The SWANS software is organized as independent software components that can be composed to form complete wireless network or sensor network simulations, as shown in Figure 1. Its capabilities are similar to ns2  and GloMoSim , two popular wireless network simulators. There are components that implement different types of applications; networking, routing and media access protocols; radio transmission, reception and noise models; signal propagation and fading models; and node mobility models. Instances of each component type are shown italicized in the figure.
Notably, the development of SWANS has been relatively painless. Since JiST inter-entity message creation and delivery is implicit, as well as message garbage collection and typing, the code is compact and intuitive. Components in JiST consume less than half of the code (in uncommented line counts) of comparable components in GloMoSim, which are already smaller than their counterpart implementations in ns2.
Every SWANS component is encapsulated as a JiST entity: it stores it own local state and interacts with other components via exposed event-based interfaces. SWANS contains components for constructing a node stack, as well components for a variety of mobility models and field configurations. This pattern simplifies simulation development by reducing the problem to creating relatively small, event-driven components. It also explicitly partitions the simulation state and the degree of inter-dependence between components, unlike the design of ns2 and GloMoSim. It also allows components to be readily interchanged with suitable alternate implementations of the common interfaces and for each simulated node to be independently configured. Finally, it also confines the simulation communication pattern. For example, Application or Routing components of different nodes cannot communicate directly. They can only pass messages along their own node stacks.
Consequently, the elements of the simulated node stack above the Radio layer become trivially parallelizable, and may be distributed with low synchronization cost. In contrast, different Radios do contend (in simulation time) over the shared Field entity and raise the synchronization cost of a concurrent simulation execution. To reduce this contention in a distributed simulation, the simulated field may be partitioned into non-overlapping, cooperating Field entities along a grid.
It is important to note that, in JiST, communication among entities is very efficient. The design incurs no serialization, copy, or context-switching cost among co-located entities, since the Java objects contained within events are passed along by reference via the simulation time kernel. Simulated network packets are actually a chain of nested objects that mimic the chain of packet headers added by the network stack. Moreover, since the packets are timeless by design, a single broadcasted packet can be safely shared among all the receiving nodes and the very same object sent by an Application entity on one node will be received at the Application entity of another node. Similarly, if we use TCP in our node stack, then the same object will be referenced in the sending node's TCP retransmit buffer. This design conserves memory, which in turn allows for the simulation of larger network models.
Dynamically created objects such as packets can traverse many different control paths within the simulator and can have highly variable lifetimes. The accounting for when to free unused packets is handled entirely by the garbage collector. This not only simplifies the memory management protocol, but also eliminates a common source of memory leaks that can accumulate over long simulation runs.
The partitioning of node functionality into individual, fine-grained entities provides an additional degree of flexibility for distributed simulations. The entities can be vertically aggregated, as in GloMoSim, which allows communication along a network stack within a node to occur more efficiently. However, the entities can also be horizontally aggregated to allow communication across nodes to occur more efficiently. In JiST, this reconfiguration can happen without any change to the entities themselves. The distribution of entities across physical hosts running the simulation can be changed dynamically in response to simulation communication patterns and it does not need to be homogeneous.