IJRIT International Journal of Research in Information Technology, Volume 1, Issue 12, December, 2013, Pg. 214-219

International Journal of Research in Information Technology (IJRIT)

www.ijrit.com

ISSN 2001-5569

Wireless sensor Network Simulation Tools: A Survey Anup A. Kawathekar1 and Rambabu Vatti2 1

Student, Vishwakarma Institute of Technology, Pune University Pune, Maharashtra, India [email protected] 2

Professor, Vishwakarma Institute of Technology, Pune University Pune, Maharashtra, India [email protected]

Abstract Applications of Wireless Sensor Networks are growing exponentially and playing important role in every wake of human life. To explore more of this area, either the applications can be designed and built practically using the hardware or the applications can be implemented using simulator first and tested for their proper functionality. Hardware implementation involves cost and requires more time for development. The simulation tool reduces the cost and time of deployment. However selection of a simulation tool for a particular application is a challenging task. It requires good knowledge to evaluate simulator tools along with their merits and demerits. It is also important to see that the results obtained out of the simulators are credible so meeting standard benchmarks. In this paper we have presented key points of ten simulators to reduce the efforts of the researchers or application developer.

Keywords: Wireless Sensor Networks (WSNs), Simulation tools.

1. Introduction A network simulator is an software that simulates a network without an actual network is present. This is mainly used for research and development purpose. Depending upon the use of simulator they are differentiated. In previous days Simulator use wireless media and then create sensor nodes in network but now sensor nodes are having detailed information of wireless media [1]. Simulation is very useful as the behavior of the network can be modeled by calculating the interaction between different components network. Simulation we use for observing different applications simultaneously that is end-to-end or point-to-point. Key factors of good simulator are reusability, availability, performance, scalability, graphical, debug and trace support. To test the results that may be difficult, expensive to simulate using real hardware or system also testing of new network protocols and for doing some changes in existing protocols.

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2. Survey of existing network simulators: 2.1 NS-2 NS-2 is the abbreviation of Network simulator version two, which first been developed by 1989 using as the REAL network simulator [2],[3]. NS-2 is supported by Defence Advanced Research Projects agency and National Science Foundation. NS-2 is a discrete event network simulator built in Object- Oriented extension of tool Command Language and C++. People can run NS-2 simulator on Linux Operating Systems or on Cygwin, which is a Unix-like environment and command-line interface running on Windows. NS-2 is a popular non-specific network simulator can used in both wire and wireless area. This simulator is open source and provides online document [4]. NS2 has continuously gained tremendous interest from industry, academia, and government it has been under constant investigation and enhancement for years. NS2 now contains modules for numerous network components such as routing, transport layer protocol, application, etc. To investigate network performance, researchers can simply use an easy to use scripting language to configure a network, and observe results generated by NS2. Undoubtedly, NS2 has become the most widely used open source network simulator, and one of the most widely used network simulators.

2.2 NS-3 The NS-3 simulator is a discrete-event network simulator for Internet systems, targeted primarily for research and educational use. The NS-3 project, started in 2006, is an open-source project developing NS-3. NS-3 is free software. It will rely on the ongoing contributions of the community to develop new models, debug or maintain existing ones, and share results. NS-3 is a discrete-event network simulator in which the simulation core and models are implemented in C++ [2]. NS-3 is built as a library which may be statically or dynamically linked to a C++ main program that defines the simulation topology and starts the simulator. NS-3 also exports nearly its entire API to Python, allowing Python programs to import an “NS-3” module in much the same way as the NS-3 library is linked by executables in C++. The source code for NS-3 is mostly organized in the src directory.

2.3 TOSSIM It is discrete event simulator for TinyOS Wireless Sensor Network, which is open source operating system targeting embedded operating system [5]. It was first developed at UC Berkeley. TOSSIM is a bit-level discrete event network emulator built in Python, a high-level programming language emphasizing code readability, and C++. People can run TOSSIM on Linux Operating Systems or on Cygwin on Windows. TOSSIM also provides open sources and online documents. It runs on custom mote hardware. It chooses the accuracy and complexity of model necessary for the simulation. Instead of compiling a TinyOS application for a mote, users can compile it into the TOSSIM framework, which runs on a PC [6]. This allows users to debug, test, and analyze algorithms in a controlled and repeatable environment. As TOSSIM runs on a PC, users can examine their TinyOS code using debuggers and other development tools. This document briefly describes the design philosophy of TOSSIM, its capabilities, its structure. It also provides a brief tutorial on how to use TOSSIM for testing or analysis. TOSSIM’s primary goal is to provide a high fidelity simulation of TinyOS applications. For this reason, it focuses on simulating TinyOS and its execution, rather than simulating the real world. While TOSSIM can be used to understand the causes of behavior observed in the real world, it does not capture all of them, and should not be used for absolute evaluations.

2.4 J-Sim A component-based simulation environment developed entirely in Java. It provides real-time process based simulation. The main benefit of J-Sim is its considerable list of supported protocols, including a WSN simulation framework with a very detailed model of WSNs, and an implementation of localization, routing and data diffusion WSN algorithms [7],[8]. J-Sim provides support for physical and sensors phenomenon. The only MAC protocol provided for wireless networks is IEEE 802.11. J-Sim has been developed by a team at the Distributed Real-time Computing Laboratory (DRCL). The project has been sponsored by the National Science Foundation (NSF), DARPA’s Information Technology Office, air Force Office of Scientific Research’s Multidisciplinary University

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Research Initiative, the Ohio State University and the University of Illinois at Urbana-Champaign. J-Sim is free and available with source code.

2.5 OMNET++ OMNET is an extensible, modular, component based C++ simulation library and framework has recently been released for OMNET++, and it can be used as a starting point for WSN modeling. OMNET++ is becoming a popular tool and its lack of models is being cut down by recent contributions [9], [5]. OMNET++ is an object oriented modular discrete event network simulation framework. It has a generic architecture; it can be used in various domains such as modeling of wired and wireless communication networks, protocol modeling, modeling of queuing networks, modeling and simulation of any system where the discrete event approach is suitable. OMNET++ itself is not a simulator of anything concrete [10], but rather provides infrastructure and tools for writing simulations of this infrastructure of component architecture for simulation models. Models are assembled from reusable components termed modules. OMNeT++ also supports parallel distributed simulation. OMNeT++ can use several mechanisms for communication between partitions of a parallel distributed simulation, the parallel simulation algorithm can easily be extended, or new ones can be plugged in. Models do not need any special instrumentation to be run in parallel. It is just a matter of configuration. OMNET++ can even be used for classroom presentation of parallel simulation algorithms, because simulations can be run in parallel even under the GUI that provides detailed feedback on what is going on.

2.6 Castalia Castalia is a simulator for Wireless Sensor Networks (WSN), Body Area Networks (BAN) and generally networks of low-power embedded devices. It is based on the OMNET++ platform and can be used by researchers and developers who want to test their distributed algorithms and/or protocols in realistic wireless channel and radio models, with a realistic node behaviour especially relating to access of the radio. Castalia can also be used to evaluate different platform characteristics for specific applications, since it is highly parametric, and can simulate a wide range of platforms [11], [12]. Designed for adaptation and expansion Castalia was designed right from the beginning so that the users can easily implement/import their algorithms and protocols into Castalia while making use of the features the simulator is providing. Proper modularization and a configurable, automated build procedure help towards this end. Castalia is not sensor-platform specific. Castalia is meant to provide a generic reliable and realistic framework for the first order validation of an algorithm before moving to implementation on a specific sensor platform. Castalia is not useful if one would like to test code compiled for a specific sensor node platform.

2.7 QualNet QualNet [13] is the commercial version of GloMo-Sim with upgraded features such as, providing a comprehensive environment for designing protocols, creating and animating experiments, and analyzing the results of those experiments. QualNet based on C++. It was released in 2000 by Scalable Network Technology (SNT).with upgraded features such as, providing a broad environment for designing protocols, creating and animation and analysis [14]. QualNet is a commercial derivative of GloMo-Sim, Rapid prototyping of protocols, comparative performance evaluation of alternative protocols at each layer, built-in measurements on each layer, modular, layered stack design, standard API for composition of protocols across different layers, scalability via support for parallel execution and GUI Tools for system/protocol modeling.

2.8 OPNET OPNET is slightly different from NS and GloMo-Sim; it supports the use of modeling different sensor specific hardware. It can also be used to define custom packet formats. OPNET is a high level event based network level simulation tool [15], [16]. Simulation operates at “packet-level” Originally built for the simulation of fixed networks. OPNET contains a huge library of accurate models of commercially available fixed network hardware and protocols. The possibilities for wireless network simulations are also very wide accurate radio transmission pipeline stage for the modeling of the physical layer (radio interface).The simulator has a lot of potentiality, but there exists typically a lack of the recent wireless systems. OPNET can be used as a research tool or as a network design/analysis tool (end user). The threshold for the usage is high for the developer, but low for the end user.

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OPNET consist of high level user interface, which is constructed from C and C++ source code block with a huge library of OPNET specific function.

2.9 ATEMU ATEMU is a fine grained sensor network simulator. ATEMU is its ability to simulate a heterogeneous sensor network. Using ATEMU it is possible to not only accurately simulate the operation of different application on the MICA2 platform but also a complete sensor network where the sensor nodes themselves maybe based on different hardware platforms [17].The accuracy and emulation capabilities provided by ATEMU ensure that when and if actual hardware is used, the software will already have undergone rigorous testing and debugging on an accurate platform. This would provide the sensor network deployment community with a much more accurate estimate of the performance of various algorithms and protocols in realistic scenarios and platforms. ATEMU provides low-level emulation of the operation of each individual sensor node. It emulates the operation of the various components on a sensor node, such as the processor, timers, and the radio interface. ATEMU can be directly used by developers of TinyOS related software as it is binary compatible with the MICA2 hardware.

2.10 SENSE SENSE is the component-based simulation [Szymanski and Chen, 2002]. A component-port model free simulation models from interdependence usually found in an object-oriented architecture, and a simulation component classification. SENSE is a simulator created for simulation of WSN, providing scalability and extensibility. This simulator uses component-port model to represent parts of a network, thus featuring extension capabilities [18]. In this section we briefly present some background content on the SENSE simulator. It does not support sensors, physical phenomenon. The MAC protocol support and radio propagation make SENSE less than ideal for accurate evaluation of WSNs. SENSE was developed as a statistical analysis tool, providing results directly on the terminal interface, without any native file output for permanent storage.

Table 1 Comparison of different simulators: Programming Type of Routing language Simulator Protocol Used C++ Network AODV, based DSR routing

Sr.no

simulator

1

NS-2

2

NS-3

C++

Network based

AODV, DSR routing

3

TOSSIM

Nes C

Code level

Base station driven

Anup A. Kawathekar, IJRIT

Features

Limitation

Fast discrete event simulator, Lot of component library, Event Scheduler and visualization, 32 & 64 bit parallel simulation kernel Fast discrete event simulator, alignment with real system, Modular, documented core Update model High degree of accuracy, visualisation tool available

Supports only 802.11 MAC and a single hop TDMA protocol.

Only IPv4 is supported

Complicated steps loose timing and interrupt code

217

4

J-Sim

Java

Cross level

Graphic routing

Reusability and interchangeability, Provides GUI library, Component oriented architecture

5

OMNET++

C++

Network Based

Dynamic routing

6

Castalia

C++

Network Based

AODV, LEACH

7

Qualnet

C++

Network based

AODV, DSR

8

OPnet

C, C++

Network based

Static Routing

Graphical output vector plotting tool, Model based architecture, Random number generator tool, Simulate power consumption problem Extended sensing modeling, Node clock drift Easy to use and clear user interface, Support for multiprocessor system, animation capability Supports the use of modeling different sensor specific hardware, Use to define custom packet format

9

ATEMU

C

Code level

AODV, MAC layer

10

SENSE

C++

Network & Application base

AODV, DSR

Anup A. Kawathekar, IJRIT

Different sensor nodes can run different programs, most accurate simulator, simulate a heterogeneous sensor network Is a statistical simulator, userfriendliness, relies on command line parameters

Complicated to use, more execution time, only 802.11 MAC protocol support Protocols are not enough, not portable

Not a sensor platform specific Difficult to installation, Very expensive

Scalability problem

User need to familiar about Mica2 hardware architecture

No sensor support

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4. Conclusions In this paper, we have discussed the need of simulation tools in WSN application development and listed key factors of a good simulator and present the key features, limitations of ten simulators which help the researcher to select a suitable simulation tool for their application.

Acknowledgments I would like to my sincere thanks the Prof. Rambabu Vatti dept. of Electronics and Telecommunication, Vishwakarma Institute of Technology Pune, for his valuable suggestions.

References [1] A. K. Dwivedi, V. K. Patle and O. P. Vyas, “Investigation on Effectiveness of Simulation Results for Wireless Sensor Networks,” Information Processing and Management, Vol. 70, 2010, pp. 202-208. [2] M. Greis, “Tutorial for the Network Simulator NS”, http://www.isi.edu/nsnam/ns/tutorial/index.html [accessed 25 May 2005] [3] E. Altman, T. Jimenez, “NS Simulator for beginners”, http://www.sop.inria.fr/maestro/personnel/Eitan.Altman/COURSE-NS/n3.pdf [accessed 25 May 2005]. [4] The Network Simulator ns-2: Documentation, http://www.isi.edu/nsnam/ns/ns-documentation.html [accessed 25 May 2005]. [5] E. Egea-Lopez, J. Vales-Alonso, A. S. Martinez-Sala, P. Pavon-Marino, J. Garcia-Haro; “Simulation Tools for Wireless Sensor Networks”, Summer Simulation Multiconference, SPECTS, 2005, pp.2-9 [6] P. Levis, N. Lee, “TOSSIM: A Simulator for TinyOS Networks”, Computer Science Division, University of California Berkeley, California, 17 September 2003. [7] A. Sobeih, M. Viswanathan, D. Marinov and J. C. Hou, “J-Sim: An Integrated Environment for Simulation and Model Checking of Network Protocols,” Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2007, pp. 1-6. http://www.j-sim.zcu.cz/ [8] J-Sim Tutorial, http://www.j-sim.org/ [accessed 25 May 2005]. [9] OMNeT++ simulation system. http://www.omnetpp.org/ [10] C. Mallanda, A. Suri, V. Kunchakarra, S.S. Iyengar, R. Kannan, A. Durresi, “Simulating Wireless Sensor Network with OMNeT++”, Sensor Network Research Group, Department of Computer Science, Louisiana State Unversity, Baton Rouge, LA, 24 January 2005. [11] D. Pediaditakis, S. H. Mohajerani and A. Boulis, “Poster Abstract: Castalia: the Difference of Accurate Simulation in WSN,” Proceedings of the 4th European Conference on Wireless Sensor Networks (EWSN), Delft, 29-31 Janu-ary 2007. http://castalia.npc.nicta.com.au/index.php [12] http://castalia.npc.nicta.com.au/documentation.php [13] QualNet Simulator by Scalable Network Technologies http://www.scalable-networks.com/products/qualnet/ [14] Tobias Doerel, “Simulation of wireless ad-hoc sensor networks with QualNet”, Chemnitz, 2009 [15] OPNET Modeller, OPNET Technologies Inc. http://www.opnet.com [16] I.S. Hammoodi, B.G. Stewart, A. Kocian, and S.G. McMeekin. A Comprehensive Performance Study of OPNET Modeler for ZigBee Wireless Sensor Networks. In Third International Conference on Next Generation Mobile Applications, Services and Technologies, 2009. NGMAST ’09., pages 357 –362, 15-18 2009. doi:10.1109/NGMAST. 2009.12. [17] ATEMU. Sensor Network Emulator/Simulator/Debugger. http://www.isr.umd.edu/CSHCN/research/atemu. [18] G. Chen, J. Branch, M.J. Pflug, L. Zhu, andB. Szymanski, Sense: A sensor network simulator,Advances in Pervasive Computing and Networking(2004), 249–267.

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Wireless sensor Network Simulation Tools: A Survey - IJRIT

simulation tool for a particular application is a challenging task. It requires good ... The NS-3 project, started in 2006, is an open-source project developing NS-3. NS-3 is free ..... Mobile Applications, Services and Technologies, 2009. NGMAST ...

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