DoSDefender: A Kernel-Mode TCP DoS Prevention in Software-Defined Networking.

The limited computation resource of the centralized controller and communication bandwidth between the control and data planes become the bottleneck in forwarding the packets in Software-Defined Networking (SDN). Denial of Service (DoS) attacks based on Transmission Control Protocol (TCP) can exhaust the resources of the control plane and overload the infrastructure of SDN networks. To mitigate TCP DoS attacks, DoSDefender is proposed as an efficient kernel-mode TCP DoS prevention framework in the data plane for SDN. It can prevent TCP DoS attacks from entering SDN by verifying the validity of the attempts to establish a TCP connection from the source, migrating the connection, and relaying the packets between the source and the destination in kernel space. DoSDefender conforms to the de facto standard SDN protocol, the OpenFlow policy, which requires no additional devices and no modifications in the control plane. Experimental results show that DoSDefender can effectively prevent TCP DoS attacks in low computing consumption while maintaining low connection delay and high packet forwarding throughput.

Joint Optimization for Mobile Edge Computing-Enabled Blockchain Systems: A Deep Reinforcement Learning Approach.

A mobile edge computing (MEC)-enabled blockchain system is proposed in this study for secure data storage and sharing in internet of things (IoT) networks, with the MEC acting as an overlay system to provide dynamic computation offloading services. Considering latency-critical, resource-limited, and dynamic IoT scenarios, an adaptive system resource allocation and computation offloading scheme is designed to optimize the scalability performance for MEC-enabled blockchain systems, wherein the scalability is quantified as MEC computational efficiency and blockchain system throughput. Specifically, we jointly optimize the computation offloading policy and block generation strategy to maximize the scalability of MEC-enabled blockchain systems and meanwhile guarantee data security and system efficiency. In contrast to existing works that ignore frequent user movement and dynamic task requirements in IoT networks, the joint performance optimization scheme is formulated as a Markov decision process (MDP). Furthermore, we design a deep deterministic policy gradient (DDPG)-based algorithm to solve the MDP problem and define the multiple and variable number of consecutive time slots as a decision epoch to conduct model training. Specifically, DDPG can solve an MDP problem with a continuous action space and it only requires a straightforward actor-critic architecture, making it suitable for tackling the dynamics and complexity of the MEC-enabled blockchain system. As demonstrated by simulations, the proposed scheme can achieve performance improvements over the deep Q network (DQN)-based scheme and some other greedy schemes in terms of long-term transactional throughput.

Comparative analysis of effectiveness of asthma control test-guided treatment versus usual care in patients with asthma from China.

OBJECTIVE: The present study compared the effectiveness of asthma control test (ACT)-guided treatment vs. usual care (UC) in patients with asthma from China. METHODS: This prospective, phase IV, multicenter, cluster-randomized, open-label 24-week study was conducted in China; patients were randomized to either ACT-guided treatment or UC group. The patients recorded peak expiratory flow, symptoms, and medication in a diary card every day and completed ACT at every clinic visit. For the UC group, patients completed ACT after the physician's treatment decision. RESULTS: In total, 83.6% patients (n = 443/530; ACT: n = 209, UC: n = 234) completed the study. A significantly higher proportion of patients (adjusted OR [95% CI]: 7.87 (1.29, 48.11; p = 0.027) responded to the treatment and had ACT total score ≥20 or demonstrated an improvement of >3 points in ACT total score in ≥1 post-baseline assessment in the ACT-guided treatment vs. UC group. A higher proportion of patients had an ACT total score ≥20 and an improvement of >3 points in ACT total score at Week 24 in the ACT-guided treatment vs. the UC group (adjusted OR (95% CI):2.28 (1.07, 4.85; p = 0.036). A significant difference (p = 0.005) in change from baseline in ACT total score was observed in ACT-guided treatment vs. UC group at Week 24. The mean annual exacerbation rate was similar in both the groups. CONCLUSIONS: ACT-guided treatment was more effective in achieving ACT total score ≥20 or showing an improvement of >3 points in the ACT total score and well tolerated compared with UC treatment in the 24-week treatment period. TRIAL REGISTRATION: Clinical trials.gov Identifier: NCT02868281, https://clinicaltrials.gov/; GlaxoSmithKline study ID: 201097, https://www.gsk-studyregister.com/.

Trustworthiness and a Zero Leakage OTMP-P2L Scheme Based on NP Problems for Edge Security Access.

Resource constraints have prevented comprehensive cryptography and multifactor authentication in numerous Internet of Things (IoT) connectivity scenarios. Existing IoT systems generally adopt lightweight security protocols that lead to compromise and privacy leakage. Edge computing enables better access control and privacy protection, furthermore, blockchain architecture has achieved a trusted store of value by open-source and distributed consensus mechanisms. To embrace these new paradigms, we propose a scheme that employs one-time association multitasking proofs for peer to local authentication (OTMP-P2L). The scheme chooses relevant nondeterministic polynomial (NP) problem tasks, and manages localized trust and anonymity by using smart devices such as phones and pads, thereby enabling IoT devices to autonomously perform consensus validation with an enhanced message authentication code. This nested code is a one-time zero-knowledge proof that comprises multiple logic verification arguments. To increase diversity and reduce the workload of each one, these arguments are chained by a method that establishes some of the inputs of the following task from the output of previous tasks. We implemented a smart lock system and confirmed that the scheme outperforms IoT authentication methods. The result demonstrates superior flexibility through dynamic difficulty strategies and succinct non-interactive peer-to-peer (P2P) verification.

C-band 56-Gb/s PAM4 transmission over 80-km SSMF with electrical equalization at receiver.

In this paper, a memory polynomial equalizer combined with decision feedback equalizer (MPE-DFE) is proposed to eliminate channel distortions for intensity modulation and direct detection (IM/DD) systems. Compared with traditional feedforward equalizer and decision feedback equalizer (FFE-DFE), the proposed MPE-DFE introduces extra square terms and cubic terms to jointly equalize chromatic dispersion and nonlinear distortions. We demonstrated a C-band 56-Gb/s four-level pulse-amplitude modulation (PAM4) system over 80-km standard single mode fiber (SSMF) transmission. Experimental results show that the proposed MPE-DFE achieved up to 6.2 dB higher SNR than traditional FFE-DFE. Moreover, the achieved bit error ratio (BER) with MPE-DFE reaches 3.1 × 10-3, which is below 7% feedforward error correction (FEC) threshold of 3.8 × 10-3. To the best of our knowledge, we achieved a record transmission distance for C-band 56-Gb/s PAM4 signal with only electrical equalization at the receiver.

Simple and efficient nonlinear polarization evolution mode-locked fiber laser by three-dimensionally manipulating a polarization beam splitter.

A simple and efficient femtosecond nonlinear polarization evolution (NPE) mode-locked laser is presented. Different from conventional NPE fiber lasers, the polarization beam splitter (PBS) is three-dimensionally manipulated to achieve polarization control and state selection in our NPE laser. The polarizer, half-wave plate, and quarter-wave plate from conventional NPE fiber lasers are replaced by this PBS. Thus, the configuration and the system gain of our proposed laser are simply and efficiently improved. As a result, transfer efficiency of 24.17% is experimentally demonstrated. In addition, measured self-started pulses with average power of 49 mW and center wavelength of 1584 nm are generated with single-pulse energy of 1.51 nJ.

Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City.

Smart city (SC) technologies can provide appropriate services according to citizens’ demands. One of the key enablers in a SC is the Internet of Things (IoT) technology, which enables a massive number of devices to connect with each other. However, these devices usually come from different manufacturers with different product standards, which confront interactive control problems. Moreover, these devices will produce large amounts of data, and efficiently analyzing these data for intelligent services. In this paper, we propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture to integrate heterogeneous IoT devices to support intelligent services. In particular, the proposed architecture is empowered by semantic and AI technologies, which enable flexible connections among heterogeneous devices. The AI technology can support very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Furthermore, we also present several practical use cases of the proposed AI-SIoT architecture and the opportunities and challenges to implement the proposed AI-SIoT for future SCs are also discussed.

Stable frequency dissemination over multi-access fiber loop link with optical comb.

An optical comb based stable frequency dissemination system is proposed and experimentally demonstrated over a multi-access optical fiber loop link. In the system, a new technique based on optical-microwave phase locking loop is designed for phase compensation. In the experiment, a mode-locked fiber laser at a repetition rate of 100 MHz is used to provide an optical source at local site, then it transmits along a 150 km fiber loop link. To testify the proposed system, two accessing nodes are measured in the loop link. The dissemination frequency instability is measured at 3.65 × 10-15/1 s and 7.8 × 10-18/1000 s at the intermediate node. The similar performance is shown at the other node. Hence, the system has the potential application in high-precision frequency transmission system via a long-haul multi-access loop link.

Equalization scheme of C-band PAM4 signal for optical amplified 50-Gb/s PON.

The bandwidth limit of devices and the chromatic dispersion (CD) of optical fiber severely distort the high-speed signal in a passive optical network (PON). In this paper, an efficient equalization scheme is proposed for optical amplified 50-Gb/s PAM4-PON with a 10G-class transmitter. The proposed equalization scheme is based on fast frequency domain equalization (FDE) with circular convolution, an optimized post-filter, and a low-complexity maximum likelihood sequence detector (MLSD), which requires only total 23 real-valued multiplications for each output symbol. Experimental results show that up to 33.2 dB power budget is successfully achieved over 20 km transmission without using any optical CD compensation module in the C-band. Moreover, there is only 0.5 dB penalty of receiver sensitivity compared to optical back to back (BTB) transmission. Therefore, the CD distortion has been nearly compensated for by the proposed equalization scheme. To the best of our knowledge, this is the best performance of an optical amplified 50-Gb/s PAM4-PON system in the C-band.

Pseudo almost periodic solutions for shunting inhibitory cellular neural networks with continuously distributed delays.

The shunting inhibitory cellular neural networks with continuously distributed delays and pseudo almost periodic coefficients are considered. First, we make a generalization of the Halanay inequality, and then establish some sufficient conditions for the existence and asymptotical stability of pseudo almost periodic solutions. Finally, a numerical simulation is presented to illustrate the theoretical results.

Thiosteranes in samples impacted by fecal materials and their potential use as marker of sewage input.

Sewage impacted soil, sludge and water samples were studied to understand the occurrence and formation of thiosteranes and to determine the relevance of these compounds as tracers for sewage input into the environment. Soils were collected from wastewater irrigation fields (Wroclaw, Poland), water from the Nexapa River Basin (Mexico), which also received wastewater and wastewater treatment plant(WWTP) effluent, and water and sludge from the Norman WWTP (USA) at different treatment stages. Thiosteranes represented a high proportion of the steroid fraction in the Wroclaw irrigation field and the Nexapa River Basin samples. Small amounts of thiosteranes were found in anaerobically digested sludge from the Norman WWTP. A good correlation between coprostanone and thiosterane concentrations suggests thiosteranes were produced by stanone sulphurization under anoxic conditions. Thiosterane stability under anoxic and suboxic conditions indicates their potential use as tracers for environmental input of sewage products or land application of sewage sludge.

A 12-month clinical survey of incidence and outcome of acute respiratory distress syndrome in Shanghai intensive care units.

OBJECTIVE: To investigate incidence, causes, and outcome of acute respiratory distress syndrome (ARDS) in adult patients admitted to intensive care units (ICU) in Shanghai. DESIGN: A prospective 12-month survey during 2001-2002 of the predispositions, clinical management strategies, complications, and 90-day survival rates of patients with ARDS. PATIENTS AND SETTING: Fifteen ICU in 12 university hospitals in Shanghai. All ICU admissions >/=15 years of age in the 12-month period were assessed. Patients fulfilling diagnostic criteria of ARDS, as defined by the American-European Consensus Conference, and having a continuous treatment period >/=24 h, were recruited. MEASUREMENTS AND RESULTS: Of 5320 adult patients admitted to ICUs, there were 108 (2%) with ARDS. At inclusion, ARDS patients had a mean PaO(2)/FiO(2) value of 111.3+/-40.3 mmHg and a mean acute physiology and chronic health evaluation score (APACHE II) of 17.3+/-8.0; 33 patients had a lung injury score >2.5. Forty-one and 67 patients had ARDS associated with diseases of pulmonary and extrapulmonary origin, respectively. The most common predisposing factors for ARDS were pneumonia (34.3%) and nonpulmonary sepsis (30.6%). The overall ICU mortality was 10.3%. In-hospital and 90-day mortalities of ARDS patients were 68.5 and 70.4%, respectively, and accounted for 13.5% of the overall ICU mortality. For ARDS patients, multiple organ dysfunction syndrome was a major risk factor associated with death (59.5%). CONCLUSION: The high morbidity and mortality of ARDS in the ICUs in Shanghai require reassessment of respiratory and intensive care management and implementation of effective therapeutic interventions.