Clustered Coordinator SABTS (CC-SABTS) for Beacon Transmission in IEEE802.15.4 LR-WPAN

IEEE802.15.4 standard for Wireless Sensor Network (WSN) provides low-power transmission in the low-rate wireless personal area network (WPAN). It has three types of topology: star, peer-to-peer and cluster tree. Star topology has limit to expand network. Peer-to-peer topology has a complex multihop routing during network expansion due to the large number of full-function devices. A full-function device can act as coordinator and personal area network coordinator (PAN-C). Cluster tree topology is preferable because it can expand networks using less number of full-function devices and thus reduces complexity in routing messages. A cluster tree topology consists of a wireless PAN-C, several cluster coordinators and a number of end devices. The coordinators periodically transmit beacon frames to one another to allow synchronization and communication. However, collision will happen if the coordinators transmit beacon frames at the same time and will degrade the network performance. Different mechanisms have been introduced to solve the collision problem and one of the mechanisms is superframe adjustment and beacon transmission scheme (SABTS). SABTS calculates the precise time for beacon transmission by assigning an accurate value of beacon order and superframe order for PAN-C, cluster coordinators and end devices. As the number of cluster coordinator increases, SABTS method reiterates the calculation for beacon transmission time numerously. Hence, in order to decrease the iteration, this paper introduces clustered coordinator SABTS (CC-SABTS) by clustering coordinator nodes that are separated by two length radius. The performance of CC-SABTS is simulated and evaluated using NS2 simulation software. Result shows that CC-SABTS provides better average throughput, packet delivery ratio and end-to-end delay compared to the conventional SABTS

Enhanced Beacon Scheduling for Cluster Tree Topology in Wireless Personal Area Network

IEEE 802.15.4 Low Rate Wireless Personal Area Network (LR-WPAN) is one of the standards for Wireless Sensor Network (WSN) which provides low power multihop transmission in Wireless Personal Area Network (WPAN). The LR-WPAN has two types of nodes which can either be full function devices (FFD) or reduced function devices (RFD). The number of FFD and RFD in a WPAN determines the two types of topology for the network: star and peer-to-peer. Star topology restricts communication between a PAN-C and RFD, while peer-to-peer topology may establish a mesh or tree topology depending on the nodes’ restrictions. A cluster tree topology extends network with less FFD and as a result, reduces routing complexity. The coordinators in a cluster tree topology network transmit beacons periodically to allow nodes synchronization and communications. However, if concurrent beacons transmission is within the same transmission range, it will cause beacons collision, therefore resulting in poor network performance. In order to increase network performance, an enhancement on the available beacon scheduling method, superframe adjustment and beacon transmission scheme (SABTS) was introduced. This enhanced method is called coordinator clustering SABTS (CC-SABTS). CC-SABTS improves the gap in SABTS which causes delay in beacon transmission and communication by clustering coordinator nodes that are separated by two length radius to avoid an overlapping transmission range. The non-overlapping coordinators can be clustered to share beacon transmission time and this reduces delay for beacons transmission. Hence, nodes can start their communications process earlier. This study compares the average throughput, packet delivery ratio (PDR), end to end delay and packet loss between SABTS and CC-SABTS. Simulation results showed that in a network with varied interarrival rate (INTV), CC-SABTS outperformed conventional SABTS up to 39%, 5%, 22% and 29% for average throughput, PDR, end to end delay and packet loss, respectively. CC-SABTS also improved the conventional SABTS by 37%, 30%, 29% and 9% for average throughput, PDR, end to end delay and packet loss, respectively for a varied number of end devices. The average throughput, PDR, end to end delay and packet loss also improved by 3%, 25%, 8% and 22%, respectively in a varied packet size network. In addition, an improvement up to 41%, 30%, 41% and 27% for average throughput, PDR, end to end delay and packet loss was achieved in a varied density network. Lastly, the CC-SABTS worked 62% and 18% better for average throughput and PDR when simulated in a constant bit rate (CBR) traffic environment. However, in the case of average end to end delay and packet loss, CC-SABTS improved performance up to 30% and 69%, respectively in Poisson traffic environment. In conclusion, the CC-SABTS improves network significantly compared to the conventional SABTS when simulated in a varied interaarival rate, end devices, packet size, network density and network traffic