Scheduling Protocol Research Articles

Full-Duplex Multiple Access Mechanism for Connected Vehicles Operating at Different Autonomous Levels in NR eV2X VANETs

Future connected and autonomous vehicles (CAVs) will operate at different autonomous levels for decades. Therefore, we propose a novel prioritisation scheme according to the autonomous levels of CAVs, and a corresponding multiple access mechanism, to be named full-duplex prioritised scheduling (FDPS) protocol, to enhance the delivery of high-priority packets in future New Radio (NR) enhanced vehicle-to-everything communication (eV2X) vehicular ad hoc networks (VANETs). Comparing to the standardised sensing-based semi-persistent scheduling (SB-SPS) protocol, this paper presents how collision detection is enabled during the broadcast, how collisions are resolved, how the priority of a packet from a colliding CAV is recognised, and how the broadcast of high-priority packets is enhanced. Both protocols are evaluated through mathematical formulations and simulations in terms of average successful packet delivery rate (PDR), collision duration, and latency. Simulation results have firstly validated the mathematical analysis, they have also shown the enhancement of packets delivery in future NR eV2X VANETs when the self-interference suppression (SIS) factor is better than 16%, which is achievable by deploying the existing SIS technologies.

H∞ State Estimation for BAM Neural Networks With Binary Mode Switching and Distributed Leakage Delays Under Periodic Scheduling Protocol.

This article is concerned with the H∞ state estimation problem for a class of bidirectional associative memory (BAM) neural networks with binary mode switching, where the distributed delays are included in the leakage terms. A couple of stochastic variables taking values of 1 or 0 are introduced to characterize the switching behavior between the redundant models of the BAM neural network, and a general type of neuron activation function (i.e., the sector-bounded nonlinearity) is considered. In order to prevent the data transmissions from collisions, a periodic scheduling protocol (i.e., round-robin protocol) is adopted to orchestrate the transmission order of sensors. The purpose of this work is to develop a full-order estimator such that the error dynamics of the state estimation is exponentially mean-square stable and the H∞ performance requirement of the output estimation error is also achieved. Sufficient conditions are established to ensure the existence of the required estimator by constructing a mode-dependent Lyapunov-Krasovskii functional. Then, the desired estimator parameters are obtained by solving a set of matrix inequalities. Finally, a numerical example is provided to show the effectiveness of the proposed estimator design method.

Exploring the Non-Overlapping Visibility Regions in XL-MIMO Random Access and Scheduling

The recent extra-large scale massive multiple-input multiple-output (XL-MIMO) systems are seen as a promising technology for providing very high data rates in high user-density scenarios. Spatial non-stationarities and visibility regions (VRs) appear across the XL-MIMO array, since its large dimension is of the same order of the distances to the user-equipments (UEs). Due to the increased density of UEs in typical applications of XL-MIMO systems and the scarcity of pilots, the design of random access (RA) protocols and scheduling algorithms become challenging. In this paper, we propose a joint RA and scheduling protocol, namely non-overlapping VR XL-MIMO (NOVR-XL) RA protocol, which takes advantage of the different VRs of the UEs for improving RA performance, besides of seeking UEs with non-overlapping VRs to be scheduled in the same payload data pilot (PDP) resource. Our results reveal that the proposed scheme achieves significant gains in terms of sum-rate compared with traditional RA schemes, as well as reducing access latency and improving connectivity performance as a whole.

Cross Layer Based Dynamic Traffic Scheduling Algorithm for Wireless Multimedia Sensor Network

The data traffic volume is generally huge in multimedia networks since it comprises multimodal sensor nodes also communication takes place with variable capacity during video transmission. The data should be processed in a collision free mode. Therefore, the packets should be scheduled and prioritized dynamically. Dynamic traffic scheduling and optimal routing protocol with cross layer design is proposed here to select the energy efficient nodes and to transmit the scheduled data effectively. At first, the optimal routes are discovered by selecting the best prime nodes then the packets are dynamically scheduled on the basis of severity of data traffic. The proposed method works in two stages such as (i) Selection of chief nodes and (ii) Dynamic packet scheduling. The first stage of this mechanism is chief node selection and these chief nodes are selected for optimal routing. Selection of chief nodes is done by estimating the distance between the nodes, and energy value of the nodes. This stage makes the network energy efficient. The second stage is involved with dynamic scheduling of packets and sending the packets with respect to the Packet Priority of queue index key value. Real-time data packets (PQP1) have very high priority and it is scheduled using Earliest Deadline First Scheduling (EDFS) algorithm when compared to non-real time data packets (PQP2 and PQP3) which is scheduled on basis of First Come First Serve (FCFS) manner. This process minimizes the congestion and avoids the unnecessary transmission delay. Therefore, the results are analyzed through the simulation process and the efficiency of the proposed methodology is 56% better than the existing methodologies.

Multiple Concurrent Slotframe Scheduling for Wireless Power Transfer-Enabled Wireless Sensor Networks

This paper presents a multiple concurrent slotframe scheduling (MCSS) protocol for wireless power transfer (WPT)-enabled wireless sensor networks. The MCSS supports a cluster-tree network topology composed of heterogeneous devices, including hybrid access points (HAPs) serving as power transmitting units and sensor nodes serving as power receiving units as well as various types of traffic, such as power, data, and control messages (CMs). To this end, MCSS defines three types of time-slotted channel hopping (TSCH) concurrent slotframes: the CM slotframe, HAP slotframe, and WPT slotframe. These slotframes are used for CM traffic, inter-cluster traffic, and intra-cluster traffic, respectively. In MCSS, the length of each TSCH concurrent slotframe is set to be mutually prime to minimize the overlap between cells allocated in the slotframes, and its transmission priority is determined according to the characteristics of transmitted traffic. In addition, MCSS determines the WPT slotframe length, considering the minimum number of power and data cells required for energy harvesting and data transmission of sensor nodes and the number of overprovisioned cells needed to compensate for overlap between cells. The simulation results demonstrated that MCSS outperforms the legacy TSCH medium access control protocol and TSCH multiple slotframe scheduling (TMSS) for the average end-to-end delay, aggregate throughput, and average harvested energy.

A zonotope-based fault detection for multirate systems with improved dynamical scheduling protocols

This paper investigates the distributed fault detection problem for a class of discrete-time multi-rate systems over sensor networks with an improved communication protocol, where both unknown-but-bounded (UBB) noises and faults are comprised in two zonotopic sequences. Inspired by famous try-once-discard (TOD) protocols, a novel quasi-TOD-based protocol with dynamical weights is proposed to govern the signal transmission between the sensor nodes and the remote filter. In terms of lifting techniques, the augmented filtering error dynamics is set up a unified sampling rate. By resorting to the properties of zonotopes as well as the mathematical induction, a series of zonotopic sets confining filtering errors is first received, and then their F-radii are minimized to derive the desired filter parameters. Furthermore, a zonotope-based residual evaluation mechanism is designed to detect possibly occurred faults. Finally, a numerical example is employed to verify the availability of the presented zonotope-based fault detection scheme.

Toward Efficient Time-Sensitive Network Scheduling

Time-sensitive networks (TSNs) provide reliable, deterministic message delivery, ideal for networked control systems. Such networks are increasingly implemented in dynamic, resource-constrained avionics environments. This places pressure on the TSN scheduler to compute network flow schedules faster with slower processors, less memory, and limited power consumption. Avionics full-duplex switched Ethernet and IEEE 802.1 Time-Sensitive Networking are briefly compared and found to be largely similar in concept except for mechanisms enforcing determinism (BAG versus IEEE 802.1Qbv gate control) and the added requirement for time synchronization in time-sensitive networking. A new form of reliability known as polymorphic reconfiguration is introduced and contrasted with static, preconfigured redundancy. Scalability issues impacting TSN scheduling for polymorphic reconfiguration are derived. Preconfiguring and storing the TSN schedule for every possible network failure is infeasible in terms of memory storage. IEEE 802.1CB and other redundancy mechanisms exacerbate the problem by further increasing the number of flows that have to be reconfigured and scheduled. The computational complexity of TSN scheduling is reviewed and the notion of a processing-storage tradeoff via a schedule seed is introduced. The resource constrained scheduling challenge is addressed by analyzing tradeoffs in efficient scheduling approaches where qualitative performance metrics are inferred, high-level computational methods are compared, and suggestions for future approaches are outlined. This article contributes to time-sensitive networking scheduling capable of operating in a resource-constrained, dynamically changing network environment rather than in fixed avionics network environments to which they are limited today. Finally, the need for standards for TSN scheduling performance profiling and benchmarks as well as partial schedules and distributed TSN scheduling protocol standards is highlighted.

Flexible and Reliable Multiuser SWIPT IoT Network Enhanced by UAV-Mounted Intelligent Reflecting Surface

Intelligent reflecting surface (IRS) cooperated with the simultaneous wireless information and power transfer (SWIPT) can reinforce the desired signal and deal with the energy supply problem effectively. By leveraging the on-demand mobility of unmanned aerial vehicles (UAVs), the IRS cooperated SWIPT can be deployed in more flexible and reliable scenarios. In this article, we investigate the UAV-mounted IRS-assisted SWIPT for Internet of Things (IoT) networks. In particular, a UAV-mounted IRS is deployed to assist the information transmission and power transfer from the access point to several IoT devices simultaneously. Taking full advantage of the UAV-mounted IRS in attending multiple IoT devices flexibly, a time division multiple access (TDMA)-based scheduling protocol is proposed to serve different IoT devices alternatively during the UAV flying along an optimized trajectory with the information and power transfer executed. Then, an optimization problem of maximizing the minimum average achievable rate of multiple devices is formulated with the specific energy harvesting requirement guaranteed. To solve the nonconvex problem, we leverage the successive convex approximation and block coordinate descent methods to develop an iterative algorithm. Simulation results demonstrate that with the help of the more flexible and reliable UAV-mounted IRS, the minimum achievable rate of the IoT network can be significantly improved.

Set-membership filtering for complex networks with constraint communication channels

The set-membership filtering is studied for a class of multi-rate sampling complex networks with communication capacity constraint. For reducing communication load, the weighted try-once-discard scheduling protocol is utilized to transmit the most needed measurement. To improve the filtering performance, a novel mixed compensation method is proposed to obtain a compensatory measurement that is closer to the actual value. Accordingly, a mixed compensation dependent filter is designed, and a filtering error system is obtained. Sufficient conditions are established to ensure that the filtering error system satisfies PTk-dependent constraint. Then, a new algorithm is designed to obtain the optimized ellipsoid by minimizing the constraint matrix. Finally, an illustrative example is given to demonstrate the validity of the developed filter.

Distributed recursive filtering under random access protocols: A multirate strategy

AbstractThis article addresses the distributed recursive filtering problem for a class of time‐varying multirate systems in sensor networks with randomly occurring nonlinearities and the communication protocol. A multirate model is considered where the sampling period of the sensors is slower than the updating period of the system state. Accordingly, the lifting technique is proposed to transform the multirate system into a single‐rate system. In order to avoid data collisions, the random access protocol (RAP) scheduling is applied to determine which signal/packet selected by RAP scheduling can access the shared network for each sensor. Attention is focused on the design of a distributed recursive filter such that, in the simultaneous presence of randomly occurring nonlinearities, the multirate strategy and the RAP scheduling, an upper bound for the filtering error covariance is obtained with the help of the mathematical induction method. Furthermore, by utilizing a novel matrix simplification technique, the filter parameters are recursively calculated by minimizing the obtained upper bound. Finally, the effectiveness of the proposed distributed recursive filtering scheme is demonstrated via a numerical example.

An energy aware cluster‐based routing and adaptive semi‐synchronized MAC for energy harvesting WSN

AbstractMedium access control (MAC) layer scheduling is an intelligent solution to protract the lifetime of energy harvesting wireless sensor network (WSN) which is challenging issue in recent times. Self‐adaptive MAC protocol was working upon reinforcement learning. However, this decentralized adaptive scheduling introduces collisions and degrades the overall network performance. To fix this problem, this paper proposes novel semi‐synchronized MAC approach for energy harvesting WSN. The major objective of this work is to improve energy efficiency of the network by minimizing energy consumption which is the major issue in WSN. Proposed WSN network is modeled with dual mobile sinks with circular moving path and static sensor nodes to monitor the environment. Our novel MAC approach is initiated with unequal cluster formation by correlation based unequal clustering scheme in which multi‐objective elephant herding optimization (CUC‐MEHO) algorithm is incorporated for cluster head (CH) selection. In clustered network, all sensor nodes follow semi‐synchronized adaptive active period MAC scheduling (S2A2MAC) protocol. In this work, S2A2MAC operates upon hidden Markov model (HMM) which controls the active time period of a node in an adaptive manner. Energy efficient hop‐by‐hop intra‐cluster routing is empowered by Bayes rule enabled perfect matching (BR‐PM) algorithm. Before route selection, all candidate nodes are regarded into perfect match, partially match, and no match nodes. Furthermore, emergency data is identified by CH based on flag value and transmitted without any time delay. For emergency data transmission, extremity aware routing (EAR) algorithm is presented and EAR algorithm is functioning on hopcount and distance criteria. Finally, proposed network is evaluated by extensive simulations in NS‐3.26. Simulation upshots show better performance in percentage of dead nodes, network lifetime, energy consumption, PDR, and delay.

Opportunistic non-contiguous OFDMA scheduling framework for future B5G/6G cellular networks

In this paper, we consider the problem of resource allocation within Beyond 5G (B5G) and the envisioned 6G wireless networks with Cognitive Radio (CR) capability. CR technology allows opportunistic and dynamic access to the unused licensed spectrum bands. Unlike the conventional orthogonal frequency division multiple access (OFDMA) schemes that impose spectrum contiguity constraints in assigning the OFDMA resource blocks (RBs), the Dis-contiguous OFDMA (D-OFDMA) approach allows for flexible time–frequency RB scheduling, in which each contending CR user can access adjacent and/or non-adjacent RBs. This can provide a more efficient and flexible spectrum utilization compared to conventional OFDMA schemes. Specifically, we formulate the spectrum assignment and access problem as an optimization problem that attempts to effectively utilize the time–frequency spectrum holes of the D-OFDMA RBs. The main goal is to improve the total network throughput by maximizing the achieved sum-rate of all contending CR users subject to achieving a set of interference and performance requirement constraints. The formulated problem is classified as a binary-linear program (BLP), which is, in general, NP-hard. Thus, we develop a sub-optimal polynomial-time solution based on a relaxing-and-rounding method. Simulation results reveal that the proposed D-OFDMA RB scheduling protocol significantly improves the network throughput while maintaining fairness compared to conventional contiguous-based OFDMA protocols. Specifically, the proposed protocol achieves up to 90% and 150% performance improvements over the contiguous frequency-OFDMA and contiguous time-OFDMA, respectively.

Implementation of electronic messaging protocol for pediatric urology preoperative scheduling: A pilot study

Preparing patients for surgery is a task healthcare organizations strive to optimize. Electronic messaging (EM) provides an opportunity for streamlining components of this arduous process. Our study aims to evaluate our early experience in utilizing EM to provide preoperative information to pediatric urology patients. To assess the effectiveness of EM in preparing patients for pediatric urologic surgery. This study compared a 6-week pilot program of EM (Figure1) with traditional nurse phone calls (NPC) in preoperative instruction of pediatric urology patients. The same preoperative instructional information was provided via either source. Data collected included time and resources used by the healthcare system and patient/parent satisfaction. The EM group included 98 patients, while the NPC group included 212 patients. Case cancellation rate between the two cohorts was similar, with a 6.67% cancellation rate in the EM cohort and a 10.55% cancellation rate in the NPC cohort (z=-1.137, p=0.25). There were 4EM-related operating room delays with an average case delay of 31.5min (5-60min). Twenty-four (24%) EM patients/families required secondary phone calls, while 106 (50%) NPC required a follow up phone call (p<0.01). 94% of EM participants recommended EM for future perioperative instructions. Accounting for the average case volume within our entire children's hospital, the average total daily cost for EM is $5.96/day, as compared to an average total cost of $87.78/day to perform NPC. This represents an estimated cost savings of $81.82 per day or $21,273.20 per year, based upon average total case volume at our institution. In our initial experience, EM effectively communicates the necessary preoperative information to patients and/or families undergoing pediatric urology surgery. Our results demonstrate low case cancellation and delay rates and high patient/family satisfaction. Also demonstrated was the cost savings by replacing the NPC with EM. A great benefit of EM was the increased time it provided for nurses to perform other patient care duties, which is important given our current nationwide nursing shortage. Limitations of the study included a narrow scope assessing only pediatric urology patients as well as a short study period. Further studies will further define and refine the role of perioperative EM. Changing to an EM system for preoperative instructions in the pediatric urology population met with a high degree of patient satisfaction and decreased costs for healthcare systems without increasing case delay or cancellation rates.

Reliable state estimation for neural networks with TOD protocol and mixed compensation

This paper considers the reliable state estimation issue for discrete-time neural networks with the try-once-discard (TOD) scheduling protocol and mixed compensation strategy. For the phenomenon of medium access constraint, the measurement transmitted from sensors to the estimator is subjected to the TOD scheduling protocol. The mixed compensation is proposed to flexibly compensate those missing measurements caused by the TOD protocol. By using a novel polytopic uncertain model, a reliable state estimator is designed, where the gain matrix is determined by two vertex matrices. Then sufficient conditions are established, which ensure the error system meets the stochastic stability and the l2-l∞ performance. Finally, an illustrative example shows the validity of the proposed reliable state estimator.

Particle swarm optimization based sleep scheduling and clustering protocol in wireless sensor network

Particle swarm optimization based sleep scheduling and clustering protocol in wireless sensor network

Phase Ib study of durvalumab (MEDI4736) in combination with carbon-ion radiotherapy and weekly cisplatin for patients with locally advanced cervical cancer (DECISION study): study protocol for a prospective open-label single-arm study

IntroductionConcurrent chemoradiotherapy is considered the standard treatment strategy for locally advanced cervical cancer. Most recent reports indicate that patients with bulky tumours or adenocarcinoma subtypes have poorer local control. Carbon-ion...

Cost-Effectiveness Analysis and Microsimulation of Serial Multiparametric Magnetic Resonance Imaging in Active Surveillance of Localized Prostate Cancer.

Many localized prostate cancers will follow an indolent course. Management has shifted toward active surveillance (AS), yet an optimal regimen remains controversial especially regarding expensive multiparametric magnetic resonance imaging (MRI). We aimed to assess cost-effectiveness of MRI in AS protocols. A probabilistic microsimulation modeled individual patient trajectories for men diagnosed with low-risk cancer. We assessed no surveillance, up-front treatment (surgery or radiation), and scheduled AS protocols incorporating transrectal ultrasound-guided (TRUS) biopsy or MRI based regimens at serial intervals. Lifetime quality-adjusted life-years and costs adjusted to 2020 US$ were used to calculate expected net monetary benefit at $50,000/quality-adjusted life-year and incremental cost-effectiveness ratios. Uncertainty was assessed with probabilistic sensitivity analysis and linear regression metamodeling. Conservative management with AS outperformed up-front definitive treatment in a modeled cohort reflecting characteristics from a multi-institutional trial. Biopsy decision conditional on positive imaging (MRI triage) at 2-year intervals provided the highest expected net monetary benefit (incremental cost-effectiveness ratio $44,576). Biopsy after both positive and negative imaging (MRI pathway) and TRUS biopsy based regimens were not cost-effective. MRI triage resulted in fewer biopsies while reducing metastatic disease or cancer death. Results were sensitive to test performance and cost. MRI triage was the most likely cost-effective strategy on probabilistic sensitivity analysis. For men with low-risk prostate cancer, our modeling demonstrated that AS with sequential MRI triage is more cost-effective than biopsy regardless of imaging, TRUS biopsy alone or immediate treatment. AS guidelines should specify the role of imaging, and prospective studies should be encouraged.

On extended state estimation for nonlinear uncertain systems with round-robin protocol

This work studies the state estimation problem for nonlinear uncertain systems over a shared communication channel. We transform the original system into an extended state system to handle the nonlinear uncertainty. The round-robin protocol is used to overcome the communication capacity constraint by sending the measurements periodically. The measurements’ structure is changed by the scheduling protocol, which may cause the round-robin-induced periodic extended state system (RRIPESS) to be unobservable. A necessary and sufficient condition of a class of RRIPESS’s observability is established. An extended state estimator is designed. The upper bound of the priori estimation error covariance is derived via a set of periodic Riccati equations (PREs). The stability of these PREs is ensured by the detectability and the stabilizability of the original system’s parameters. In addition, we give an iterative algorithm to improve the upper bound by optimizing a set of scalars induced by Young’s inequality. Finally, a simulation example is given to illustrate the effectiveness of the developed scheme.

Hierarchical Clustering Nodes Collaborative Scheduling in Wireless Sensor Network

Network lifetime and coverage are the key evaluation metrics of Wireless Sensor Networks (WSNs). Aiming at network lifetime, Hierarchical Clustering-task Scheduling Policy (HCSP) breaks the traditional clustering framework, but it doesnt fully consider the network coverage problem. We propose a Hierarchical Clustering Node Collaborative Scheduling (HCNCS) protocol that optimizes HCSP to extend the network lifetime and improves the coverage performance of WSNs by nodes collaborative sensing. According to the deployment location, HCNCS classifies nodes into Node Collaborative Sensing Disks(NCSDs), which as units for data sensing and transmission. Nodes are rotated in WSNs to balance the energy consumption and through collaborative sensing to improve the coverage of NCSDs. In addition, HCNCS constrains the number of clusters by NCSDs classification based on K-means to reduce the communication energy consumption of clustering. Based on the HCNCS, this paper further proposes an Enhanced Hierarchical Clustering Node Collaborative Scheduling (EHCNCS) protocol. Compared with HCNCS, EHCNCS selects NCSDs according to Node Collaborative Scheduling (NCS) algorithm after clustering, which improves the coverage capability of NCSDs at the cost of increasing a small amount of the communication energy consumption. EHCNCS also rotates Cluster Heads (CHs) by the CH rotation candidate table to balance network energy consumption. The extensive simulations show that HCNCS has an obvious advantage over HCSP in terms of network lifetime and network coverage. Compared with HCNCS, EHCNCS significantly prolongs the network lifetime of WSNs at the expense of a bit of coverage performance.

Scheduling of over-actuated networked control systems

We investigate the scenario where an over-actuated plant is controlled over a network. We concentrate on the effect of two network-induced phenomena: varying transmission intervals and scheduling, in the sense that only one of the actuators receives new data at each transmission instant. We present an emulation-based solution for the controller design, i.e., the controller is first designed to stabilize the origin of the plant ignoring the network and second, the packet-based network is taken into account and conditions on the maximum allowable transmission interval (MATI) and the scheduling protocol are given to preserve the stability of the closed-loop system. Our results are tailored to over-actuated plants leading to significant improvements compared to applying off-the-shelf results available in the literature. In particular, a new model is derived and new conditions on the scheduling protocol are given, which lead to a two-measure stability property for the networked control system. We illustrate how new classes of scheduling protocols can be derived by exploiting over-actuation, which leads to larger MATI bounds compared to applying existing results, as shown on a numerical example.