A novel routing optimization strategy based on reinforcement learning in perception layer networks

Wireless sensor networks have become incredibly popular due to the Internet of Things’ (IoT) rapid development. IoT routing is the basis for the efficient operation of the perception-layer network. As a popular type of machine learning, reinforcement learning techniques have gained significant attention due to their successful application in the field of network communication. In the traditional Routing Protocol for low-power and Lossy Networks (RPL) protocol, to solve the fairness of control message transmission between IoT terminals, a fair broadcast suppression mechanism, or Drizzle algorithm, is usually used, but the Drizzle algorithm cannot allocate priority. Moreover, the Drizzle algorithm keeps changing its redundant constant k value but never converges to the optimal value of k. To address this problem, this paper uses a combination based on reinforcement learning (RL) and trickle timer. This paper proposes an RL Intelligent Adaptive Trickle-Timer Algorithm (RLATT) for routing optimization of the IoT awareness layer. RLATT has triple-optimized the trickle timer algorithm. To verify the algorithm’s effectiveness, the simulation is carried out on Contiki operating system and compared with the standard trickling timer and Drizzle algorithm. Experiments show that the proposed algorithm performs better in terms of packet delivery ratio (PDR), power consumption, network convergence time, and total control cost ratio

Cyberattacks and security of cloud computing: a complete guideline

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, key exposure, auditing, privacy preservability, and cloud-assisted IoT applications. We then propose security attacks and countermeasures specifically for the different cloud models based on the security trends and problems. In the end, we pinpoint some of the futuristic directions and implications relevant to the security of cloud models. The future directions will help researchers in academia and industry work toward cloud computing security

Cyberattacks and Security of Cloud Computing: A Complete Guideline

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, key exposure, auditing, privacy preservability, and cloud-assisted IoT applications. We then propose security attacks and countermeasures specifically for the different cloud models based on the security trends and problems. In the end, we pinpoint some of the futuristic directions and implications relevant to the security of cloud models. The future directions will help researchers in academia and industry work toward cloud computing security

The role of plant growth promoting bacteria on arsenic removal: a review of existing perspectives

Phytobial remediation is an innovative tool that uses plants and microbes to mitigate Arsenic (As) contamination of the environment. Recently, plant growth-promoting bacteria (PGPB) that assists phytoremediation has been highly touted for both improving plant metal tolerance and promoting plant growth while achieving the goal of large-scale removal of As. This review focuses on the PGPB characteristics influencing plants and the mechanisms in which they function to overcome/lessen As-induced adversities. Several recent examples of mechanisms responsible for increasing the availability of As to plants and coping with As stresses facilitated by PGPB will be reviewed. Although drawbacks to phytoremediation have been reported, encouraging results have been developed with regular monitoring. Introducing PGPB-assisted phytoremediation of As in a field requires an assessment of the environmental effects of PGPB, especially with respect to the impacts on indigenous bacteria

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Security in fog computing: A novel technique to tackle an impersonation attack

Fog computing is an encouraging technology in the coming generation to pipeline the breach between cloud data centers and Internet of Things (IoT) devices. Fog computing is not a counterfeit for cloud computing but a persuasive counterpart. It also accredits by utilizing the edge of the network while still rendering the possibility to interact with the cloud. Nevertheless, the features of fog computing are encountering novel security challenges. The security of end users and/or fog nodes brings a major dilemma in the implementation of real life scenario. Although there are several works investigated in the security challenges, physical layer security (PLS) in fog computing is not investigated in the above. The distinctive and evolving IoT applications necessitate new security regulations, models, and evaluations disseminated at the network edge. Notwithstanding, the achievement of the current cryptographic solutions in the customary way, many aspects, i.e., system imperfections, hacking skills, and augmented attack, has upheld the inexorableness of the detection techniques. Hence, we investigate PLS that exploits the properties of channel between end user and fog node to detect the impersonation attack in fog computing network. Moreover, it is also challenging to achieve the accurate channel constraints between end user and fog node. Therefore, we propose Q-learning algorithm to attain the optimum value of test threshold in the impersonation attack. The performance of the propose scheme validates and guarantees to detect the impersonation attack accurately in fog computing networks

Drive for Muscularity and Tendencies of Muscle Dysmorphia among Pakistani Bodybuilders: A Prevalence Study

Objective: Preoccupation with a belief of insufficient muscularity affects mostly male gender throughout the world. Hence, it was necessary to study relationship between Drive for Muscularity and muscle dysmorphic tendencies in Pakistani culture. Method: A cross sectional research design was conducted on 211 participants (bodybuilders) in the age range early and middle adulthood (M= 26.25; SD= 5.946). Study was carried out in Lahore Pakistan in 2017 from June to September 2017. An indigenous Drive for Muscularity Inventory and Y-BOCS (BDD-YBOCS) administered to determine the drive for muscularity and tendencies of muscle dysmorphia. Results: The results indicated positive relationship between drive for muscularity and tendencies of muscle dysmorphia. Moreover, it revealed that 130 (62%) of the bodybuilders have a moderate level of drive for muscularity. Likewise, the unmarried bodybuilders with the age range of 18-25 years showed more drive for muscularity as compared to married bodybuilders with the age range of 26 and above (p< 0.001***). Conclusion: It was concluded that drive for muscularity and muscle dysmorphic tendencies are prevailing in Pakistani culture. Keywords: Drive for Muscularity, Tendencies of Muscle Dysmorphia, Continuous..