing,
perform cooperative processing, energy optimized, and modular. These four requirements in
particular impact heavily on the form of the software architecture.
1)

Self-Organization

The large number of nodes in a WSN renders direct manipulation by a user for network
organization impractical [1]. A user could not go through thousands of nodes directing the
network configuration and clustering. Subsequently, the nodes must be capable of organizing
the network and partitioning it for efficient operation given the environment and network
attributes [1].
Additionally, the nodes of a sensor network must be robust [2]. The aggregate formed by the
nodes must have a high up time. The large number of nodes in a network along with unattended
operation complicates any attempt at a fault tolerant design [2]. Sensor networks with wired
connections do not necessarily rely on other nodes to transmit data. This reduces the need for
redundancy and the robustness of individual nodes.
In contrast, wireless sensor network nodes transmit information from node to node with a
small amount of processing in between [2]. Consequently individual nodes must be highly
robust, while the organization of the network must tolerate individual device failure [2].
Variations in the network topology can affect the degree of network vulnerability to failures,
necessitating complex routines to implement fault tolerance [4].

2)

Concurrency, Cooperative Processing

The nodes in a network primarily direct information flow through the network to various datasinks – the points to which data from the network is fed [2]. Each sensor node may posses a
limited amount of memory, so the buffering of data is impractical [2]. Additionally, the node
performs a number of simultaneous operations: capturing, processing, and transmitting sensor
data, while simultaneously forwarding data from other nodes in multi-hop or bridging situations
[2].
WSNs also provide a unique opportunity for cooperative processing. Cooperative processing
can reduce network traffic through data aggregation and preprocessing [1]. For example, the

establishment of a wireless network might involve the triangulation of a new node when it joins a
network to establish the node’s position.
3)

Energy Efficiency

Wired sensor network have the luxury of external power sources such as power over Ethernet.
The nodes of wireless networks have no practical way of utilizing an external energy source,
which would in any case be contrary to the point of a WSN. A sensor network may also be
distributed in hostile or remote environments [1]. Energy efficiency dictates the minimization of
communication between nodes. Therefore the choice of protocols and network configuration are
key in terms of network lifespan [1]. Protocol related energy savings are directly related to the
physical, link, and network layers [1].
Additional power savings come from an operation system (OS) for the nodes which supports
advanced power management and lower power task scheduling [1]. Power sensitive task
scheduling can minimize power use though non linear battery effects [1]. Advanced power
management would put any hardware not in use to sleep, minimizing power consumption [2].
4)

Modularity

Sensor nodes in a network tend to be specific, and therefore contain only the hardware needed
for the application [2]. The range of possible applications dictates a large variance in the
hardware required for sensor nodes [2]. Accordingly, the software for the nodes must exhibit a
high degree of modularity [2].

III.

SOFTWARE ARCHITECTURE COMPONENTS

The nature of a sensor network lends itself to a service oriented component based framework.
Applications split into sensor, node, and network applications, providing the basis for
fundamental application layers in a sensor network [2].
Sensor applications interface with the sensors, local data, and hardware on a node, along with
the operating system [2]. Sensor applications form the base layer and provide the basic functions
of a sensor node [2].
Node applications use the basic functions provided by sensor applications to perform
middleware tasks for network buildup, maintenance, and localization [2]. Network applications
deal with the services and tasks of the network as a whole [2]. Network applications thereby act
as an interface to the layer administrating to the network [2].

A.

Middleware

Middleware refers “to the software layer between operating system and sensor application on
the one hand and the distributed application which interacts over the network on the other hand.”
[2] Opinions vary on the actual granularity limitations. Some maintain that middleware, in
various forms, exists in a sensor network hierarchy all the way down to individual nodes [2].
Others favor the cluster as the basic unit of middleware [3]. Regardless of the granularity, the
design of middleware aims to be scalable, adaptive, generic, and reflective.
Scalable middleware performs optimization based on resource constraints at runtime [2]. The
nature of wireless sensor networks calls for lightweight middleware, or middleware which has
low communication and computations requirements [3]. By performing optimizations at runtime
the interfaces of middleware are customized [2].
The sensor network changes as nodes move, necessitating runtime adaptations of the
middleware to exchange and run components as needed by the application [2]. Localized
algorithms can be used to enhance system scalability and robustness in the face of interactions
between sensor nodes [3]. These algorithms can also provide reflective middleware, which
changes the behavior of layers on the fly instead of exchanging them [2].
Generic middleware attempts to reduce overhead imposed by using generic interfaces for
middleware components [2]. This implies the customization of the application interfaces and
features, allowing for interpretation by middleware and compile time optimization [2][3].
Generic interfaces also allow for the standardization of system services to diverse application [3].
Conversely, while middleware interfaces may be generic, the interfaces of application
component on a specific sensor node are anything but. In short, middleware acts as an
abstraction layer to help hide software specifics from the application layer.

IV.

SOFTWARE ARCHITECTURE

The requirements and characteristics of a wireless sensor network mentioned in the previous
sections call for a service based architecture. The services provided naturally divide into layers
which vary depending on the exact topology of the network. Sections A and B examine two
possible software architectures for a WSN detailed in [1], [2], [3], and [4], accompanied by the
underlying reasoning for each architecture.

A.

A Basic Service Oriented Architecture

1) Architectural Description
A simple use case can help determine the software architecture. An example use case in [1]
provides illustration.
The client application requests data from the network about surface conditions in a certain
area. The client first sends a request to a surrogate proxy for the desired information. The proxy
communicates with the appropriate nodes, which in turn then determine the surface conditions in
the area using cooperative algorithms [1]. The proxy takes the information returned from the
nodes, translates it, and sends it back to the client [1].

Fig 1: Surrogate Architecture in Sensor Networks [1].

Fig. 1 illustrates the use case. The use case, along with the requirements and characteristics
specified in previous sections of this paper, calls for a flexible software architecture.
Such architecture can be realized using the node application structure shown in Fig. 2, along
with the sensor network architecture shown in Fig. 3.

Fig 2: Node Application Structure [1].

Figure 2 illustrates the division of node applications into three layers. The lowest layer
handles hardware specifics, such as hardware and sensor drivers. The node operating system
acts as a buffer layer between the hardware specifics and the host middleware application layer.
The operating system layer handles the processes which relate strictly to the node operation,
while the host middleware handles processes concerning the services offered by the node to the
network [1].
The middleware is comprised of four different components which are called as needed, with
the option to add additional modules for security or routing [1]. The VM or Virtual machine
component enables platform independent program execution, while algorithms define the
behavior of modules [1].

Fig 3: Sensor Network Software Architecture [1].

The general overall software architecture of the sensor net is shown in Fig. 3. The individual
nodes interact with the distributed middleware layer to perform the functions dictated by the
sensor network application. The administration terminal is a connection point independent
external actor which evaluates results from the sensor network application [1]. The diagram
specifically illustrates the behavior of the sensor network application, which cannot assign tasks
to individual nodes. Instead the layer abstract shown indicates that the distributed middleware
handles tasks for the entire network and acts as network service coordinator [1].
2) Architectural Issues
While the architecture presented certainly presents a solid and basic design for a sensor
network, it does not reflect some of the requirements such as energy efficiency which can have a
significant effect of software architecture. Network topology control in particular proves
effective to extending network life and increasing network capacity [5].
Additionally, the amount of energy available to each sensor cannot support long range
communication, necessitating a tiered network structure [4]. The need for such a network
structure then influences the software architecture design.
Finally, the use of a single tier architecture increases network load on nodes surrounding the

command node [4]. The increases traffic on these key nodes decreases their lifetime, and in turn
shortens the lifetime of the entire network. The adaptation of a multi-tiered network structure
can reduce the energy consumption imbalance if the network supports sufficient fault-tolerance
[4].

B.

A Cluster Based Service Oriented Architecture

The factors mention above can influence the software architecture of a wireless sensor network
when taken into account. A second architecture, proposed in [3], uses clustering to handle the
factors mentioned, and provide for application Quality of Service (QoS) management.
1) Architectural Description
One of the more favored network architectures for wireless sensor networks involves
clustering. A cluster is a set of adjacent sensors which are grouped together and interface with
the rest of the network through a gateway, or cluster head [4]. Gateways are higher energy nodes
which maintain the network in the cluster, perform data aggregation, and organize sensors into
subsets [4].
Clusters exhibit dynamic behavior. Clusters form and are modified on the fly depending on
conditions and node availability [4]. During cluster formation, one node is elected as the
gateway. It is important to note, that while clusters can overlap spatially, one node cannot
belong to multiple clusters [3] [4].

Distributed Cluster Middleware

Node A

Node B

Node C

Middleware

Middleware

Middleware

Operating
System

Operating
System

Operating
System

Hardware

Hardware

Hardware

Fig 4: Cluster Software Base Architecture

Given the presence of clustering, a cluster can be regarded as the base unit for the software
architecture. Given such, data collection would be performed in a distributed manner [3].
However, in order to dynamically manage these clusters, the architecture of the middleware
needs be fairly complex. Figure 4 displays the software architecture at the cluster level. Figure

5 shows a cluster based middleware architecture proposed in [3].
As shown in Figure 5, the architecture proposed contains an abstraction modeled as a Virtual
Machine, similar to the architecture conceived in Section IV.A of this paper. The Virtual
Machine provides the same service as in the first architecture – that of hardware independent
program execution [3]. However, this Virtual Machine splits down into two additional layers:
the resource management layer and the cluster layer.
The cluster layer encompasses the distributed cluster middleware illustrated in Figure 4. This
software layer forms clusters from the collection of sensor nodes surrounding the target area [3].
The exact factors controlling the initial formation of clusters can vary depending on the
application of the sensor network, and do not have significant impact on the software
architecture.

Figure 5: Middleware architecture for a cluster based WSN [3].

The resource management layer controls resource allocation and adaptation to meet QoS
requirements for the sensor network application [3]. Resource management is an important part
of QoS in distributed application such as a wireless sensor network. Environmental and system
changes can affect the amount of available resources, requiring the middleware to reallocate
resources on the fly to accomplish the tasks given by the sensor network application [3].

2) Architectural Issues
The cluster based architecture proposed faces a number of challenges inherent in its design.
The more complicated network topology incurs higher overhead costs for forming and
maintaining clusters [3]. Specifically, clusters must be formed dynamically in order to track
moving phenomena [3]. Therefore nodes would be changing cluster membership depending on
the speed of the target phenomena.
Using clusters also increases the vulnerability of the network to faults [4]. If a gateway fails,
the members of the cluster must quickly deal with the fault, by electing a new cluster head or
resorting to ad hoc networking to members of other clusters [4]. The more time is spent in
network reconfiguration the more data can be lost due to memory limitations at the effected
nodes [4]. This behavior implies an increased network vulnerability to the algorithms used for
network formation.
Overhead also comes from resource management layer. In order to effectively manage the
resources of the network, the layer must gather and update information on node energy levels,
network connectivity, cluster loads, and a number of other statistics [3]. Such polling can result
in a dramatic increase to overhead if it is not handled correctly. Obviously the amount of
overhead depends on the exact implementation of the resource management.

V.

A.

NODE SOFTWARE DEVELOPMENT

Software Development for Sensor Nodes

Sensor node software in particular lends itself well to an iterative form of development. As
with any real-time embedded system, the code must be optimized to perform within certain
parameters.
Due to the sensitivity of the performance, efficiency, and lifetime of a WSN to the algorithms
controlling network configuration, an iterative design, implementation, and test phase is
required. Since the applications of WSNs vary so greatly, the algorithms involved in a specific
type of WSN must be optimized through a large amount of calculation and design.
The development pattern for node applications suggested in [1] favors the highly iterative
design pattern show in Figure 6. The design method closely follows standard software
engineering practices. Of note, component interface optimization is performed during the design
stage as mentioned in Section III.A of this paper [1]. Evaluation through the monitoring of
results leads to additional iterations. The development pattern results in a specific application for

the node comprised of specially tailed parts.
Due to the presumption of generic middleware interfaces mentioned in Section III.A of this
paper, the design process of the distributed middleware for either of the architectures mentioned
conforms to the applicable processes used in software engineering.

Figure 6: Proposed Node Software Development Process [1].

VI.

CONCLUSION

As described above, wireless sensor networks possess the potential for many
applications. The advance of technology enabled the creation of prototype WSNs, but the
hardware and software both have a ways to go before WSNs are practical, cost-effective, and
usefully.
Numerous software difficulties must be solved before wireless sensor networks may be
considered a mature technology. Chief among these problems stands the formation, creation,
and testing of a robust, efficient software architecture that can fulfill all of the goals and
requirements needed. Despite (or because of ) the work still to be done, wireless sensor
networks are a great example of the unique challenges in software engineering produced by the
advance of technology.

REFERENCES
[1] Blumenthal, Jan; Handy, Matthias; Golatowski, Frank; Hasse, Marc; Timmermann, Dirk.
Wireless Sensor Networks – New Challenges in Software Engineering. Emerging Technologies
and Factory Automation, 2003. Proceedings. ETFA '03. IEEE Conference , Volume: 1 , 16-19
Sept. 2003

[2] Hill, Jason; Szewczyk, Robert; Woo, Alec; Hollar, Seth; Culler, David; Pister; Kristofer.
System Architecture Directions for Networked Sensors. ASPLOS 2000.
[3] Yu, Yang; Krishnamachari, Bhaskar; Prasanna, Viktor K. Issues in Designing Middleware
for Wireless Sensor Networks. IEEE Network, Volume: 18 , Issue: 1 , Jan/Feb 2004
Pages:15 – 21. Copyright 2004 IEEE.
[4] Gupta, G.; Younis, M. Fault-Tolerant Clustering of Wireless Sensor Networks Wireless
Communications and Networking, 2003. WCNC 2003. 2003 IEEE , Volume: 3 , 16-20 March
2003. Pages:1579 - 1584 vol. Copyright 2003 IEEE.
[5] Liu, J.; Li, B., Distributed Topology Control in Wireless Sensor Networks with Asymmetric
Links, Global Telecommunications Conference, 2003. GLOBECOM '03. IEEE , Volume: 3 , 1-5
Dec. 2003, Pages:1257 - 1262 vol.3, Copyright IEEE 2003.

Basic Architecture of Wireless Sensor Network

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