NetTopo: A framework of simulation and visualization for wireless sensor networks

Abstract

Network simulators are necessary for testing algorithms of large scale wireless sensor networks (WSNs), but lack the accuracy of real-world deployments. Deploying real WSN testbed provides a more realistic test environment, and allows users to get more accurate test results. However, deploying real testbed is highly constrained by the available budget when the test needs a large scale WSN environment. By leveraging the advantages of both network simulator and real testbed, an approach that integrates simulation environment and testbed can effectively solve both scalability and accuracy issues. Hence, the simulation of virtual WSN, the visualization of real testbed, and the interaction between simulated WSN and testbed emerge as three key challenges. In this paper, we present an integrated framework called NetTopo for providing both simulation and visualization functions to assist the investigation of algorithms in WSNs. NetTopo provides a common virtual WSN for the purpose of interaction between sensor devices and simulated virtual nodes. Two case studies are described to prove the effectiveness of NetTopo.

Introduction

The increasing market requirements of wireless sensor networks (WSNs) applications drive the fast development of research in various aspects, e.g., sensor hardware design, sensor operating system development. Among all kinds of research issues in WSNs, various algorithms, e.g., routing algorithm, topology control algorithm, are highly concentrated. Designing and validating algorithms pertaining to WSNs are among the most fundamental focuses of researchers. Network simulators are widely used for the purpose of analysis in these tasks due to the fast prototyping and the capability of tackling large scale systems. However, even the best simulators are still not able to provide real condition simulation environments in terms of completeness, complexity and accuracy, e.g., theoretical model based simulation may trade accuracy for simulation performance [1]. Taking this drawback of simulators into account, using real testbed to evaluate algorithms of WSNs is essentially necessary before applying them into commercial applications. Testbeds allow for rigorous and replicable testing. Nevertheless, there are two serious limitations on this approach in the following two conditions: (1) Large scale. Till today, it is still very expensive to buy a large number of sensor devices for a large scale testbed, e.g., the price of a Crossbow professional kit with eight sensor nodes is around 2800 Euros. Especially, for most academic researches the cost for building a large scale testbed is not acceptable. (2) Not replicable environment. For some specific applications, e.g., monitoring an erupting volcano [2], rescue in a sudden earthquake and monitoring hazardous situations [3], deploying a testbed is unwanted since the devices are exposed to dangerous conditions which can cause serious damage.

Even though simulation models are usually not able to represent the real environments with the levels of completeness and accuracy, simulators are still very important tools, because that simulators enable rapid prototyping and early evaluation of sensor network applications and algorithms. Compared to the cost and time involved in setting up an entire testbed containing multiple networked computers, routers and data links, network simulators are relatively fast and inexpensive. Due to the complementary properties of simulators and testbeds, a better solution could be the integration of simulation environment and physical testbed. Using this technology, applications can run partially in a simulation environment and partially in a physical WSN testbed and interact with each other to create an environment where scalability issues, heterogeneous environments, etc. can be better studied.

Thus, the subject of this research work is about building a new software framework, which integrates simulation and visualization functions to assist the investigation of various algorithms in WSNs. This integration is specially motivated by the following two concrete scenarios:

• Researchers want to compare the performance of running a same algorithm in both simulator and real testbed. The comparison can guide researchers to improve the algorithm design and incorporate more realistic conditions. A good example is the applying of face routing algorithm in GPSR [4], which is proved to be loop free in theory but actually is not loop free in realistic situations, due to the irregular radio coverage [5].

• A budget limitation prevents researchers from buying enough real sensor nodes but the research work has to base on a large scale WSN. For example, to evaluate the performance of any sensor middleware, e.g., [6], a large scale sensor network is needed. Researchers can actually do the research work by integrating a small number of real sensor nodes and a large number of virtual sensor nodes generated from the simulator.

The integration of simulation environment and physical testbed brings three major challenges:

• Sensor node simulation. Normally, a number of heterogeneous sensor devices can be used for building a WSN testbed. The integrated platform should not simulate only a specific sensor device, which means that the heterogeneous problem requires the integrated platform to be flexible enough to simulate any new sensor device.

• Testbed visualization. On one hand, sensor nodes are small in size and do not have user interfaces as displays or keyboards, which is difficult to track the testbed communication status. On the other hand, the communication topology in testbed is invisible, but researchers usually need to see the topology to analyze their algorithms. For example, when implementing a routing algorithm in the testbed, the actual routing path is expected to be visible.

• Interaction between the simulated WSN and testbed. The simulated WSN and the real testbed need to exchange information, e.g., routing packet. Their horizontal interconnection, communication, interaction, and collaboration are all emerging difficult problems that need to be addressed.

In this paper, we present an extensible integrated framework of simulation and visualization called NetTopo to assist investigation of algorithms in WSNs. With respect to the simulation module, users can easily define a large number of on-demand initial parameters for sensor nodes, e.g., residential energy, transmission bandwidth, radio radius. Users also can define and extend the internal processing behavior of sensor nodes, e.g., energy consumption, bandwidth management. NetTopo allows users to simulate an extremely large scale heterogeneous WSN. For the visualization module, it works as a plug-in component to visualize testbed’s connection status, topology, sensed data, etc. These two modules paint the virtual sensor nodes and links on the same canvas, which is an integration point for centralized visualization. Since node attributes and internal operations are user definable, it guarantees simulated virtual nodes to have the same properties with those of real nodes. The sensed data captured from real sensor nodes can drive the simulation in a pre-deployed virtual WSN. Topology layouts and algorithms of virtual WSN are customizable and work as user defined plug-ins, both of which can easily match the corresponding topology and algorithms of real WSN testbed. Currently, NetTopo is released as open source software on SourceForge and its own website [7].

The rest of the paper is organized as follows: Section 2 presents an overview of the related work in terms of simulators and WSN visualization and positions our work with respect to the related literature. Section 3 illustrates design issues of the framework including architecture, mechanism of modular components, module interfaces and interaction between these interfaces. Section 4 describes the features of NetTopo and analyzes the implementation of the framework. It is focused on logic, programming techniques and interesting code of some core features. Section 5 presents two case studies provided in NetTopo as examples for testing the effectiveness of the framework. Section 6 concludes this paper.