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Multihop wireless networks can be subjected to nonstationary phenomena due to a dynamic network topology and time varying traffic. However, the simulation techniques used to study multihop wireless networks focus on the steady-state performance even though transient or nonstationary periods will often occur. Moreover, the majority of the simulators suffer from poor scalability. In this paper, we develop an efficient performance modeling technique for analyzing the time varying queueing behavior of multihop wireless networks. The one-hop packet transmission (service) time is assumed to be deterministic, which could be achieved by contention-free transmission, or approximated in sparse or lightly loaded multihop wireless networks. Our model is a hybrid of time varying adjacency matrix and fluid flow based differential equations, which represent dynamic topology changes and nonstationary network queues, respectively. Numerical experiments show that the hybrid fluid based model can provide reasonably accurate results much more efficiently than standard simulators. Also an example application of the modeling technique is given showing the nonstationary network performance as a function of node mobility, traffic load and wireless link quality. [ABSTRACT FROM PUBLISHER]

IEEE 802.15.4 Low Rate Wireless Personal Area Network (LR-WPAN) intends to provide low-power ubiquitous communications between devices. However, energy utilization by devices (or nodes) in the network often impacts the application functionality and lifetime due to limited battery capacity. For instance, in the typical multihop LR-WPAN used for data detection and monitoring, the traffic flow often converges to the data sink and such a many-to-one pattern typically results in energy imbalance. Previous research has proposed many approaches to solve this issue. However, a common limitation is about using the idealized energy model, such as “first order radio model”, which is the idealized estimation for RF transmission energy cost of the node. In this paper, we develop a realistic and representative LR-WPAN RF transceiver energy model from the measured data on Chipcon CC2420 and corresponding power control policy. Further, with this energy model, we formulate an optimized energy balanced chain (OEBC) model to maximize the network lifetime. Finally, the OEBC model is applied to develop the network deployment strategy by optimizing node placement, node density and traffic flow distribution. [ABSTRACT FROM PUBLISHER]