Sensor networks

In the past few years, the development of complex dynamical networks or systems has stimulated great interest in the study of the principles and mechanisms underlying the Internet of things (IoT). IoT is envisioned as an intelligent network infrastructure with a vast number of ubiquitous smart devices present in diverse application domains and have already improved many aspects of daily life. Many overtly futuristic IoT applications acquire data gathered via distributed sensors that can be uniquely identified, localized, and communicated with, i.e., the support of sensor networks. Soft-sensing models are in demand to support IoT applications to achieve the maximal exploitation of transforming the information of measurements into more useful knowledge, which plays essential roles in condition monitoring, quality prediction, smooth control, and many other essential aspects of complex dynamical systems. This in turn calls for innovative soft-sensing models that account for scalability, heterogeneity, adaptivity, and robustness to unpredictable uncertainties. The advent of big data, the advantages of ever-evolving deep learning (DL) techniques (where models use multiple layers to extract multi-levels of feature representations progressively), as well as ever-increasing processing power in hardware, has triggered a proliferation of research that applies DL to soft-sensing models. However, many critical questions need to be further investigated in the deep learning-based soft-sensing.

In recent years, advances in wireless technologies have enabled novel applications for wireless devices. Sensor network is one such application that consists of large number of battery-operated nodes. To simulate such networks with large number of nodes, a wireless sensor network simulator that is highly scalable is vital. JiST/SWANS is one such simulator that is highly scalable. However, the JiST/SWANS MAC layer implementation of 802.11b is not suitable for sensor networks, which are energy-constrained. Hence, our main focus is to implement the S-MAC protocol in JiST/SWANS. The S-MAC protocol allows the nodes to go to sleep and thereby it helps conserve energy. This subsequently helps the nodes to extend their effective lifetime. We validate our S-MAC protocol implementation in the JiST/SWANS through simulations.

We consider a heterogeneous wireless sensor network, which has several supernodes for data relay and a large number of energy-constrained sensor nodes that are deployed randomly to cover certain targets. Since targets are covered by many sensors, we create several cover sets that are active successively to save power. We introduce the Heterogeneous Connected Set Covers (HCSC) which aims to find at least one cover set that covers all the targets and is connected to a data-relaying supernode. A sensor node can participate in different set covers but the sum of energy spent in all sets is constrained by the initial energy resources of that sensor node. This is the first solution proposed for the target coverage in heterogeneous wireless sensor networks. We show that the HCSC is an NP-Complete problem and propose three distributed algorithms for it and showing simulation results to verify the proposed approaches.

This thesis considers two important issues in wireless networks. In first part, we address Energy-Efficient Range Assignment in Heterogeneous Wireless Sensor Networks (HRA) and in second part, we present a survey on security attacks in ad hoc wireless networks. We address the HRA problem by selecting the transmission range for each energy-constraint sensor node such that a multi-hop communication path exists between each sensor' node and a resource-rich supernode while maximum power required is minimized. This is the first work to address this problem. We propose several solutions: an Integer Programming approach, a distributed greedy protocol, and a minimum spanning tree protocol based on clustering. In second part of this thesis, a survey is carried out on security attacks on routing protocols in ad hoc wireless network. We examine and classify major routing attacks and present a comprehensive survey on the state-of-the-art mechanisms and solutions designed to defeat such attacks.

Wireless sensor networks are one of the first real world examples of pervasive computing, the notion that small, smart, and cheap sensing and computing devices will eventually permeate the environment. Sensor networks consist of very large number of energy constrained nodes and to properly evaluate these networks a scalable ad-hoc wireless network simulator with an energy model is needed. Since most of the existing simulators have been designed for ad-hoc network with low scalability they can not be used to accurately simulate sensor networks. The JiST/SWANS simulator is one of the newer simulators that has been developed by Cornell University for simulating ad-hoc networks and is highly scalable which makes it appropriate for use in evaluating sensor networks. Since this simulator lack energy model our objective is to design and implement an energy model for JiST/SWANS so that it can adequately and accurately calculate the amount of energy consumption in the simulation of sensor networks.

Energy consumption is a critical design issue in Wireless Sensor Networks (WSNs), since sensor nodes are battery operated, and replacing or recharging the battery is usually infeasible. Energy efficient solutions are sought at all network levels, especially at the medium access level. The IEEE 802.11 MAC protocol is optimized for Ad hoc Wireless Networks, but cannot be adopted for WSNs because it has the idle listening problem, which is a major source of energy waste. Several Medium Access Control (MAC) protocols have been proposed for WSNs to save the transceiver energy by introducing periodic listen/sleep cycles, and thus overcome the idle listing problem. The periodic listen sleep cycles, however, will increase the network latency and require extra overhead to establish and maintain synchronization among nodes in the network. This dissertation introduces a new MAC protocol for WSNs based on the SMAC protocol to improve its latency performance without compromising its energy consumption. The original SMAC provides an efficient solution for the energy consumption problem due to idle listening, but it increases latency especially in low duty cycle applications. TMAC was proposed to further reduce the energy consumption in SMAC and introduced the Forward Request-To-Send (FRTS) packet to solve the early sleep problem observed in TMAC. Later, Adaptive SMAC was proposed to reduce the latency problem in SMAC by at least 50% at light traffic load. Our new protocol, FASMAC, combines the advantages of both adaptive listening and the usage of FRTS packet in TMAC to further reduce the latency of SMAC. In FASMAC, a packet can travel at least three hops away from its source node within one time cycle. This results in at least 67% reduction in latency at light traffic when compared with the original SMAC. We also propose an energy model for performance evaluation of WSNs protocols using the network simulator NS2. The current energy model of NS2 was designed to handle Ad hoc Wireless Networks where the low power consumption sleep mode was not an issue. However, this is not the case in WSNs. We show that NS2 energy model is not suitable to evaluate the performance of WSNs protocols because it does not account for the low power sleep mode. This dissertation proposes a solution to this deficiency and provides simulation results that match real experimental results performed on the actual sensor motes.

Wireless ad hoc networks are infrastructure-less multi-hop networks consisting of mobile (such as in mobile ad hoc networks) or stationary (such as in wireless sensor networks) wireless devices. These networks involve several challenges, including limited bandwidth and energy resources, frequent topology changes, and a lack of central control. Local acting, self-organizing, and self-healing algorithms (also called localized algorithms) are essential to the design of wireless ad hoc networks. A connected dominating set (CDS) is frequently used in wireless ad hoc networks as a virtual backbone to support efficient routing, service discovery, and area monitoring. In addition, efficient broadcasting (i.e., finding a small set of forward nodes to ensure full delivery) can be viewed as forming a CDS on-the-fly. The periodically maintained virtual backbone is called a static CDS, and the temporarily formed forward node set is called a dynamic CDS. For efficiency and robustness, the ideal CDS construction algorithm is lightweight, has fast convergence, and minimizes the CDS size. This dissertation focuses on providing a generic framework to unify localized CDS construction schemes, including both static and dynamic CDS constructions, for wireless ad hoc networks. The goal is to provide insights on how to form a small CDS (forward node set) in dynamic networks with affordable overhead and high robustness. A classification of CDS construction algorithms for wireless ad hoc networks has been provided at the beginning. An efficient scheme, called Rule K, has been proposed for static CDS construction. Rule K achieves a probabilistic constant upper bound on the expected CDS size, which is currently the best known performance guarantee for localized CDS algorithms. Rule K has been extended to a unified framework, called the coverage condition, which contains most existing localized virtual backbone construction and efficient broadcast algorithms as its special cases. The coverage condition has been further extended to construct a k-connected k-dominating set for higher robustness, and integrated in an iterative process that further reduces the CDS size while maintaining the same level of robustness.

This dissertation presents the results of research that led to the development of a novel reputation and trust-based monitoring paradigm for secure and reliable computing in Wireless Sensor Networks (WSNs). WSNs have undergone tremendous technological advances over the last few years. They have caused a giant leap toward "proactive computing," a paradigm where computers anticipate human needs and, when necessary, act on their behalf. Therefore, we cannot deploy such a critical technology without first addressing the security and privacy challenges to ensure that it does not turn against those whom it is meant to benefit. The core application of WSNs is to detect and report events, be it military or civilian applications. The building blocks of a WSN are small, battery-powered, lowcost, self-contained devices called "sensors" that measure factors like light, temperature, pressure, vibration, motion, etc. A WSN usually consists of hundreds of thousands of sensors that operate in unattended, hostile territories to monitor a given geographical area. Once deployed, the wireless sensors self-organize into ad-hoc wireless networks in order to cope with the dynamics of the surveillance field. During the post deployment phase, the wireless sensors aggregate data, then process and generate a report, which is subsequently relayed from one sensor to the next using secure multi-hop routing until the data reaches its desired destination, which is usually the sink. Since sensors operate in unattended and hostile territories, the adversary can capture a sensor node physically and extract all the information stored onboard, including cryptographic keying material. With this unique situation, WSNs are subject to a unique attack referred to as an "Insider Attack," in which the adversary becomes a legitimate member of the network being represented by the captured node.

This research addresses communication security in the highly constrained wireless sensor environment. The goal of the research is twofold: (1) to develop a key management scheme that provides these constrained systems with the basic security requirements and evaluate its effectiveness in terms of scalability, efficiency, resiliency, connectivity, and flexibility, and (2) to implement this scheme on an appropriate routing platform and measure its efficiency.

The ZigBee standard is a wireless networking standard created and maintained by the ZigBee Alliance. The standard aims to provide an inexpensive, reliable, and efficient solution for wirelessly networked sensing and control products. The ZigBee Alliance is composed of over 300 member companies making use of the standard in different ways, ranging from energy management and efficiency, to RF remote controls, to health care products. Home automation is one market that greatly benefits from the use of ZigBee. With a focus on conserving home electricity use, a sample design is created to test a home automation network using Freescale's ZigBee platform. Multiple electrical designs are tested utilizing sensors ranging from proximity sensors to current sense transformers. Software is fashioned as well, creating a PC application that interacts with two ZigBee transceiver boards performing different home automation functions such as air conditioner and automatic lighting control.