We consider a wireless sensor network, in which end users are interested in maximizing the useful information supplied by the network till network partition due to inevitable node deaths. Neither throughput maximization nor network lifetime maximization achieves the objective: A network with high throughput provides information at a high rate, but can exhaust the nodes of their energies quickly; similarly, a network can achieve a long lifetime by remaining idle for most of the time. We propose and seek to maximize a new metric: “Aggregate bit transported before network partition” (a product of throughput and lifetime), which precisely captures the usefulness of sensor networks. We model the links in the wireless sensor network as wired links with reduced equivalent capacities, formulate and solve the problem of maximizing bits transported before network partition on arbitrary networks. To assess the benefits that network coding can yield for the same objective, we study a scenario where the coding-capable nodes are placed on a regular grid. We propose an optimal algorithm to choose the minimum number of coding points in the grid to ensure energy efficiency. Our results show that, even with simple XOR coding, the bits transported can increase up to 83 % of that without coding. Further, we study the problem of in-network data aggregation in a wireless sensor network to achieve minimum delay. The nodes in the network compute and forward data as per a query graph, which allows operations belonging to a general class of functions. We aim to extract the best sub-network that achieves the minimum delay. We design an algorithm to schedule the sub-network such that the computed data reaches sink at the earliest. We consider directed acyclic query graphs as opposed to the existing work which considers tree query graphs only.

Wireless sensor networks(WSNs) have a diverse set of applications such as military surveillance, health and environmental monitoring, and home automation. Sensor nodes are equipped with pre-charged batteries, which drain out when the nodes sense, process, and communicate data. Eventually, the nodes of the WSN die and the network dies. Energy harvesting(EH) is a green alternative to solve the limited lifetime problem in WSNs. EH nodes recharge their batteries by harvesting ambient energy such as solar, wind, and radio energy. However, due to the randomness in the EH process and the limited amounts of energy that can be harvested, the EH nodes are often intermittently available. Therefore, even though EH nodes live perpetually, they do not cater to the network continuously. We focus on the energy-efficient design of WSNs that incorporate EH, and investigate the new design trade-offs that arise in exploiting the potentially scarce and random energy arrivals and channel fading encountered by the network. To this end, firstly, we compare the performance of conventional, all-EH, and hybrid WSNs, which consist of both conventional and EH nodes. We then study max function computation, which aims at energy-efficient data aggregation, in EH WSNs. We first argue that the conventional performance criteria used for evaluating WSNs, which are motivated by lifetime, and for evaluating EH networks are at odds with each other and are unsuitable for evaluating hybrid WSNs. We propose two new and insightful performance criteria called the k-outage and n-transmission durations to evaluate and compare different WSNs. These criteria capture the effect of the battery energies of the nodes and the channel fading conditions on the network operations. We prove two computationally-efficient bounds for evaluating these criteria, and show their use in a cost-constrained deployment of a WSN involving EH nodes. Next, we study the estimation of maximum of sensor readings in an all-EH WSN. We analyze the mean absolute error(MAE) in estimating the maximum reading when a random subset of the EH nodes periodically transmit their readings to the fusion node. We determine the optimal transmit power and the number of scheduled nodes that minimize the MAE. We weigh the benefits of the availability of channel information at the nodes against the cost of acquiring it. The results are first developed assuming that the readings are transmitted with infinite resolution. The new trade-offs that arise when quantized readings are instead transmitted are then characterized.Our results hold for any distribution of sensor readings, and for any stationary and ergodic EH process.

The nodes in wireless sensor networks (WSNs) utilize the radio frequency (RF) channel to communicate. Given that the RF channel is the primary communication channel, many researchers have developed techniques for securing that channel. However, the RF channel is not the only interface into a sensor. The sensing components, which are primarily designed to sense characteristics about the outside world, can also be used (or misused) as a communication (side) channel. In our work, we aim to characterize the side channels for various sensory components (i.e., light sensor, acoustic sensor, and accelerometer). While previous work has focused on the use of these side channels to improve the security and performance of a WSN, we seek to determine if the side channels have enough capacity to potentially be used for malicious activity. Specifically, we evaluate the feasibility and practicality of the side channels using today's sensor technology and illustrate that these channels have enough capacity to enable the transfer of common, well-known malware. Given that a significant number of modern robotic systems depend on the external side channels for navigation and environment-sensing, they become potential targets for side-channel attacks. Therefore, we demonstrate this relatively new form of attack which exploits the uninvestigated but predominantly used side channels to trigger malware residing in real-time robotic systems such as the iRobot Create. The ultimate goal of our work is to show the impact of this new class of attack and also to motivate the need for an intrusion detection system (IDS) that not only monitors the RF channel, but also monitors the values returned by the sensory components.

Wireless Sensor Networks (WSNs) are rapidly gaining popularity in various critical domains like health care, critical infrastructure, and climate monitoring, where application builders have diversified development needs. Independent of the functionalities provided by the WSN applications, many of the developers use visualization, simulation, and programming tools. However, these tools are designed as separate stand-alone applications, which force developers to use multiple tools. This situation often poses confusion and hampers an efficient development experience. To avoid the complexity of using multiple tools, a new, extensible, multi-platform, scalable, and open-source framework called PROVIZ is designed. PROVIZ is an integrated visualization and programming framework with the following features: PROVIZ 1) visualizes sensor nodes and WSN traffic by parsing the data received either from a packet sniffer (e.g., a sensor-based sniffer, or a commercial TI SmartRF 802.15.4 packet sniffer), or from a simulator (e.g., OMNeT); 2) visualizes a heterogeneous WSN consisting of different sensor nodes sending packets with different packet payload formats; and 3) provides a programming framework, which provides a graphical and script-based programming functionality, for developing WSN applications. Also, PROVIZ includes built-in extensible visual demo deployment capabilities that allow users to quickly craft network scenarios and share them with other users. Additionally, a secure and energy efficient wireless code dissemination protocol, named SIMAGE, was developed. SIMAGE is used by PROVIZ to wirelessly reprogram the sensor nodes. SIMAGE uses a link quality cognizant adaptive packet-sizing technique along with energy-efficient encryption protocols for secure and efficient code dissemination. In this thesis, the various features of PROVIZ's visualization and programming framework are explained, the functionality and performance of SIMAGE protocol is described, an example WSN security attack scenario is analyzed, and how PROVIZ can be used as a visual debugging tool to identify the security attack and aid in providing a software fix are discussed.

Today, wireless sensor networks (WSNs) are no longer a nascent technology and future networks, especially Cyber-Physical Systems (CPS) will integrate more sensor-based systems into a variety of application scenarios. Typical application areas include medical, environmental, military, and commercial enterprises. Providing security to this diverse set of sensor-based applications is necessary for the healthy operations of the overall system because untrusted entities may target the proper functioning of applications and disturb the critical decision-making processes by injecting false information into the network. One way to address this issue is to employ en-route-filtering-based solutions utilizing keys generated by either static or dynamic key management schemes in the WSN literature. However, current schemes are complicated for resource-constrained sensors as they utilize many keys and more importantly as they transmit many keying messages in the network, which increases the energy consumption of WSNs that are already severely limited in the technical capabilities and resources (i.e., power, computational capacities, and memory) available to them. Nonetheless, further improvements without too much overhead are still possible by sharing a dynamically created cryptic credential. Building upon this idea, the purpose of this thesis is to introduce an efficient and secure communication framework for WSNs. Specifically, three protocols are suggested as contributions using virtual energies and local times onboard the sensors as dynamic cryptic credentials: (1) Virtual Energy-Based Encryption and Keying (VEBEK); (2) TIme-Based DynamiC Keying and En-Route Filtering (TICK); (3) Secure Source-Based Loose Time Synchronization (SOBAS) for WSNs.

Passive wireless sensor networks (WSNs) are quickly becoming popular for many applications such as article tracking, position location, temperature sensing, and passive data storage. Passive tags and sensors are unique in that they collect their electrical energy by harvesting it from the ambient environment. Tags with charge pumps collect their energy from the signal they receive from the transmitting source. The efficiency of converting the received signal to DC power is greatly enhanced using a power-optimized waveform (POW). Measurements in the first part of this dissertation show that a POW can provide efficiency gains of up to 12 dB compared to a sine-wave input. Tracking the real-time location of these passive tags is a specialized feature used in some applications such as animal tracking. A passive WSN that uses POWs for the improvement of energy-harvesting may also estimate the range to a tag by measuring the time delay of propagation from the transmitter to the tag and back to the transmitter. The maximum-likelihood (ML) estimator is used for estimating this time delay, which simplifies to taking the cross-correlation of the received signal with the transmitted signal. This research characterizes key aspects of performing range estimations in passive WSNs using POWs. The shape of the POW has a directly-measurable effect on ranging performance. Measurements and simulations show that the RMS bandwidth of the waveform has an inversely proportional relationship to the uncertainty of a range measurement. The clutter of an environment greatly affects the uncertainty and bias exhibited by a range estimator. Random frequency-selective environments with heavy clutter are shown to produce estimation uncertainties more than 20 dB higher than the theoretical lower bound. Estimation in random frequency-flat environments is well-behaved and fits the theory quite nicely. Nonlinear circuits such as the charge pump distort the POW during reflection, which biases the range estimations. This research derives an empirical model for predicting the estimation bias for Dickson charge pumps and verifies it with simulations and measurements.

Το αντικείμενο της παρούσας διπλωματικής εργασίας είναι η δημιουργία ενός υποβρύχιου ασύρματου δικτύου αισθητήρων για την πραγματοποίηση της μέτρησης της στάθμης μίας δεξαμενής γεμισμένης με νερό και λύματα. Πραγματοποιήθηκε μία πλήρη βιβλιογραϕική αναζήτηση πάνω στο θέμα των των υποβρύχιων ασύρματων δικτύων αισθητήρων και στην συνέχεια αγοράστηκε ο κατάλληλος εξοπλισμός για την πραγματοποίηση των πειραμάτων. Με την χρήση του ολοκληρωμένου εξοπλισμού evaluation kit EK010-JN5148, δημιουργήσαμε ένα δίκτυο μεταξύ ενός συντονιστή, ενός δρομολογητή και διαϕόρων τερματικών συσκευών. Ο δρομολογητής και οι τερματικές συσκευές πραγματοποιούν μετρήσεις της θερμοκρασίας στο υδάτινο περιβάλλον και ο δρομολογητής είναι υπεύθυνος για την μεταϕορά των πληροϕοριών εκτός του υποβρύχιου περιβάλλοντος, στον συντονιστή, ο οποίος απεικονίζει τα πακέτα δεδομένων στην LCD οθόνη. Με αυτό τον τρόπο, ο χρήστης βλέπει ανά πάσα στιγμή τις μετρήσεις που τον ενδιαϕέρουν, αλλά και ταυτόγχρονα παρακολουθεί την ισχύ του δικτύου στα διάϕορα βάθη,στα οποία εμβυθίζονται οι μικροεπεξεργαστές που ϕέρουν τους αισθητήρες. Απώτερος στόχος της εργασίας είναι η εξοικείωση του αναγνώστη με το αντικείμενο των ασύρματων δικτύων υποβρύχιων αισθητήρων και η ανάδειξη της χρησιμότητάς τους μέσω των πολυάριθμων εϕαρμογών τους. Τα πειράματα που πραγματοποιήθηκαν έδωσαν ένα αριθμό κριτηρίων για την διαπίστωση της ισχύος των ηλεκτρομαγνητικών κυμάτων στο νερό και τελευταίο και μη αμελητέο η εϕαρμογή που δημιουργήθηκε αποτελεί μία σημαντική λύση στο πρόβλημα ανίχνευσης της στάθμης των λυμάτων σε μία δεξαμενή γεμισμένη με νερό και λύματα, ουσίες οι οποίες πρέπει να διαχωριστούν στην συνέχεια. Στα πλαίσια της διπλωματικής εργασίας, έγινε λεπτομερής μελέτη της λειτουργίας του Υδροηλεκτρικού Σταθμού του Γλαύκου στην περιοχή της Αχαίας και των αναγκών του σταθμού, όπου και στο τέλος προτάθηκαν λύσεις για την βελτίωση και διευκόλυνση της ετήσιας πραγματοποίησης μετρήσεων πάνω στην ποιότητα του αρδεύσιμου νερού, χρησιμοποιώντας τον αγορασθέντα εξοπλισμό. / The object of this thesis is to create an underwater wireless sensor network for the embodiment of the level measurement of a tank filled with water and wastewater. A search in literature was conducted on the topic of underwater wireless sensor network, in order to further purchase the appropriate equipment to perform the experiments. Using the integrated equipment kit EK010-JN5148, a network was created between a coordinator device, a router device and various terminals. The router and terminal devices operate temperature measurements in the aquatic environment, while the router has the additional role to transfer the gathered information to the coordinator, who is placed outside the aquatic environment. Afterwards, the coordinator illustrates the data packets on the LCD screen for the user to see. The advantage of the network utilization is that the user can benefit from the update of the information and choose the way to depict them and concurrently monitor the power of the network in various depths. The ultimate goal of this paper is to familiarize the reader with the object of underwater wireless sensor networks highlighting their usefulness through numerous applications. The experiments that were carried out provide criteria to determine the effect of the electromagnetic waves in water. Finally, through coding in language C, an application was created to serve as a solution to the problem of detecting the level of water waste in an industrial tank and give necessary information to facilitate its separation later in the process. During the thesis, a detailed study was made on the operation of a hydroelectric power plant in Glavkos in the region of Achaea, Greece. Solutions including the use of the kit EK010-JN5148 were proposed in order to enhance and facilitate the annual measurements on the quality of the irrigable water.

An Opportunistic Large Array (OLA) is a form of cooperative diversity in which a large group of simple, inexpensive relays operate without any mutual coordination, but naturally fire together in response to the energy received from a single source or another OLA. The main contributions of this thesis are the introduction of two OLA-based routing protocols: OLA Concentric Routing Algorithm (OLACRA), which is an upstream routing algorithm suitable for static wireless sensor networks (WSNs), and OLA Routing On-Demand (OLAROAD), which is a robust reactive routing scheme suitable for mobile ad hoc networks (MANETs). In fixed multi-hop wireless sensor networks with a single sink, where energy conservation is often a concern, simulations of the new algorithms show as much as 80% of the transmit energy required to broadcast data can be saved, relative to existing OLA-based broadcasting approaches. In MANETs, where robustness of the routes is an important performance indicator, OLAROAD-based cooperative routes last much longer compared to their state-of-art multi-hop non-cooperative transmission (CT)-based counterparts. However, OLACRA and OLAROAD have higher node participation, and thereby lower throughput, in comparison with the non-CT schemes. To improve the throughput, and thereby bandwidth utilization, the properties of uplink OLAs and their suppression regions are carefully studied. Based on the observations, Hop-Optimized OLACRA (HOLA), which is a variant of OLACRA, and has the maximum bandwidth utilization amongst all the OLA unicast schemes studied, is proposed. HOLA routes have bandwidth utilization comparable to non-CT schemes, but a much lower (~10 dB less) transmit power per node. The last section of this thesis treats the MAC design for OLA-based networks. In contrast to non-CT networks, a 802.11-based RTS/CTS MAC scheme is shown to reduce the reliability in OLA unicast schemes. A distributed cluster-head-based MAC scheme for channel reservation and OLA Size Adaptation Mechanism for link repair/maintenance are proposed for OLA-based networks. The performances of these protocols are shown to be comparable to a non-CT multihop scheme using the RTS/CTS/DATA/ACK handshake-based link layer design.

An opportunistic large array (OLA) is a form of cooperative diversity in which a large group of simple, inexpensive relays or forwarding nodes operate without any mutual coordination, but naturally fire together in response to energy received from a single source or another OLA. When used for broadcast, OLAs form concentric rings around the source, and have been shown to use less energy than conventional multi-hop protocols. This simple broadcasting scheme, which is already known, is called Basic OLA. The OLA Concentric Routing Algorithm (OLACRA), which is our contribution, takes advantage of the concentric ring structure of broadcast OLAs to limit flooding on the upstream connection. By limiting the node participation, OLACRA saves over 80% of the energy compared to Basic OLA, without requiring GPS, individual node addressing, or inter-node interaction. This thesis analyzes the performance of OLACRA over 'deterministic channels' where transmissions are on non-faded orthogonal channels and on 'diversity channels' where transmissions are on Rayleigh flat fading limited orthogonal channels. The performance of diversity channels is shown to approach the deterministic channel at moderate orders of diversity. Enhancements to OLACRA to further improve its efficiency by flooding in the initial upstream level and limiting the downlink 'step sizes' are also considered. The protocols are tested using Monte Carlo evaluation.

Master of Science / Department of Computing and Information Sciences / Gurdip Singh / TinyOS is a component based operating system written in nesC programming language. TinyOS provides interfaces and components for common low level abstractions such as packet communication, routing and sensing for node level sensor network application programming. This project aims to provide high level abstractions to users by providing the notion of a virtual node, which represents a set of physical nodes, allowing users to specify global scenarios, and a mechanism to decompose a high level global scenario into local node level scenarios for each of the individual sensor nodes. A global scenario with virtual components, provided by the user, is first converted into a global scenario by eliminating the virtual components from the model by using a mapping information provided the user and replacing these virtual components by their respective physical components. Appropriate algorithm components and the automatically generated adapter components for these algorithm components are then plugged-in to implement inter-node interactions. This global scenario is then converted to the node level local scenarios by introducing the automatically generated proxy components for the remote components and connecting these proxy components using the RMI layer. The Cadena model is modified to include the attribute location for the components to identify the remote components. The make files are then generated for these local scenarios and are ready to be deployed on the physical motes. The framework provides a GUI tool which is used to visualize the data of the sensor network in both simulation and deployment. The framework provides the user with commands that can be issued to the network from the Cadena component model as a set of interfaces to the components and a python script is used to capture this information in an xml file. The Cadena model is modified to include the attribute observable to the interfaces to identify them as the GUI commands. The GUI loads this XML file and the topology file for the actual deployment, can issue commands to the network and displays the results to the user. The GUI tool also enhances the Tossim simulator to model the external effects over the sensor network and to place the motes based on the topology information using the Tython environment.