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

Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

A cyber-physical system for smart healthcare

Abstract: The increasing number of patients in hospitals is becoming a serious concern in most countries owing to the significantly associated implications for resources such as staff and budget shortages. This problem has prompted researchers to investigate low-cost alternative systems that may assist medical staff with monitoring and caring for patients. In view of the recent widespread availability of cost-effective internet of things (IoT) technologies such as ZigBee, WiFi and sensors integrated into cyber-physical systems, there is the potential for deployment as different topologies in applications such as patient diagnoses and remote patient monitoring...M.Tech. (Electrical and Electronic Engineering Technology

Energy-efficient and lifetime aware routing in WSNs

Network lifetime is an important performance metric in Wireless Sensor Networks (WSNs). Transmission Power Control (TPC) is a well-established method to minimise energy consumption in transmission in order to extend node lifetime and, consequently, lead to solutions that help extend network lifetime. The accurate lifetime estimation of sensor nodes is useful for routing to make more energy-efficient decisions and prolong lifetime. This research proposes an Energy-Efficient TPC (EETPC) mechanism using the measured Received Signal Strength (RSS) to calculate the ideal transmission power. This includes the investigation of the impact factors on RSS, such as distance, height above ground, multipath environment, the capability of node, noise and interference, and temperature. Furthermore, a Dynamic Node Lifetime Estimation (DNLE) technique for WSNs is also presented, including the impact factors on node lifetime, such as battery type, model, brand, self-discharge, discharge rate, age, charge cycles, and temperature. In addition, an Energy-Efficient and Lifetime Aware Routing (EELAR) algorithm is designed and developed for prolonging network lifetime in multihop WSNs. The proposed routing algorithm includes transmission power and lifetime metrics for path selection in addition to the Expected Transmission Count (ETX) metric. Both simulation and real hardware testbed experiments are used to verify the effectiveness of the proposed schemes. The simulation experiments run on the AVRORA simulator for two hardware platforms: Mica2 and MicaZ. The testbed experiments run on two real hardware platforms: the N740 NanoSensor and Mica2. The corresponding implementations are on two operating systems: Contiki and TinyOS. The proposed TPC mechanism covers those investigated factors and gives an overall performance better than the existing techniques, i.e. it gives lower packet loss and power consumption rates, while delays do not significantly increase. It can be applied for single-hop with multihoming and multihop networks. Using the DNLE technique, node lifetime can be predicted more accurately, which can be applied for both static and dynamic loads. EELAR gives the best performance on packet loss rate, average node lifetime and network lifetime compared to the other algorithms and no significant difference is found between each algorithm with the packet delay

Mobility-based Routing Overhead Management in Reconfigurable Wireless Ad hoc Networks

Mobility-Based Routing Overhead Management in Reconfigurable Wireless Ad Hoc Networks Routing Overheads are the non-data message packets whose roles are establishment and maintenance of routes for data packets as well as neighbourhood discovery and maintenance. They have to be broadcasted in the network either through flooding or other techniques that can ensure that a path exists before data packets can be sent to various destinations. They can be sent reactively or periodically to neighbours so as to keep nodes updated on their neighbourhoods. While we cannot do without these overhead packets, they occupy much of the limited wireless bandwidth available in wireless networks. In a reconfigurable wireless ad hoc network scenario, these packets have more negative effects, as links need to be confirmed more frequently than in traditional networks mainly because of the unpredictable behaviour of the ad hoc networks. We therefore need suitable algorithms that will manage these overheads so as to allow data packet to have more access to the wireless medium, save node energy for longer life of the network, increased efficiency, and scalability. Various protocols have been suggested in the research area. They mostly address routing overheads for suitability of particular protocols leading to lack of standardisation and inapplicability to other protocol classes. In this dissertation ways of ensuring that the routing overheads are kept low are investigated. The issue is addressed both at node and network levels with a common goal of improving efficiency and performance of ad hoc networks without dedicating ourselves to a particular class of routing protocol. At node level, a method hereby referred to as "link availability forecast", that minimises routing overheads used for maintenance of neighbourhood, is derived. The targeted packets are packets that are broadcasted periodically (e.g. hello messages). The basic idea in this method is collection of mobility parameters from the neighbours and predictions or forecasts of these parameters in future. Using these parameters in simple calculations helps in identifying link availabilities between nodes participating in maintenance of networks backbone. At the network level, various approaches have been suggested. The first approach is the cone flooding method that broadcasts route request messages through a predetermined cone shaped region. This region is determined through computation using last known mobility parameters of the destination. Another approach is what is hereby referred as "destination search reverse zone method". In this method, a node will keep routes to destinations for a long time and use these routes for tracing the destination. The destination will then initiate route search in a reverse manner, whereby the source selects the best route for next delivery. A modification to this method is for the source node to determine the zone of route search and define the boundaries within which the packet should be broadcasted. The later method has been used for simulation purposes. The protocol used for verification of the improvements offered by the schemes was the AODV. The link availability forecast scheme was implemented on the AODV and labelled AODV_LA while the network level implementation was labelled AODV_RO. A combination of the two schemes was labelled AODV_LARO

Estimating distances via connectivity in wireless sensor networks

Distance estimation is vital for localization and many other applications in wireless sensor networks. In this paper, we develop a method that employs a maximum-likelihood estimator to estimate distances between a pair of neighboring nodes in a static wireless sensor network using their local connectivity information, namely the numbers of their common and non-common one-hop neighbors. We present the distance estimation method under a generic channel model, including the unit disk (communication) model and the more realistic log-normal (shadowing) model as special cases. Under the log-normal model, we investigate the impact of the log-normal model uncertainty; we numerically evaluate the bias and standard deviation associated with our method, which show that for long distances our method outperforms the method based on received signal strength; and we provide a Cramér-Rao lower bound analysis for the problem of estimating distances via connectivity and derive helpful guidelines for implementing our method. Finally, on implementing the proposed method on the basis of measurement data from a realistic environment and applying it in connectivity-based sensor localization, the advantages of the proposed method are confirmed. Copyright © 2012 John Wiley & Sons, Ltd

The MAGCLOUD wireless sensor network

Initially, the aim of this project consisted in manufacturing some nodes for a wireless sensor network by hand. If this document concludes that they can be properly produced in the EETAC lab, the cost of a future large deployment using raw components would be much lower than in the case of acquiring the genuine factory assembled hardware. Also, the future students involved in the process could learn many useful advanced techniques along the way. The project ended sowing a future WSN concept, so powerful that even could end competing on the market. We designed an almost unlimited scalable platform in terms of range, number of nodes, connectivity and measuring capabilities that is 100% free, open and environment sustainable. We called this unique wireless magnitude acquisition cloud: THE MAGCLOUD. The whole system cannot be fully finished within the time and budget restrictions of a single PFC but slicing it into diverse future upgrades is a completely realistic approach. In this document, sticking to the original idea, we explain how to produce the functional hardware and software skeleton but also guide the reader on the future upgrades required to complete the MAGCLOUD system. During the realization of the project we found countless problems that luckily end up solved. Those are carefully treated so can be avoided in the future

Correct-by-Construction Development of Dynamic Topology Control Algorithms

Wireless devices are influencing our everyday lives today and will even more so in the future. A wireless sensor network (WSN) consists of dozens to hundreds of small, cheap, battery-powered, resource-constrained sensor devices (motes) that cooperate to serve a common purpose. These networks are applied in safety- and security-critical areas (e.g., e-health, intrusion detection). The topology of such a system is an attributed graph consisting of nodes representing the devices and edges representing the communication links between devices. Topology control (TC) improves the energy consumption behavior of a WSN by blocking costly links. This allows a mote to reduce its transmission power. A TC algorithm must fulfill important consistency properties (e.g., that the resulting topology is connected). The traditional development process for TC algorithms only considers consistency properties during the initial specification phase. The actual implementation is carried out manually, which is error prone and time consuming. Thus, it is difficult to verify that the implementation fulfills the required consistency properties. The problem becomes even more severe if the development process is iterative. Additionally, many TC algorithms are batch algorithms, which process the entire topology, irrespective of the extent of the topology modifications since the last execution. Therefore, dynamic TC is desirable, which reacts to change events of the topology. In this thesis, we propose a model-driven correct-by-construction methodology for developing dynamic TC algorithms. We model local consistency properties using graph constraints and global consistency properties using second-order logic. Graph transformation rules capture the different types of topology modifications. To specify the control flow of a TC algorithm, we employ the programmed graph transformation language story-driven modeling. We presume that local consistency properties jointly imply the global consistency properties. We ensure the fulfillment of the local consistency properties by synthesizing weakest preconditions for each rule. The synthesized preconditions prohibit the application of a rule if and only if the application would lead to a violation of a consistency property. Still, this restriction is infeasible for topology modifications that need to be executed in any case. Therefore, as a major contribution of this thesis, we propose the anticipation loop synthesis algorithm, which transforms the synthesized preconditions into routines that anticipate all violations of these preconditions. This algorithm also enables the correct-by-construction runtime reconfiguration of adaptive WSNs. We provide tooling for both common evaluation steps. Cobolt allows to evaluate the specified TC algorithms rapidly using the network simulator Simonstrator. cMoflon generates embedded C code for hardware testbeds that build on the sensor operating system Contiki

Energy Technology and Management

The civilization of present age is predominantly dependent on energy resources and their utilization. Almost every human activity in today's life needs one or other form of energy. As world's energy resources are not unlimited, it is extremely important to use energy efficiently. Both energy related technological issues and policy and planning paradigms are highly needed to effectively exploit and utilize energy resources. This book covers topics, ranging from technology to policy, relevant to efficient energy utilization. Those academic and practitioners who have background knowledge of energy issues can take benefit from this book