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.

/pdf/context-aware-computing-for-the-internet-of-things-a-survey-3nibvvc921.pdf

Context Aware Computing for The Internet of Things: A Survey

Intelligent Manufacturing in the Context of Industry 4.0: A Review

Indoor localization has recently witnessed an increase in interest, due to the potential wide range of services it can provide by leveraging Internet of Things (IoT), and ubiquitous connectivity. Different techniques, wireless technologies and mechanisms have been proposed in the literature to provide indoor localization services in order to improve the services provided to the users. However, there is a lack of an up-to-date survey paper that incorporates some of the recently proposed accurate and reliable localization systems. In this paper, we aim to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time of flight (RTOF), and received signal strength (RSS); based on technologies, such as WiFi, radio frequency identification device (RFID), ultra wideband (UWB), Bluetooth, and systems that have been proposed in the literature. This paper primarily discusses localization and positioning of human users and their devices. We highlight the strengths of the existing systems proposed in the literature. In contrast with the existing surveys, we also evaluate different systems from the perspective of energy efficiency, availability, cost, reception range, latency, scalability, and tracking accuracy. Rather than comparing the technologies or techniques, we compare the localization systems and summarize their working principle. We also discuss remaining challenges to accurate indoor localization.

A Survey of Indoor Localization Systems and Technologies

In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.

https://www.mdpi.com/1424-8220/16/5/707/pdf

Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

The complexity of indoor radio propagation has resulted in location-awareness being derived from empirical fingerprinting techniques, where positioning is performed via a previously-constructed radio map, usually of WiFi signals. The recent introduction of the Bluetooth Low Energy (BLE) radio protocol provides new opportunities for indoor location. It supports portable battery-powered beacons that can be easily distributed at low cost, giving it distinct advantages over WiFi. However, its differing use of the radio band brings new challenges too. In this work, we provide a detailed study of BLE fingerprinting using 19 beacons distributed around a $\sim\! 600\ \mbox{m}^2$ testbed to position a consumer device. We demonstrate the high susceptibility of BLE to fast fading, show how to mitigate this, and quantify the true power cost of continuous BLE scanning. We further investigate the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency. We also provide quantitative comparison with WiFi fingerprinting. Our results show advantages to the use of BLE beacons for positioning. For one-shot (push-to-fix) positioning we achieve $30\ \mbox{m}^2$ ), compared to $100\ \mbox{m}^2$ ) and < 8.5 m for an established WiFi network in the same area.

/pdf/location-fingerprinting-with-bluetooth-low-energy-beacons-23u5zgmm8y.pdf

Location Fingerprinting With Bluetooth Low Energy Beacons

Load Balancing is essential for efficient operations indistributed environments. As Cloud Computing is growingrapidly and clients are demanding more services and betterresults, load balancing for the Cloud has become a veryinteresting and important research area. Many algorithms weresuggested to provide efficient mechanisms and algorithms forassigning the client's requests to available Cloud nodes. Theseapproaches aim to enhance the overall performance of the Cloudand provide the user more satisfying and efficient services. Inthis paper, we investigate the different algorithms proposed toresolve the issue of load balancing and task scheduling in CloudComputing. We discuss and compare these algorithms to providean overview of the latest approaches in the field.

A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms

Positioning objects has been an important topic since it is needed to locate people, guide them to a certain place, and assist companies and organizations with their assets management. Several systems and algorithms were proposed to solve the positioning problem and to enhance existing systems. In this paper, we survey various indoor positioning systems to explore the related challenges that exist in this area and evaluate some proposed solutions. We provide a categorization and classification of the current indoor positioning systems and identify some possible areas of enhancements

A survey of indoor positioning systems and algorithms

We present a survey of architectures and applications used in the field of sensor web. The rapidly-increasing and pervasive use of sensors in advanced information technology applications has spawn diverse and fertile research areas. Sensor networks are used in many applications such as health care, traffic control, smart homes, and many other fields in which data are needed to be collected. An area of research that is gaining high importance is the integration of sensor networks with the web to provide various services for different users and applications. In this paper, we present and compare the main architectures and applications of the sensor web. We also provide an analysis of the main issues and challenges that are involved in this important area of research.

http://middleware-tech.net/papers/ICUIMC2012.pdf

Web-based wireless sensor networks: a survey of architectures and applications

Several approaches for fault-tolerance in distributed systems were introduced; however, they require prior knowledge of the environment's operating conditions and/or constant monitoring of these conditions at run time. That allows the applications to adjust the load and redistribute the tasks when failures occur. These techniques work well when there is no high communication delay. Yet, this is not true in the Cloud, where data and computation servers are connected over the Internet and distributed across large geographic areas. Thus they usually exhibit high and dynamic communication delays that make discovering and recovering from failures take a long time. This paper proposes a delay-tolerant fault-tolerance algorithm that effectively reduces execution time and adapts for failures while minimizing the fault discovery and recovery overhead in the Cloud. Distributed tasks that can use this algorithm include downloading data from replicated servers and executing parallel applications on multiple independent distributed servers in the Cloud. The experimental results show the efficiency of the algorithm and its fault tolerance feature.

An Efficient Fault-Tolerant Algorithm for Distributed Cloud Services

Large-scale deployments of Wireless Sensor Networks (WSNs) and the need for efficient optimization of network resources to prolong the life time of such networks opened the door for researchers to find efficient clustering techniques. Clustering has proven to be an effective approach for organizing a large scale network into connected groups which increases the life time and the reliability. In this paper, we highlight the challenges in clustering a large scale WSN, discuss some of clustering protocols, and classify them based on the clusters technique formation and the way that data is aggregated to the base station. We further consider the case of border monitoring and simulate these protocols and compare their performance results using different scenarios.

Klaithem Al Nuaimi

Papers

A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms

A survey of indoor positioning systems and algorithms

Web-based wireless sensor networks: a survey of architectures and applications

An Efficient Fault-Tolerant Algorithm for Distributed Cloud Services

Performance analysis of clustering protocols in WSN