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 Smart Game for Data Transmission and Energy Consumption in the Internet of Things

The current trend in developing smart technology for the Internet of Things (IoT) has motivated a lot of research interest in optimizing data transmission or minimizing energy consumption, but with little evidence of proposals for achieving both objectives in a single model. Using the concept of game theory, we develop a new MAC protocol for IEEE 802.15.4 and IoT networks in which we formulate a novel expression for the players' utility function and establish a stable Nash equilibrium (NE) for the game. The proposed IEEE 802.15.4 MAC protocol is modeled as a smart game in which analytical expressions are derived for channel access probability, data transmission probability, and energy used. These analytical expressions are used in formulating an optimization problem (OP) that maximizes data transmission and minimizes energy consumption by nodes. The analysis and simulation results suggest that the proposed scheme is scalable and achieves better performance in terms of data transmission, energy-efficiency, and longevity, when compared with the default IEEE 802.15.4 access mechanism.Peer reviewe

Performance Prediction and Tuning for Symmetric Coexistence of WiFi and ZigBee Networks

Due to the explosive deployment of WiFi and ZigBee wireless networks, 2.4GHz ISM bands (2.4GHz-2.5GHz) are becoming increasingly crowded, and the co-channel coexistence of these two networks is inevitable. For coexistence networks, people always want to predict their performance (e.g. throughput, energy consumption, etc.) before deployment, or even want to tune parameters to compensate unnecessary performance degradation (owing to the huge differences between these two MAC protocols) or to satisfy some performance requirements (e.g., priority, delay constraint, etc.) of them. However, predicting and tuning performance of coexisting WiFi and ZigBee networks has been a challenging task, primarily due to the lack of corresponding simulators and analytical models. In this dissertation, we addressed the aforementioned problems by presenting simulators and models for the coexistence of WiFi and ZigBee devices. Specifically, based on the energy efficiency and traffic pattern of three practical coexistence scenarios: disaster rescue site, smart hospital and home automation. We first of all classify them into three classes, which are non-sleeping devices with saturated traffic (SAT), non-sleeping devices with unsaturated traffic (UNSAT) and duty-cycling devices with unsaturated traffic (DC-UNSAT). Then a simulator and an analytical model are proposed for each class, where each simulator is verified by simple hardware based experiment. Next, we derive the expressions for performance metrics like throughput, delay etc., and predict them using both the proposed simulator and the model. Due to the higher accuracy of the simulator, the results from them are used as the ground truth to validate the accuracy of the model. Last, according to some common performance tuning requirements for each class, we formulate them into optimization problems and propose the corresponding solving methods. The results show that the proposed simulators have high accuracy in performance prediction, while the models, although are less accurate than the former, can be used in fast prediction. In particular, the models can also be easily used in optimization problems for performance tuning, and the results prove its high efficiency

Cluster based jamming and countermeasures for wireless sensor network MAC protocols

A wireless sensor network (WSN) is a collection of wireless nodes, usually with limited computing resources and available energy. The medium access control layer (MAC layer) directly guides the radio hardware and manages access to the radio spectrum in controlled way. A top priority for a WSN MAC protocol is to conserve energy, however tailoring the algorithm for this purpose can create or expose a number of security vulnerabilities. In particular, a regular duty cycle makes a node vulnerable to periodic jamming attacks. This vulnerability limits the use of use of a WSN in applications requiring high levels of security. We present a new WSN MAC protocol, RSMAC (Random Sleep MAC) that is designed to provide resistance to periodic jamming attacks while maintaining elements that are essential to WSN functionality. CPU, memory and especially radio usage are kept to a minimum to conserve energy while maintaining an acceptable level of network performance so that applications can be run transparently on top of the secure MAC layer. We use a coordinated yet pseudo-random duty cycle that is loosely synchronized across the entire network via a distributed algorithm. This thwarts an attacker\u27s ability to predict when nodes will be awake and likewise thwarts energy efficient intelligent jamming attacks by reducing their effectiveness and energy-efficiency to that of non-intelligent attacks. Implementing the random duty cycle requires additional energy usage, but also offers an opportunity to reduce asymmetric energy use and eliminate energy use lost to explicit neighbor discovery. We perform testing of RSMAC against non-secure protocols in a novel simulator that we designed to make prototyping new WSN algorithms efficient, informative and consistent. First we perform tests of the existing SMAC protocol to demonstrate the relevance of the novel simulation for estimating energy usage, data transmission rates, MAC timing and other relevant macro characteristics of wireless sensor networks. Second, we use the simulation to perform detailed testing of RSMAC that demonstrates its performance characteristics with different configurations and its effectiveness in confounding intelligent jammers

Optimising lower layers of the protocol stack to improve communication performance in a wireless temperature sensor network

The function of wireless sensor networks is to monitor events or gather information and report the information to a sink node, a central location or a base station. It is a requirement that the information is transmitted through the network efficiently. Wireless communication is the main activity that consumes energy in wireless sensor networks through idle listening, overhearing, interference and collision. It becomes essential to limit energy usage while maintaining communication between the sensor nodes and the sink node as the nodes die after the battery has been exhausted. Thus, conserving energy in a wireless sensor network is of utmost importance. Numerous methods to decrease energy expenditure and extend the lifetime of the network have been proposed. Researchers have devised methods to efficiently utilise the limited energy available for wireless sensor networks by optimising the design parameters and protocols. Cross-layer optimisation is an approach that has been employed to improve wireless communication. The essence of cross-layer scheme is to optimise the exchange and control of data between two or more layers to improve efficiency. The number of transmissions is therefore a vital element in evaluating overall energy usage. In this dissertation, a Markov Chain model was employed to analyse the tuning of two layers of the protocol stack, namely the Physical Layer (PHY) and Media Access Control layer (MAC), to find possible energy gains. The study was conducted utilising the IEEE 802.11 channel, SensorMAC (SMAC) and Slotted-Aloha (S-Aloha) medium access protocols in a star topology Wireless Temperature Sensor Network (WTSN). The research explored the prospective energy gains that could be realised through optimizing the Forward Error Correction (FEC) rate. Different Reed Solomon codes were analysed to explore the effect of protocol tuning on energy efficiency, namely transmission power, modulation method, and channel access. The case where no FEC code was used and analysed as the control condition. A MATLAB simulation model was used to identify the statistics of collisions, overall packets transmitted, as well as the total number of slots used during the transmission phase. The bit error probability results computed analytically were utilised in the simulation model to measure the probability of successful transmitting data in the physical layer. The analytical values and the simulation results were compared to corroborate the correctness of the models. The results indicate that energy gains can be accomplished by the suggested layer tuning approach.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

A Comparative Study of Energy Efficient Medium Access Control Protocols in Wireless Sensor Networks

This project investigates energy usage in three energy-efficient WSN MAC protocols (AS-MAC, SCP-MAC, and Crankshaft) on TelosB wireless sensors. It additionally presents BAS-MAC, an energy-efficient protocol of our own design. Our evaluations show that in single-hop networks with large send intervals and staggered sending, AS-MAC is best in the local gossip and convergecast scenarios, while SCP-MAC is best overall in the broadcast scenario. We conjecture that Crankshaft would perform best in extremely dense hybrid (unicast and broadcast) network topologies, especially those which broadcast frequently. Finally, BAS-MAC would be optimal in networks which utilize hybrid traffic with infrequent broadcasts, and where broadcasting is performed by motes that do not have an unlimited power source

Energy-Efficient Boarder Node Medium Access Control Protocol for Wireless Sensor Networks

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle.https://doi.org/10.3390/s14030507