Total Average Delay Research Articles

The performance of priority rules for the decentralized resource-constrained multi-project scheduling

Decentralized resource-constrained multi-project scheduling (DRCMPSP) is becoming increasingly common in construction, supply chains, and many other industrial disciplines. DRCMPSP faces difficult decisions in resolving resource conflicts to generate a baseline schedule to optimize global objectives. We propose an agent-based approach to address the DRCMPSP based on two global objectives: average project delay and total project delay. A heuristic based on the priority rule (PR) is developed to coordinate the global resource allocation. A comprehensive analysis of 30 PRs was conducted on 16,000 portfolios containing 48,000 projects . We confirmed that using the same PR to allocate global resources on all occasions often results in unnecessarily poor performance. The best PR depends on project and portfolio characteristics such as serial/parallel indicators, global resource distribution, and tightness. Moreover, the best PR differs from various perspectives (e.g., projects and portfolios). We summarized our results in three decision tables and further distilled these results for practical use, which only provide a rough estimate of the project and portfolio characteristics.

Enhanced Traffic Congestion Management with Fog Computing - A Simulation-Based Investigation using IFOG-Simulator

Accurate latency computation is essential for the Internet of Things (IoT) since the connected devices generate a vast amount of data that is processed on cloud infrastructure. However, the cloud is not an optimal solution. To overcome this issue, fog computing is used to enable processing at the edge while still allowing communication with the cloud. Many applications rely on fog computing, including traffic management. In this paper, an Intelligent Traffic Congestion Mitigation System (ITCMS) is proposed to address traffic congestion in heavily populated smart cities. The proposed system is implemented using fog computing and tested in a crowdedCairo city. The results obtained indicate that the execution time of the simulation is 4,538 seconds, and the delay in the application loop is 49.67 seconds. The paper addresses various issues, including CPU usage, heap memory usage, throughput, and the total average delay, which are essential for evaluating the performance of the ITCMS. Our system model is also compared with other models to assess its performance. A comparison is made using two parameters, namely throughput and the total average delay, between the ITCMS, IOV (Internet of Vehicle), and STL (Seasonal-Trend Decomposition Procedure based on LOESS). Consequently, the results confirm that the proposed system outperforms the others in terms of higher accuracy, lower latency, and improved traffic efficiency.

LEO satellites selection-based computation offloading algorithm in aircraft–satellite multi-access edge computing networks

The emergence of sixth-generation (6G) mobile networks and non-terrestrial networks (NTNs) has led to increased interest in low Earth orbit (LEO) satellite-based communication networks for their potential to provide global coverage and ubiquitous connectivity. In this paper, we investigate the LEO satellites selection-based computation offloading problem in the aircraft–satellite multi-access edge computing (ASMEC) network, where LEO satellites and edge computing processors are integrated to provide ubiquitous and low-latency communication and computation services for aircraft during flights. In contrast to most existing works, which directly assume a fixed number of satellites or orbits in satellite-based MEC networks, we investigate the problem of how many satellites and which satellites to select in the ASMEC network. Our objective is to minimize the average total time delay of tasks during aircraft–satellite computation offloading. To achieve this, we formulate a nonlinear integer programming (NLIP) problem and propose the LEO satellites selection-based computation offloading (LSSBCO) algorithm to solve it, which includes the shortest aircraft–satellite distance based access satellite selection (ASS-SD) algorithm and the nearest k(t) neighboring satellites selection (NSS-k(t)) algorithm. We evaluate the performance of the LSSBCO algorithm in terms of the average total time delay, the maximum throughput, the average aircraft–satellite distance, the average connection duration, and the number of satellite handovers. Numerical results show that the proposed algorithm outperforms the benchmark algorithms with a lower average total time delay.

Key technologies of earthquake early warning system for China’s high-speed railway

PurposeThe purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.Design/methodology/approachThe paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.FindingsThe study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.Originality/valueThe paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

Real-Time Adjustment Method for Metro Systems with Train Delays Based on Improved Q-Learning

This paper presents a solution to address the challenges of unexpected events in the operation of metro trains, which can lead to increased delays and safety risks. An improved Q-learning algorithm is proposed to reschedule train timetables via incorporating train detention and different section running times as actions. To enhance computational efficiency and convergence rate, a simulated annealing dynamic factor is introduced to improve action selection strategies. Additionally, importance sampling is employed to evaluate different policies effectively. A case study of Shenzhen Metro is conducted to demonstrate the effectiveness of the proposed method. The results show that the method achieves convergence, fast computation speed, and real-time adjustment capabilities. Compared to traditional methods such as no adjustment, manual adjustment, and FIFO (First-In-First-Out), the proposed method significantly reduces the average total train delay by 54% and leads to more uniform train headways. The proposed method utilizes a limited number of variables for practical state descriptions, making it well suited for real-world applications. It also exhibits good scalability and transferability to other metro systems.

Research on weighted energy consumption and delay optimization algorithm based on dual‐queue model

AbstractThis article investigates a mobile edge computing (MEC) network assisted by multiple unmanned aerial vehicles (UAVs) to address the computational and offloading requirements for mobile intelligent terminals (MITs) within crowded venues. The objective is to tackle intricate task processing and diminish MITs' waiting times. Considering the randomness of task arrival at the MITs and the imbalance between the amount of data and computation for complex tasks, a dual‐queue model with data cache queue and computation queue is proposed, with minimizing the weighted system total energy consumption and average delay as the optimization objectives. Lyapunov optimization theory is employed to convert the stochastic optimization problem into a deterministic one, and the initial deployment quantity and hovering position of the UAVs are determined by the density‐based spatial clustering of applications with noise (DBSCAN) method with noise. Then PPO algorithm for MIT task, resource allocation, and UAV trajectory optimization. Numerical results display the proposed scheme can efficaciously diminish energy consumption and delay by 10% and 33% respectively, compared with the baseline scheme. This paper proposes a practical and feasible solution for stochastic computing offloading in UAV‐assisted MEC, which fills the gap in existing research on regarding the consideration of complex task imbalances.

Patient experiences of endometriosis diagnosis: A mixed methods approach.

To examine patient-described experiences of endometriosis diagnosis. Mixed-methods study. Online patient-led endometriosis support groups. People with endometriosis aged over 18. A survey with qualitative and quantitative questions was distributed through online patient-led endometriosis support groups. Descriptive statistics were used to analyse quantitative data, and thematic analysis was used for qualitative responses. Quantitative and qualitative data were triangulated to examine patient experiences of endometriosis diagnosis across age groups. Experiences of endometriosis diagnosis among people with endometriosis. A total of 2017 people with endometriosis from 63 countries responded to the questionnaire. Patients experienced an average delay of 3.7 years between symptom onset and first presentation of symptoms to a physician (the care-seeking delay) and an average delay of 5.8 years between first presentation of symptoms to a physician and diagnosis of endometriosis (the healthcare-related delay). Patients experienced an average total diagnostic delay of 9.6 years. Participants aged over 35 at the time of the study reported significantly longer times to receive an endometriosis diagnosis (mean 10.7, 95% confidence interval [CI] 10.2-11.2) compared with participants age 18-24 (6.8, 95% CI 6.1-7.5 years). The qualitative analysis identified the following themes: physicians normalised endometriosis symptoms, patients felt their symptoms were ignored by physicians because they were considered unreliable, and participant character attributes (e.g. age, appearance, weight or physical ability) led to clinician dismissal. People with endometriosis of all age groups reported pervasive negative healthcare experiences during their adolescence. Patients experience delays in seeking care and in receiving a diagnosis once presenting for care.

A multi-objective nonlinear integer programming model for mixed runway operations within the TMAs

AbstractGlobal air traffic demand has shown rapid growth for the last three decades. This growth led to more delays and congestion within terminal manoeuvring areas (TMAs) around major airports. The efficient use of airport capacities through the careful planning of air traffic flows is imperative to overcome these problems. In this study, a mixed-integer nonlinear programming (MINLP) model with a multi-objective approach was developed to solve the aircraft sequencing and scheduling problem for mixed runway operations within the TMAs. The model contains fuel cost functions based on airspeed, altitude, bank angle, and the aerodynamic characteristics of the aircraft. The optimisation problem was solved by using the $\varepsilon$ -constraint method where total delay and total fuel functions were simultaneously optimised. We tested the model with different scenarios generated based on the real traffic data of Istanbul Sabiha Gökçen Airport. The results revealed that the average total delay and average total fuel were reduced by 26.4% and 6.7%, respectively.

IMPLEMENTASI KOMUNIKASI DATA MENGGUNAKAN PROTOKOL RF24NETWORK PADA SISTEM PEMANTAUAN KONDISI RUANGAN BERBASIS JARINGAN SENSOR NIRKABEL

Wireless Sensor Network (WSN) is an infrastructure consisting of a number of sensor nodes that are distributed in certain environments and coordinated using a wireless network. WSN can be implemented using the nRF24L01 module. One protocol that supports the nRF24L01 module is the RF24 protocol. But for the implementation of monitoring the vast room conditions this protocol has the disadvantage of using a single-hop mechanism. So that for a large area range, multi-hop mechanism is needed. The RF24Network protocol is a protocol designed to meet the needs of RF24-based multi-hop mechanisms, users simply build a header that contains the correct destination address and the network will forward it to the destination node. In accordance with the above problems, the authors implement sensor nodes using Arduino Nano as Microcontroller, nRF24L01 for communication media and DHT11 to acquire sensor data. From the implementation results obtained network performance for monitoring the condition of the room with the level of accuracy of data transmission and delay as follows. Single-hop data transmission mechanism without barrier distance 3-12 meters 100% accuracy, 15 meters 70%, 18 meters 40%, 21 meters 0% with a total average delay of 145 ms, with a distance barrier of 3-9 meters 100% accuracy , 12 meters 60%, 15 meters 30%, 18 meters 0% with a total average delay of 276 ms. The multi-hop mechanism of data transmission accuracy reaches 100% with average delay (1 hop without barrier 110 ms with a total distance of 24 meters, with a barrier of 270 ms with a total distance of 18 meters. 2 hops without barrier 270 ms with a total distance of 36 meters , with a 350 ms barrier with a total distance of 27 meters, 3 hops without a 280 ms barrier with a total distance of 48 meters, with a barrier of 260 ms with a total distance of 36 meters)..

Model of optimal distribution of network resources with constraints on quality of service indicators

Existing algorithms and mathematical models of queuing at the nodes of a telecommunications network are considered in this paper. The necessity of coordinated solutions to problems of distribution of channel and buffer resources of the network is shown. A model for the optimal distribution of channel and buffer resources on network nodes has been developed. The optimization (minimization) criterion is the total average packet delay with constraints on the quality of service (QoS) indicators of heterogeneous flows. The optimization problem is presented as a constrained nonlinear programming problem and solved using the “fmincon” program of the optimization toolbox MATLAB package.

Space-Time Resource Integrated Optimization Method for Time-of-Day Division at Intersection Based on Multidimensional Traffic Flows

Based on the change trends of traffic flow in different controlled directions at an intersection, the space-time resource integrated optimization method for TOD (time-of-day) division based on multidimensional traffic-flow data is proposed in this paper. By analyzing the traffic-flow data of 8, 4, 2, and 1 dimensions commonly used at the intersection, the dynamic Fisher algorithm is used to complete the time segment division of the traffic-flow sequence of different dimensions. On this basis, the preliminary TOD division is completed, and the phase timing and lane-use assignment corresponding to the preliminary time periods are optimized. Then, the adjacent time periods are merged and tested to complete the final result of the TOD division. In order to verify the effectiveness of the proposed method, the schemes based on traffic-flow data of different dimensions are carried out by using the data at an actual intersection in Wuhu City, and the total and average vehicle delays of different schemes throughout the day are evaluated by VISSIM. The results show that the more dimensions of traffic flow data are adopted, the more refined the TOD division scheme is, and the less the total delay and average delay at intersections throughout the day are. In particular, the TOD division scheme after further optimizing the lane-use assignment can further reduce the total and average vehicle delay throughout the day. It shows that the method using multidimensional traffic-flow data at an intersection to carry out the integrated optimization of TOD division, lane-use assignment, and phase timing has good applicability.

Bunching Effect of Motorised Two Wheelers on Delay at Signalized Intersections under Heterogeneous Traffic Conditions

The performance of signalized intersections is usually evaluated by measuring delay occurring to vehicles which are passing through the signalized intersections. The field delay under heterogeneous traffic condition will be influenced by many parameters such as cycle time, traffic volume, degree of saturation, percentage of different vehicle categories especially the bunching of motorized two wheelers. In the present research work, the delay is estimated from the field using Indian Highway Capacity Manual (Indo HCM) (2017) procedure and the bunching effect of motorised two wheelers is studied on delay at signalized intersections under heterogeneous traffic conditions. Also, a linear delay model is developed for control delay estimation considering heterogeneous traffic conditions. From the field data, it was observed that, the percentage of motorised two wheelers in a bunch is varying from 37% to 57% whereas the total average delay occurred to vehicles which are passing the approach is varying from 106 s to 163 s respectively.

Preventable operating room delays in robotic-assisted thoracic surgery: Identifying opportunities for cost reduction

BackgroundThis study aimed to characterize the types of intraoperative delays during robotic-assisted thoracic surgery, operating room staff awareness/perceptions of delays, and cost impact of delays on overall operative costs. MethodsRobotic-assisted thoracic surgery cases from May to August 2019 were attended by 3 third-party observers to record intraoperative delays. The postoperative surveys were given to operating room staff to elicit perceived delays. Observed versus perceived delays were compared using the McNemar test. Direct costs and charges per delay were calculated. ResultsForty-four cases were observed, of which a majority were lobectomies (n = 38 [86%]). A total of 71 delays were recorded by observers, encompassing 75% of cases (n = 33), with an average delay length of 3.6 minutes (±5.3 minutes). The following delays were observed: equipment failure (n = 40, average delay length 5.0 minutes (±6.5 minutes), equipment missing (n = 15, 2.2 minutes [±1.4 minutes]), staff unfamiliarity with equipment (n = 4, 3.4 minutes [± 1.5 minutes]), and other (n = 12, 4.5 minutes [±5.3 minutes]). The detection rates for any intraoperative delay were consistently lower for all of the operating room team members compared with observers, including surgeons (34.3% vs 77.1%; P = .0003), first assistants (41.9% vs 74.2%; P = .0075), surgical technologists (39.4% vs 72.7%; P = .0045), and circulating nurses (41.18% vs 76.47% minutes; P = .0013). The average operating room variable direct cost of delays based on the average total delay length per case was $225.52 (±$350.18) and was 1.6% (range 0–10.6%) of the total case charges. ConclusionThe lack of perception of intraoperative delays hinders operating teams from effectively closing the variable cost gaps. Future studies are needed to explore methods of increasing perception of delays and opportunities to improve operating room efficiency.

Saturated arterial coordinate control strategy optimization considering macroscopic fundamental diagram

MFD is widely used in traffic state evaluation because of its description of the macro level of urban road net-work. Aiming at the control strategy optimization problem of urban arterial road network under saturated traffic flow state, this study analyzes the MFD characteristics of a typical three-segment "ascending-stable-descending segment" and its advantages in characterizing the macroscopic operation efficiency of the road network, a arte-rial coordination control strategy considering MFD is proposed. According to the characteristics of MFD, it is proposed that the slope of the ascending segment and the capacity of the road network represent the operating efficiency of the free flow and saturated flow of the road network respectively. The traffic flow and density data of road segment are obtained by the road detector through Vissim simulation software. Aiming at the problem that the MFD is too discrete due to unreasonable control strategy or traffic condition, and in order to extract the MFD optimization target indicators, it is proposed to extract the key boundary points of the MFD by the “tic-tac-toe” method and divide the MFD state by Gaussian mixture clustering. The genetic algorithm integrates the multi-objective particle swarm algorithm as the solution algorithm, and the simulation iterative process is com-pleted through Python programming and the com interface of Vissim software. In order to verify the validity of the model and algorithm, the actual three-intersections arterial road network is used for verification, and the model in this study is compared with the optimization model without considering MFD, the model solved by traditional algebraic method, and the optimization model solved by typical multi-objective particle swarm. Re-sults show that the model in this research performs well in efficiency indicators such as total delay, average delay, and queue coefficient. At the same time, the MFD form has highest stability, the control effect is the best in the saturated state. The solution algorithm GA-MOPSO also has a better solution effect.

Development of a Non-Contacting Muscular Activity Measurement System for Evaluating Knee Extensors Training in Real-Time.

To give people more specific information on the quality of their daily motion, it is necessary to continuously measure muscular activity during everyday occupations in an easy way. The traditional methods to measure muscle activity using a combination of surface electromyography (sEMG) sensors and optical motion capture system are expensive and not suitable for non-technical users and unstructured environment. For this reason, in our group we are researching methods to estimate leg muscle activity using non-contact wearable sensors, improving ease of movement and system usability. In a previous study, we developed a method to estimate muscle activity via only a single inertial measurement unit (IMU) on the shank. In this study, we describe a method to estimate muscle activity during walking via two IMU sensors, using an original sensing system and specifically developed estimation algorithms based on ANN techniques. The muscle activity estimation results, estimated by the proposed algorithm after optimization, showed a relatively high estimation accuracy with a correlation efficient of R2 = 0.48 and a standard deviation STD = 0.10, with a total system average delay of 192 ms. As the average interval between different gait phases in human gait is 250–1000 ms, a 192 ms delay is still acceptable for daily walking requirements. For this reason, compared with the previous study, the newly proposed system presents a higher accuracy and is better suitable for real-time leg muscle activity estimation during walking.

On Efficient Service Function Chaining in Hybrid Software Defined Networks

To minimize operating expenses (OPEX) and enhance flexibility for network service provisioning, network function virtualization (NFV) is used to chain an ordered sequence of virtualized network functions (VNFs), also known as service function chain (SFC), which can be placed on commodity servers. As a highly complementary to NFV, software-defined networking (SDN) can offer an agile way of VNF orchestration with the capability of fine-granularity network control over flows. However, one-step migration to SDN is impossible in ISP networks. Thus, in this paper we resort to hybrid SDN to implement SFC provisioning. By jointly optimizing SDN deployment that largely determines capital expenditures (CAPEX) and VNF placement that decides OPEX, we manage to make a tradeoff between CAPEX and OPEX, and to find out an appropriate SDN deployment rate for network operator. We first formulate the problem as an integer linear programming (ILP) model <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> , then, reformulate it with column generation technique and decomposition theory to develop a distributed approximation algorithm CGPD which obtains a tight upper bound of optimal solution to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> . In order to better decrease CAPEX, a dynamic programming-based heuristic EOES giving importance to effective resource sharing is further designed based on a hidden Markov model. The simulation results indicate that, the difference between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> and CGPD is marginal. CGPD outperforms EOES in terms of total cost, average delay and bandwidth utilization, and EOES on the other hand demands 20% SDN deployment rate which is half of that of CGPD.

Application of 5G technology to conduct tele-surgical robot-assisted laparoscopic radical cystectomy.

The aim of this study was to test the effectiveness, safety and stability of the 5G communication technology in clinical laparoscopic telesurgery. An ultra-remote radical cystectomy (network communication distance of nearly 3000km) was performed on patient diagnosed with T2N0M0 stage bladder cancer using a domestically produced "MicroHand" surgical robot. The network delay, operative time, blood loss, intraoperative complications, postoperative recovery, and hospitalisation time were recorded. The 5G network was used throughout the operation, with an average total delay of 254ms. The operation went well and the patient recovered smoothly. Ultra-remote clinical laparoscopic surgery can be performed safely and smoothly. More importantly, our model can provide insights for promoting the future development of telesurgery in China.

Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic

We develop and assess centralized and decentralized signal control systems with short-term origin-destination (OD) demands as inputs. Considering each intersection turning movement as a virtual link, we assign traffic demand to paths based on minimal instantaneous travel time. Then, the optimal control is formulated using a G/G/n/FIFO open queueing network model (QNM). We also solve the issue of optimal control using a three-step naïve method for the centralized system with the new inputs. Because the optimization of large-scale network traffic signals can involve sizeable numbers of decision variables and nonlinear constraints, making it a nondeterministic polynomial time (NP) complete problem, we further decompose the centralized system into a decentralized system where the network is divided into subnetworks. Each subnetwork has a dedicated agent that optimizes signals within it. Furthermore, traffic demand for the entire network is decomposed into demands for subnetworks via path decomposition index (PDI). The proposed control systems are applied to test scenarios constructed using different demand profiles in grid networks. We also investigate the impact of network decomposition strategy on signal control system performance. Results show that network decomposition with smaller subnetworks results in less computational time (CT) but increased average travel time (ATT) and total travel delay (TTD).

Secure Location-Aided Routing Protocols With Wi-Fi Direct For Vehicular Ad Hoc Networks

Secure routing protocols are proposed for the vehicular ad hoc networks. The protocolsintegrate the security authentication process with the Location-Aided Routing (LAR) protocol to supportWi-Fi Direct communications between the vehicles. The methods are robust against various security threats.The security authentication process adopts a modified Diffie-Hellman key agreement protocol. The Diffie-Hellman protocol is used with a short authentication string (SAS)-based key agreement over Wi-Fi Directout-of-band communication channels. It protects the communication from any man-in-the-middle securitythreats. In particular, the security process is integrated into two LAR routing schemes, i.e., the request-zoneLAR scheme and the distance-based LAR scheme.We conduct extensive simulations with different networkparameters such as the vehicular node density, the number of the malicious nodes, and the speed of thenodes. Simulation results show that the proposed routing protocols provide superior performance in securedata delivery and average total packet delay. Also, the secure distance-based LAR protocol outperforms thesecure request-zone LAR protocol.

SDN-based gateway architecture for electromagnetic nano-networks

Electromagnetic nano-communication has increasing attention in recent years. Several developments have been achieved in the fabrication, communication and management of various nano-network devices serving potential applications ranging from software-defined metamaterials, wireless robotic materials and body-centric communication. Such applications need uplink and downlink communication between the deployed nano-network and the external macro-world or the Internet through nano-interfaces. As a result, heterogeneous nano-network devices and their interoperability in different Internet of nano-things applications become new challenges for nano-network communication. In this regard, dynamic, flexible and distributed micro/nano-gateways can accommodate such sustainable issues and make the nano-network fully operational, regardless of the adopted application domain or the protocols used in communication. Network functions virtualization and software-defined networking technologies altogether can overcome these challenges. This article proposes SDN-based architecture and software module for the micro/nano-gateway. The proposed software module converts data formats and protocols between nano-network and traditional network domains allowing the nano-devices to be linked to the Internet. A prototype of the module is built, and the performance of the proposed algorithm is evaluated based on two communication scenarios; single tenant and multitenant. The result shows the effect of the total number of connected nano-devices and the number of packets sent by each device on the total average round-trip processing delay and the overall throughput of the micro/nano-gateway.