Total Average Delay Research Articles

5G communication resource allocation strategy based on edge computing

Aiming at the problem that most of the existing strategies cannot deal with the explosive growth of user data after the popularization of 5G communication technology, this paper proposes a 5G communication resource allocation strategy based on edge computing. First, the 5G communication network is virtualized to build mobile edge computing system with multiple mobile user equipment and multiple servers. Then, the communication model and calculation model of system are established. Besides, the optimization objectives are proposed based on this, which can minimize total user cost and maximize the success rate of task offloading and successful execution rate. Finally, the resource allocation problem is formalized and modelled as Markov model. The objective is to minimize the ratio of overall system energy consumption to task execution time and delay constraints, the optimal communication resource allocation scheme is obtained by solving it based on Q-learning algorithm. The experimental demonstration of proposed strategy is carried out based on the python simulation platform. Experimental results show that the total system cost and average delay of proposed strategy do not exceed 500 W and 1000 ms under the experimental conditions; its overall performance is better than other comparison strategies, can meet the interest requirements of users and service providers.

Computation Offloading and Shunting Scheme in Wireless Wireline Internetwork

In the multi-server multi-access edge computing (MEC) system, the computing capacity could be insufficient and the computing resource could be over-utilized when an excessive number of computing tasks are offloaded for execution. To alleviate the excessive burden in the multi-server MEC system and tap the underutilized resources of wired edge devices, which are called edge computers in this paper, we investigate the computation offloading and shunting scheme in the wireless wireline internetwork. We formulate an optimization problem to minimize the average total time delay and use the deep reinforcement learning method to obtain the optimal shunting policy. By sensing the state of the wireless wireline internetwork, the proposed scheme can adaptively adjust the shunting ratio and utilize the resources of MEC servers and edge computers intelligently and jointly. Finally, we evaluate the computational complexity and validate the convergence property of this scheme. The extensive simulation results demonstrate that this scheme can improve the resource productivity and reduce the average total time delay.

Optimal patient protocols in regional acute stroke care

In acute stroke care two proven reperfusion treatments exist: (1) a blood thinner and (2) an interventional procedure. The interventional procedure can only be given in a stroke centre with specialized facilities. Rapid initiation of either is key to improving the functional outcome (often emphasized by the common phrase in acute stroke care “time=brain”). Delays between the moment the ambulance is called and the initiation of one or both reperfusion treatment(s) should therefore be as short as possible. The speed of the process strongly depends on five factors: patient location, regional patient allocation by emergency medical services (EMS), travel times of EMS, treatment locations, and in-hospital delays. Regional patient allocation by EMS and treatment locations are sub-optimally configured in daily practice. Our aim is to construct a mathematical model for the joint decision of treatment locations and allocation of acute stroke patients in a region, such that the time until treatment is minimized. We describe acute stroke care as a multi-flow two-level hierarchical facility location problem and the model is formulated as a mixed integer linear program. The objective of the model is the minimization of the total time until treatment in a region and it incorporates volume-dependent in-hospital delays. The resulting model is used to gain insight in the performance of practically oriented patient allocation protocols, used by EMS. We observe that the protocol of directly driving to the nearest stroke centre with special facilities (i.e., the mothership protocol) performs closest to optimal, with an average total time delay that is 3.9% above optimal. Driving to the nearest regional stroke centre (i.e., the drip-and-ship protocol) is on average 8.6% worse than optimal. However, drip-and-ship performs better than the mothership protocol in rural areas and when a small fraction of the population (at most 30%) requires the second procedure, assuming sufficient patient volumes per stroke centre. In the experiments, the time until treatment using the optimal model is reduced by at most 18.9 minutes per treated patient. In economical terms, assuming 150 interventional procedures per year, the value of medical intervention in acute stroke can be improved upon up to € 1,800,000 per year.

Smart Dynamic Traffic Monitoring and Enforcement System

Enforcement of traffic rules and regulations involves a wide range of complex tasks, many of which demand the use of modern technologies. variable speed limits (VSL) control is to change the current speed limit according to the current traffic situation based on the observed traffic conditions. The aim of this study is to provide a simulation-based methodological framework to evaluate (VSL) as an effective Intelligent Transportation System (ITS) enforcement system. The focus of the study is on measuring the effectiveness of the dynamic traffic control strategy on traffic performance and safety considering various performance indicators such as total travel time, average delay, and average number of stops. United Arab Emirates (UAE) was selected as a case study to evaluate the effectiveness of this strategy. A micro simulation software package VISSIM with add-on module VisVAP is used to evaluate the impacts of VSL. It has been observed that VSL control strategy reduced the average delay time per vehicle to around 7%, travel time by 3.2%, and number of stops by 48.5%. Dynamic traffic control strategies also alleviated congestion by increasing the capacity of the bottleneck section and improving safety. Results of this study would act as a guidance for engineers and decision makers to new traffic control system implementation.

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.

A New Framework for Mobile Edge Caching by Proposing Flexible User in Heterogeneous Cellular Networks

The bursting increase in requesting wireless data has caused several issues in network peak-traffic duration. This negatively results in significant data delivery delay imposed on users that can eventually impact the network's quality of service and users' quality of experience. In this research, regarding mobile edge caching as a potential solution to decrease such delay, we propose a new framework in which we introduce the concept of the flexible user where he requests for a set of multiple files from the library with a unique feature, e.g., 5 movies within comedy genre from the library in the peak-traffic duration. The satisfactory criterion for the flexible user is to receive any of the files within the requested set. This definition of the flexible user indicates a new concept which captures interesting scenarios. In order to model this concept, we generalize the conventional Zipf distribution to a multivariate one as the modeling method for popular data. We formulate the problem of finding the optimal cache data placement, which minimizes the average total delivery delay in the network while satisfying the helpers' cache size constraints. To this end, we derive the average delivery delay per user as well as the average total delivery delay in the network, according to the new generalized Zipf distribution. Finding the optimal solution is proved to be NP-Hard. We leverage on the problem property to propose an efficient approximation method, called greedy algorithm, which performs within a constant factor as good as the optimal solution. Afterwards, we propose an algorithm called speedy-greedy to significantly reduce the computational complexity of the greedy algorithm while achieving the same performance. Simulation results indicate that our proposed framework significantly decreases the average total delivery delay of the system model that can help the network maintain its quality of service in network peak-traffic duration.

Throughput and delay optimization for NOMA systems with energy harvesting

In this paper, we analyse and optimise the total throughput and average delay in non orthogonal multiple access (NOMA) with energy harvesting. The source harvest energy from radio frequency (RF) signals received from another node A. Node A can be any node transmitting RF signals. The frame with duration T contains two time slots. The first slot has duration δT and is dedicated to energy harvesting where 0 < δ < 1 is harvesting duration percentage. The second slot has duration (1 - δ)T and is dedicated to transmission of a linear combination of symbols to N NOMA users. We optimise harvesting duration and power allocation coefficient to maximise the total throughput or minimise the average delay. Our theoretical derivation are valid for Rayleigh fading channels.

Smart Door System Prototype with a Control Based on Biometric Palmprint and the Internet of Things

Safety is important in terms of comfort and security in a home, because a house is a place where people live and store valuable items. However, conventional keys that are widely used today are still vulnerable to break-ins. Therefore, a reliable and qualified security system is needed to safeguard a person’s home. To overcome this problem, this study proposed a security system to access the door of a house to maintain the home’s security. This door access security system is based on Palmprint, in which a certain line on a person’s palm is used to open the door and gain access into the house. Palmprint is supported by the Internet of Things system so that residents can remotely control and access the door lock. The use of biometric authentication will replace a conventional key so that the door will only be opened if the lines on the palm of the hand can be identified in accordance with the data registered by the owner. If a burglary occurs or if the lock is forced, the system will notify the residents of the house through their Palmprint application. The results show that the network system works optimally in the Line of Sight scenario with a distance of 5 meters, and it produces a data delay measuring 0.255436 s; moreover, a throughput of 8825,933 bytes/s is obtained from end-to-end testing of the total system in the 5 meter Line of Sight scenario with a total average delay of 0.570077 s and an average throughput of 11776.27 bytes/s.

Analisis Perbandingan Algoritma Static Round-Robin dengan Least-Connection Terhadap Efisiensi Load Balancing pada Load Balancer Haproxy

In IT networking, load balancing used to share the traffic between backend servers. The idea is to make effective and efficient load sharing. Load balancing uses scheduling algorithms in the process includes Static round-robin and Least-connection algorithm. Haproxy is a load balancer that can be used to perform the load balancing technique and run by Linux operating systems. In this research, Haproxy uses 4 Nginx web server as backend servers. Haproxy act as a reverse proxy which accessed by the client while the backend servers handle HTTP requests. The experiment involves 20 Client PCs that are used to perform HTTP requests simultaneously, using the Static round-robin algorithm and Least-connection on the haproxy load balancer alternately. When using Static round-robin algorithm, the results obtained average percentages of CPU usage successively for 1 minute; 5 minutes; and 15 minutes are; 0.1%; 0.25%; and 1.15% with average throughput produced is 14.74 kbps. Average total delay produced 64.3 kbps. The average total delay and jitter is 181.3 ms and 11.1 ms, respectively. As for the Least-connection algorithm average percentage obtained successively for 1 minute; 5 minutes; and 15 minutes are 0.1%; 0.3%; and 1.25% with the average throughput produced is 14.66 kbps. The average total delay and jitter is 350.3 ms and 24.5 ms, respectively. It means Static round-robin algorithm is more efficient than the algorithms Least-connection because it can produce a greater throughput with less CPU load and less total delay.

A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation

Mobile edge caching/computing (MEC) has been emerging as a promising paradigm to provide ultra-high rate, ultra-reliable, and/or low-latency communications in future wireless networks. In this paper, we introduce a novel MEC network architecture that leverages the optimal joint caching-delivering with horizontal cooperation among mobile edge nodes (MENs). To that end, we first formulate the content-access delay minimization problem by jointly optimizing the content caching and delivering decisions under various network constraints (e.g., network topology, storage capacity and users' demands at each MEN). However, the strongly mutual dependency between the decisions makes the problem a nested dual optimization that is proved to be NP-hard. To deal with it, we propose a novel transformation method to transform the nested dual problem to an equivalent mixed-integer nonlinear programming (MINLP) optimization problem. Then, we design a centralized solution using an improved branch-and-bound algorithm with the interior-point method to find the joint caching and delivering policy which is within 1 percent of the optimal solution. Since the centralized solution requires the full network topology and information from all MENs, to make our solution scalable, we develop a distributed algorithm which allows each MEN to make its own decisions based on its local observations. Extensive simulations demonstrate that the proposed solutions can reduce the total average delay for the whole network up to 40 percent compared with other current caching policies. Furthermore, the proposed solutions also increase the cache hit ratio for the network up to 4 times, thereby dramatically reducing the traffic load on the backhaul network.

Delays of Shared-Short Lanes at Unsignalized Intersections

At unsignalized intersections, both on the major street and on the minor street, there may be short turning lanes alongside the through lanes following downstream from one single lane. This combined system is termed a shared-short lane (SSL). Up to now it has only been possible to calculate the capacity of these lanes at the stop line and the capacity of the diverging point, where the turning lane diverges from the through lane. For the total average delay of the involved individual movements, there is no applicable estimation procedure. As a special case, the shared lane (SL), which is used by several movements without a separate turning lane, must also be reconsidered. This paper presents a new model for the estimation of average delays of SSL with SL as a special case at unsignalized intersections. The model is based on the analogy to standard queuing systems. The results depend on the length of the short lane. The model is validated by simulation. The results demonstrate that the outcome of the models in current highway capacity manuals may be misleading, with the risk of inaccurately classifying the level of service of an intersection. Therefore, there is an urgent need to complete the relevant procedures in highway capacity manuals by more realistic estimation procedures for the total delay at an SSL or an SL. The methods in this paper—even if they are rather complex—are recommended to be incorporated into future versions of highway capacity manuals using some simplifications.

Symmetry breaking of identical projects in the high-multiplicity RCPSP/max

This article considers the high-multiplicity resource-constrained project scheduling problem with generalised precedence constraints (RCPSP/max). Projects, which can be partitioned into relatively few classes, are to be scheduled subject to resource and generalised precedence constraints. We show that there exists symmetry between projects of the same class and propose two approaches of symmetry breaking: (1) adding additional constraints to the model in the form of precedence constraints, (2) remodelling the problem to reduce the number of variables. To test the usefulness of the symmetry breaking approaches a computational study is completed considering two families of discrete-time based MIP models and a number of state-of-the-art CP-based scheduling approaches. The study shows that both symmetry breaking approaches allow all solving methods to find and prove more optimal solutions. The best CP approach is then used to find a number of new best solutions to relevant problems from the MPSPlib, a multi-project scheduling problem library, for both the total makespan and average project delay objective, whereas the best MIP approach is used to determine a number of tighter lower bounds.

Reduction and follow-up of hospital discharge letter delay using Little's law.

As discharge letters (DL) hold important information for healthcare professionals and especially for general practitioners, rapid and efficient finalization is required. We describe a project aiming to reduce DL submission within 8 days in our Urology Department (UD), as required by the local Hospital Board (HB). A team was built in UD with staff members and one external expert to study the root causes of delayed DL creation and develop sustainable strategies to improve and monitor the process, including habits changing, training and application of Little's Law. The study started on January 2015 and ended up on March 2016, involving 908 and 616 DL for old and new process, respectively. The new process decreased the average delay of DL completion from 24.88 days to 14.7 days. Standard deviation of total average delay for DL completion fell from 10.1 days to 7.5 days. We identified four steps needed to DL creation and allowed maximum 2 days for every step completion. No additional resources were employed. We were able to improve the process of DL creation, by analysing its steps and reducing their variability. This can be easily transposed to other medical departments.

Dynamic User Equilibrium of Mobility-on-Demand System with Linear Programming Rebalancing Strategy

Mobility-on-demand (MoD) services are provided by multiple competing companies. In their competition for travelers, they need to provide minimum travel costs, or travelers will switch to competitors. This study developed a dynamic traffic assignment of MoD systems. A static traffic assignment (STA) model is first defined. When demand is asymmetric, empty rebalancing trips are required to move vehicles to traveler origins, and the optimal rebalancing flows are found by a linear program. Because of the time-dependent nature of traveler demand, the model was converted to dynamic traffic assignment (DTA). The method of successive averages, which is provably convergent for STA, was used to find dynamic user equilibrium (DUE). The simulation was conducted on two networks. The MoD system was simulated with different fleet sizes and demands. The results showed that the average total delay and travel distance decreased with the increase in fleet size whereas the average on-road travel time increased with the fleet size. The result of traffic assignment of one network with MoD system was compared with a network where all travelers use private vehicles. The results showed that the network with MoD system created more trips but less traffic congestion.

A real-time multi-agent system for cryptographic key generation using imaging-based textural features

Traditional network security protocols depend on exchanging the security keys between the network nodes, and thus opposing the network to different classes of security threats. In this paper, a multi-agent system for cryptographic key generation is proposed for real-time networks. The proposed key generation technique generates a 256-bit security key for the advanced encryption standard (AES) algorithm using the textural features of digital images. By implementing this key generation technique at both the sender and receiver network nodes, the process of exchanging the security keys through the network would be eliminated, and thus making communication between network nodes robust against different security threats. Simulation results over a real-time network show the efficiency of the proposed system in reducing the overhead of the security associations performed by the IPsec protocol. On the other hand, the proposed agent-based system shows a high efficiency in guaranteeing the quality-of-service (QoS) of the real-time requests in terms of miss-ratio and total average delay through applying the best scheduling algorithm.

Bio-inspired energy conserving adaptive power and rate control in MANET

Maximizing network lifetime of unreliable and resource constrained wireless networks such as mobile ad hoc networks involves optimal allocation of power and shared channels in the network. Existing optimal power and channel allocation mechanisms mainly focus on throughput maximization and energy efficiency but fail to obtain a trade-off between delay and energy consumption in the network. This paper proposes a game theoretic energy efficient approach that mimics a fair non-cooperative game among nodes competing for shared channels and power level. Unlike existing power and rate control mechanisms, the proposed energy conserving adaptive power and rate control (ECAPRC) mechanism takes into consideration the constraints of outage probability and total average delay to deal with stochastic changes in the channel that improves the network performance in terms of throughput, delay and total energy consumption. Proposed super-modular game has a unique convergence point called “Nash Equilibrium” and its existence and uniqueness is proved in the paper. To enhance the convergence rate of proposed ECAPRC approach, an adaptive grey wolf optimizer is employed to deal with delay and energy constraints. Simulation results and their analysis show that proposed ECAPRC approach outperforms existing approaches such as dynamic rate and power allocation algorithm, rate-effective network utility maximization and energy conserving power and rate control in terms of above mentioned network parameters and total utility of the system.

Stability and Hopf bifurcation analysis of a 4‐dimensional hypothalamic‐pituitary‐adrenal axis model with distributed delays

A 4‐dimensional mathematical model of the hypothalamus‐pituitary‐adrenal axis is investigated, incorporating the influence of the glucocorticoid receptors concentration and general feedback functions. The inclusion of distributed time delays provides a more realistic modeling approach, since the whole past history of the variables is taken into account. The positivity of the solutions and the existence of a positively invariant bounded region are proved. It is shown that the considered 4‐dimensional system has at least 1 equilibrium state, and a detailed local stability and Hopf bifurcation analysis is given. Numerical results reveal the fact that an appropriate choice of the system's parameters leads to the coexistence of 2 asymptotically stable equilibria in the nondelayed case. When the total average time delay of the system is large enough, the coexistence of 2 stable limit cycles is revealed, which successfully model the ultradian rhythm of the hypothalamus‐pituitary‐adrenal axis both in a normal disease‐free situation and in a diseased hypocortisolism state, respectively. Numerical simulations reflect the importance of the theoretical results.

Adaptive coordinated traffic control for stochastic demand

Traffic arrivals at intersections are inherently uncertain. This paper develops an adaptive coordinated traffic control approach in the presence of traffic demand uncertainty via the notion of Phase Clearance Reliability (PCR). We propose a method to adjust signal offset adaptively in order to deal with stochastic demands. Based on the cumulative queuing regime, this study first extends the delay models, which are usually formulated for isolated intersections, to the case of coordinated intersections by explicitly incorporating the effects of residual queue and signal offset. Two types of delay formulae are considered regarding two different arrival patterns on the intersection approaches, i.e. coordinated approach and non-coordinated approach delay. We then formulate a two-stage stochastic program to optimize (minimize) the expected total delay for the coordinated control system. The base timing plan is derived at the first stage, while the recourse decisions of adaptive signal offsets are made at the second stage to compensate for the overflow effects. Furthermore, a PCR-based gradient solution algorithm is developed to solve the two-stage stochastic program. The case study on a test network confirms the effectiveness of the proposed PCR-based control method in terms of minimizing average total delay. The optimal control performance stems partly from the short cycle lengths, which are attributed to the fact that part of the random arrivals are addressed by adjusting the signal offsets adaptively. This effective use of signal offset provides a new perspective for designing coordinated signal control plans.

A Multi-Objective Decision Support System for Real-Time Train Rescheduling

This study proposes a multi-objective simulation-based optimization framework to effectively manage the train traffic after the occurrences of a disturbance caused by a partial/full blockage. In such conditions, the train orders and the corresponding priorities can be changed to effectively manage the disturbed situation. At this point, a multi-objective version of the variable neighborhood search meta-heuristic is proposed to solve the real-time traffic rescheduling problem and generate Pareto frontiers. The obtained Pareto optimal solutions for disturbance management model supports the decisions made by the rail controllers to find a trade-off between both user and operator viewpoints. We evaluate the proposed approach on a set of disturbance scenarios covering a large part of the Iranian rail network. The computational results demonstrate that the proposed model can generate good-quality disposition timetables with the minimum total average delay of trains at destinations and deviation from the initial timetable. The results indicate that the disturbance management methodology has important advantages in producing practical solution quickly when compared to existing solutions.

Channel and queue aware joint relay selection and resource allocation for MISO-OFDMA based user-relay assisted cellular networks

User-relay assisted orthogonal frequency division multiple access (OFDMA) networks are cost-effective solutions to meet the growing capacity and coverage demands of the next generation cellular networks. These networks can be used with multiple antennas technology in order to obtain a diversity gain to combat signal fading and to obtain more capacity gain without increasing the bandwidth or transmit power. Efficient relay selection and resource allocation are crucial in such a multi-user, multi-relay and multi-antenna environment to fully exploit the benefits of the combination of user-relaying and multiple antennas technology. Thus, we propose a channel and queue aware joint relay selection and resource allocation algorithm for multiple-input single-output (MISO)-OFDMA based user-relay assisted downlink cellular networks. Since, the proposed algorithm is not only channel but also queue-aware, the system resources are allocated efficiently among the users. The proposed algorithm for the MISO-OFDMA based user-relay assisted scheme is compared to existing MISO-OFDMA based non-relaying and fixed relay assisted schemes and it is also compared with the existing single-input single-output (SISO)-OFDMA based user-relay assisted scheme. Simulation results revealed that the proposed scheme outperforms the existing schemes in terms of cell-edge users’ total data rate, average backlog and average delay.