On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of 1.0×10(-21). It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203,000 years, equivalent to a significance greater than 5.1σ. The source lies at a luminosity distance of 410(-180)(+160)  Mpc corresponding to a redshift z=0.09(-0.04)(+0.03). In the source frame, the initial black hole masses are 36(-4)(+5)M⊙ and 29(-4)(+4)M⊙, and the final black hole mass is 62(-4)(+4)M⊙, with 3.0(-0.5)(+0.5)M⊙c(2) radiated in gravitational waves. All uncertainties define 90% credible intervals. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

/pdf/the-observation-of-gravitational-waves-from-a-binary-black-58srpupgg9.pdf

The Observation of Gravitational Waves from a Binary Black Hole Merger

The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the “class of bald men,” or the “class of numbers which are much greater than 10,” or the “class of adaptive systems,” etc. A basic concept which makes it possible to treat fuzziness in a quantitative manner is that of a fuzzy set, that is, a class in which there may be grades of membership intermediate between full membership and non-membership. Thus, a fuzzy set is characterized by a membership function which assigns to each object its grade of membership (a number lying between 0 and 1) in the fuzzy set. After a review of some of the relevant properties of fuzzy sets, the notions of a fuzzy system and a fuzzy class of systems are introduced and briefly analyzed. The paper closes with a section dealing with optimization under fuzzy constraints in which an approach to...

Fuzzy sets and systems

Feature Issue on
Optical Access Networks (OAN) The passive optical network (PON) is
an optical fiber based network architecture, which can provide much higher bandwidth
in the access network compared to traditional copper-based networks. Incorporating
wavelength-division multiplexing (WDM) in a PON allows one to support much higher
bandwidth compared to the standard PON, which operates in the "single-wavelength
mode" where one wavelength is used for upstream transmission and a separate one is
used for downstream transmission. We present a comprehensive review of various
aspects of WDM-PONs proposed in the literature. This includes enabling device
technologies for WDM-PONs and network architectures, as well as the corresponding
protocols and services that may be deployed on a WDM-PON. The WDM-PON will become a
revolutionary and scalable broadband access technology that will provide high
bandwidth to end users.

/pdf/wavelength-division-multiplexed-passive-optical-network-wdm-428jyy569l.pdf

Wavelength-division-multiplexed passive optical network (WDM-PON) technologies for broadband access: a review (Invited)

The main bandwidth bottleneck in today's networks is in the access segment. To address that bottleneck, broadband fiber access technologies such as passive optical networks (PONs) are an indispensable solution. The industry has selected time-division multiplexing (TDM) for current PON deployments. To satisfy future bandwidth demands, however, next-generation PON systems are being investigated to provide even higher performance. In this paper, we first review current TDM-PONs; we designate them as generation C. Next, we review next-generation PON systems, which we categorize into C+1 and C+2 generations. We expect C+1 systems to provide economic near-term bandwidth upgrade by overlaying new services on current TDM-PONs. For the long term, C+2 systems will provide more dramatic system improvement using wavelength division multiplexing technologies. Some C+2 architectures require new infrastructures and/or equipment, whereas others employ a more evolutionary approach. We also review key enabling components and technologies for C+1 and C+2 generations and point out important topics for future research.

/pdf/next-generation-optical-access-networks-41pmztcn8d.pdf

Next-Generation Optical Access Networks

Passive optical networks (PONs) are currently evolving into next-generation PONs (NG-PONs) which aim at achieving higher data rates, wavelength channel counts, number of optical network units (ONUs), and extended coverage compared to their conventional counterparts. Due to the increased number of stages and ONUs, NG-PONs face significant challenges to provide the same level of survivability like conventional PONs without exceeding the budget constraints of cost-sensitive access networks. Toward this end, partial optical protection, in combination with interconnecting a subset of ONUs through a wireless mesh network (WMN) front-end, are promising solutions to render NG-PONs survivable in a cost-effective manner. In this paper, we present a probabilistic analysis of the survivability of NG-PONs and hybrid fiber-wireless (FiWi) access networks, taking both optical and wireless protection into account. In addition, we propose different selection schemes to wirelessly upgrade a subset of ONUs, and investigate their performance for a wide range of fiber link failure scenarios and different NG-PON topologies.

Survivability Analysis of Next-Generation Passive Optical Networks and Fiber-Wireless Access Networks

In this paper we propose and investigate the performance of a multi-channel scheduling algorithm based on the well-known deficit round-robin (DRR), which we call multi-channel DRR (MCDRR). We extend the original DRR to the case of multiple channels with tunable transmitters and fixed receivers to provide efficient fair queueing in hybrid time division multiplexing (TDM)/wavelength division multiplexing (WDM) optical networks. We take into account the availability of channels and tunable transmitters in extending the DRR and allow the overlap of `rounds' in scheduling to efficiently utilize channels and tunable transmitters. Simulation results show that the proposed MCDRR can provide nearly perfect fairness with ill-behaved flows for different sets of conditions for interframe times and frame sizes in hybrid TDM/WDM optical networks with tunable transmitters and fixed receivers.

/pdf/multi-channel-deficit-round-robin-scheduling-for-hybrid-tdm-3vljlkhywd.pdf

Multi-Channel Deficit Round-Robin Scheduling for Hybrid TDM/WDM Optical Networks

A similarity measure is a measure evaluating the degree of similarity between two fuzzy data sets and has become an essential tool in many applications including data mining, pattern recognition, and clustering. In this paper, we propose a similarity measure capable of handling non-overlapped data as well as overlapped data and analyze its characteristics on data distributions. We first design the similarity measure based on a distance measure and apply it to overlapped data distributions. From the calculations for example data distributions, we find that, though the similarity calculation is effective, the designed similarity measure cannot distinguish two non-overlapped data distributions, thus resulting in the same value for both data sets. To obtain discriminative similarity values for non-overlapped data, we consider two approaches. The first one is to use a conventional similarity measure after preprocessing non-overlapped data. The second one is to take into account neighbor data information in designing the similarity measure, where we consider the relation to specific data and residual data information. Two artificial patterns of non-overlapped data are analyzed in an illustrative example. The calculation results demonstrate that the proposed similarity measures can discriminate non-overlapped data.

https://www.mdpi.com/2073-8994/9/5/68/pdf

Analysis of a Similarity Measure for Non-Overlapped Data

Key scalability issues in the management of routing information at each node in wireless networks running a proactive routing protocol have been identified and a solution is set forth based on hybrid proactive on-demand routing with focus on the STA association information management at each MP in a WLAN mesh. A fisheye-scope-based GAB management scheme is described where the priority of an entry is the reverse of the hop count of its associated MAP/MPP from the MP, which can be easily applicable to the case of management of general routing information. For example, the GAB proposed can maintain only those entries whose associated MAPs/MPPs are two or less hops away from the MP.

Hybrid proactive on-demand routing in wireless networks

Location fingerprinting based on Received Signal Strength Indicator (RSSI) has become a mainstream indoor localization technique due to its advantage of not requiring the installation of new infrastructure and the modification of existing devices, especially given the prevalence of Wi-Fi-enabled devices and the ubiquitous Wi-Fi access in modern buildings. The use of Artificial Intelligence (AI)/Machine Learning (ML) technologies like Deep Neural Networks (DNNs) makes location fingerprinting more accurate and reliable, especially for large-scale multi-building and multi-floor indoor localization. The application of DNNs for indoor localization, however, depends on a large amount of preprocessed and deliberately-labeled data for their training. Considering the difficulty of the data collection in an indoor environment, especially under the current epidemic situation of COVID-19, we investigate three different methods of RSSI data augmentation based on Multi-Output Gaussian Process (MOGP), i.e., by a single floor, by neighboring floors, and by a single building; unlike Single-Output Gaussian Process (SOGP), MOGP can take into account the correlation among RSSI observations from multiple Access Points (APs) deployed closely to each other (e.g., APs on the same floor of a building) by collectively handling them. The feasibility of the MOGP-based RSSI data augmentation is demonstrated through experiments using a recently-published work based on Recurrent Neural Network (RNN) indoor localization model and the UJIIndoorLoc, i.e., the most popular publicly-available multi-building and multi-floor indoor localization database; the RNN model trained with the UJIIndoorLoc database, augmented by using the whole RSSI data of a building in fitting an MOGP model (i.e., by a single building), outperforms the other two augmentation methods and reduces the mean three-dimensional positioning error from 8.62 m to 8.42 m in comparison to the RNN model trained with the original UJIIndoorLoc database.

/pdf/multi-output-gaussian-process-based-data-augmentation-for-10lzjpm1.pdf

Multi-Output Gaussian Process-Based Data Augmentation for Multi-Building and Multi-Floor Indoor Localization

Traffic shaping is a mechanism used by Internet Service Providers (ISPs) to limit subscribers' traffic based on their service contracts. This paper investigates the current implementation of traffic shaping based on the token bucket filter (TBF), discusses its advantages and disadvantages, and proposes a cooperative TBF that can improve subscribers' quality of service (QoS)/quality of experience (QoE) without compromising business aspects of the service contract model by proportionally allocating excess bandwidth from inactive subscribers to active ones based on the long-term bandwidths per their service contracts.

Kyeong Soo Kim

Papers

Multi-Channel Deficit Round-Robin Scheduling for Hybrid TDM/WDM Optical Networks

Analysis of a Similarity Measure for Non-Overlapped Data

Hybrid proactive on-demand routing in wireless networks

Multi-Output Gaussian Process-Based Data Augmentation for Multi-Building and Multi-Floor Indoor Localization

Cooperative ISP traffic shaping schemes in broadband shared access networks