http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

Recent advances in miniaturization and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is critical in sensor networks for diverse purposes including sensor data fusion, coordinated actuation, and power-efficient duty cycling. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals.We present Reference-Broadcast Synchronization, a scheme in which nodes send reference beacons to their neighbors using physical-layer broadcasts. A reference broadcast does not contain an explicit timestamp; instead, receivers use its arrival time as a point of reference for comparing their clocks. In this paper, we use measurements from two wireless implementations to show that removing the sender's nondeterminism from the critical path in this way produces high-precision clock agreement (1.85 ± 1.28μsec, using off-the-shelf 802.11 wireless Ethernet), while using minimal energy. We also describe a novel algorithm that uses this same broadcast property to federate clocks across broadcast domains with a slow decay in precision (3.68 ± 2.57μsec after 4 hops). RBS can be used without external references, forming a precise relative timescale, or can maintain microsecond-level synchronization to an external timescale such as UTC. We show a significant improvement over the Network Time Protocol (NTP) under similar conditions.

/pdf/fine-grained-network-time-synchronization-using-reference-3go0i1u94g.pdf

Fine-grained network time synchronization using reference broadcasts

Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages that are time-stamped using the local clocks on the nodes. Therefore, time synchronization becomes an indispensable piece of infrastructure in such systems. For years, protocols such as NTP have kept the clocks of networked systems in perfect synchrony. However, this new class of networks has a large density of nodes and very limited energy resource at every node; this leads to scalability requirements while limiting the resources that can be used to achieve them. A new approach to time synchronization is needed for sensor networks.In this paper, we present Timing-sync Protocol for Sensor Networks (TPSN) that aims at providing network-wide time synchronization in a sensor network. The algorithm works in two steps. In the first step, a hierarchical structure is established in the network and then a pair wise synchronization is performed along the edges of this structure to establish a global timescale throughout the network. Eventually all nodes in the network synchronize their clocks to a reference node. We implement our algorithm on Berkeley motes and show that it can synchronize a pair of neighboring motes to an average accuracy of less than 20ms. We argue that TPSN roughly gives a 2x better performance as compared to Reference Broadcast Synchronization (RBS) and verify this by implementing RBS on motes. We also show the performance of TPSN over small multihop networks of motes and use simulations to verify its accuracy over large-scale networks. We show that the synchronization accuracy does not degrade significantly with the increase in number of nodes being deployed, making TPSN completely scalable.

/pdf/timing-sync-protocol-for-sensor-networks-53aov77qpj.pdf

Timing-sync protocol for sensor networks

The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern health care with promising technological, economic, and social prospects. This paper surveys advances in IoT-based health care technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the health care perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.

The Internet of Things for Health Care: A Comprehensive Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence

In the recent past, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics. As a consequence, it is becoming increasingly difficult to discuss typical requirements regarding hardware issues and software support. This is particularly problematic in a multidisciplinary research area such as wireless sensor networks, where close collaboration between users, application domain experts, hardware designers, and software developers is needed to implement efficient systems. In this article we discuss the consequences of this fact with regard to the design space of wireless sensor networks by considering its various dimensions. We justify our view by demonstrating that specific existing applications occupy different points in the design space.

/pdf/the-design-space-of-wireless-sensor-networks-2lr8ozcx58.pdf

The design space of wireless sensor networks

Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. Sensor nodes cooperate in order to merge individual sensor readings into a high-level sensing result, such as integrating a time series of position measurements into a velocity estimate. The physical time of sensor readings is a key element in this process called data fusion. Hence, time synchronization is a crucial component of WSNs. We argue that time synchronization schemes developed for traditional networks such as NTP [23] are ill-suited for WSNs and suggest more appropriate approaches.

http://ccr.sigcomm.org/archive/2003/jan03/ccr-2003-1-elson.pdf

Wireless sensor networks: a new regime for time synchronization

Ubiquitous computing environments are typically based upon ad hoc networks of mobile computing devices. These devices may be equipped with sensor hardware to sense the physical environment and may be attached to real world artifacts to form so-called smart things. The data sensed by various smart things can then be combined to derive knowledge about the environment, which in turn enables the smart things to "react" intelligently to their environment. For this so-called sensor fusion, temporal relationships (X happened before Y) and real-time issues (X and Y happended within a certain time interval) play an important role. Thus physical time and clock synchronization are crucial in such environments. However, due to the characteristics of sparse ad hoc networks, classical clock synchronization algorithms are not applicable in this setting. We present a time synchronization scheme that is appropriate for sparse ad hoc networks

/pdf/time-synchronization-in-ad-hoc-networks-1mdjfeneu1.pdf

Time synchronization in ad hoc networks

The developed world is awash with sensors. However, they are typically locked into unimodal closed systems. To unleash their full potential, access to sensors should be opened such that their data and services can be integrated with data and services available in other information systems, facilitating novel applications and services that are based on the state of the real world. We describe our vision and architecture of a Semantic Web of Things: a service infrastructure that makes the deployment and use of semantic applications involving Internet-connected sensors almost as easy as building, searching, and reading a web page today.

SPITFIRE: toward a semantic web of things

Middleware for sensor networks aims to support the development of applications for large populations of wirelessly connected nodes capable of computation, communication, and sensing. We examine the purpose, functionality, and characteristics of such middleware.

/pdf/middleware-challenges-for-wireless-sensor-networks-10d97yxoqe.pdf

Kay Römer

Papers

The design space of wireless sensor networks

Wireless sensor networks: a new regime for time synchronization

Time synchronization in ad hoc networks

SPITFIRE: toward a semantic web of things

Middleware challenges for wireless sensor networks