Scrounger Outbreaks Strenuous Life From Wireless Adhoc Sensor Networks

Network survivability is the ability of a network keeping connected under failures and attacks, which is a fundamental issue to the design and performance evaluation of wireless ad hoc networks. Ad-hoc low power wireless networks are in research in both sensing and pervasive computing. The proposed method discusses about resource depletion attacks at the routing protocol layer, which drains battery power. The motivation of a large portion of research efforts has been to maximize the lifetime of the network, where network lifetime is typically measured from the instant of deployment to the point when one of the nodes has exp¬¬¬anded its limited power source and becomes in-operational – commonly referred as first node failure. A novel approach for routing protocols, affect from attack even those designed to be protected, be short of protection from these attacks, which call Vampire attacks, which permanently disable networks by quickly draining nodes battery power. These energy draining attacks are not specific to any specific protocol which are disturbing, difficult to detect, and are easy to carry out using as few as one malicious insider sending only protocol compliant messages. There are a lot of protocols developed to protect from Denial of Service attack, but it is not completely possible. One such Denial of Service attack is Vampire attack-Draining of node life from wireless ad-hoc sensor networks. This paper presents a method to tolerate the attack by using the Cluster Head. In case of any energy draining attack, the Cluster Head engages in the situation and delivers the packet to destination without dropping the packet. Thus providing a victorious and reliable message delivery even in case of Vampire attack. A novel PLGP method is proposed to mitigate the battery power draining attacks by improving the existing routing protoco

CMOS Image Sensors in Surveillance System Applications

Recent technology advances in CMOS image sensors (CIS) enable their utilization in the most demanding of surveillance fields, especially visual surveillance and intrusion detection in intelligent surveillance systems, aerial surveillance in war zones, Earth environmental surveillance by satellites in space monitoring, agricultural monitoring using wireless sensor networks and internet of things and driver assistance in automotive fields. This paper presents an overview of CMOS image sensor-based surveillance applications over the last decade by tabulating the design characteristics related to image quality such as resolution, frame rate, dynamic range, signal-to-noise ratio, and also processing technology. Different models of CMOS image sensors used in all applications have been surveyed and tabulated for every year and application.https://doi.org/10.3390/s2102048

System support for robust data collection in wireless sensing systems

This dissertation studied how to provide system support for robust data collection in wireless sensing systems through addressing a few urgent design issues in the existing systems. A wireless sensing system may suffer issues arising at the sensors, during the data transmission, and during the data access by applications. Due to the unique characteristics of wireless sensing systems, certain conventional solutions for networked systems may not work well with these issues. We developed approaches to resolve these urgent problems in the design of wireless sensing systems. Specially, we have achieved the following: (1) we developed a resilient trust model to effectively detect faulty data in wireless sensing systems due to either sensor malfunctioning or malicious attempts to report false data; (2) we developed a low-cost, self-contained, accurate localization system for small-sized ground robotic vehicles, which enhances the wireless sensing systems containing mobile sensors by providing more accurate and highly available location data, with only limited overhead in economic cost and management; (3) we designed and implemented a robust trust-aware routing framework to secure multi-hop routing through a set of sensors in wireless sensing systems; (4) we developed a privacy-preserving wireless sensing system, which protects the user privacy while allowing arbitrary third-party applications to extract knowledge from the collected data

Efficient and Secure Network Services in Wireless Sensor Networks.

Wireless sensor networks (WSNs) have been deployed for environment monitoring and surveillance. A message delivery service is one of the most fundamental services for WSNs, thus making its efficiency and effectiveness important. A widely-adopted protocol for message delivery in WSNs is a geographic forward routing (GFR), in which messages are greedily forwarded to their destinations. In this thesis, we develop network services complementary to the existing GFR for efficient and secure message delivery in WSNs. We first develop a distributed location service protocol (DLSP) for message delivery to mobile nodes. Since GFR represents destinations of messages with destinations' geographic locations, the knowledge of location of mobile nodes is necessary to ensure correct message delivery. In DLSP, mobile nodes select some sensor nodes as their location servers, and publish the mobiles' location information to the location servers. Sensor nodes contact those location servers to retrieve the current location of mobile nodes when needed. DLSP provides systematic methods for mobile nodes to select location servers and publish their location to those servers, and for sensor nodes to query mobiles' location. We then design an algorithm called Traverse for hole boundary detection and geographic forward routing with hole avoidance (GFRHA) for efficient message routing. Traverse identifies boundaries of holes, i.e., areas without any functioning sensor node. GFRHA then utilizes the identified hole information to route messages around holes while being forwarded before they encounter holes. This way, the message path lengths, and subsequently the message delay and energy consumption, can be significantly reduced, depending on hole shapes and source and destination locations. We also develop attack-resilient collaborative message authentication (ARCMA) for message delivery. ARCMA is designed to tolerate node-capture attacks, in which attackers obtain valid keys by compromising physically-exposed sensor nodes, and use the keys to generate forged messages. To defend against such attacks, in ARCMA, messages are collaboratively authenticated by a set of sensor nodes rather than by one node. The security of ARCMA does not degrade unless attackers simultaneously compromise more than a certain number of sensor nodes.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64831/1/mgcho_1.pd

Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method

Convergence of Intelligent Data Acquisition and Advanced Computing Systems

This book is a collection of published articles from the Sensors Special Issue on "Convergence of Intelligent Data Acquisition and Advanced Computing Systems". It includes extended versions of the conference contributions from the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2019), Metz, France, as well as external contributions

Double smart energy harvesting system for self-powered industrial IoT

312 p. 335 p. (confidencial)Future factories would be based on the Industry 4.0 paradigm. IndustrialInternet of Things (IIoT) represent a part of the solution in this field. Asautonomous systems, powering challenges could be solved using energy harvestingtechnology. The present thesis work combines two alternatives of energy input andmanagement on a single architecture. A mini-reactor and an indoor photovoltaiccell as energy harvesters and a double power manager with AC/DC and DC/DCconverters controlled by a low power single controller. Furthermore, theaforementioned energy management is improved with artificial intelligencetechniques, which allows a smart and optimal energy management. Besides, theharvested energy is going to be stored in a low power supercapacitor. The workconcludes with the integration of these solutions making IIoT self-powered devices.IK4 Teknike