Using a Grid-Enabled Wireless Sensor Network for Flood Management

Flooding is becoming an increasing problem. As a result there is a need to deploy more sophisticated sensor networks to detect and react to flooding. This paper outlines a demonstration that illustrates our proposed solution to this problem involving embedded wireless hardware, component based middleware and overlay networks

Wireless and Physical Security via Embedded Sensor Networks

Wireless Intrusion Detection Systems (WIDS) monitor 802.11 wireless frames (Layer-2) in an attempt to detect misuse. What distinguishes a WIDS from a traditional Network IDS is the ability to utilize the broadcast nature of the medium to reconstruct the physical location of the offending party, as opposed to its possibly spoofed (MAC addresses) identity in cyber space. Traditional Wireless Network Security Systems are still heavily anchored in the digital plane of "cyber space" and hence cannot be used reliably or effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts, for example by escorting an intruder off the premises based on physical evidence. In this paper, we argue that Embedded Sensor Networks could be used effectively to bridge the gap between digital and physical security planes, and thus could be leveraged to provide reciprocal benefit to surveillance and security tasks on both planes. Toward that end, we present our recent experience integrating wireless networking security services into the SNBENCH (Sensor Network workBench). The SNBENCH provides an extensible framework that enables the rapid development and automated deployment of Sensor Network applications on a shared, embedded sensing and actuation infrastructure. The SNBENCH's extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the SNBENCH framework, while high-level languages and compilers allow novice SN programmers to compose SN service logic, unaware of the lower-level implementation details of tools on which their services rely. In this paper we convey the simplicity of the service composition through concrete examples that illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CIES/CNS 0520166, CNS/ITR 0205294, CISE/ERA RI 0202067

LEE: Light‐Weight Energy‐Efficient encryption algorithm for sensor networks

Data confidentiality in wireless sensor networks is mainly achieved by RC5 and Skipjack encryption algorithms. However, both algorithms have their weaknesses, for example RC5 supports variable-bit rotations, which are computationally expensive operations and Skipjack uses a key length of 80-bits, which is subject to brute force attack. In this paper we introduce a light-weight energy- fficient encryption-algorithm (LEE) for tiny embedded devices, such as sensor network nodes. We present experimental results of LEE under real sensor nodes operating in TinyOS. We also discuss the secrecy of our algorithm by presenting a security analysis of various tests and cryptanalytic attacks

Designing and Implimentation of Spatial IP Address Assignment Scheme for a Wireless Network

Wireless sensor networks are composed of large numbers up to thousands of tiny radio- equipped sensors. Every sensor has a small microprocessor with enough power to allow the sensors to autonomously form networks through which sensor information is gathered. Wireless sensor networks makes it possible to monitor places like nuclear disaster areas or volcano craters without requiring humans to be immediately present. Many wireless sensor network applications cannot be performed in isolation; the sensor network must somehow be connected to monitoring and controlling entities. This research paper investigates a novel approach for connecting sensor networks to existing networks: by using the TCP/IP protocol suite in the sensor network, the sensors can be directly connected to an outside network without the need for special proxy servers or protocol converters. Bringing TCP/IP to wireless sensor networks is a challenging task, however. First, because of their limited physical size and low cost, sensors are severely constrained in terms of memory and processing power. Traditionally, these constraints have been considered too limiting for a sensor to be able to use the TCP/IP protocols. In this research paper, I show that even tiny sensors can communicate using TCP/IP. Second, the harsh communication conditions make TCP/IP perform poorly in terms of both throughput and energy efficiency. With this research paper, I suggest a number of optimizations that are intended to increase the performance of TCP/IP for sensor networks. The results of the work presented in this research paper have a significant impact on the embedded TCP/IP networking community. The software evolves as part of the research paper has become widely known in the community. The software is mentioned in books on embedded systems and networking, is used in academic courses on embedded systems, is the focus of articles in professional magazines, is incorporated in embedded operating systems, and is used in a

Multi-channel wireless sensor networks : protocols, design and evaluation

Pervasive systems, which are described as networked embedded systems integrated with everyday environments, are considered to have the potential to change our daily lives by creating smart surroundings and by their ubiquity, just as the Internet. In the last decade, “Wireless Sensor Networks” have appeared as one of the real-world examples of pervasive systems by combining automated sensing, embedded computing and wireless networking into tiny embedded devices.\ud A wireless sensor network typically comprises a large number of spatially distributed, tiny, battery-operated, embedded sensor devices that are networked to cooperatively collect, process, and deliver data about a phenomenon that is of interest to the users. Traditionally, wireless sensor networks have been used for monitoring applications based on low-rate data collection with low periods of operation. Current wireless sensor networks are considered to support more complex operations ranging from target tracking to health care which require efficient and timely collection of large amounts of data. Considering the low-bandwidth, low-power operation of the radios on the sensor devices, interference and contention over the wireless medium and the energy-efficiency requirements due to the battery-operated devices, fulfilling the mentioned data-collection requirements in complex applications becomes a challenging task. This thesis focuses on the efficient delivery of large amounts of data in bandwidth-limited wireless sensor networks by making use of the multi-channel capability of the sensor radios and by using optimal routing topologies. We start with experimenting the operation of the sensor radios to characterize the behavior of multi-channel communication. We propose a set of algorithms to increase the throughput and timely delivery of the data and analyze the bounds on the data collection capacity of the wireless sensor networks

Adaptive Embedded Roadmaps for Sensor Networks

In this paper, we propose a new approach to wireless sensor network assisted navigation while avoiding moving dangers. Our approach relies on an embedded roadmap in the sensor network that always contains safe paths. The roadmap is adaptive, i.e., it adapts its topology to changing dangers. The mobile robots in the environment uses the roadmap to reach their destinations. We evaluated the performance of embedded roadmap both in simulations using realistic conditions and with real hardware. Our results show that the proposed navigation algorithm is better suited for sensor networks than traditional navigation field based algorithms. Our observations suggest that there are two drawbacks of traditional navigation field based algorithms, (i) increased power consumption, (ii) message congestion that can prevent important danger avoidance messages to be received by the robots. In contrast, our approach significantly reduces the number of messages on the network (up to 160 times in some scenarios) and power consumption while increasing the navigation performance

Development of security in wireless sensor network using IPv6

The Wireless Sensor Networks (WSNs) is one of core technologies expected to become a potential basis of future ever-present networks. WSN consists of multiple low cost sensor nodes, which could either, have a fixed location or randomly deployed that can communicate with each other for monitoring environments, medical systems, home network, industry automation and so on. However, most of the application scenarios require connectivity between WSNs and the Internet. Though WSN is typically not IP-enabled, connection to the IP network makes it easy to monitor sensors everywhere in the world. One of the purposes of the research work is to incorporate the IPv6 with WSNs, where IPv6 offers a larger address space. Therefore each of the sensor nodes will have their own IP address compare to IPv4, which has limited address space.The main objective of this research is to implement security in WSNs. Sensor networks are typically characterized by limited power supplies, low bandwidth, small memory sizes and limited energy. In addition, unlike traditional networks, sensor nodes are often deployed in accessible areas, presenting the added risk of physical attack. This leads to a very demanding environment in providing security. The research proposed XOR encryption algorithm that possesses built-in and enhanced security measure. The encryption and decryption of the payload secure the data's of the packet transfer. Other than that the XOR encryption is meant to realize the real time routing where the packets will be delivered within their end-to-end deadlines.XOR encryption security has been implemented in the 61owpan/IPv6 stack for TinyOS 2.1. TinyOS 2.1 an embedded operating system commonly used in wireless sensor networks. The hardware platforms used in this project, the TelosB motes, the 802.15.4 wireless communication standard and the TinyOS 2.1 operating syste

Optimization Based Self-localization for IoT Wireless Sensor Networks

In this paper we propose an embedded optimization framework for the simultaneous self-localization of all sensors in wireless sensor networks making use of range measurements from ultra-wideband (UWB) signals. Low-power UWB radios, which provide time-of-arrival measurements with decimeter accuracy over large distances, have been increasingly envisioned for realtime localization of IoT devices in GPS-denied environments and large sensor networks. In this work, we therefore explore different non-linear least-squares optimization problems to formulate the localization task based on UWB range measurements. We solve the resulting optimization problems directly using non-linear-programming algorithms that guarantee convergence to locally optimal solutions. This optimization framework allows the consistent comparison of different optimization methods for sensor localization. We propose and demonstrate the best optimization approach for the self-localization of sensors equipped with off-the-shelf microcontrollers using state-of-the-art code generation techniques for the plug-and-play deployment of the optimal localization algorithm. Numerical results indicate that the proposed approach improves localization accuracy and decreases computation times relative to existing iterative methods