The problem of admission control at the sensor cluster coordinator is considered in a beacon enabled 802.15.4 network. The admission control algorithm is based on analytical modeling of the packet service time, using the number of nodes in a cluster, packet arrival rate, and packet size as independent variables. Simulation experiments confirm the validity of the chosen admission control algorithm, which is shown to provide a slightly conservative estimate with respect to the ideal condition.

The performance of an IEEE 802.15.4 compliant network operating in the beacon enabled mode with both downlink and uplink traffic is analyzed through discrete time Markov chains and the theory of M/G/1 queues. The model considers acknowledged transmissions and includes the impact of different network and traffic parameters such as the packet arrival rate, packet size, inactive period between the beacons, and the number of stations. We investigate the nonsaturation region and outline the conditions under which the network abruptly goes to saturation. The analysis of stability of the network queues shows that the stability of the downlink queue at the coordinator is the most critical for network operation. Due to the abruptness with which the switch from nonsaturation to saturation occurs, the network operating point has to be carefully chosen according to the volume of downlink traffic. Furthermore, our model shows that certain features prescribed by the standard actually limit the performance of 802.15.4 networks.

The activity of individual nodes in a sensor network has to be managed in order to meet the simultaneous goals of maximizing the network lifetime and achieving the desired information throughput at the network sink. In this work we investigate the interaction of activity management with the CSMA-CA-based MAC layer in a beacon enabled IEEE 802.15.4-compliant network cluster. Activity management is performed through Bernoulli scheduling of service and sleep periods, which gives better results than the traditional, exhaustive and I-limited scheduling of the active and sleep periods. We derive the event reliability at the cluster coordinator as the function of physical layer parameters, data link layer parameters, Bernoulli scheduling parameter, and the probability distribution of sleep period. Based on the centralized analytical model, we derive distributed algorithm for calculating sleep parameters and demonstrate that the proposed distributed activity management policy is capable of achieving and maintaining the desired network reliability while maximizing the network lifetime.

Achieving the desired data rate from a sensor network while simultaneously maximizing the lifetime of individual sensors are somewhat conflicting goals, further complicated by the fact that collisions at the MAC layer will affect both the throughput and power consumption. We address this problem in the context of a beacon enabled 802.15.4 sensor network by analytically modeling the network reliability as the function of the activity management policy and MAC layer parameters. The network coordinator monitors the throughput and adjusts the probability with which individual sensors go to sleep after sending their data. Results show that this activity management policy is able to maintain the desired data rate in a wide range of sensor network sizes and packet arrival rates at the nodes.

In this work, we derive the probability distribution of access delay and calculate throughput of a personal area network operating under the IEEE standard 802.15.4 in the beacon enabled mode. We model the network using the theory of discrete time Markov chains and M/G/1/K queues. The model considers acknowledged uplink transmission in non-saturation mode, and includes the impact of different parameters such as packet arrival rate, number of stations, the finite size of individual node buffers, packet size, and inactive period between the beacons. Our model also captures the problem of congestion at the beginning of the superframe due to multiple transmissions delayed from the previous superframe. The results show that average access delays, even for small buffer sizes, may be quite high if the throughput exceeds 50%, which can seriously affect applications with delay bounds. Values of throughput larger than 50% can be achieved at the expense of larger buffer sizes, which imposes implementation problems on devices with small memory resources.