“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Appearing in 1st IEEE International Workshop on Sensor Net Protocols and Applications (SNPA). Anchorage, Alaska, USA. May 11, 2003. RMST: Reliable Data Transport in Sensor Networks Fred Stann, John Heidemann Abstract – Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi- Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. Second, these energy constraints, plus relatively low wireless bandwidths, make in-network processing both feasible and desirable [3]. Third, because nodes in sensor networks are usually collaborating towards a common task, rather than representing independent users, optimization of the shared network focuses on throughput rather than fairness. Finally, because sensor networks are often deployed by a single organization with inexpensive hardware, there is less need for interoperability with existing standards. For all of these reasons, sensor networks provide an environment that encourages rethinking the structure of traditional communications protocols. The main contribution is an evaluation of the placement of reliability for data transport at different levels of the protocol stack. We consider implementing reliability in the MAC, transport layer, application, and combinations of these. We conclude that reliability is important at the MAC layer and the transport layer. MAC-level reliability is important not just to provide hop-by-hop error recovery for the transport layer, but also because it is needed for route discovery and maintenance. (This conclusion differs from previous studies in reliability for sensor nets that did not simulate routing. [4]) Second, we have developed RMST (Reliable Multi-Segment Transport), a new transport layer, in order to understand the role of in- network processing for reliable data transfer. RMST benefits from diffusion routing, adding minimal additional control traffic. RMST guarantees delivery, even when multiple hops exhibit very high error rates. 1 Introduction Wireless sensor networks provide an economical, fully distributed, sensing and computing solution for environments where conventional networks are impractical. This paper explores the design decisions related to providing reliable data transport in sensor nets. The reliable data transport problem in sensor nets is multi-faceted. The emphasis on energy conservation in sensor nets implies that poor paths should not be artificially bolstered via mechanisms such as MAC layer ARQ during route discovery and path selection [1]. Path maintenance, on the other hand, benefits from well- engineered recovery either at the MAC layer or the transport layer, or both. Recovery should not be costly however, since many applications in sensor nets are impervious to occasional packet loss, relying on the regular delivery of coarse-grained event descriptions. Other applications require loss detection and repair. These aspects of reliable data transport include the provision of guaranteed delivery and fragmentation/ reassembly of data entities larger than the network MTU. Sensor networks have different constraints than traditional wired nets. First, energy constraints are paramount in sensor networks since nodes can often not be recharged, so any wasted energy shortens their useful lifetime [2]. This work was supported by DARPA under grant DABT63-99-1-0011 as part of the SCAADS project, and was also made possible in part due to support from Intel Corporation and Xerox Corporation. Fred Stann and John Heidemann are with USC/Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA, USA E-mail: fstann@usc.edu, johnh@isi.edu. 2 Architectural Choices There are a number of key areas to consider when engineering reliability for sensor nets. Many current sensor networks exhibit high loss rates compared to wired networks (2% to 30% to immediate neighbors)[1,5,6]. While error detection and correction at the physical layer are important, approaches at the MAC layer and higher adapt well to the very wide range of loss rates seen in sensor networks and are the focus of this paper. MAC layer protocols can ameliorate PHY layer unreliability, and transport layers can guarantee delivery. An important question for this paper is the trade off between implementation of reliability at the MAC layer (i.e. hop to hop) vs. the Transport layer, which has traditionally been concerned with end-to-end reliability. Because sensor net applications are distributed, we also considered implementing reliability at the application layer. Our goal is to minimize the cost of repair in terms of transmission.

RMST: Reliable Data Transport in Sensor Networks

As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators. These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means. In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data. To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes.We briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application. The remainder of the paper presents details of our experimental platform.

Habitat monitoring: Application driver for wireless communications technology

The pervasiveness of wireless technology has indeed created massive opportunity to integrate almost everything into the Internet fabric. This can be seen with the advent of Internet of Things and Cyber Physical Systems, which involves cooperation of massive number of intelligent devices to provide intelligent services. Fairness amongst these devices is an important issue that can be analysed from several dimensions, e.g., energy usage, achieving required quality of services, spectrum sharing, and so on. This article focusses on these viewpoints while looking at fairness research. To generalize, mainly wireless networks are considered. First, we present a general view of fairness studies, and pose three core questions that help us delineate the nuances in defining fairness. Then, the existing fairness models are summarized and compared. We also look into the major fairness research domains in wireless networks such as fair energy consumption control, power control, topology control, link and flow scheduling, channel assignment, rate allocation, congestion control and routing protocols. We make a distinction amongst fairness, utility and resource allocation to begin with. Later, we present their inter-relation. At the end of this article, we list the common properties of fairness and give an example of fairness management. Several open research challenges that point to further work on fairness in wireless networks are also discussed. Indeed, the research on fairness is entangled with many other aspects such as performance, utility, optimization and throughput at the network and node levels. While consolidating the contributions in the literature, this article tries to explain the niceties of all these aspects in the domain of wireless networking.

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Fairness in Wireless Networks:Issues, Measures and Challenges

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000–2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Finally, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture.

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A Survey of Smart Parking Solutions

Congestion in a Wireless Sensor Network (WSN) can cause missing packets, low energy efficiency, and long delay. Moreover, some applications, e.g. multimedia and image, need to transmit large volumes of data concurrently from several sensors. These applications have different delay and QoS requirements. Congestion problem is more urgent in such applications. To address this challenge, we propose a novel energy efficient congestion control scheme for sensor networks, called ECODA (Enhanced congestion detection and avoidance) which comprises three mechanisms: (1) Use dual buffer thresholds and weighted buffer difference for congestion detection; (2) Flexible Queue Scheduler for packets scheduling; (3) A bottleneck-node-based source sending rate control scheme. Simulations show that ECODA achieves efficient congestion control and flexible weighted fairness for different class of traffic. Therefore it leads to higher energy efficiency and better QoS in terms of throughput, fairness, and delay.

ECODA: enhanced congestion detection and avoidance for multiple class of traffic in sensor networks

Recently, with the explosive increase of automobiles in cities, parking problems are serious and even worsen in many cities. This paper proposes a street parking system (SPS) based on wireless sensor networks. The system can monitor the state of every parking space by deploying a magnetic sensor node on the space. For accurately detecting a parking car, a vehicle detection algorithm is proposed. And an adaptive sampling mechanism is used to reduce the energy consumption. Eighty-two sensor nodes are deployed on the street parking spaces to evaluate the performance of SPS. By running the system for more than one year, we observed that the vehicle detection accuracy of the SPS is better than 98%, and the lifetime of the sensor node is more than 5 years with a pair of 2500 mAh Li batteries.

A Street Parking System Using Wireless Sensor Networks

Vehicle detections are an important research field and attract many researchers. Most research efforts have been focused on vehicle parking detection (VPD) in indoor parking lot. For on-street parking, strong noise disturbances affect detection accuracy. To deal with vehicle detections in on-street environment, we propose two vehicle detection algorithms based on a cross-correlation technique in wireless magnetic sensor networks. One is for VPD, and the other one is for vehicle speed estimation (VSE). The proposed VPD algorithm combines the state-machine detection and the cross-correlation detection. In the VSE, speed estimation is based on the calculation of the normalized cross correlation between the signals of two sensors along the road with a certain spacing. Experimental results show that the VPD has an accuracy of 99.65% for arrival and 99.44% for departure, while the VSE has an accuracy of 92%.

A Cross-Correlation Technique for Vehicle Detections in Wireless Magnetic Sensor Network

Congestion in a Wireless Sensor Network (WSN) can cause missing packets, low energy efficiency, and long delay. Moreover, some applications, e.g. multimedia and image, need to transmit large volumes of data concurrently from several sensors. These applications have different delay and QoS requirements. Congestion problem is more urgent in such applications. To address this challenge, we propose an energy efficient congestion control scheme for sensor networks, called ECODA (Enhanced congestion detection and avoidance) which comprises three mechanisms: 1) use buffer and weighted buffer difference for congestion detection; 2) propose a bottleneck-node-based source data sending rate control scheme; 3) use Flexible Queue Scheduler for packets transfer. Simulations show that ECODA achieves efficient congestion control and flexible weighted fairness for different class of traffic. Therefore it leads to higher energy efficiency and better QoS in terms of throughput, fairness, and delay.

ECODA: Enhanced congestion detection and avoidance for multiple class of traffic in sensor networks

Recently, significant research efforts have been focused on vehicle parking detection due to fuel consumption and traffic congestion. Many solutions have been successfully applied in indoor parking lots. However, due to the strong noise disturbance in outdoor parking environment, the detection accuracy for on-street parking is still a challenging task. In this paper, we propose a vehicle parking detection method by the use of normalized cross-correlation (NCC) of magnetic signals generated by magnetoresistive sensors. In the proposed method, the sensed signal is correlated with a reference. If the result is greater than a threshold, a pulse is generated. One of the primary factors that affect the accuracy of the NCC-based detection is the choice of reference which is obtained by using a k-means clustering algorithm in this paper. Compared with the-state-of-the-art vehicle detection methods, the proposed method is competitive in terms of cost, accuracy, and complexity. The proposed method is simulated and tested on the Xueyuan Boulevard, University Town of Shenzhen, Nanshan, Shenzhen, China. The experimental results show that the proposed method can provide the detection accuracy of 99.33% for arrival and 99.63% for departure.

https://journals.sagepub.com/doi/pdf/10.1155/2015/361242

Fengqi Yu

Papers

ECODA: enhanced congestion detection and avoidance for multiple class of traffic in sensor networks

A Street Parking System Using Wireless Sensor Networks

A Cross-Correlation Technique for Vehicle Detections in Wireless Magnetic Sensor Network

ECODA: Enhanced congestion detection and avoidance for multiple class of traffic in sensor networks

A vehicle parking detection method based on correlation of magnetic signals