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

Energy Efficient and Secure Wireless Sensor Networks Design

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired level of quality of service. Inspired by these challenges, this dissertation is dedicated to exploiting optimization and game theoretic approaches/solutions to handle several important issues in WSN communication, including energy efficiency, latency, congestion, dynamic traffic load, and security. We present several novel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes are proposed for the network layer stack to achieve the following: (a) to enhance energy efficiency through optimized sleep intervals, that also considers the underlying dynamic traffic load and (b) to develop the routing protocol in order to handle wasted energy, congestion, and clustering. We also propose efficient routing and energy-efficient clustering algorithms based on optimization and game theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between attacker and defender as a non-cooperative security game that considers the resource limitation. All the proposed schemes are validated by extensive experimental analyses, obtained by running simulations depicting various situations in WSNs in order to represent real-world scenarios as realistically as possible. The results show that the proposed schemes achieve high performance in different terms, such as network lifetime, compared with the state-of-the-art schemes

The Design of Medium Access Control (MAC) Protocols for Energy Efficient and QoS Provision in Wireless Sensor Networks

This thesis work focuses on innovative design of media access control (MAC) protocols in wireless sensor networks (WNSs). The characteristics of the WSN inquire that the network service design considers both energy efficiency and the associated application requirement. However, most existing protocols address only the issue of energy efficiency. In this thesis, a MAC protocol has been proposed (referred to as Q-MAC) that not only minimized the energy consumption in multi-hop WSNs, but also provides Quality of Service (QoS) by differentiating network services based on priority levels prescribed by different applications. The priority levels reflect the state of system resources including residual energy and queue occupancies. Q-MAC contains both intra- and inter- node arbitration mechanisms. The intra-node packet scheduling employs a multiple queuing architectures, and applies a scheduling scheme consisting of packet classification and weighted arbitration. We introduce the Power Conservation MACAW (PC-MACAW), a power-aware scheduling mechanism which, together with the Loosely Prioritized Random Access (LPRA) algorithm, govern the inter-node scheduling. Performance evaluation are conducted between Q-MAC and S-MAC with respect to two performance metrics: energy consumption and average latency. Simulation results indicate Q-MAC achieves comparable performance to that of S-MAC in non-prioritized traffic scenarios. When packets with different priorities are introduced, Q-MAC yields noticeable average latency differentiations between the classes of service, while preserving the same degree of energy consumption as that of S-MAC. Since the high density nature of WSN may introduce heavy traffic load and thus consume large amount of energy for communication, another MAC protocol, referred to as the Deployment-oriented MAC (D-MAC)has been further proposed. D-MAC minimalizes both sensing and communication redundancy by putting majority of redundant nodes into the sleep state. The idea is to establish a sensing and communication backbone covering the whole sensing field with the least sensing and communication redundancy. In specific, we use equal-size rectangular cells to partition the sensing field and chose the size of each cell in a way such that regardless of the actual location within the cell, a node can always sense the whole cell and communicate with all the nodes in neighboring cells. Once the sensing field has been partitioned using these cells, a localized Location-aware Selection Algorithm (LSA) is carried out to pick up only one node within each cell to be active for a fixed amount of period. This selection is energy-oriented, only nodes with a maximum energy will be on and the rest of nodes will be put into the sleep state once the selection process is over. To balance the energy consumption, the selection algorithm is periodically conducted until all the nodes are out of power. Simulation results indicated that D-MAC saves around 80% energy compared to that of S-MAC and Q-MAC, while maintaining 99% coverage. D-MAC is also superior to S-MAC and Q-MAC in terms of average latency. However, the use of GPS in D-MAC in identifying the nodes within the same cell, would cause extra cost and complexity for the design of sensor nodes

Critical data-based incremental cooperative communication for wireless body area network

Wireless Body Area Networks (WBANs) are single-hop network systems, where sensors gather the body’s vital signs and send them directly to master nodes (MNs). The sensors are distributed in or on the body. Therefore, body posture, clothing, muscle movement, body temperature, and climatic conditions generally influence the quality of the wireless link between sensors and the destination. Hence, in some cases, single hop transmission (‘direct transmission’) is not sufficient to deliver the signals to the destination. Therefore, we propose an emergency-based cooperative communication protocol for WBAN, named Critical Data-based Incremental Cooperative Communication (CD-ICC), based on the IEEE 802.15.6 CSMA standard but assuming a lognormal shadowing channel model. In this paper, a complete study of a system model is inspected in the terms of the channel path loss, the successful transmission probability, and the outage probability. Then a mathematical model is derived for the proposed protocol, end-to-end delay, duty cycle, and average power consumption. A new back-off time is proposed within CD-ICC, which ensures the best relays cooperate in a distributed manner. The design objective of the CD-ICC is to reduce the end-to-end delay, the duty cycle, and the average power transmission. The simulation and numerical results presented here show that, under general conditions, CD-ICC can enhance network performance compared to direct transmission mode (DTM) IEEE 802.15.6 CSMA and benchmarking. To this end, we have shown that the power saving when using CD-ICC is 37.5% with respect to DTM IEEE 802.15.6 CSMA and 10% with respect to MI-ICC