Effect of Relay Nodes on End-To-End Delay in Multi-Hop Wireless Ad-Hoc Networks

Channel access delay in a wireless adhoc network is the major source of delay while considering the total end to-end delay. Channel access delays experienced by different relay nodes are different in multi-hop adhoc network scenario. These delays in multi-hop network are analysed in the literature assuming channel access delays are independent and are of same magnitude at all the nodes in the network. In this work, the end to-end delay in a multi-hop adhoc network is analysed taking into account the silent relay nodes. Along with silent relay node effect, Channel access probability (p), transmission radius (r) analogous to transmit power, network throughput and density of nodes arête other factors considered for the end-to-end delay analysis. Effect of network parameters along with silent relay nodes on end-to-end delay is found to be considerably high compared to the previous literature results. Given a bound on end-to-end delay with percentage of silent relay nodes, throughput, node density requirements for a multi-hop adhoc network, optimal ranges of transmission radius and channel access probability can be obtained from the proposed analysis. End-to-end delay increases with silent relay nodes along with transmission radius(r), channel access probability(p), node density and throughput. It is clear from the analysis, that the effect of silent relay nodes on end to-end delay cannot be ignored to maintain certain Quality of service (QoS) metrics for the multi-hop wireless adhoc networ

Effect of relay nodes and transmit power on end-to-end delay in multi-hop wireless ad hoc networks

Channel access delay in a wireless multi-hop ad hoc network is the major source of delay while considering end-to-end delay. In this work, end-to-end delay is analysed considering silent relay nodes and effect of network parameters like node density and throughput. Given network parameter requirements and bound on end-to-end delay, optimal ranges of transmission radius and channel access probability can be obtained from the proposed analysis. Effect of silent relay nodes must be considered to maintain quality of service (QoS) metrics. Transmission power adaptability to reduce end-to-end delay is analysed considering the interference model. Increase in transmission power is not reducing end-to-end delay linearly. Simulation results show that increase in end-to-end delay due to channel access probability and throughput is onsiderably higher than node density. Also given the network parameters, end-to-end delay can be minimised only up to certain value irrespective of increase in transmit power

Neural Network based Short Term Forecasting Engine To Optimize Energy And Big Data Storage Resources Of Wireless Sensor Networks

Energy efficient wireless networks is the primary research goal for evolving billion device applications like IoT, smart grids and CPS. Monitoring of multiple physical events using sensors and data collection at central gateways is the general architecture followed by most commercial, residential and test bed implementations. Most of the events monitored at regular intervals are largely redundant/minor variations leading to large wastage of data storage resources in Big data servers and communication energy at relay and sensor nodes. In this paper a novel architecture of Neural Network (NN) based day ahead steady state forecasting engine is implemented at the gateway using historical database. Gateway generates an optimal transmit schedules based on NN outputs thereby reducing the redundant sensor data when there is minor variations in the respective predicted sensor estimates. It is observed that NN based load forecasting for power monitoring system predicts load with less than 3% Mean Absolute Percentage Error (MAPE). Gateway forward transmit schedules to all power sensing nodes day ahead to reduce sensor and relay nodes communication energy. Matlab based simulation for evaluating the benefits of proposed model for extending the wireless network life time is developed and confirmed with an emulation scenario of our testbed. Network life time is improved by 43% from the observed results using proposed model

Reliability and delay analysis of slotted anycast multi-hop wireless networks targeting dense traffic iot applications

Studies on IEEE 802.15.4 MAC in the current literature for anycast multi-hop networks do not capture a node's behaviour accurately. Due to the inaccurate modeling of state-wise behaviour of a node, the optimization of network parameters has not been efficient so far. In this work, we include the state-wise behaviour of a relay node into a 3D Markov model to more accurately investigate the protocol performance. Performance analysis of the proposed analytical model is evaluated for different variants of active state length, packet length and wake up rates considering reliability and delay as key performance metrics. Performance analysis shows that the model captures the behaviour of relay nodes most accurately

Real time Power Capping with Smart Circuit Breaker to maximize Power Utilization of Local Generator

Effective energy management and control is an important and urgent issue in the emerging and developing countries, so as to achieve their sustainable growth, because of poor quality of power supply by their electric power companies. In order to come up with the frequent electric power outage by the power company, most of buildings in developing and emerging countries install a power generator. Although because of poor control system in the premises, utilization factor of output capability of power generators is typically low except at peak periods. To improve the utilization factor of power generator, we propose a system, which can manage power segments in the building using SCB (Smart Circuit Breaker). SCBs are connected by wireless technologies with battery backup, and set their power capping based on the indication issued by central manager. The central manager computes power capping threshold of each SCB using the proposed algorithm, in real-time fashion. Experimental results show that the proposed algorithm can optimize the required capacity of the local power generator and that we need a feedback-looped adaptive threshold calculation algorithm

Real Time Net Zero Energy Building Energy Manager with Heterogeneous Wireless Ad hoc Network Adaptable To IoT Architectures

Significant energy consumption by buildings from utility grid has made researchers revisit existing Building Energy Management Systems (BEMS). Most of the developing countries have taken a green initiative of Net Zero Energy Buildings (NZEB) to reduce carbon foot print and fast depletion of conventional energy sources. Though the integration of solar and wind based systems to grid is successful in recent years, residential building energy management systems with renewable energy sources is still an evolving research area. Monitoring, control and actuation systems should be tightly coupled with the help of any to any device communication namely Internet of Things (IoT) to realize an efficient NZEB. In this paper a real time NZEB is proposed and developed with bi-directional wireless sensor and actuation system. Proposed NZEB central server collects and maintains a database of on site solar generation, battery state of charge and load power consumption data of a building with help of IEEE 802.15.4 and IEEE 802.11 wireless networks. Proposed system was deployed as a test bed with sensing, control, actuation and server modules and connecting them with a bi-directional wireless network architecture similar to IoT. Data observed at experimental test bed confirm that developed system can estimate on site solar power generation, state of charge on battery bank and load power consumption with negligible error. A simulation study with experimental data collected at NZEB test bed shows that NZEB can optimally schedule loads between local generation and utility grid thereby minimizing peak demand on the grid

WSN based power monitoring in smart grids

Smart grid technology is one of the recent developments in the area of electric power systems that aid the use of non-conventional sources of energy in parallel with the conventional sources of energy. Monitoring and control of smart grids is essential for its efficient and effective functioning. In this paper, we propose an architecture for monitoring power in smart grid applications using wireless sensor network (WSN) technology. A prototype power sensing module is designed and developed to calculate the power for any kind of loads. Using WSN technology, the monitored power is communicated to the sink at periodic intervals. Multi hop wireless mesh network is set up using IRIS motes to enhance the communication between the power sensing nodes and the sink. The data collected is a rich source of repository for data analysis and modelling. A number of smart actions and applications, such as power theft detection, energy efficient building design, smart automation systems and smart metering can evolve out of the proposed model. A novel Power theft detection algorithm is proposed and simulated in this paper. The system is also scaled using GSM technology to extend the range of communication. Load monitoring can aid distributed architecture in smart grids with automated technology to switch between the non-conventional source of energy and the grid

Telemedicine During COVID-19 and Beyond: A Practical Guide and Best Practices Multidisciplinary Approach for the Orthopedic and Neurologic Pain Physical Examination.

BACKGROUND:The COVID pandemic has impacted almost every aspect of human interaction, causing global changes in financial, health care, and social environments for the foreseeable future. More than 1.3 million of the 4 million cases of COVID-19 confirmed globally as of May 2020 have been identified in the United States, testing the capacity and resilience of our hospitals and health care workers. The impacts of the ongoing pandemic, caused by a novel strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have far-reaching implications for the future of our health care system and how we deliver routine care to patients. The adoption of social distancing during this pandemic has demonstrated efficacy in controlling the spread of this virus and has been the only proven means of infection control thus far. Social distancing has prompted hospital closures and the reduction of all non-COVID clinical visits, causing widespread financial despair to many outpatient centers. However, the need to treat patients for non-COVID problems remains important despite this pandemic, as care must continue to be delivered to patients despite their ability or desire to report to outpatient centers for their general care. Our national health care system has realized this need and has incentivized providers to adopt distance-based care in the form of telemedicine and video medicine visits. Many institutions have since incorporated these into their practices without financial penalty because of Medicare\u27s 1135 waiver, which currently reimburses telemedicine at the same rate as evaluation and management codes (E/M Codes). Although the financial burden has been alleviated by this policy, the practitioner remains accountable for providing proper assessment with this new modality of health care delivery. This is a challenge for most physicians, so our team of national experts has created a reference guide for musculoskeletal and neurologic examination selection to retrofit into the telemedicine experience. OBJECTIVES:To describe and illustrate musculoskeletal and neurologic examination techniques that can be used effectively in telemedicine. STUDY DESIGN:Consensus-based multispecialty guidelines. SETTING:Tertiary care center. METHODS:Literature review of the neck, shoulder, elbow, wrist, hand, lumbar, hip, and knee physical examinations were performed. A multidisciplinary team comprised of physical medicine and rehabilitation, orthopedics, rheumatology, neurology, and anesthesia experts evaluated each examination and provided consensus opinion to select the examinations most appropriate for telemedicine evaluation. The team also provided consensus opinion on how to modify some examinations to incorporate into a nonhealth care office setting. RESULTS:Sixty-nine examinations were selected by the consensus team. Household objects were identified that modified standard and validated examinations, which could facilitate the examinations.The consensus review team did not believe that the modified tests altered the validity of the standardized tests. LIMITATIONS:Examinations selected are not validated for telemedicine. Qualitative and quantitative analyses were not performed. CONCLUSIONS:The physical examination is an essential component for sound clinical judgment and patient care planning. The physical examinations described in this manuscript provide a comprehensive framework for the musculoskeletal and neurologic examination, which has been vetted by a committee of national experts for incorporation into the telemedicine evaluation

Young CSF restores oligodendrogenesis and memory in aged mice via Fgf17

Recent understanding of how the systemic environment shapes the brain throughout life has led to numerous intervention strategies to slow brain ageing1-3. Cerebrospinal fluid (CSF) makes up the immediate environment of brain cells, providing them with nourishing compounds4,5. We discovered that infusing young CSF directly into aged brains improves memory function. Unbiased transcriptome analysis of the hippocampus identified oligodendrocytes to be most responsive to this rejuvenated CSF environment. We further showed that young CSF boosts oligodendrocyte progenitor cell (OPC) proliferation and differentiation in the aged hippocampus and in primary OPC cultures. Using SLAMseq to metabolically label nascent mRNA, we identified serum response factor (SRF), a transcription factor that drives actin cytoskeleton rearrangement, as a mediator of OPC proliferation following exposure to young CSF. With age, SRF expression decreases in hippocampal OPCs, and the pathway is induced by acute injection with young CSF. We screened for potential SRF activators in CSF and found that fibroblast growth factor 17 (Fgf17) infusion is sufficient to induce OPC proliferation and long-term memory consolidation in aged mice while Fgf17 blockade impairs cognition in young mice. These findings demonstrate the rejuvenating power of young CSF and identify Fgf17 as a key target to restore oligodendrocyte function in the ageing brain

Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

Aims  The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin–kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI. Methods and results  Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77–0.99; P = 0.032) and Type 2 (0.77, 0.61–0.97; P = 0.025), but not Type 4 MI. Conclusion  After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.For complete list of authors see http://dx.doi.org/10.1093/eurheartj/ehz299</p