A new class of Wireless Sensor Networks (WSNs) is emerging within the Internet of Things (IoT) that features extremely high node density, low data rates per node, and high network dependability. Applications such as industrial IoT, factory automation, vehicular networks, aviation, spacecraft and others will soon feature hundreds of low power, low data rate (1-15 kbps) wireless sensor nodes within a limited spatial environment. Existing Medium Access Control (MAC) layer protocols, namely IEEE 802.15.4, may not be suitable for highly dense, low rate networks. A new MAC protocol has been proposed that supports a Receiver-Assigned Code Division Multiple Access (RA-CDMA) physical (PHY) layer multiple access technique, which may enable higher network scalability while maintaining performance and contributing additional robustness. This thesis presents a comparison of the contention mechanisms of IEEE 802.15.4 non- beacon enabled mode and RA-CDMA along with a Matlab simulation framework used for end-to-end simulations of the protocols. Simulations suggest that IEEE 802.15.4 networks begin to break down in terms of throughput, latency, and delivery ratio at a relatively low overall traffic rate compared to RA-CDMA networks. Results show that networks using the proposed RA-CDMA multiple access can support node densities on the order of two to three times higher than IEEE 802.15.4 within the same bandwidth. Furthermore, features of a new MAC layer protocol are proposed that is optimized for RA-CDMA, which could further improve network performance over IEEE 802.15.4. The protocol's simple and lightweight design eliminates significant overhead compared to other protocols while meeting performance requirements, and could further enable the deployment of RA-CDMA WSNs. / Master of Science / Factories, automobiles, planes, spacecraft and other systems in the future will require hundreds of sensors within a relatively small area for data gathering purposes. The sensors, which form Wireless Sensor Networks (WSNs), must have some method of wireless communication that allows each of them to transmit information when needed without obstructing other sensors’ transmissions. Wireless communication protocols provide a method for doing so. Some recognizable examples of wireless communication protocols include Bluetooth, WiFi, 3G and LTE. For WSNs in the future, the industry’s leading candidate protocol is called IEEE 802.15.4, but it may not be most suitable because it is known to break down as large amounts of sensors are added to its networks. Because of this, a new protocol has been proposed around a channel sharing technique called Receiver-Assigned Code Division Multiple Access (RACDMA), which uses a different strategy to efficiently distribute network resources among sensors. This work analyzes the differences between IEEE 802.15.4 and RA-CDMA, focusing specifically on how each protocol allows sensors to transmit without conflicting with one another. A simulation framework is introduced for complete simulations of each protocol. The result of the simulations shows that IEEE 802.15.4 breaks down in dense sensor networks. RACDMA, however, is able to support very large networks, on the order of two to three times the size of IEEE 802.15.4. This result could be an enabling technology for large wireless sensor networks in the future. Additionally, a new protocol optimized for RA-CDMA is presented. Its simple design could further enable the deployment of RA-CDMA WSNs.

Yes / The recent advancements in wireless sensor hardware ensures sensing multiple sensor data such as temperature, pressure, humidity, etc. using a single hardware unit, thus defining it as multi-sensor data communication in wireless sensor networks (WSNs). The in-processing technique of data aggregation is crucial in energy-efficient WSNs; however, with the requirement of end-to-end data confidentiality it may prove to be a challenge. End-to-end data confidentiality along with data aggregation is possible with the implementation of a special type of encryption scheme called privacy homomorphic (PH) encryption schemes. This paper proposes an optimized PH encryption scheme for WSN integrated networks handling multi-sensor data. The proposed scheme ensures light-weight payloads, significant energy and bandwidth consumption along with lower latencies. The performance analysis of the proposed scheme is presented in this paper with respect to the existing scheme. The working principle of the multi-sensor data framework is also presented in this paper along with the appropriate packet structures and process. It can be concluded that the scheme proves to decrease the payload size by 56.86% and spend an average energy of 8-18 mJ at the aggregator node for sensor nodes varying from 10-50 thereby ensuring scalability of the WSN unlike the existing scheme.

Mobile wireless sensor networks are not widely implemented in the real world, even after years of research carried out in this field. One reason is the lack of understanding of the impact that mobility has on network performance. The simulation and emulation of mobile wireless sensor networks is necessary before they are deployed for the real-world applications. This thesis presents a simulation-based study of different mobility models. The total area coverage that depends on the pattern of node movements is observed through simulations. The spatial distribution of node locations is also studied. Various synthetic mobility models available are explored based on their theoretical descriptions. ‘BonnMotion' is used as the network simulator for investigating different mobility scenarios. The results obtained after simulations are imported to MATLAB and the analysis of node movements is done through various plots and inferences from the data. The comparison of mobility models is also discussed based on their spatial node distribution in the simulated scenarios.

ZigBee is a substandard of IEEE 802.15 family that is specially designed to take care of factors such as power, data rate and area that primarily affect network performance. This has controlling and monitoring capability, which finds potential applications in different sectors. ZigBee allows the concept of hybrid networks and mobility. A comprehensive analysis of ZigBee networks was carried out by constructing and simulating the networks to evaluate the performance in terms of throughput, delay, network load, and packets dropped. This research is aimed at evaluating the effect of network topology on the system performance. A careful review of simulation platforms brought the conclusion of using OPNET Modeler which has the required frame work. Different network topologies of simple and hybrid were built and simulated. Throughout the simulations, the best-case scenarios were drawn to the conclusion by the graphical analysis of parameters of evaluation. Mobile networks were constructed and simulated to investigate the effect of mobility on communication.

付記する学位プログラム名: 京都大学卓越大学院プログラム「先端光・電子デバイス創成学」 / 京都大学 / 新制・課程博士 / 博士(工学) / 甲第25290号 / 工博第5249号 / 新制||工||1999(附属図書館) / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 阪本 卓也, 教授 引原 隆士, 准教授 薄 良彦, 教授 土居 伸二 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

We investigate sequential event detection problems arising in Wireless Sensor Networks (WSNs). A number of battery–powered sensor nodes of the same sensing modality are deployed in a region of interest(ROI). By an event we mean a random time(and, for spatial events, a random location) after which the random process being observed by the sensor field experiences a change in its probability law. The sensors make measurements at periodic time instants, perform some computations, and then communicate the results of their computations to the fusion centre. The decision making algorithm in the fusion centre employs a procedure that makes a decision on whether the event has occurred or not based on the information it has received until the current decision instant. We seek event detection algorithms in various scenarios, that are optimal in the sense that the mean detection delay (delay between the event occurrence time and the alarm time) is minimum under certain detection error constraints. In the first part of the thesis, we study event detection problems in a small extent network where the sensing coverage of any sensor includes the ROI. In particular, we are interested in the following problems: 1) quickest event detection with optimal control of the number of sensors that make observations(while the others sleep),2) quickest event detection on wireless ad hoc networks, and3) optimal transient change detection. In the second part of the thesis, we study the problem of quickest detection and isolation of an event in a large extent sensor network where the sensing coverage of any sensor is only a small portion of the ROI. One of the major applications envisioned for WSNs is detecting any abnormal activity or intrusions in the ROI. An intrusion is typically a rare event, and hence, much of the energy of sensors gets drained away in the pre–intrusion period. Hence, keeping all the sensors in the awake state is wasteful of resources and reduces the lifetime of the WSN. This motivates us to consider the problem of sleep–wake scheduling of sensors along with quickest event detection. We formulate the Bayesian quickest event detection problem with the objective of minimising the expected total cost due to i)the detection delay and ii) the usage of sensors, subject to the constraint that the probability of false alarm is upper bounded by .We obtain optimal event detection procedures, along with optimal closed loop and open loop control for the sleep–wake scheduling of sensors. In the classical change detection problem, at each sampling instant, a batch of samples(where is the number of sensors deployed in the ROI) is generated at the sensors and reaches the fusion centre instantaneously. However, in practice, the communication between the sensors and the fusion centre is facilitated by a wireless ad hoc network based on a random access mechanism such as in IEEE802.11 or IEEE802.15.4. Because of the medium access control(MAC)protocol of the wireless network employed, different samples of the same batch reach the fusion centre after random delays. The problem is to detect the occurrence of an event as early as possible subject to a false alarm constraint. In this more realistic situation, we consider a design in which the fusion centre comprises a sequencer followed by a decision maker. In earlier work from our research group, a Network Oblivious Decision Making (NODM) was considered. In NODM, the decision maker in the fusion centre is presented with complete batches of observations as if the network was not present and makes a decision only at instants at which these batches are presented. In this thesis, we consider the design in which the decision maker makes a decision at all time instants based on the samples of all the complete batches received thus far, and the samples, if any, that it has received from the next (partial) batch. We show that for optimal decision making the network–state is required by the decision maker. Hence, we call this setting Network Aware Decision Making (NADM). Also, we obtain a mean delay optimal NADM procedure, and show that it is a network–state dependent threshold rule on the a posteriori probability of change. In the classical change detection problem, the change is persistent, i.e., after the change–point, the state of nature remains in the in–change state for ever. However, in applications like intrusion detection, the event which causes the change disappears after a finite time, and the system goes to an out–of–change state. The distribution of observations in the out–of–change state is the same as that in the pre–change state. We call this short–lived change a transient change. We are interested in detecting whether a change has occurred, even after the change has disappeared at the time of detection. We model the transient change and formulate the problem of quickest transient change detection under the constraint that the probability of false alarm is bounded by . We also formulate a change detection problem which maximizes the probability of detection (i.e., probability of stopping in the in–change state) subject to the probability of false alarm being bounded by . We obtain optimal detection rules and show that they are threshold d rules on the a posteriori probability of pre–change, where the threshold depends on the a posteriori probabilities of pre–change, in–change, and out–of–change states. Finally, we consider the problem of detecting an event in a large extent WSN, where the event influences the observations of sensors only in the vicinity of where it occurs. Thus, in addition to the problem of event detection, we are faced with the problem of locating the event, also called the isolation problem. Since the distance of the sensor from the event affects the mean signal level that the sensor node senses, we consider a realistic signal propagation model in which the signal strength decays with distance. Thus, the post–change mean of the distribution of observations across sensors is different, and is unknown as the location of the event is unknown, making the problem highly challenging. Also, for a large extent WSN, a distributed solution is desirable. Thus, we are interested in obtaining distributed detection/isolation procedures which are detection delay optimal subject to false alarm and false isolation constraints. For this problem, we propose the following local decision rules, MAX, HALL, and ALL, which are based on the CUSUM statistic, at each of the sensor nodes. We identify corroborating sets of sensor nodes for event location, and propose a global rule for detection/isolation based on the local decisions of sensors in the corroborating sets. Also, we show the minimax detection delay optimality of the procedures HALL and ALL.

Advances in wireless communication and microelectronics have led to the development of low-power compact sensor nodes (popularly called motes) that are capable of sensing, computing, and communication. A large number of these nodes can be deployed over some area of interest to form a multi-hop network, commonly referred to as a wireless sensor network (WSN). Typical applications of WSNs include, environment and process monitoring in industrial installations, forest fire detection, structural health monitoring, etc. In such applications where the variables to be measured are slowly varying, or the events to be monitored are rare, continuous sensing is unnecessary. Instead, the nodes, in order to conserve their battery power, can sleep-wake cycle whereby each node is allowed to independently alternate between an ON state and a low power OFF state. Sleep-wake cycling, while increasing the network lifetime, renders the network disconnected a large fraction of the time; however, connectivity can be established over time by transporting packets in a store-and-forward manner, whereby packets are held by a forwarding node until a suitable node wakes up in its neighborhood that can serve to forward the packet towards the destination. We are concerned with sleep-wake cycling multi-hop wireless networks whose main task is to carry sporadic alarms packets from sensing nodes to a sink node. Our objective is to design simple local-information based routing solutions for such networks. With this in mind, we propose a relay selection problem that arises at a forwarding node (which is currently holding the alarm packet) while choosing a next-hop relay node. The forwarder, as and when the relays wake-up, evaluating the goodness of a relay based on a “reward” metric (e.g., a function of the relay’s progress towards sink, and the power required to get the packet across), has to decide whether to forward to this relay or to wait for future ones (i.e., to stop or continue). The forwarder’s objective is to choose a relay so as to minimize a combination of the average delay incurred and the average reward achieved. A basic version of our relay selection problem is equivalent to the basic asset selling problem studied in the operations research literature. After reviewing the solution to the basic problem we will proceed to study a model with full information, referred to as the completely observable (CO) model, where the number of relays is exactly known to the forwarder. Formulating the problem as a Markov decision process (MDP) we will characterize the solution to the CO model in terms of recursively-computable threshold functions. Next, we consider the partially observable (PO) model where only a belief (probability mass function) on the number of relays is known. Hence, the PO model falls within the realm of partially observable MDPs. After incorporating our model into this framework we will characterize the solution in terms of stopping sets, which is the set of all belief states where it is optimal to stop. Our main contribution here is to obtain inner and outer bounds for the stopping sets. We next propose a variant where the relays, upon waking up, do not reveal their rewards immediately, but instead the forwarder can choose to probe the relay to know its reward, incurring a probing cost. Thus, to the existing set of stop and continue actions, we have added a new probe action. This model is motivated by the efforts required to learn the channel gains (by probing) in a wireless system. A key result we prove here is that the solution is characterized in terms of stage independent thresholds. Finally, we study a model comprising two forwarders which are competing against each other to choose a next-hop relay (one for each). Here, a relay is allowed to offer possibly different reward to each forwarder. We will first consider a complete information case where the reward pair of a relay is known to both the forwarders. Using stochastic game theory we will characterize the solution to this model in terms of Nash equilibrium policy pairs (NEPPs). We obtain results illustrating the structure of NEPPs. Next, we study a partial information model where each forwarder gets to observe only its reward value. Towards obtaining the solution for this model, we will first formulate a Bayesian game which is effectively played by both the forwarders at each stage. Next, for this Bayesian game we prove the existence of Nash equilibrium strategies within the class of threshold strategies. This result will enable us to construct NEPPs for the partial information model. Although our primary contribution from the thesis is the theoretical study of the above mentioned variants of the basic relay selection model, we have also conducted extensive simulations to study the end-to-end performance obtained by applying the solution to these models at each hop en-route to the sink in a sleep-wake cycling WSN.

Master of Science / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / In this thesis, we first consider the problem of distributed estimation in an energy and rate-constrained wireless sensor network. To this end, we study three estimators namely - (1) Best Linear Unbiased Estimator (BLUE-1) that accounts for the variance of noise in measurement, uniform quantization and channel, and derive its variance and its lower bound; (2) Best Linear Unbiased Estimator (BLUE-2) that accounts for the variance of noise in measurement and uniform quantization, and derive lower and upper bounds for its variance; (3) Best Linear Unbiased Estima- tor (BLUE-3) that incorporates the effects of probabilistic quantization noise and measurement noise, and derive an upper bound for its variance. Then using BLUE-1, we analyze the tradeoff between estimation error (BLUE variance) at the fusion center and the total amount of resources utilized (power and rate) using three different system design approaches or optimization formulations. For all the formulations, we determine optimum quantization bits and transmission power per bit (or optimum actions) for all sensors jointly. Unlike prior efforts, we in- corporate the operating state (characterized by the amount of residual battery power) of the sensors in the optimization framework. We study the e®ect of channel quality, local measurement noise, and operating states of the sensors on their optimum choice for quantization bits and transmit power per bit. In the sequel, we consider a problem in distributed detection and signal processing in the context of biomedical wireless sensors and more specifically pulse- oximeter devices that record photoplethysmographic data. We propose an automated, two-stage PPG data processing method to minimize the effect of motion artifact. Regarding stage one, we present novel and consistent techniques to detect the presence of motion artifact in photoplethysmograms given higher order statistical information present in the data.For stage two, we propose an effective motion artifact reduction method that involves enhanced PPG data preprocessing followed by frequency domain Independent Component Analysis (FD-ICA). Experimental results are presented to demonstrate the efficacy of the overall motion artifact reduction method. Finally, we analyze a wireless ad hoc/sensor network where nodes are connected via random channels and information is transported in the network in a cooperative multihop fashion using amplify and forward relay strategy.

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.

Machine-to-Machine (M2M) communications is an emerging communication paradigm that provides ubiquitous connectivity between devices along with an ability to communicate autonomously without human intervention. M2M communications acts as an enabling technology for the practical realization of Internet-of-Things (IoT). However, M2M communications differs from conventional Human-to-Human (H2H) communications due to its unique features such as massive number of connected devices, small data transmissions, little or no mobility, requirements of high energy efficiency and reliability, etc. These features create various challenges for existing communication networks which are primarily optimized for H2H communications. Therefore, novel solutions are required to meet the key requirements of M2M communications. In addition, enhancements are required at different layers of the protocol stack to support co-existence of M2M devices and H2H users. The main objective of this research is to investigate the challenges of M2M communications in two broad types of M2M networks; capillary M2M and cellular M2M networks. The primary focus is on developing novel solutions, algorithms, and protocol enhancements for successfully enabling M2M communications. Since cognitive radio technology is very promising for M2M communications, special emphasis is on capillary M2M networks with cognitive radio based Physical layer. Besides, the focus is also on exploring new frontiers in M2M communications. This thesis covers different aspects of M2M communications. Considering the motivation for cognitive M2M and service requirements of M2M devices, two cognitive MAC protocols have been proposed. The first protocol is centralized in nature and utilizes a specialized frame structure for co-existence with the primary network as well as handling different Quality-of-Service (QoS) requirements of M2M devices. The second protocol is a distributed cognitive MAC protocol, which is specially designed to provide high energy efficiency and reliability for M2M devices operating in challenging wireless environments. Both protocols explicitly account for the peculiarities of cognitive radio environments. The protocols have been evaluated using analytical modeling and simulation studies. Recently IETF has standardized a specially designed routing protocol for capillary M2M networks, known as RPL (Routing for Low Power and Lossy Networks). RPL is emerging as the de facto routing protocol for many M2M applications including the smart grid. On the other hand, the application of cognitive radio for smart grid communication is under active investigation in the research community. Hence, it is important to investigate the applicability and adaptation of RPL in cognitive radio environments. In this regard, an enhanced RPL based routing protocol has been proposed for cognitive radio enabled smart grid networks. The enhanced protocol provides novel modifications to RPL for protecting the primary users along with meeting the utility requirements of the secondary network. An important challenge in LTE-based cellular networks with M2M communications is the uplink radio resource management as available resources are shared between M2M devices and H2H users, having different and often conflicting QoS requirements. Apart from this, energy efficiency requirements become critically important. Further, the specific constraints of Single Carrier Frequency Division Multiple Access (SC-FDMA) complicate the resource allocation problem. In this respect, an energy efficient resource allocation algorithm for the uplink of LTE networks with M2M/H2H co-existence under statistical QoS guarantees has been developed, that is based on canonical duality theory. The proposed algorithm outperforms classical algorithms in terms of energy efficiency while satisfying the QoS requirements of M2M devices and H2H users. A new frontier in M2M communications is the nano-M2M communications, which is envisioned to create the Internet-of-Nano-Things (IoNT). Molecular communication (MC) is a promising communication technique for nano-M2M communications. In literature, no model for error performance of MC exists. Therefore, an error performance model has been developed that explicitly accounts for noise and interference effects. Since relaying and network coding based solutions are gaining popularity for nano-M2M networks, the error performance of a network coded molecular nano-M2M network has been evaluated as well. Finally, the thesis is concluded based on the overall picture of the research conducted. In addition, some directions for future work are included as well.