BIOGRAFISCHE ANGABEN TECHNISCHE UNIVERSITÄT DRESDEN TECHNISCHE UNIVERSITÄT DRESDEN FAKULTÄT ELEKTROTECHNIK UND INFORMATIONSTECHNIK INSTITUT FÜR NACHRICHTENTECHNIK DIPLOMARBEIT Prakash Rao, Vaddina Thema: The Simulative Investigation of Zigbee/IEEE The Simulative Investigation of Zigbee/IEEE Secondary Education, India Bachelor of Engineering, CBIT, Osmania University, India Master(MSc.), ET, TU Dresden Internship, Auvidea GmbH, Denklingen. Thesis, TUD & ZMD. Autor: Vaddina, Prakash Rao Eingereicht am: 10. November 2005 Betreuer: Dipl. –Ing. Dimitri Marandin Hochschullehrer: Prof. Dr. -Ing. Ralf Lehnert Dipl. –Ing. Falk Hofmann, ZMD AG 1. Abstract The IEEE is a new personal wireless area network standard designed for applications like wireless monitoring and control of lights, security alarms, motion sensors, thermostats and smoke detectors. IEEE specifies physical and media access control layers that have been optimized to ensure low-power consumption. The MAC layer defines different network topologies, including a star topology (with one node working as a network coordinator, like an access point in IEEE ), tree topology (where some nodes communicate through other nodes to send data to the network coordinator), and mesh topology (where routing responsibilities are distributed between nodes and master coordinator is not needed). In this thesis a star network topology according to the standard has to be simulated with the simulator ns-2. The goals of the thesis are to build a simulation model and to investigate different functional modes of IEEE and their impact on energy consumption and network performance. Different application scenarios have to be evaluated. The simulation results must be generated with input from ZMD for their transceiver ZMD Introduction ZIGBEE is a new wireless technology guided by the IEEE Personal Area Networks standard. It is primarily designed for the wide ranging automation applications and to replace the existing non- standard technologies. It currently operates in the 868MHz band at a data rate of 20Kbps in Europe, 914MHz band at 40Kbps in the USA, and the 2.4GHz ISM bands Worldwide at a maximum data-rate of 250Kbps. Some of its primary features are: Standards-based wireless technology Interoperability and worldwide usability Low data-rates Ultra low power consumption Very small protocol stack Support for small to excessively large networks Simple design Security, and Reliability 3. Outline The current study firstly tries to build a reliable, definitive and deterministic simulation environment, identify the simulation parameters and provide the performance metrics: throughput, delay analysis, delivery ratio and energy consumption for the 868Mhz. The results obtained for the 868Mhz band, can be in a way, applied to the frequency band of 915Mhz, due to their close proximity in the spectral space. This report also focuses on the network congestion giving out reasons, and highlighting the inefficiency in terms of backoff exponent management on part of the channel access mechanism CSMA-CA. The degradation in performance because of this inefficiency is explained and a proposal has been made to have an efficient backoff exponent mechanism for the devices involved in transmission, called the Adaptive Backoff Exponent Algorithm, and results are presented to support the performance improvement achieved by it. 4. Functional Overview 4.1 Network Topologies The IEEE can support two types of network formations. Firstly is the Star topology where communication is only possible with the coordinator and the peer-to-peer topology where communication among nodes is also possible if the devices are capable. 4.2 Superframe Structure The superframe structure is an optional part of a WPAN. It is the time duration between two consecutive beacons. The structure of the superframe is determined by the coordinator. The coordinator can also switch off the use of a superframe by not transmitting the beacons. The superframe duration is divided into 16 concurrent slots. The beacon is transmitted in the first slot. The remaining part of the superframe duration can be described by the terms, CAP, CFP and Inactive. The superframe is used to provide vital statistics like synchronization, identifying the PAN and the superframe structure, to the devices connected in a Wireless PAN. This information is critical for the operation of the PAN in a Beacon enabled network. 5. Simulation Parameters The simulations are conducted using the following simulation parameters 6. Performance Analysis at 868Mhz The graphs inidcate the performance measure of a standard Zigbee network with a star network topology at 868Mhz. The results are produced with a 95% confidence level. The impact due to receiver sensitivity is studied. The graphs predict the performance of the system with different receiver sensitivities and taking their sensing threshold similar to that of the receiver sensitivities. Observing figure-2, for the throughput analysis, in the case of -97dBm of receiver sensitivity and a -97dBm of carrier sensing range, the throughput increases linearly through the datarates from 0.1 to 1.0, and following the trend until, 2.0, where it achieves a stagnation due to network congestion. These experiments reveal a maximum of 5100bits/second can be achieved at this sensitivity. The peak performance is considered at datarates of pkts/sec. Taking the delivery ratio into consideration, ideally a peak datarate of 1.0pkts/sec is achievable for the said frequency band, receiver and simulation characteristics. And in the case of lower receiver sensitivity and corresponding sensing ranges, the performance at higher datarates has been considerably lower, and during congestion the performance reaches their lowest point. Their peak performance can be viewed at rates of packets per second where the nodes were able to receive 2700bits/sec for -92dBm sensitive receiver and nearly 2200bits/sec for the other sensitive ranges. With reference to figure-3 a system when using a receiver capable of detecting packets with power as low as -97dBm, the delivery ratio is close to 100% in the range of packets/second. As higher traffic is applied to the network, more and more packets are dropped due to collisions and bad link quality of the transmitted packets. This would increase the number of retransmissions exponentially, effectively congesting the network even further. With reference to the above graphs and the energy analysis, we can deduce the following statements: Maximum achievable data bandwidth = 5.3Kbps Achievable Data 99% delivery ratio = 5.25kbps The battery of a device Kbytes/day will last for 4 months 7. Adaptive Backoff Exponent A study of the system performance at collision scenarios reveals an exponential increase in the number of packet drops, for higher datarate operation. Poor link quality is a direct consequence of the hidden node problem. Even if the nodes can detect each others presence, collisions are caused when two or more of them choose an identical backoff time duration. Hence they transmit without being aware that an other node has also detected an idle channel. This result in frequent confrontations among nodes often resulting in collisions. The reason can be traced back to the inefficient backoff mechanism. An a efficient backoff maintenance algorithm has been proposed called the Adaptive backoff Exponent. The new mechanism will effectively allow the devices to choose any value within 1 and 7 based on their contribution to the network congestion (called the decision algorithm). Thus minimizing the odds of using the same backoff wait duration. The more a node congests the network the more will be its BE. It has been observed that at lower datarates this mechanism allows the network to perform identical to the original scenario while considerably improving its performance at higher rates before succumbing to network congestion. The following improvement is brought about by the application of Adaptive Backoff Exponent Algorithm. Maximum achievable data bandwidth = 6.73kbps Improvement of 27% in maximum throughput Achievable Data 99% delivery ratio = 6.554kbps 25% Improvement in the maximum throughput 1% PER 8. Conclusions A detailed study of the Zigbee technology with its internal architecture, and the layered structure has been conducted. It is followed by a detailed study of the simulation environment (ns-2) and the Zigbee modules built under ns-2. Later a well behaved and near realistic simulation scenario is built in TCL. The Zigbee modules have been exclusively tested for the simulator environment and several loopholes have been identified. Some of the inconsistencies that have been modified are the Routing mechanism, the Address resolution mechanism, the active and passive scan, the energy threshold and the carrier sense threshold, etc. A detailed performance study has been done and the working areas have been identified. This has highlighted the inconsistency in the CSMA-CA algorithm which has been fixed by the Adaptive Backoff Exponent mechanism. A comparative analysis focusing on the gain in performance when using the new algorithm is presented to validate the claim of better performance. ParameterValue TopologySTAR Number of nodes15 Number of Flows8 Traffic TypeCBR Traffic Direction Node  Coordinator Packet Size70 Bytes Radio Propagation ModelTwo-Ray Ground Antenna TypeOmniAntenna Queue TypeDropTail Queue Length150 Transmit Power0dBm (1mW) Receiver Sensitivity-97dBm Carrier sensing threshold-97dBm Capture Threshold10 Antenna Height1.0m Transmitting Power0.0744W Receiving Power0.0648W Table-1: Simulation Parameters