Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

Survey of Wireless Indoor Positioning Techniques and Systems

On robust estimation of the location parameter

Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. This paper surveys recent routing protocols for sensor networks and presents a classification for the various approaches pursued. The three main categories explored in this paper are data-centric, hierarchical and location-based. Each routing protocol is described and discussed under the appropriate category. Moreover, protocols using contemporary methodologies such as network flow and quality of service modeling are also discussed. The paper concludes with open research issues. � 2003 Elsevier B.V. All rights reserved.

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A survey on routing protocols for wireless sensor networks

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of applications. In cooperative localization, sensors work together in a peer-to-peer manner to make measurements and then forms a map of the network. Various application requirements influence the design of sensor localization systems. In this article, the authors describe the measurement-based statistical models useful to describe time-of-arrival (TOA), angle-of-arrival (AOA), and received-signal-strength (RSS) measurements in wireless sensor networks. Wideband and ultra-wideband (UWB) measurements, and RF and acoustic media are also discussed. Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements. The article briefly surveys a large and growing body of sensor localization algorithms. This article is intended to emphasize the basic statistical signal processing background necessary to understand the state-of-the-art and to make progress in the new and largely open areas of sensor network localization research.

Locating the nodes: cooperative localization in wireless sensor networks

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

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Context Aware Computing for The Internet of Things: A Survey

To control congestion, either the traffic from sources should be "reduced" (traffic controlling) or the available resources should be "increased" (resource controlling). Compared to the wired and other wireless counterparts, wireless sensor networks usually have elastic resource availability, and the applications require a certain level of throughput called fidelity. As a result, resource control strategies cannot only alleviate congestion but also ensure the required fidelity level during congestion by accommodating higher incoming traffic. In this paper, we first attempt to formally define the resource control framework that adjusts the resource provisioning at the hotspot nodes during congestion. In an effort to find the optimal resource control under the fidelity and energy constraints, we present a resource increase and decrease algorithm called Early Increase/Early Decrease (EIED) that tries to adjust the effective channel capacity quickly to suit the incoming traffic volume in an energy-efficient manner, thereby increasing the fidelity level observed by the application. Under the energy-constrained optimization, we prove this algorithm incurs the lowest overhead of energy consumption for the given fidelity level that is required by the application. We also prove that the EIED algorithm performed in a distributed manner also lowers the energy consumption per packet at an end-to-end level. The effectiveness of the EIED algorithm is verified by simulations based on realistic sensor network configurations.

/pdf/an-optimal-resource-control-scheme-under-fidelity-and-energy-3rd1c8xmr0.pdf

An optimal resource control scheme under fidelity and energy constraints in sensor networks

Wireless sensor networks are being envisioned for various civil, military and environmental monitoring applications. Since they are highly resource constrained, algorithms and protocols are designed to minimize resources. Minimizing the resources consumed for different protocols usually leads to degradation in the performance provided in terms of the application requirements. For mission critical applications, we sometimes need to provide guarantees even at the cost of extra overhead. Thus, efficient and intelligent use of resources rather than minimization of resource consumption should be the major focus in sensor network research. This is the primary theme of this thesis. We divide different protocols under two major categories, namely sensor data dissemination and network management and propose adaptive algorithms with the aim of maximizing resource utilization in sensor networks. 
For the data dissemination problem, we show that providing different levels of assurances (reliability, latency etc.) in data delivery based on the information content in the sensed data is critical for proper utilization of resources. For the network management problem we consider two important functions: network state retrieval and topology control. We show that retrieving the network state at different levels of resolution and adaptively controlling the topology based on the current network conditions, application characteristics leads to a more prudent approach while conserving resources. I.e. we shift the algorithm design paradigm from an unconstrained optimization problem (the fixed schemes which aggressively minimize resource consumption) to optimization under application constraints. We propose adaptive algorithms for both the data dissemination and the network management problems which exploit the fundamental tradeoffs between resource consumption and protocol performance. The algorithms are not only more efficient in the resources they consume, but more importantly are also aware of the requirements of the applications they are designed for.

Algorithms for resource utilization in sensor networks

Traffic congestion has become a part of daily life of most of us. One possible way of preventing congestion from building up is by disseminating traffic information. Today a number of commercial solutions exist for disseminating traffic information (e.g., Traffic.com, Metrocommute, EtakTraffic). However, these solutions are plagued by prohibitive deployment and maintenance cost that prevents widespread deployment. As a result, these solutions cover select highways while leaving out major fractions of the highways. In this paper we present our vision of a low cost, highly scalable zero-infrastructure system for collecting and disseminating information about traffic conditions. Our goal is to devise a system that can cover the entire road network of the US. We describe the proposed architecture for the system, and evaluate it using a micro-traffic simulator and a calibrated model of the South Jersey transportation network.

Poster abstract: sensors on wheels -- towards a zero-infrastructure solution for intelligent transportation systems

It is an inherently challenging task to provide quality of service (QoS) to real time applications in cellular networks owing to their mobility-induced uncertainties. Here we consider an adaptive framework where services may undergo bandwidth degradation. In contrast to the existing schemes, we here provide a reservation states based approach to provision the QoS to the individual adaptive applications. By using information related to users' mobility, the proposed approach can assure probabilistic QoS to multiple level of degradation as maybe required by such adaptive services. Simulation results show the effectiveness of the scheme in realizing the target QoS.

QoS provisioning for adaptive services with degradation in cellular network

The present invention is a method and system for sending SIP notification messages to a wireless device, for example a wireless telephone, that can accept SIP control messages. A method is described for establishing a data session between a wireless device and a management server over a wireless network, the wireless device operable to receive and parse SIP messages, the wireless network operable to transmit messages between the wireless device and the management server. The method includes retrieving an address for the wireless device on the management server, sending a SIP invite message from the management server to the wireless device, receiving the SIP invite message on the wireless device, parsing the SIP invite message on the wireless device, and establishing the data session between the wireless device and the management server.

Badri Nath

Papers

An optimal resource control scheme under fidelity and energy constraints in sensor networks

Algorithms for resource utilization in sensor networks

Poster abstract: sensors on wheels -- towards a zero-infrastructure solution for intelligent transportation systems

QoS provisioning for adaptive services with degradation in cellular network

System and method for sending notification message to a mobile station using session initiation protocol (sip)