Communication Scheduling Research Articles

2P6-16 High Data Rate Scheduling for Underwater Acoustic Communication in Shallow Water(Poster Session)

2P6-16 High Data Rate Scheduling for Underwater Acoustic Communication in Shallow Water(Poster Session)

Approaches to communication assessment with children and adults with profound intellectual and multiple disabilities.

Communication assessment of people with profound intellectual and multiple disabilities (PIMD) has seldom been investigated. Here, we explore approaches and decision making in undertaking communication assessments in this group of people. A questionnaire was sent to UK practitioners. The questionnaire elicited information about assessment approaches used and rationales for assessment choices. Fifty‐five speech and language therapists (SLTs) responded. Findings revealed that the Preverbal Communication Schedule, the Affective Communication Assessment and the Checklist of Communication Competence were the most frequently used published assessments. Both published and unpublished assessments were often used. Rationales for assessment choice related to assessment utility, sensitivity to detail and change and their applicability to people with PIMD. Underpinning evidence for assessments was seldom mentioned demonstrating the need for more empirical support for assessments used. Variability in practice and the eclectic use of a range of assessments was evident, underpinned by practice‐focused evidence based on tacit knowledge.

Fuzzy based priority aware scheduling technique for dense industrial IoT networks

Smart manufacturing is the next industrial revolution. The requirements from the manufacturing sector, and more generally, the Industrial Internet of Things (IIoT) has been one of the driving verticals for the design and development of new concepts and technologies. Time Slotted Channel Hopping (TSCH) is one such technology which provides ultra-low power and reliable communication in industrial scenarios. The heart of TSCH is the scheduling algorithm that creates a communication schedule for each node. This paper proposes a fuzzy based priority aware (FPAS) TSCH scheduling technique for scalable industrial IoT networks. The proposed technique supports service differentiation, to improve battery life and reduce latency. The algorithm uses fuzzy logic to determine the priority of a node. The allocation module allocates the required number of slots based on the priority and the amount of traffic generated.The proposed FPAS algorithm is compared with two existing state of the art scheduling functions (SF), scheduling function-zero (SF0) and low latency scheduling function (LLSF). The result shows that FPAS is more scalable than SF0 and LLSF, provides collision free communication and improves duty cycle by 7%, battery life by 28.26%, packet loss ratio by 94% and reduces latency by 74.63% and collisions by 89% respectively.

Cooperative control and communication of connected vehicles considering packet dropping rate

ABSTRACTThis paper investigates cooperative control and communication scheduling of a platoon of connected vehicles. Considering the effect of packet dropout and the network access limitation, the vehicular platoon is modelled as a discrete-time switching system. We obtain a set of sufficient conditions (where the rate of different platoon control modes is factored in) for string stability and schedulability of the vehicular platoon. A unified framework of network access scheduling and platoon control is proposed, which can guarantee string stability of the platoon of vehicles and resolve network access conflicts among them. Both numerical simulations and experimental studies with laboratory-scale cars have demonstrated the effectiveness of the presented co-design algorithm.

Dynamic Data Communications for Real-time Information Fusion

This paper studies dynamic data communications between airplanes and a control tower, where the control tower needs to monitor the state of each aircraft close to the airport or on the ground in real time. Given limited communication bandwidth, it is impossible for the control tower to communicate with all aircrafts at the same time. This paper focuses on the problem of optimal scheduling of data communications for the control tower to acquire information from aircrafts to minimize tracking errors. A dynamic learning problem with limited communication bandwidth is formulated in this paper where the objective is to minimize the total variance of real-time tracking. To solve the problem, a dynamic scheduling algorithm for data communications is proposed, which prioritizes data communications based on the tracking variances of the aircrafts, channel conditions and importance of the information. Our simulations demonstrate that our algorithm outperforms policies such as a round robin policy.

An optimisation approach for pre-runtime scheduling of tasks and communication in an integrated modular avionic system

In modern integrated modular avionic systems, applications share hardware resources on a common avionic platform. Such an architecture necessitates strict requirements on the spatial and temporal partitioning of the system to prevent fault propagation between different aircraft functions. One way to establish a temporal partitioning is through pre-runtime scheduling of the system, which involves creating a schedule for both tasks and a communication network. While avionic systems are growing more and more complex, so is the challenge of scheduling them. The scheduling of the system has an important role in the development of new avionic systems, since functionality is typically added to the system over a period of several years and a scheduling tool is used both to detect if the platform can host the new functionality and, if this is possible, to create a new schedule. For this reason an exact solution strategy for avionics scheduling is preferred over a heuristic one. In this paper we present a mathematical model for an industrially relevant avionic system and present a constraint generation procedure for the scheduling of such systems. We apply our optimisation approach to instances provided by our industrial partner. These instances are of relevance for the development of future avionic systems and contain up to 20,000 tasks to be scheduled. The computational results show that our optimisation approach can be used to create schedules for such instances within a reasonable time.

Overcoming Endurance Issue: UAV-Enabled Communications With Proactive Caching

Wireless communication enabled by unmanned aerial vehicles (UAVs) has emerged as an appealing technology for many application scenarios in future wireless systems. However, the limited endurance of UAVs greatly hinders the practical implementation of UAV-enabled communications. To overcome this issue, this paper proposes a novel scheme for UAV-enabled communications by utilizing the promising technique of proactive caching at the users. Specifically, we focus on content-centric communication systems, where a UAV is dispatched to serve a group of ground nodes (GNs) with random and asynchronous requests for files drawn from a given set. With the proposed scheme, at the beginning of each operation period, the UAV pro-actively transmits the files to a subset of selected GNs that cooperatively cache all the files in the set. As a result, when requested, a file can be retrieved by each GN either directly from its local cache or from its nearest neighbor that has cached the file via device-to-device (D2D) communications. It is revealed that there exists a fundamental trade-off between the file caching cost, which is the total time required for the UAV to transmit the files to their designated caching GNs, and the file retrieval cost, which is the average time required for serving one file request. To characterize this trade-off, we formulate an optimization problem to minimize the weighted sum of the two costs, via jointly designing the file caching policy, the UAV trajectory and communication scheduling. As the formulated problem is NP-hard in general, we propose efficient algorithms to find high-quality approximate solutions for it. Numerical results are provided to corroborate our study and show the great potential of proactive caching for overcoming the limited endurance issue in UAV-enabled communications.

Communication scheduling in data gathering networks of heterogeneous sensors with data compression: Algorithms and empirical experiments

We consider a communication scheduling problem to address data compression and data communication together, arising from the data gathering wireless sensor networks with data compression. In the problem, the deployed sensors are heterogeneous, in that the data compression ratios, in terms of size reduction, the compression time, and the compression costs, in terms of energy consumption, on different sensors are different. The bi-objective is to minimize the total compression cost and to minimize the total time to transfer all the data to the base station. The problem reduces to two mono-objective optimization problems in two separate ways: in the original problem a time bound is given and the mono-objective is to minimize the total compression cost, and in the complementary problem a global compression budget is given and the mono-objective is to minimize the makespan. We present a unified exact algorithm for both of them based on dynamic programming; this exact algorithm is then developed into a fully polynomial time approximation scheme for the complementary problem, and a dual fully polynomial time approximation scheme for the original problem. All these approximation algorithms have been implemented and extensive computational experiments show that they run fast and return the optimal solutions almost all the time.

Energy-efficient DRX scheduling for D2D communication in 5G networks

In recent years, intelligent devices such as smart phones and smart tablets are grown and developed rapidly. High-bandwidth media services such as live streaming, gaming and multi-user video conferencing are more and more popular. This results in spectrum resource depletion of the cellular network. To alleviate the problem, the 3rd Generation Partnership Project (3GPP) has proposed a new technology, called device-to-device (D2D) communications. However, D2D devices and direct link cellular users all share and access the same spectrum resource, thus degrading the network performance significantly due to the interference. In addition, due to the frequent communication nature of streaming and gaming services, the power consumption of devices is increasing dramatically. To mitigate above problems, this paper investigates how to improve the spectrum efficiency by well scheduling and allocating radio resource to more concurrent D2D and cellular users on the uplink direction and reduce unnecessary power consumption of devices via Discontinuous Reception (DRX) scheduling while guaranteeing users' Quality of Service (QoS). We propose an energy-efficient resource and sleep scheduling scheme. This scheme first establishes a conflict graph to maintain the transmission and interference relationship, and then tries to maximize concurrent D2D and mobile users by resource reuse. At the same time, the method also exploits DRX technology to further decrease possible interference and conserve devices’ power consumption through optimizing their sleep operation. Simulation results show that our scheme can achieve better performance on system throughput, network capacity, and power saving compared to the existing schemes.

Virtual Cell Based Resource Allocation for Efficient Frequency Utilization in Unmanned Aircraft Systems

Recently, unmanned aircraft systems (UASs) have attracted attention as a new avenue for commercial services. Using the flexible mobility of unmanned aircrafts (UAs), commercial services can be operated in wide areas. However, there is a problem in the wireless communication between the UA and its ground station. When several UASs are operated within the neighboring airspace, wireless-communication conflicts occur. One of the most effective solutions for this issue is to decide the communication schedule using a time-division multiple access (TDMA) scheme. Furthermore, by spatially reusing the time slot, numerous UAs can be operated within the neighboring airspace, in a limited frequency band. In this paper, we propose an efficient time-slot allocation for enhancing the frequency resource utilization. Our proposed scheme determines the time-slot allocation considering the time-slot spatial reuse, using a virtual cell based space partitioning method. In addition, we consider the influence of the UA mobility on the network to decide the parameters for the proposed resource allocation system. The effectiveness of our proposed resource allocation is evaluated through computer-based simulation.

A Mathematical Model for Optimal Communication Scheduling between Multiple Satellites and Multiple Ground Stations

A Mathematical Model for Optimal Communication Scheduling between Multiple Satellites and Multiple Ground Stations

A Joint Local Short Scheduling Mechanism for a Successful MIMO–OFDM Communication System

In recent days, the allocation of resources in a wireless communication system is one of the demanding and crucial task. Multi input multi output (MIMO)–Orthogonal frequency division multiplexing is the widely used communication system, in which scheduling the resource to the appropriate user equipment (UE) is quite a challenging process. To overcome this a different scheduling mechanisms are proposed in the traditional works for efficient resource allocation. But, it lacks with some limitations such as, increased error rate, inefficient allocation, increased load at tower, and increased interference. Thus, this paper objects to introduce a new optimization based scheduling mechanism, namely, Joint local shortest scheduling (JLSS) for a successful MIMO communication. Initially, the Rayleigh channel initialization and estimation processes are performed after creating the Cellular radio network with different number of users. Then, the features of the channel are extracted by implementing a beamforming feature extraction technique. Here, a Multi-channel bacterial foraging optimization algorithm (MC-BFOA) is implemented for selecting the most suitable channel for communication, due to its increased efficiency. Finally, the JLSS is employed to scheduling the resource to the user equipment (UE), in which three different mechanisms such as Primary channel bit allocation, Secondary channel bit allocation, and Extra channel bit allocation are used. Based on the priority level, the resource is allocated with the use of these mechanisms. During experimentation, the scheduling results of existing and proposed techniques are evaluated by employing different parameters.

Communication scheduling method of big data in Internet of Things based on decision feedback equalization and spread spectrum modulation technology

In order to improve the accuracy of communication transmission of big data in Internet of Things and reduce output bit error rate, a communication scheduling method of big data in Internet of things based on decision feedback equalization and spread spectrum modulation technology is proposed in this paper. In this method, a model of big data communication channel in Internet of Things is constructed, and the autocorrelation matched filtering method is used for multi-path interference suppression to communication of big data in Internet of Things; the decision feedback equalization method is used for channel equalization design of communication scheduling, and the adaptive filter is used to compensate distorted output samples; the spread spectrum modulation technology is used to improve the bandwidth of communication scheduling channel of big data and to correct frequency characteristics, so as to optimize the communication scheduling of big data in Internet of Things. The simulation results show that when the proposed method is used for communication scheduling of big data in Internet of Things, the amplitude-frequency response is improved by 300 m and the output bit error rate is reduced by 34%, which effectively improves the communication quality of big data.

Master–Slave Synchronization of Heterogeneous Systems Under Scheduling Communication

Under the mild assumption that only the sampled-data output information about the master system is available, synchronization of networked master–salve system consisting of a high-order master system and a low-order slave system is investigated in this paper. Specifically, the dynamics of the master system and those of the slave system are allowed to be characterized by heterogeneous nonlinear systems. The communication between these two systems are transmitted by multiple sensors over a communication network, while at each sampling instant, only one sensor is allowed to transmit its current information to the controller’s side according to some carefully designed scheduling protocols. To achieve master–salve synchronization, the stochastic scheduling and the Round-Robin scheduling protocols are, respectively, proposed and utilized. By appropriately designing observer and controller for the slave system, some sufficient synchronization criteria regarding to the gain matrices, sampling intervals and communication delays are derived for the closed-loop master–salve system under respectively the stochastic scheduling and the Round-Robin scheduling protocols. Last, two numerical examples are simulated to validate the effectiveness of the theoretical results.

Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

Unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations (BSs) are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAVs' trajectory and power control. The formulated problem is a mixed integer non-convex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the non-convex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge to at least a locally optimal solution. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.

Autonomous and traffic-aware scheduling for TSCH networks

Wireless Sensor Networks (WSNs) have been recognized as a promising communication technology for smart grid monitoring and control applications. However, the deployment of WSNs in smart grid brought new challenges that pertain to the harsh electrical grid nature, and the different and often contradicting communication requirements of smart grid monitoring applications. MAC protocols play a crucial role to meet the reliability and latency requirements of WSN-based smart grid communications. In particular, the IEEE 802.15.4 TSCH (Time Slotted Channel Hopping), the latest generation of low-power and highly reliable MAC protocols, orchestrates the medium access according to a time-frequency communication schedule. However, TSCH specification does not provide any practical solution for the establishment of the schedule. Orchestra is a recent scheduling solution for TSCH that brings significant advantages such as, the use of simple scheduling rules, the low signaling overhead, and the high delivery ratio. Despite its unique features, Orchestra has the limitation of computing the TSCH schedule at each node independently from its traffic load, which can drastically affect the communication delay. This limitation makes Orchestra not sufficiently convenient for several delay-sensitive smart grid applications. Further, the current TSCH specification does not support traffic differentiation (i.e. handle all packets equally regardless of their criticality levels). In this paper, we propose an enhanced Orchestra-based TSCH protocol, called e-TSCH-Orch, that dynamically adjusts time slots assignment according to traffic load and criticality level. The performance analysis of e-TSCH-Orch shows that it significantly reduces the communication delay compared to the original Orchestra-based TSCH, while preserving the low signaling overhead and the high packet delivery ratio.

CPS-Based Smart Warehouse for Industry 4.0: A Survey of the Underlying Technologies

This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate building smart warehouses to achieve the promising vision of industry 4.0. We focus on four significant issues when applying CPS techniques in smart warehouses. First, efficient CPS data collection: when limited communication bandwidth meets numerous CPS devices, we need to make more effort to study efficient wireless communication scheduling strategies. Second, accurate and robust localization: localization is the basis for many fundamental operations in smart warehouses, but still needs to be improved from various aspects like accuracy and robustness. Third, human activity recognition: human activity recognition can be applied in human–computer interaction for remote machine operations. Fourth, multi-robot collaboration: smart robots will take the place of humans to accomplish most tasks particularly in a harsh environment, and smart and fully-distributed robot collaborating algorithms should be investigated. Finally, we point out some challenging issues in the future CPS-based smart warehouse, which could open some new research directions.

Schedule communication routing approach to maximize energy efficiency in wireless body sensor networks

E-Health allows you to supersede the central patient wireless healthcare system. Wireless Body Sensor Network (WBSN) is the first phase of the e-Health system. In this paper, we aim to understand e-Health architecture and configuration, and attempt to minimize energy consumption and latency in transmission routing protocols during restrictive latency in data delivery of WBSN phase. The goal is to concentrate on polling protocol to improve and optimize the routing time interval and schedule communication to reduce energy utilization. In this research, two types of network models routing protocols are proposed – elemental and clustering. The elemental model improves efficiency by using a polling protocol, and the clustering model is the extension of the elemental model that Destruct Supervised Decision Tree (DSDT) algorithm has been proposed to solve the time interval conflict transmission. The simulation study verifies that the proposed models deliver better performance than the existing BSN protocol for WBSN.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN.

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

Sampled-Data State Observation over Lossy Networks under Round-Robin Scheduling

In this paper, we study the problem of continuous-time state observation over lossy communication networks. We consider the situation in which the samplers for measuring the output of the plant are spatially distributed and their communication with the observer is scheduled according to a round-robin scheduling protocol. We allow the observer gains to dynamically change in synchronization with the scheduling of communications. In this context, we propose a linear matrix inequality (LMI) framework to design the observer gains that ensure the asymptotic stability of the error dynamics in continuous time. We illustrate the effectiveness of the proposed methods by several numerical simulations.