Industrial wireless sensor network (IWSN) is an application area of WSN used in industrial process monitoring and control with strict time and reliability requirement. WirelessHART standard is the first international standard for IWSN approved by International Electrotechnical Commission (IEC). This is worthwhile to implement this standard on simulator platform. Based on the study of WirelessHART standard, this thesis set up a primary implementation of the MAC layer of WirelessHART standard. To our best knowledge, this is the first comprehensive implementation of WirelessHART using OPNET simulator. The implementation has been evaluated rational. And some improvement of current implementation and standard have also been proposed and implemented. Flexible dedicated slot assignment has also been proposed to reduce the packet loss rate caused by influences of the physical channel.

In passive RFID systems, how to reduce the collision among tags is an important issue at the medium access control layer. The Framed Slotted ALOHA and its variations are well-known anti-collision algorithms for RFID systems. However, when the Framed Slotted ALOHA is used, the system efficiency and the average time delay deteriorate rapidly when the total number of tags increases. On the other hand, the total number of slots in a frame can¡¦t be infinity. In this thesis, we first compare existing anti-collision protocols and then propose a novel algorithm based on the Enhanced Dynamic Framed Slotted ALOHA (EDFSA) and the Progressing Scanning (PS) algorithm. The proposed algorithm is called Dynamic Grouping (DG). The DG algorithm partitions the RFID tags according to the distances from tags to the reader in order to avoid using too many slots in a frame. Inparticular, the DG algorithm estimates the spatial distribution of tags based on previous scanning results and then adjusts the partition accordingly. Unlike PS algorithm, the DG algorithm is applicable when the RFID tags are uniformly distributed or normally distributed.

In this thesis, We propose two power saving strategy in wireless sensor networks with multi-packet reception and slotted ALOHA is as a systematic model. We concentrate on the case in which the packet arrival process is Bernoulli and the maximum queue is 1.This thesis first simulate results and to compare with the analytical results of pervious thesis. Traditional slotted ALOHA only have transmit and idle state. In this thesis, add a sleep state to decrease the energy consumption, and according to different strategy propose two different methods. This two methods decide to the sleep time and the retransmission probability to achieve the energy-efficient. At last we will use the simulation result to show the performance of our power saving strategy.

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We design, analyze, and optimize distributed detection and estimation algorithms in a large, shared-channel, single-hop wireless sensor network (WSN). The fusion center (FC) is allocated a shared transmission channel to collect local decisions/estimates but cannot collect all of them because of limited energy, bandwidth, or time. We propose a strategy called reliability-based splitting algorithm that enables the FC to collect local decisions/estimates in descending order of their reliabilities through a shared collision channel. The algorithm divides the transmission channel into time frames and the sensor nodes into groups based on their observation reliabilities. Only nodes with a specified range of reliabilities compete for the channel using slotted ALOHA within each frame. Nodes with the most reliable decisions/estimates attempt transmission in the first frame; nodes with the next most reliable set of decisions/estimates attempt in the next frame; etc. The reliability-based splitting algorithm is applied in three scenarios: time-constrained distributed detection; sequential distributed detection; and time-constrained estimation. Performance measures of interest - including detection error probability, efficacy, asymptotic relative efficiency, and estimator variance - are derived. In addition, we propose and analyze algorithms that exploit information from the occurrence of collisions to improve the performance of both time-constrained distributed detection and sequential distributed detection.

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In a passive radio-frequency identification (RFID) system the reader communicates with the tags using the EPC Global UHF Class 1 Generation 2 (EPC Gen-2) protocol with dynamic framed slotted ALOHA. Due to the unique challenges presented by a low-power, random link, the channel efficiency of even the most modern passive RFID system is less than 40%. Hence, a variety of methods have been proposed to estimate the number of tags in the environment and set the optimal frame size. Some of the algorithms in the literature even claim system efficiency beyond 90%. However, these algorithms require fundamental changes to the underlying protocol framework which makes them ineligible to be used with the current hardware running on the EPC Gen-2 platform and this infrastructure change of the existing industry will cost billions of dollars. Though numerous types of tag estimation algorithms have been proposed in the literature, none had their performance analyzed thoroughly when incorporated with the industry standard EPC Gen-2. In this study, we focus on some of the algorithms which can be utilized on today’s current hardware with minimal modifications. EPC Gen-2 already provides a dynamic platform in adjusting frame sizes based on subsequent knowledge of collision slots in a given frame. We choose some of the popular probabilistic tag estimation algorithms in the literature such as Dynamic Frame Slotted ALOHA (DFSA) – I, and DFSA – II, and rule based algorithms such as two conditional tag estimation (2CTE) method and incorporate them with EPC Gen-2 using different strategies to see if they can significantly improve channel efficiency and dynamicity. The results from each algorithm are also evaluated and compared with the performance of pure EPC Gen-2. It is important to note that while integrating these algorithms with EPC Gen-2 to modify the frame size, the protocol is not altered in any substantial way. We also kept the maximum system efficiency for any MAC layer protocol using DFSA as the upper bound to have an impartial comparison between the algorithms. Finally, we present a novel and comprehensive analysis of the probabilistic tag estimation algorithms (DFSA-I & DFSA-II) in terms of their statistically significant correlations between channel efficiency, algorithm estimation accuracy and algorithm utilization rate as the existing literature only look at channel efficiency with no auxiliary analysis. In this study, we use a scalable and flexible simulation framework and created a light-weight, verifiable Gen-2 simulation tool to measure these performance parameters as it is very difficult, if not impossible, to calculate system performance analytically. This framework can easily be used to test and compare more algorithms in the literature with Gen-2 and other DFSA based approaches.

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