Information Packets Research Articles

Age-Optimal Hybrid Temporal-Spatial Generalized Deduplication and ARQ for Satellite-Integrated Internet of Things

In a typical Satellite-integrated Internet of Things (SIoT), the limited transmission rate of a sensor causes a stale in data freshness due to unavoidable time waiting for transmission. Moreover, due to the high bit error rate (BER) of the satellite-to-ground link, data freshness will be further exacerbated by frequent retransmissions. Generally, this issue is partially solved using a powerful compression scheme that can reduce the data volume. However, conventional compression schemes will necessitate a significant amount of time to accumulate constant data to a certain quantity, posing a difficult challenge. Therefore, this study proposes an age-optimal hybrid temporal-spatial generalized deduplication and automatic repeat request (HARQ-GD) protocol for the high-sampling data collection in SIoT, considering data compression, and transmission collaboratively. A novel Age of Information (AoI) metric is developed for timeliness evaluation over a two-hop end-to-end link of SIoT, which is optimized to design the proposed HARQ-GD protocol by considering the temporal and spatial correlations of sampled data with specific encoding/decoding algorithms and packet formats. The simulation results indicate that the proposed HARQ-GD protocol performs better performance than typical generalized deduplication (GD) and hybrid automatic repeat request with chase combing (HARQ-CC) schemes in reducing AoI, because of its fewer transmission times and higher compression rate.

Cyclical Trends of Network Load Fluctuations in Traffic Jamming

The transport of information packets in complex networks is a prototype system for the study of traffic jamming, a nonlinear dynamic phenomenon that arises with increased traffic load and limited network capacity. The underlying mathematical framework helps to reveal how the macroscopic jams build-up from microscopic dynamics, depending on the posting rate, navigation rules, and network structure. We investigate the time series of traffic loads before congestion occurs on two networks with structures that support efficient transport at low traffic or higher traffic density, respectively. Each node has a fixed finite queue length and uses next-nearest-neighbour search to navigate the packets toward their destination nodes and the LIFO queueing rule. We find that when approaching the respective congestion thresholds in these networks, the traffic load fluctuations show a similar temporal pattern; it is described by dominant cyclical trends with multifractal features and the broadening of the singularity spectrum regarding small-scale fluctuations. The long-range correlations captured by the power spectra show a power-law decay with network-dependent exponents. Meanwhile, the short-range correlations dominate at the onset of congestion. These findings reveal inherent characteristics of traffic jams inferred from traffic load time series as warning signs of congestion, complementing statistical indicators such as increased travel time and prolonged queuing in different transportation networks.

Learning to Transmit Fresh Information in Energy Harvesting Networks

We study age of information (AoI) minimization in an ad hoc network consisting of energy harvesting transmitters that are scheduled to send status updates to their intended receivers. The transmission scheduling with power allocation problem over a communication session is first studied assuming apriori knowledge of channel state information, harvested energy, and update packet arrivals, i.e., the offline setting. The global optimal scheduling policy in this case is the solution of a mixed integer linear program which is known to be computationally hard. We propose a supervised-learning-based algorithm to mitigate the high computational complexity. A bidirectional recurrent neural network that interprets user scheduling as a time-series classification problem is trained and tested to achieve near-optimal AoI. Next, we consider online scheduling and power allocation with causal knowledge of the system state, which is an infinite-state Markov decision problem. In this case, the related reinforcement learning problem is solved by a model-free on-policy deep reinforcement learning, where the actor-critic algorithm with deep neural network function approximation is implemented. Comparable AoI to the optimal is demonstrated and faster runtime of learning solvers is observed, verifying the efficacy of learning in terms of both optimality and computational energy efficiency for AoI-focused scheduling and resource allocation problems in wireless networks.

Blood tests of brain function: Neuronal extracellular vesicles

Extracellular vesicles (EVs) are tiny (<1 µm) membrane-bound vesicles released by all tissues (including the brain) that cross the blood-brain barrier and facilitate cell-to-cell communication within and among tissues. They represent the body’s “Twitter system,” rapidly disseminating packets of information throughout the brain and body. Not unlike Twitter, EVs convey short messages through their cargos (e.g., RNAs, proteins, lipids, and metabolites), which direct the molecular activity of recipient cells in both health and disease. Extracellular vesicles serve as mediators of brain function and represent a reservoir for CNS-specific biomarkers that can be sequestered from plasma to guide diagnosis and treatment, representing a new frontier in the molecular study of psychiatric illness and in the development of biomarkers. The EV field has immense potential to revolutionize diagnostic approaches in psychiatry, facilitate precision treatment, predict response, and discover much-needed novel therapeutics.

Comparative analysis of routing protocols for wireless area networks and evaluation of the effectiveness

A Mobile Ad Hoc Network (MANET) is a gathering of mobile nodes that want to communicate without any preplanned infrastructure and fixed organization of available links. Each node in MANET operates as a router, forwarding information packets for other mobile nodes. There are many routing protocols that possess different performance levels in different scenarios. The main task is to evaluate the existing routing protocols and finding by comparing them the best one. In this article been compared AODV, DSR and DSDV routing protocols in mobile ad hoc networks (MANETs) to specify the best operational conditions for each MANETs protocol. I study these three MANETs routing protocols by different simulations in NS-2 simulator. We describe that pause time parameter affect their performance. This performance analysis is measured in terms of Packet Delivery Ratio, Average End-to-End Delay, Normalized Routing Load and Average Throughput.

Broadcast Approach to Uplink NOMA: Queuing Delay Analysis.

Emerging wireless technologies are envisioned to support a variety of applications that require simultaneously maintaining low latency and high reliability. Non-orthogonal multiple access techniques constitute one candidate for grant-free transmission alleviating the signaling requirements for uplink transmissions. In open-loop transmissions over fading channels, in which the transmitters do not have access to the channel state information, the existing approaches are prone to facing frequent outage events. Such outage events lead to repeated re-transmissions of the duplicate information packets, penalizing the latency. This paper proposes a multi-access broadcast approach in which each user splits its information stream into several information layers, each adapted to one possible channel state. This approach facilitates preventing outage events and improves the overall transmission latency. Based on the proposed approach, the average queuing delay of each user is analyzed for different arrival processes at each transmitter. First, for deterministic arrivals, closed-form lower and upper bounds on the average delay are characterized analytically. Secondly, for Poisson arrivals, a closed-form expression for the average delay is delineated using the Pollaczek-Khinchin formula. Based on the established bounds, the proposed approach achieves less average delay than single-layer outage approaches. Under optimal power allocation among the encoded layers, numerical evaluations demonstrate that the proposed approach significantly minimizes average sum delays compared to traditional outage approaches, especially under high arrival rates.

Strong Anonymous Communication System Based on Segment Routing Over SDN

AbstractSoftware defined networking (SDN) has brought a novel networking paradigm for achieving the goal of anonymous communication. In this paper, we propose a strong anonymous communication scheme based on segment routing (STAR), which does not need all forwarding devices to support OpenFlow protocol and is easy to deploy in SDNs. In STAR, by expanding the packet format of segment routing via Sphinx protocol, the required routing information is encrypted and hidden in the packet header to prevent the enemy from associating with the communication parties. Moreover, to avoid the adversary connecting the communication parties based on load information, the trust controller is employed as an auxiliary node to negotiate the symmetric key between the communication parties for encrypting the packet load. The theoretical analysis shows that, when the adversary compromises multiple intermediate nodes, a low correct linking probability and effective attack resistance are obtained, which proves the weak correlation and stronger anonymity of STAR. Besides, evaluation results confirm that, compared with existing anonymous systems, the proposed STAR can ensure stronger anonymity and higher throughput (83.7% for that of no anonymity) by just introducing very small communication latency (microseconds) and resource cost. Especially for the large-volume data in large-scale SDNs, the advantages will be more obvious.

Nonlinear electrostatic ion cyclotron wave collapse and formation of wave packets in the presence of trapped electrons.

The weakly nonlinear and dispersive electrostatic ion cyclotron wave dynamics in the presence of Schamel distributed trapped electrons is studied in collisionless plasmas. The dynamics of the nonlinear wave is shown to be governed by a Schamel-Ostrovsky type equation. Analytical and numerical solutions of this equationreveal the collapse of a solitary (localized) pulse at a critical time that depends on the trapping parameter and the strength of the magnetic field. The time-dependent computational result is noteworthy, which predictstheformation of wave packets (wave group) beyond the critical time. The results are in good agreement with the astrophysical observations in auroral plasmas.

A secure cross-layer architecture for reactive routing in vehicle to vehicle (V2V) communications

Vehicular communication is one of the essential technologies for increasing road safety, traffic efficiency, and comfort for pedestrians and drivers. In this context, the internet of vehicles is an emerging paradigm. However, with advances in vehicular communication, security threats have also emerged. Several vulnerabilities exist in vehicular communications, including Denial of Service (DoS), black hole attacks, and fabrication attacks. A malicious attack alters the packet information in a fabrication attack, causing congestion and high delays in the vehicular network. We propose two algorithms to protect the routing protocols in a vehicle-to-vehicle scenario against several attacks that target confidentiality, authentication, privacy, and integrity. The first algorithm detects the malicious behavior of each vehicle by calculating the percentage of modified destination addresses. If it exceeds a predetermined threshold, this vehicle is classified as malicious. Otherwise, it is a normal vehicle. The second algorithm detects malicious modifications based on the Signal to Interference Ratio (SIR) by monitoring the SIR value, adjusting the distance, altering the power received, and changing the transmitted power value. We performed simulations using the SUMO 0.22 simulator and Network Simulator (NS). The results obtained show an improvement in End-to-End (E2E) delay, Packet Delivery Ratio (PDR), and reduced overhead.

Age-Optimal Network Coding HARQ Scheme for Satellite-Based Internet of Things

Satellite-based Internet of Things (S-IoT) is viewed as an efficient solution to provide timely status updates to the terrestrial user equipment (UE), due to its ubiquitous coverage and broadband access capability inherited from high throughput satellite (HTS). However, the conventional hybrid automatic repeat request (HARQ) cannot guarantee the freshness of status update transmission, because the reliable transmission needs the retransmission of the lost packets, which deteriorates the freshness due to the nontrivial propagation delay and high bit error rate (BER) of the satellite–territory link (STL). In this article, we propose an age-optimal network coding HARQ (NC HARQ) scheme with the metric of information timeliness, i.e., Age of Information (AoI) to realize timely status updates in S-IoT. First, we model the STL as a shadowed Rician (SR) fading channel and derive the closed-form expressions of BER. Then, we propose a fixed interval NC inserted HARQ (f-NC HARQ) scheme, where the NC packets are inserted in the information packets with fixed interval to accelerate the recovery of lost information packets and derive the expressions of Peak AoI (PAoI) and average end-to-end delay. Furthermore, we propose an adaptive NC inserted HARQ (A-NC HARQ) scheme for the drastic variations in the SR fading channel, where the transmission of the status update is modeled as a partially observable Markov decision process (POMDP) problem and solved by a low complexity improved fast informed bound (iFIB) algorithm. Simulation results validate the accuracy of our theoretical derivations and show that the A-NC HARQ scheme can achieve the lowest PAoI and average end-to-end delay.

Age of Information Aware Resource Allocation and Packet Sampling Control in Vehicular Networks

In this letter, we analyze the age of information (AoI) outage probability for the D/Geo/1 queueing system. Then, we formulate a problem of resource allocation and packet sampling rate optimization to maximize the sum ergodic capacity of V2N links while guaranteeing the AoI outage probability of V2V links in vehicular communication networks. For each possible V2N-V2V spectrum reusing pair, the optimal power allocation and packet sampling rate are obtained by a low-complexity algorithm. Afterwards, spectrum allocation is optimized by bipartite matching. Simulation results validate our AoI analysis and show the effectiveness of the proposed algorithm.

New timestamp mark–based energy efficient time synchronization method for wireless sensor networks

Aimed at the demands of wireless sensor networks for high energy-efficient time synchronization, the reduction of synchronization energy consumption is studied from the aspects of both accurate timestamps marking and synchronous information transmission mechanism. First, the network is divided into several parent–child groups periodically. The group-wise pair selection algorithm is used to select the network’s pairwise synchronization nodes, and chain-type network topology is thus generated. Second, the sequential multi-hop synchronization algorithm is introduced to realize the synchronization information exchange among pairwise synchronization nodes. The overhearing synchronization (OS) nodes obtain the synchronization information packet based on a one-way overhearing mechanism. Moreover, the accurate acquisition of the synchronization ack packet’s timestamp is carried out through the use of receiving-time-plus-fixed-delay mode. Third, the joint maximum likelihood method and the minimum variance unbiased estimation method are used to estimate the clock offsets of pairwise synchronization nodes and overhearing nodes to the parent nodes, respectively, based on which the child nodes adjust their local virtual clocks. Periodically, the pairwise synchronization nodes initiate the network’s time synchronization, estimate, and broadcast the relative offset to the gateway node, assisting the upper layer child nodes in synchronizing to the gateway node. Simulation results show that the proposed method not only achieves the millisecond level synchronization accuracy but also reduces the synchronization energy consumption and thus improves the network lifetime.

Exact Analytical Model of Age of Information in Multi-Source Status Update Systems With Per-Source Queueing

We study a multisource status update system with Poisson information packet arrivals and exponentially distributed service times. The server is equipped with a waiting room holding the freshest packet from each source referred to as single buffer per-source queueing (SBPSQ). The sources are assumed to be equally important, i.e., (nonweighted) average Age of Information (AoI) or average age violation probability are used as the information freshness metrics to optimize for, and subsequently, two symmetric SBPSQ-based scheduling policies are studied in this article, namely, first source first serve (FSFS) and the earliest served first serve (ESFS) policies. By employing the theory of Markov fluid queues (MFQs), an analytical model is proposed to obtain the exact distribution of the AoI for each source when the FSFS and ESFS policies are employed at the server. Additionally, a benchmark scheduling-free scheme named single buffer with replacement (SBR), which uses a single buffer to hold the freshest packet across all sources, is also studied with a similar but less complex analytical model. We comparatively study the performance of the three policies through numerical examples in terms of the average AoI and the age violation probability averaged across all sources, in a scenario of sources possessing different traffic intensities but sharing a common service time.

"A search to evaluate the efficacy of an information booklet on the knowledge and practice relating to lifestyle modifications among patients with coronary artery disease at selected hospitals of Surat, Gujarat"

The blood flow to the heart is impacted by ischemic heart disease, sometimes referred to as coronary artery disease. As a result of the buildup of plaque formation, the walls of blood arteries become constricted or clogged. The heart's musculature needs oxygen and nourishment to operate properly, which is decreased as a result. This might eventually lead to the abrupt deprivation of blood flow to a section of the heart, which would kill that section’s heart attack via damaging cardiac tissue. Any cardiac abnormality instantly impacts the flow of oxygen to the brain, kidneys, and other essential organs since the heart are the pump that delivers oxygenated blood to the other vital organs. The tissue inside these organs is impacted as a result to die, which ultimately causes failure or death. The top factor of death in several nations throughout the world is ischemic heart disease. The aim and objective of the study is the usefulness of a booklet providing advice on lifestyle changes for people with coronary artery disease. This study's conceptual model is based on "Imogene King's goal achievement theory". This study aimed to gauge people's understanding of lifestyle changes for cardiac patients. The quantitative research technique was used in this investigation. Pre- and post-testing in one group and preliminary research design were used. Techniques of non-probability random sampling were employed to choose the samples. The sample size was 60 in total. We employed both descriptive and inferential statistics in the data examination. After administering the information packet, the study's findings revealed a considerable increase in knowledge and practice during the post-test. The information booklet was a useful tool that raised patients' knowledge and practices to the desired level.

Resource Allocation and Slicing Puncture in Cellular Networks With eMBB and URLLC Terminals Coexistence

Ultrareliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) are two types of services with delay Quality-of-Service (QoS) demands. Considering the random and sporadic URLLC packets arrival feature, slicing puncture is believed to be the suitable method to support coexistence communication scenario of eMBB and URLLC terminals. However, slicing puncture in a short time is not trivial, and needs accurate wireless resource scheduling. At the same time, it may damage the QoS of eMBB service. All of these make the QoS guaranteed scheduling problem more challenging. In this article, we investigate the bandwidth, power allocations, slice puncturing problems to find the way satisfying services’ individual QoS demands. For the scheduling of eMBB service, we formulate a joint optimization problem for bandwidth and power allocations with long-term constraints of queues backlog. To solve this problem, we utilize the Lyapunov drift-plus-penalty (DPP) method to establish the relationship between the long-term constraints and the short-term optimization problem, which means that the long-term constraints are gradually satisfied by the proposed strategy at each step. We further divide the short-term optimization problem into two subproblems and adopt a block coordinate descent (BCD) algorithm to reduce the computation complexity. Then, we put forward a one-to-one matching method to solve the integer programming in resource block (RB) allocation and slicing puncture problems. Numerical results demonstrate that the proposed dynamic resource allocation and puncturing strategy (DRAPS) can solve the scheduling problem of eMBB and URLLC services in the presence of multiple randomness of channel-state information (CSI) and URLLC packet arrival.

Spread Unsourced Random Access With an Iterative MIMO Receiver

This work is dedicated to the unsourced random access (URA) with multiple-antenna receiver. We utilize a preamble-payload packet format where the preamble, selected from a pool shared between all active users, serves as a temporary activity detection identifier. The payload carries the main portion of the message data which is encoded for error correction, permuted, and scrambled. The compressed-sensing (CS) preamble receiver that estimates the active preambles and the respective user channels is followed by a payload receiver which performs several iterations of data and channel estimation and parallel interference cancellation. Our numerical and analytic results demonstrate that the presented system outperforms the related work in terms of the achievable numbers of active users and signal-to-noise ratios (SNR)s supported by the system.

A Hybrid Modified Ant Colony Optimization - Particle Swarm Optimization Algorithm for Optimal Node Positioning and Routing in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been widely deployed in hostile locations for environmental monitoring. Sensor placement and energy management are the two main factors that should be focused due to certain limitations in WSNs. The nodes in a sensor network might not stay charged when energy draining takes place; therefore, increasing the operational lifespan of the network is the primary purpose of energy management. Recently, major research interest in WSN has been focused with the essential aspect of localization. Several types of research have also taken place on the challenges of node localization of wireless sensor networks with the inclusion of range-free and range-based localization algorithms. In this work, the optimal positions of Sensor Nodes (SNs) are determined by proposing a novel Hybrid M-ACO – PSO (HMAP) algorithm. In the HMAP method, the improved PSO utilizes learning strategies for estimating the relay nodes' optimal positions. The M-ACO assures the data conveyance. A route discovers when it relates to the ideal route irrespective of the possibility of a system that includes the nodes with various transmission ranges, and the network lifetime improves. The proposed strategy is executed based on the energy, throughput, delivery ratio, overhead, and delay of the information packets.

Periodontal status and tooth loss impact on oral health related quality of life among Indian geriatric population

Background: Oral health is believed to be poor as individuals get older since oral problems like as dental caries, diseases of periodontium, and loss of tooth affecting such individuals are chronic and progressive conditions. Understanding whether oral disorders may have an impact on a person's quality of life requires more than merely tracking their prevalence. Therefore, while examining oral health, it is necessary to include quality of life related to the oral health (OHRQoL) metrics. Aim: To evaluate impact of tooth loss and periodontal status on oral health related quality of life among Indian elderly. Methods and materials: This study involved 2191 senior citizens and was cross-sectional in design. The elderly subjects of the Indian population (59 years of age and older) were chosen as the study population. Before obtaining their informed consent prior to the examination, each subject received a packet of information outlining the goals and methods of the study. Older respondents' oral health-related quality of life was assessed using the Geriatric Oral Health Assessment Index's Hindi translation (GOHAI).

A novel extended Kalman filter-based optimized routing approach for IoV environment

The development of intelligent transportation system has divulged towards traffic management, planning and control that requires precise neighboring vehicle location anticipation for information transmission. The crucial problem is to maintain QoS parameters in high speed and varying vehicular topology environment. The paper presents a novel EK-PGRP (Extended Kalman filter- Predictive Geographic Routing Protocol) routing approach to anticipate neighbor location and to select the propitious neighbor for advancing packets from source to destination vehicle using extended Kalman filter for real-time V2V communication in both urban and highway vehicular environment. This is acquired according to spatial and temporal movement attributes; every vehicle has an anticipation model to anticipate its own and neighboring vehicle mobility. Moreover, if LMP (Local Maximum Problem) state is encountered, i.e., where a vehicle is unable to locate any neighbor nearer to destination than itself to forward an information packet; then it uses predictive prediction algorithm to overcome that state. The precision, robustness and coherence attributes of the proposed routing approach are illustrated via extensive simulations. EK-PGRP is contrasted with K-PGRP (Kalman filter- Predictive Geographic Routing Protocol), PGRP (Predictive Geographic Routing Protocol) and GPSR (Greedy Perimeter Stateless Routing) routing protocols and results demonstrate that EK-PGRP outperformed most of the simulation cases and attained the minimum location error while ameliorating prediction accuracy of the vehicles in vehicular environment. The simulations were performed on MATLAB R2018a along with traffic simulator SUMO.

Nanostructured Lipid Carriers for Skin Depigmentation: A Modulated Aspect in Cosmetics

Background: Hyperpigmentation is a common disorder characterized by brown patches, differential skin tone and sunburns on the area of exposure. Hydroquinone (HQ) is considered the most effective agent in treatment of pigmentation but exhibits skin irritation and local toxicity at higher concentrations. Hence, HQ encapsulated Nano Lipid Carriers (NLCs) were designed and assessed as an alternative for treatment of pigmentation to reduce skin irritation without exhibiting toxicity. Objective: The objective of this study was to formulate and evaluate hydroquinone-encapsulated NLCs in cream base as a treatment in hyperpigmentation. Methods: The present formulation aims to encapsulate adequate hydroquinone in NLCs for potential application of depigmentation. Hydroquinone was formulated utilizing melt- emulsification ultrasound dispersion technique where aqueous phase consisted of water and Tween 80 whereas; lipid phase was prepared with oleic acid and glyceryl monostearate. The characteristics of final formulation were analyzed by surface morphology, percentage entrapment efficiency, ex-vivo release, in-vitro release and cell line studies. Results: Hydroquinone-encapsulated lipid nanocarriers demonstrated promising results within the size range of 22 ± 1.22 nm to 164 ± 0.75 nm and encapsulation efficiency of 78 ± 5.05 % in partially crystallized lipid-based state. The system displayed enhancement in absorption and penetration with zeta potential of -10.2 ± 1.86 mV to -24.6 ± 0.45 mV and presented substantial decrease in water loss as a result of packet formation. Conclusion: The results indicated that hydroquinone encapsulated NLCs are safe and effective for treatment of pigmented skin and works by reducing the appearance of dark patches and improving skin texture.