Distributed networked control systems

Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.

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A survey of network lifetime maximization techniques in wireless sensor networks

Smart world is envisioned as an era in which objects (e.g., watches, mobile phones, computers, cars, buses, and trains) can automatically and intelligently serve people in a collaborative manner. Paving the way for smart world, Internet of Things (IoT) connects everything in the smart world. Motivated by achieving a sustainable smart world, this paper discusses various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT. Particularly, an overview regarding IoT and green IoT is performed first. Then, the hot green information and communications technologies (ICTs) (e.g., green radio-frequency identification, green wireless sensor network, green cloud computing, green machine to machine, and green data center) enabling green IoT are studied, and general green ICT principles are summarized. Furthermore, the latest developments and future vision about sensor cloud, which is a novel paradigm in green IoT, are reviewed and introduced, respectively. Finally, future research directions and open problems about green IoT are presented. Our work targets to be an enlightening and latest guidance for research with respect to green IoT and smart world.

Green Internet of Things for Smart World

RPL is the IPv6 routing protocol for low-power and lossy networks, standardized by IETF in 2012 as RFC6550. Specifically, RPL is designed to be a simple and inter-operable networking protocol for resource-constrained devices in industrial, home, and urban environments, intended to support the vision of the Internet of Things with thousands of devices interconnected through multihop mesh networks. More than four-years have passed since the standardization of RPL, and we believe that it is time to examine and understand its current state. In this paper, we review the history of research efforts in RPL; what aspects have been (and have not been) investigated and evaluated, how they have been studied, what was (and was not) implemented, and what remains for future investigation. We reviewed over 97 RPL-related academic research papers published by major academic publishers and present a topic-oriented survey for these research efforts. Our survey shows that only 40.2% of the papers evaluate RPL through experiments using implementations on real embedded devices, ContikiOS and TinyOS are the two most popular implementations (92.3%), and TelosB was the most frequently used hardware platform (69%) on testbeds that have average and median size of 49.4 and 30.5 nodes, respectively. Furthermore, unfortunately, despite it being approximately four years since its initial standardization, we are yet to see wide adoption of RPL as part of real-world systems and applications. We present our observations on the reasons behind this and suggest directions on which RPL should evolve.

Challenging the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL): A Survey

Automatically configuring network device, network system architecture, and method for configuring one or a plurality of devices on a network. Device and network system architectures and methods for automatically self-initiating and configuring one, a plurality, or hundreds of wired or wireless network devices. Autoconfiguring wireless Local Area Network switch and access point devices connected to the switch. Method for accessing remote server by a device to acquire device configuration information. Method for deploying a network including at least one network device at a facility without the participation of a person having knowledge of networks or network devices at the facility. Computer program and computer program product.

Automated network device configuration and network deployment

There is provided a mesh routing method in beacon-enabled wireless AD-HOC networks that includes: broadcasting, by nodes constituting a wireless AD-HOC network, a beacon message loading neighbor node information on a beacon payload; managing, by a node receiving the broadcasted beacon message, its own neighbor node table by extracting the neighbor node information loaded on the beacon payload; and performing, by a source node attempting to transmit data or commands, mesh routing on the basis of its own neighbor node table.

Mesh routing method and mesh routing apparatus in beacon enabled wireless AD-HOC networks

Provided are a localization apparatus for recognizing a location of a node in a sensor network and a method thereof. The method includes the steps of: a) selecting reference nodes from a plurality of anchor nodes to be used for triangulation; and b) obtaining location information of a target node by performing triangulation using the selected reference node, wherein in the step a), the reference nodes are selected by removing anchor nodes having obstacle factor from a plurality of the anchor nodes where the obstacle factor causes error in a distance measured by the target node.

Localization apparatus for recognizing location of node in sensor network and method thereof

RPL is an IPv6 routing protocol for low-power and lossy networks (LLNs) designed to meet the requirements of a wide range of LLN applications including smart grid AMIs, home and building automation, industrial and environmental monitoring, health care, wireless sensor networks, and the Internet of Things (IoT) in general with thousands and millions of nodes interconnected through multihop mesh networks. RPL constructs tree-like routing topology rooted at an LLN border router (LBR) and supports bidirectional IPv6 communication to and from the mesh devices by providing both upward and downward routing over the routing tree. In this article, we focus on the interoperability of downward routing and supporting its two modes of operations (MOPs) defined in the RPL standard (RFC 6550). Specifically, we show that there exists a serious connectivity problem in RPL protocol when two MOPs are mixed within a single network, even for standard-compliant implementations, which may result in network partitions. To address this problem, this article proposes DualMOP-RPL, an enhanced version of RPL, which supports nodes with different MOPs for downward routing to communicate gracefully in a single RPL network while preserving the high bidirectional data delivery performance. DualMOP-RPL allows multiple overlapping RPL networks in the same geographical regions to cooperate as a single densely connected network even if those networks are using different MOPs. This will not only improve the link qualities and routing performances of the networks but also allow for network migrations and alternate routing in the case of LBR failures. We evaluate DualMOP-RPL through extensive simulations and testbed experiments and show that our proposal eliminates all the problems we have identified.

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DualMOP-RPL: Supporting Multiple Modes of Downward Routing in a Single RPL Network

Disclosed are a sensor node having a self localization function and a self localization method of the sensor node. The sensor node calculates a location thereof by receiving location information measured at each of two mobile nodes at different times and using four location information of the received location information. Additional cost and power consumption required for installing additional equipment such as an anchor node, a ultrasonic transceiver and a signal amplifier are reduced.

Sensor node having self localization function and self localization method thereof

Distributed localization algorithms are required for large-scale wireless sensor network applications. In this paper, we introduce an efficient algorithm, termed node distribution-based localization (NDBL), which emphasizes simple refinement and low system-load for low-cost and low-rate wireless sensors. Each node adaptively chooses neighboring nodes, updates its position estimate by minimizing a local cost-function, and then passes this updated position to neighboring nodes. This update process uses a node distribution that has the same density per unit area as large-scale networks. Neighbor nodes are selected from the range in which the strength of received signals is greater than an experimentally based threshold. Based on results of a MATLAB simulation, the proposed algorithm was more accurate than trilateration and less complex than multi-dimensional scaling. Numerically, the mean distance error of the NDBL algorithm is 1.08---5.51 less than that of distributed weighted multi-dimensional scaling (dwMDS). Implementation of the algorithm using MicaZ with TinyOS-2.x confirmed the practicality of the proposed algorithm.

Jongjun Park

Papers

Mesh routing method and mesh routing apparatus in beacon enabled wireless AD-HOC networks

Localization apparatus for recognizing location of node in sensor network and method thereof

DualMOP-RPL: Supporting Multiple Modes of Downward Routing in a Single RPL Network

Sensor node having self localization function and self localization method thereof

Node distribution-based localization for large-scale wireless sensor networks