Power Aware Routing in Mobile Ad Hoc Networks

Wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. The way these data are manipulated by the sensor nodes is a fundamental issue. Information fusion arises as a response to process data gathered by sensor nodes and benefits from their processing capability. By exploiting the synergy among the available data, information fusion techniques can reduce the amount of data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. In this work, we survey the current state-of-the-art of information fusion by presenting the known methods, algorithms, architectures, and models of information fusion, and discuss their applicability in the context of wireless sensor networks.

https://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Fall%202012/Literature/InformationFusionInSensorNetworks.pdf

Information fusion for wireless sensor networks: Methods, models, and classifications

Review: Coverage and connectivity issues in wireless sensor networks: A survey

Sensor networks, which consist of sensor nodes each capable of sensing environment and transmitting data, have lots of applications in battlefield surveillance, environmental monitoring, industrial diagnostics, etc. Coverage which is one of the most important performance metrics for sensor networks reflects how well a sensor field is monitored. Individual sensor coverage models are dependent on the sensing functions of different types of sensors, while network-wide sensing coverage is a collective performance measure for geographically distributed sensor nodes. This article surveys research progress made to address various coverage problems in sensor networks. We first provide discussions on sensor coverage models and design issues. The coverage problems in sensor networks can be classified into three categories according to the subject to be covered. We state the basic coverage problems in each category, and review representative solution approaches in the literature. We also provide comments and discussions on some extensions and variants of these basic coverage problems.

Coverage problems in sensor networks: A survey

Millimeter-wave (mmWave) radar is widely used in vehicles for applications such as adaptive cruise control and collision avoidance. In this paper, we propose an IEEE 802.11ad-based radar for long-range radar (LRR) applications at the 60 GHz unlicensed band. We exploit the preamble of a single-carrier physical layer frame, which consists of Golay complementary sequences with good correlation properties that make it suitable for radar. This system enables a joint waveform for automotive radar and a potential mmWave vehicular communication system based on the mmWave consumer wireless local area network standard, allowing hardware reuse. To formulate an integrated framework of vehicle-to-vehicle communication and LRR, we make typical assumptions for LRR applications, incorporating the full duplex radar operation. This new feature is motivated by the recent development of systems with sufficient isolation and self-interference cancellation. We develop single- and multi-frame radar receiver algorithms for target detection as well as range and velocity estimation for both single- and multi-target scenarios. Our proposed radar processing algorithms leverage channel estimation and time–frequency synchronization techniques used in a conventional IEEE 802.11ad receiver with minimal modifications. Analysis and simulations show that in a single-target scenario, a gigabits-per-second data rate is achieved simultaneously with cm-level range accuracy and cm/s-level velocity accuracy. The target vehicle is detected with a high probability (above 99.99 $\%$ ) at a low false alarm rate of 10 $^{-6}$ for an equivalent isotropically radiated power of 40 dBm up to a vehicle separation distance of about 200 m. The proposed IEEE 802.11ad-based radar meets the minimum accuracy/resolution requirement of range and velocity estimates for LRR applications.

IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System

60 GHz technology holds tremendous potential to upgrade wireless link throughput to Gbps level. To overcome inherent vulnerability to attenuation, 60 GHz radios communicate by forming highly-directional electronically-steerable beams. Standards like IEEE 802.11ad have tailored MAC/PHY protocols to such flexible-beam 60 GHz networks. However, lack of a reconfigurable platform has thwarted a realistic proof-of-concept evaluation. In this paper, we conduct an in-depth measurement of indoor 60 GHz networks using a first-of-its-kind software-radio platform. Our measurement focuses on the link-level behavior with three major perspectives: (i) coverage and bit-rate of a single link, and implications for 60 GHz MIMO; (ii) impact of beam-steering on network performance, particularly under human blockage and device mobility; (iii) spatial reuse between flexible beams. Our study dispels some common myths, and reveals key challenges in maintaining robust flexible-beam connection. We propose new principles that can tackle such challenges based on unique properties of 60 GHz channel and cognitive capability of 60 GHz links.

60 GHz Indoor Networking through Flexible Beams: A Link-Level Profiling

Due to high directionality and small wavelengths, 60 GHz links are highly vulnerable to human blockage. To overcome blockage, 60 GHz radios can use a phased-array antenna to search for and switch to unblocked beam directions. However, these techniques are reactive, and only trigger after the blockage has occurred, and hence, they take time to recover the link. In this paper, we propose BeamSpy, that can instantaneously predict the quality of 60 GHz beams, even under blockage, without the costly beam searching. BeamSpy captures unique spatial and blockage-invariant correlation among beams through a novel prediction model, exploiting which we can immediately select the best alternative beam direction whenever the current beam's quality degrades. We apply BeamSpy to a run-time fast beam adaptation protocol, and a blockage-risk assessment scheme that can guide blockage-resilient link deployment. Our experiments on a reconfigurable 60 GHz platform demonstrate the effectiveness of BeamSpy's prediction framework, and its usefulness in enabling robust 60 GHz links.

/pdf/beamspy-enabling-robust-60-ghz-links-under-blockage-59whaehphx.pdf

BeamSpy: enabling robust 60 GHz links under blockage

This paper investigates data-adaptive path planning schemes for wireless networks of mobile sensor platforms. We focus on applications of environmental monitoring, in which the goal is to reconstruct a spatial map of environmental factors of interest. Traditional sampling theory deals with data collection processes that are completely independent of the target map to be estimated, aside from possible a priori specifications reflective of assumed properties of the target. We refer to such processes as passive learning methods. Alternatively, one can envision sequential, adaptive data collection procedures that use information gleaned from previous observations to guide the process. We refer to such feedback-driven processes as active learning methods. Active learning is naturally suited to mobile path planning, in which previous samples are used to guide the motion of the mobiles for further sampling. This paper presents some of the most encouraging theoretical results to date that support the effectiveness of active over passive learning, and focuses on new results regarding the capabilities of active learning methods for mobile sensing. Tradeoffs between latency, path lengths, and accuracy are carefully assessed using our theory. Adaptive path planning methods are developed to guide mobiles in order to focus attention in interesting regions of the sensing domain, thus conducting spatial surveys much more rapidly while maintaining the accuracy of the estimated map. The theory and methods are illustrated in the application of water current mapping in a freshwater lake.

/pdf/active-learning-for-adaptive-mobile-sensing-networks-34zwm3fj1g.pdf

Active learning for adaptive mobile sensing networks

A medium access control (MAC) protocol for ad hoc networks of nodes with antenna arrays is presented. The antenna array is used for transmit and receive beamforming with the purpose of increasing spatial reuse by directing nulls at active transmitters and receivers in the neighborhood. In contrast to previous work with directional antennas, our approach is applicable to flat fading multipath channels, such as in indoor or in other rich scattering environments. The MAC protocol is designed to support the control information exchange needed to direct nulls toward other users involved in existing communication sessions. Knowledge of the channel coefficients between a transmitter or receiver and its neighbors is used to design transmit or receive beamformer weights that implement the requisite nulling. Simulations are used to demonstrate the improvements in throughput and transmit powers that are obtained in this approach relative to the conventional IEEE 802.11 MAC protocol.

NULLHOC : a MAC protocol for adaptive antenna array based wireless ad hoc networks in multipath environments

Sensor networks possess the inherent potential to detect the presence of a target in a monitored region. Although a stationary sensor network is often adequate to meet application requirements, it is not suited to many situations, for example, a huge number of nodes are required to monitor a large region. In such situations, mobile sensor networks can be used to resolve the communication and sensing coverage problems. This paper addresses the problem of detecting a target using mobile sensor networks. One of the fundamental issues in target detection problems is exposure, which measures how the region is covered by the sensor network. While traditional studies focus on stationary sensor networks, this paper formally defines and evaluates exposure in mobile sensor networks with the presence of obstacles and noise. To conform with practical situations, detection is conducted without presuming the target's activities and moving directions. As there is no fixed layout of node positions, a time expansion technique is developed to evaluate exposure. Since determining exposure can be computationally expensive, algorithms to calculate the upper and lower bounds on exposure are developed. Simulation results are also presented to illustrate the effectiveness of the algorithms

Parmesh Ramanathan

Papers

60 GHz Indoor Networking through Flexible Beams: A Link-Level Profiling

BeamSpy: enabling robust 60 GHz links under blockage

Active learning for adaptive mobile sensing networks

NULLHOC : a MAC protocol for adaptive antenna array based wireless ad hoc networks in multipath environments

Exposure for collaborative detection using mobile sensor networks