Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Innovative energy-efficient wireless sensor network applications and MAC sub-layer protocols employing RTS-CTS with packet concatenation

of energy-efficiency as well as the number of available applications. As a consequence there are challenges that need to be tackled for the future generation of WSNs. The research work from this Ph.D. thesis has involved the actual development of innovative WSN applications contributing to different research projects. In the Smart-Clothing project contributions have been given in the development of a Wireless Body Area Network (WBAN) to monitor the foetal movements of a pregnant woman in the last four weeks of pregnancy. The creation of an automatic wireless measurement system for remotely monitoring concrete structures was an contribution for the INSYSM project. This was accomplished by using an IEEE 802.15.4 network enabling for remotely monitoring the temperature and humidity within civil engineering structures. In the framework of the PROENEGY-WSN project contributions have been given in the identification the spectrum opportunities for Radio Frequency (RF) energy harvesting through power density measurements from 350 MHz to 3 GHz. The design of the circuits to harvest RF energy and the requirements needed for creating a WBAN with electromagnetic energy harvesting and Cognitive Radio (CR) capabilities have also been addressed. A performance evaluation of the state-of-the art of the hardware WSN platforms has also been addressed. This is explained by the fact that, even by using optimized Medium Access Control (MAC) protocols, if the WSNs platforms do not allow for minimizing the energy consumption in the idle and sleeping states, energy efficiency and long network lifetime will not be achieved. The research also involved the development of new innovative mechanisms that tries and solves overhead, one of the fundamental reasons for the IEEE 802.15.4 standard MAC inefficiency. In particular, this Ph.D. thesis proposes an IEEE 802.15.4 MAC layer performance enhancement by employing RTS/CTS combined with packet concatenation. The results have shown that the use of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before transmitting a data packet. In addition, the Sensor Block Acknowledgment MAC (SBACK-MAC) protocol has been proposed that allows the aggregation of several acknowledgment responses in one special Block Acknowledgment (BACK) Response packet. Two different solutions are considered. The first one considers the SBACK-MAC protocol in the presence of BACK Request (concatenation) while the second one considers the SBACK-MAC in the absence of BACK Request (piggyback). The proposed solutions address a distributed scenario with single-destination and single-rate frame aggregation. The throughput and delay performance is mathematically derived under both ideal conditions (a channel environment with no transmission errors) and non ideal conditions (a channel environment with transmission errors). An analytical model is proposed, capable of taking into account the retransmission delays and the maximum number of backoff stages. The simulation results successfully validate our analytical model. For more than 7 TX (aggregated packets) all the MAC sub-layer protocols employing RTS/CTS with packet concatenation allows for the optimization of channel use in WSNs, v8-48 % improvement in the maximum average throughput and minimum average delay, and decrease energy consumption

DESIGN OF RELIABLE AND SUSTAINABLE WIRELESS SENSOR NETWORKS: CHALLENGES, PROTOCOLS AND CASE STUDIES

Integrated with the function of sensing, processing, and wireless communication, wireless sensors are attracting strong interest for a variety of monitoring and control applications. Wireless sensor networks (WSNs) have been deployed for industrial and remote monitoring purposes. As energy shortage is a worldwide problem, more attention has been placed on incorporating energy harvesting devices in WSNs. The main objective of this research is to systematically study the design principles and technical approaches to address three key challenges in designing reliable and sustainable WSNs; namely, communication reliability, operation with extremely low and dynamic power sources, and multi-tier network architecture. Mathematical throughput models, sustainable WSN communication strategies, and multi-tier network architecture are studied in this research to address these challenges, leading to protocols for reliable communication, energy-efficient operation, and network planning for specific application requirements. To account for realistic operating conditions, the study has implemented three distinct WSN testbeds: a WSN attached to the high-speed rotating spindle of a turning lathe, a WSN powered by a microbial fuel cell based energy harvesting system, and a WSN with a multi-tier network architecture. With each testbed, models and protocols are extracted, verified and analyzed. Extensive research has studied low power WSNs and energy harvesting capabilities. Despite these efforts, some important questions have not been well understood. This dissertation addresses the following three dimensions of the challenge. First, for reliable communication protocol design, mathematical throughput or energy efficiency estimation models are essential, yet have not been investigated accounting for specific application environment characteristics and requirements. Second, for WSNs with energy harvesting power sources, most current networking protocols do not work efficiently with the systems considered in this dissertation, such as those powered by extremely low and dynamic energy sources. Third, for multi-tier wireless network system design, routing protocols that are adaptive to real-world network conditions have not been studied. This dissertation focuses on these questions and explores experimentally derived mathematical models for designing protocols to meet specific application requirements. The main contributions of this research are 1) for industrial wireless sensor systems with fast-changing but repetitive mobile conditions, understand the performance and optimal choice of reliable wireless sensor data transmission methods, 2) for ultra-low energy harvesting wireless sensor devices, design an energy neutral communication protocol, and 3) for distributed rural wireless sensor systems, understand the efficiency of realistic routing in a multi-tier wireless network. Altogether, knowledge derived from study of the systems, models, and protocols in this work fuels the establishment of a useful framework for designing future WSNs