The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

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Internet of things: Vision, applications and research challenges

The science and technology of ultracapacitors are reviewed for a number of electrode materials, including carbon, mixed metal oxides, and conducting polymers. More work has been done using microporous carbons than with the other materials and most of the commercially available devices use carbon electrodes and an organic electrolytes. The energy density of these devices is 3¯5 Wh/kg with a power density of 300¯500 W/kg for high efficiency (90¯95%) charge/discharges. Projections of future developments using carbon indicate that energy densities of 10 Wh/kg or higher are likely with power densities of 1¯2 kW/kg. A key problem in the fabrication of these advanced devices is the bonding of the thin electrodes to a current collector such the contact resistance is less than 0.1 cm2. Special attention is given in the paper to comparing the power density characteristics of ultracapacitors and batteries. The comparisons should be made at the same charge/discharge efficiency.

Ultracapacitors: Why, How, and Where is the Technology

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Detection, Estimation, and Modulation Theory

Radio Frequency IDentification (RFID) is intended to supplant legacy (optical) bar code scanning technology found in many logistic and retail applications. RFID is distinguished by inexpensive, low power and compact form factor tags, whose longevity and efficacy are predicated on using passive communication techniques and on-tag power harvesting. Such tags employ backscatter modulation, which does not require any active RF components. As a result, backscatter has become an attractive design choice for short-range communications in power constrained wireless sensor networking scenarios. The purpose of this work is two-fold. First, it aims to expose backscatter communication as an emerging topic to a communication systems-theoretic audience. Since backscatter modulation and on-tag power harvesting efficiency are coupled, it is necessary to re-examine notions of power and spectral efficiency from an energy-constraint perspective; this leads to novel coded modulation schemes for future RFID systems. Further, we investigate RFID MIMO systems where the channel fading encountered has different statistics than the classical Rayleigh fading model. In turn,the trade off between diversity order and spatial multiplexing gains are distinct from wide-area MIMO.

— Invited Paper — Backscatter Communication and RFID: Coding, Energy, and MIMO Analysis

Fundamentals of statistical signal processing: Estimation theory: by Steven M. KAY; Prentice Hall signal processing series; Prentice Hall; Englewood Cliffs, NJ, USA; 1993; xii + 595 pp.; $65; ISBN: 0-13-345711-7

The primary challenge in wireless sensor network deployment is the limited network lifetime due to finite-capacity batteries. Hence, the vast majority of research efforts thus far have focused on the development of energy-efficient communication and computing mechanisms for WSNs. In this article a fundamentally different approach and hence completely new WSN paradigm, the wireless passive sensor network, is introduced. The objective of the WPSN is to eliminate the limitation on system lifetime of the WSN. In a WPSN power is externally supplied to the sensor network node via an external RF source. Modulated backscattering is discussed as an alternative communication scheme for WPSNs. The feasibility is investigated along with the open research challenges for reliable communication and networking in WPSNs.

Wireless passive sensor networks

Symbol spaced blind channel estimation methods are presented which can essentially use the results of any existing blind equalization method to provide a blind channel estimate of the channel. Blind equalizer's task is reduced to only phase equalization (or identification) as the channel autocorrelation is used to obtain the amplitude response of the channel. Hence, when coupled with simple algorithms such as the constant modulus algorithm (CMA) these methods at baud rate processing provide alternatives to blind channel estimation algorithms that use explicit higher order statistics (HOS) or second-order statistics (subspace) based fractionally-spaced/multichannel algorithms. The proposed methods use finite impulse response (FIR) filter linear receiver equalizer or matched filter receiver based infinite impulse response+FIR linear cascade equalizer configurations to obtain blind channel estimates. It is shown that the utilization of channel autocorrelation information together with blind phase identification of the CMA is very effective to obtain blind channel estimation. The idea of combining estimated channel autocorrelation with blind phase estimation can further be extended to improve the HOS based blind channel estimators in a way that the quality of estimates are improved.

Blind channel estimation via combining autocorrelation and blind phase estimation

In Wireless Sensor Actor Networks (WSAN), sensor nodes perform the sensing task and actor nodes take action based on the sensed phenomena in the field. To ensure efficient and accurate operations of WSAN, new communication protocols are imperative to provide sensoractor coordination in order to achieve energy-efficient and reliable communication. Moreover, the protocols must honor the application-specific real-time delay bounds for the effectiveness of the actors in WSAN. In this paper, we propose a new real-time coordination and routing (RCR) framework for WSAN. It addresses the issues of coordination among sensors and actors and honors the delay bound for routing in distributed manner. RCR configures sensors to form hierarchical clusters and provides delay-constrained energy aware routing (DEAR) mechanism. It uses only cluster-heads to coordinate with sink/actors in order to save the precious energy resources. The DEAR algorithm integrates the forwardtracking and backtracking routing approaches to establish paths from source nodes to sink/actors. In the presence of the sink in WSAN, it implements the centralized version of DEAR (C-DEAR) to coordinate with the actors through the sink. In the absence of sink or ignoring its presence, there is a distributed DEAR (D-DEAR) to provide coordination among sensors and actors. Cluster-heads then select the path among multiple alternative paths to deliver the packets to the actors within the given delay bound in an efficient way. Simulation experiments prove that RCR achieves the goal to honor the realistic application-specific delay bound.

Real-time coordination and routing in wireless sensor and actor networks

In Wireless Sensor Actor Networks (WSAN), sensor nodes perform the sensing task and actor nodes take action based on the sensed phenomena in the field. To ensure efficient and accurate operations of WSAN, new communication protocols are imperative to provide sensor-actor coordination in order to achieve energy-efficient and reliable communication. Moreover, the protocols must honor the application-specific real-time delay bounds for the effectiveness of the actors in WSAN.

In this paper, we propose a new real-time coordination and routing (RCR) framework for WSAN. It addresses the issues of coordination among sensors and actors and honors the delay bound for routing in distributed manner. RCR configures sensors to form hierarchical clusters and provides delay-constrained energy aware routing (DEAR) mechanism. It uses only cluster-heads to coordinate with sink/actors in order to save the precious energy resources. The DEAR algorithm integrates the forwardtracking and backtracking routing approaches to establish paths from source nodes to sink/actors. In the presence of the sink in WSAN, it implements the centralized version of DEAR (C-DEAR) to coordinate with the actors through the sink. In the absence of sink or ignoring its presence, there is a distributed DEAR (D-DEAR) to provide coordination among sensors and actors. Cluster-heads then select the path among multiple alternative paths to deliver the packets to the actors within the given delay bound in an efficient way. Simulation experiments prove that RCR achieves the goal to honor the realistic application-specific delay bound.

/pdf/real-time-coordination-and-routing-in-wireless-sensor-and-59vk4vap8l.pdf

Buyurman Baykal

Papers

Wireless passive sensor networks

Blind channel estimation via combining autocorrelation and blind phase estimation

Real-time coordination and routing in wireless sensor and actor networks

Real-Time coordination and routing in wireless sensor and actor networks

Complexity reduction in radial basis function (RBF) networks by using radial B-spline functions