The Necessity of Network Simulation

The emergence of wireless sensor networks brought many open issues to network designers. Traditionally, the three main techniques for analyzing the performance of wired and wireless networks are analytical methods, computer simulation, and physical measurement. However, because of many constraints imposed on sensor networks, such as energy limitation, decentralized collaboration and fault tolerance, algorithms for sensor networks tend to be quite complex and usually defy analytical methods that have been proved to be fairly effective for traditional networks. Furthermore, few sensor networks have come into existence, for there are still many unsolved research problems, so measurement is virtually impossible. It appears that simulation is the only feasible approach to the quantitative analysis of sensor networks.

Why a New Simulator

ns2, perhaps the most widely used network simulator, has been extended to include some basic facilities to simulate sensor networks. However, one of the problems of ns2 is its object-oriented design that introduces much unnecessary interdependency between modules by binding functionalities with types. For example in an OO design a physical layer module has always to be a sub-type of a physical layer abstract class. This constraint is unnecessary in the sense that when we building a new physical module we should not care about its type -- as long as it has a compatible interface (meaning matching input/output methods) with other modules it should be allowed to interact with others. Such interdependency sometimes makes the addition of new protocol models extremely difficult, only mastered by those who have intimate familiarity with the simulator. Being difficult to extend is not a major problem for simulators targeted at traditional networks, for there the set of popular protocols is relatively small. For example, Ethernet is widely used for wired LAN, IEEE 802.11 for wireless LAN, TCP for reliable transmission over unreliable media. For sensor networks, however, the situation is quite different. There are no such dominant protocols or algorithms and there will unlikely be any, because a sensor network is often tailored for a particular application with specific features, and it is unlikely that a single algorithm can always be the optimal one under various circumstances.

Many other publicly available network simulators, such as JavaSim, SSFNet, Glomosim and its descendant Qualnet, attempted to address problems that were left unsolved by ns2. Among them, JavaSim developers realized the drawback of object-oriented design and tried to attack this problem by building a component-oriented architecture. However, they chose Java as the simulation language, inevitably sacrificing the efficiency of the simulation. SSFNet and Glomosim designers were more concerned about parallel simulation, with the latter more focused on wireless networks. They are not superior to ns2 in terms of design and extensibility.

Features of SENSE

SENSE is designed to be an efficient and powerful sensor network simulator that is also easy of use. We identify the three most critical factors as:

Currently Available Components and Simulation Engines


Chen, G., J. Branch, M. J. Pflug, L. Zhu and B. Szymanski (2004). SENSE: A Sensor Network Simulator. Advances in Pervasive Computing and Networking. B. Szymanski and B. Yener, Springer: 249-267.

B.K. Szymanski and G.G. Chen. Sensor Network Component Based Simulator. Handbook of Dynamic System Modeling, chapter 35, Paul Fishwick (edt.), CRC/Taylor and Francis Publ., 2007 pp. 35-1 -- 35-16.