Packet Scheduling Scheme Research Articles

Carrier Aggregation based Downlink Packet Scheduling Scheme with Improved Quality of Service

Carrier Aggregation based Downlink Packet Scheduling Scheme with Improved Quality of Service

A Performance Analysis for Packet Scheduling Schemes of Wireless Sensor Networks

A Performance Analysis for Packet Scheduling Schemes of Wireless Sensor Networks

A cross-layer design: energy efficient multilevel dynamic feedback scheduling in wireless sensor networks using deadline aware active time quantum for environmental monitoring

ABSTRACTRecently, Packet scheduling plays a vital role in Wireless Sensor Networks (WSNs). The major key challenges include delay, packet dropping, energy consumption and lifetime due to constraints in energy and computing resources. All the research works on packet scheduling scheme in WSN uses only First Come First Served (FCFS) and Dynamic Multilevel Priority (DMP) schemes. FCFS works based on packet arrival time, it leads to starvation and high processing overhead for real-time packets. DMP works in multilevel with dynamic priority reduces the transmission overhead and bandwidth; it consumes more resources for real-time task leads to deadlock. To solve these problems, this work presents Multilevel Dynamic Feedback Scheduling (MDFS) algorithm. The sensor node classifies the emergency and normal data into three different ready queues named as high, medium and low priority, respectively. The queues are connected with a feedback mechanism; each packet from the sensor node has its own time quantum value based on the deadline. The updated time quantum value is compared with the boundary value of the queues, depends on the updated value the data packets are moved between queues with help of feedback mechanism. The simulation result proves that the projected MDFS outperforms in WSN environment.

An enhanced security-aware dynamic packet scheduling scheme for wireless networks using intelligent time slice-based krill herd algorithm

ABSTRACTWireless networks perform computing on grouped users together through networks that suffer with improper scheduling and less security awareness results in terms of bandwidth, increase in error rate, power constraints, authentication problem, etc. In order to tackle these problems, an enhanced security-aware dynamic packet scheduling is implemented by utilizing integrated speed packet scheduling which utilizes node distribution by the krill herd algorithm and packet evaluation by intelligent time slice, and reducing the dimensionality of packets with some evolutionary techniques for transmission. To protect these packets from attacks during transmission, the packets are secured by identifying the malicious node and protecting them with proper authentication by PKI (public key infrastructure) with the handshake of secure exchange of distributed signatures. The experimental execution in NS-3 simulator outcomes shows that the proposed system is more efficient in the packet delivery ratio and security than other existing techniques.

A Packet Scheduling Scheme for Improving Real-time Applications Performance in Downlink LTE–advanced

Quality of Service based packet scheduling is a key-feature of LTE-A mandating selection and transmission of individual user packets based on their priority. HARQ Aware Scheduling, Retransmission Aware Proportional Fair, Chase Combining Based Max C/I Scheduling and Maximum- Largest Weighted First (M-LWDF) are popular Packet Scheduling Algorithms (PSAs) developed to meet QoS requirements. In highly erroneous LTE-A cannel, M-LWDF is considered to be one of best PSA. To validate the performance of M-LWDF for the LTE-A channel, Mean User Throughout, and Fairness performance measures were evaluated for 3 different PSAs designed based on M-LWDF algorithm in this paper. A C++ based simulation results indicate the superiority of the PSA3 algorithm within the threshold of the performance measures against benchmarks. It has shown more efficiency and the performance of RTA traffic was enhanced. Results show that PSA3 is superior to its benchmark PSA2 by 12% in Mean User Throughput and 11% in Fairness. PSA2 performed the worst because it prioritizes new users and it allocated all available RBs to the scheduled user leaving the rest to wait in the buffer. PSA3 maintians good Mean User Throughput and fairnessdue to scheduling each user on its RB which leads to multi-user diversity.

A Packet Scheduling Scheme for Improving Real-time Applications Performance in Downlink LTE–advanced

Quality of Service based packet scheduling is a key-feature of LTE-A mandating selection and transmission of individual user packets based on their priority. HARQ Aware Scheduling, Retransmission Aware Proportional Fair, Chase Combining Based Max C/I Scheduling and Maximum- Largest Weighted First (M-LWDF) are popular Packet Scheduling Algorithms (PSAs) developed to meet QoS requirements. In highly erroneous LTE-A cannel, M-LWDF is considered to be one of best PSA. To validate the performance of M-LWDF for the LTE-A channel, Mean User Throughout, and Fairness performance measures were evaluated for 3 different PSAs designed based on M-LWDF algorithm in this paper. A C++ based simulation results indicate the superiority of the PSA3 algorithm within the threshold of the performance measures against benchmarks. It has shown more efficiency and the performance of RTA traffic was enhanced. Results show that PSA3 is superior to its benchmark PSA2 by 12% in Mean User Throughput and 11% in Fairness. PSA2 performed the worst because it prioritizes new users and it allocated all available RBs to the scheduled user leaving the rest to wait in the buffer. PSA3 maintians good Mean User Throughput and fairnessdue to scheduling each user on its RB which leads to multi-user diversity.

Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks

In parallel to the advancements in communication technologies, telemedicine research has continually adapted to develop various healthcare applications. The latest wireless technology Long-Term Evolution(LTE) is being increasingly deployed across developed countries and rapidly adopted by developing countries. In this paper, a content-aware packet scheduling approach for medical ultrasound videos is proposed. The contribution of this work is introducing a utility function based on the temporal complexity of the video frames. The utility function is used with four schedulers to prioritise the video packets based on their temporal complexity and type of frame (e.g. I frame). The results show that the utility function improves the packet delay performance obtained in our simulation when compared with content-unaware approach. Further, gain in average PSNR and SSIM are also observed in the received video quality. Research on content-aware packet scheduling for telemedicine applications over advanced wireless networks is limited and our work contributes towards addressing this research gap.

A Data-Emergency-Aware Scheduling Scheme for Internet of Things in Smart Cities

With the applications of Internet of Things (IoT) for smart cities, the real-time performance for a large number of network packets is facing serious challenge. Thus, how to improve the emergency response has become a critical issue. However, traditional packet scheduling algorithms cannot meet the requirements of the large-scale IoT system for smart cities. To address this shortcoming, this paper proposes EARS, an efficient data-emergency-aware packet scheduling scheme for smart cities. EARS describes the packet emergency information with the packet priority and deadline. Each source node informs the destination node of the packet emergency information before sending the packets. The destination node determines the packet scheduling sequence and processing sequence according to emergency information. Moreover, this paper compares EARS with a first-come, first-served, multilevel queue algorithm and a dynamic multilevel priority packet scheduling algorithm. Simulation results show that EARS outperforms these previous scheduling algorithms in terms of packet loss rate, average packet waiting time, and average packet end-to-end delay.

Packet Scheduling Scheme to Guarantee QoS in Internet of Things

In this paper, a new prediction based dynamic scheduling mechanism is proposed to ensure quality of service especially in internet of things (IoT) by dynamically allocating bandwidth. The scheduling scheme is analyzed for two different applications: (1) to accommodate various streaming data of IoT applications or for medical applications. Traffic is segregated based on different traffic characteristics such as bit rate, packet loss rate and tolerable delay into different classes and they are prioritized based on these characteristics; and (2) to consider continuous long time data from all lightweight devices like sensors. The algorithm allocates bandwidth such that its utilization can be optimized for different applications. The scheduler decision is divided into two steps: (1) calculating average increase in queue length of high priority and medium priority services at current time slot from the previous time slot and, (2) adding these values to previous weight values for corresponding services and multiplying with a coefficient. The performance is carried out under different system loading and scenarios. The results illustrate the improvement of the advised scheduler with respect to end to end delay distributions, packet drop and end to end jitter values.

Packet Scheduling for Multiple‐Switch Software‐Defined Networking in Edge Computing Environment

Software‐defined networking (SDN) decouples the control plane and data forwarding plane to overcome the limitations of traditional networking infrastructure. Among several communication protocols employed for SDN, OpenFlow is most widely used for the communication between the controller and switch. In this paper two packet scheduling schemes, FCFS‐Pushout (FCFS‐PO) and FCFS‐Pushout‐Priority (FCFS‐PO‐P), are proposed to effectively handle the overload issue of multiple‐switch SDN targeting the edge computing environment. Analytical models on their operations are developed, and extensive experiment based on a testbed is carried out to evaluate the schemes. They reveal that both of them are better than the typical FCFS‐Block (FCFS‐BL) scheduling algorithm in terms of packet wait time. Furthermore, FCFS‐PO‐P is found to be more effective than FCFS‐PO in the edge computing environment.

Adaptive Packet Scheduling in IoT Environment Based on Q-learning

In the Internet of Things (IoT) environment consisting of various devices the arrival rate of data packets dynamically changes. Failure to process them in complying with the QoS requirement can significantly degrade the reliability and quality of the system. Therefore, the gateway collecting the data needs to quickly establish a new scheduling policy according to the changing traffic condition. The existing packet scheduling schemes are not effective for IoT since the data transmission pattern is not defined in advance. Q-learning is a type of reinforcement learning that can establish a dynamic scheduling policy according to the state of each queue without any prior knowledge on the network status. In this paper a novel Q-learning scheme is proposed which updates the Q-table and reward table based on the condition of the queues in the gateway and adjusts the reward value according to the time slot. Computer simulation reveals that the proposed scheme significantly reduces the scheduling time while allowing high accuracy compared to the existing Q-learning scheme based on Stochastic Learning Automaton (SLA).

A Local-Optimization Emergency Scheduling Scheme With Self-Recovery for a Smart Grid

With the widespread applications of Internet of Things (IoT), the emergency response performance for large-scale network packets is facing serious challenge, especially for renewable distributed energy resources monitoring in a smart grid. Therefore, how to improve the real-time performance of the emergency data packets has been a critical issue. Traditional packet scheduling schemes and topology optimization strategies are not suitable for a large-scale IoT-based smart grid. To address this problem, this paper proposes a new packet scheduling scheme named LOES, which first combines the priority-based packet scheduling scheme with local optimization. We exchange local geographic information to reduce the hop counts and distance between distributed source nodes and sink nodes. Each destination node determines the packet scheduling sequence according to the received emergency information. Finally, we compare LOES with first come first serve, multilevel scheme, and dynamic multilevel priority packet scheduling scheme using packet loss rate, packet waiting time, and average packet end-to-end delay as metrics. The simulation results show that LOES outperforms these previous scheduling schemes.

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks.

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement.

Better Packet Scheduling Scheme For Wireless Communication

Better Packet Scheduling Scheme For Wireless Communication

Near‐optimal packet scheduling scheme in satellite LTE networks

This study proposes a near-optimal packet scheduling scheme in the satellite long term evolution (LTE) network which uses multiuser multiple-in multiple-out technique. For the available resources in the satellite LTE network to be fully utilised and in order to meet the set targets of 4G standard, the need for an optimal scheduling scheme that will maximise the throughput without compromising the quality of service and fairness of users is very crucial. The aim of this study is to propose near-optimal scheduling schemes that have been obtained using Karush-Kuhn-Tucker multipliers and compare their performances with other throughput-optimal scheduling schemes. A new metric that can be used to compute the overall performance of the scheduling schemes is also presented. This work has adopted the use of a land mobile dual-polarised GEO satellite system.

Joint Scheduling and Transmission Power Control in Wireless Ad Hoc Networks

In this paper, we study how to determine concurrent transmissions and the transmission power level of each link to maximize spectrum efficiency and minimize energy consumption in a wireless ad hoc network. The optimal joint transmission packet scheduling and power control strategy are determined when the node density goes to infinity and the network area is unbounded. Based on the asymptotic analysis, we determine the fundamental capacity limits of a wireless network, subject to an energy consumption constraint. We propose a scheduling and transmission power control mechanism to approach the optimal solution to maximize spectrum and energy efficiencies in a practical network. The distributed implementation of the proposed scheduling and transmission power control scheme is presented based on our MAC framework proposed in [1]. Simulation results demonstrate that the proposed scheme achieves 40% higher throughput than existing schemes. Also, the energy consumption using the proposed scheme is about 20% of the energy consumed using existing power saving MAC protocols.

Video Packet Scheduling With Stochastic QoS for Cognitive Heterogeneous Networks

In this paper, a video framework with stochastic quality of service (QoS) is proposed for cognitive heterogeneous networks based on internetwork cooperation. The video packet scheduling is subject to constraints in the available energy at each call for secondary mobile terminal (MT), the time varying channel state information (CSI) at different interfaces, the total interference power, the target call duration, and the video characteristics. The objective function maximizes the minimum lower bound of video quality. In order to solve the above video packet scheduling problem with stochastic QoS guarantee, a video packet scheduling scheme based on forward-auction theory is proposed. Then, the cumulative distribution function (CDF) for video quality is analyzed. Finally, the power allocation scheme to maximize the minimization lower bound of video quality among different secondary MTs is presented. Simulation results demonstrate that the proposed video packet scheduling scheme with stochastic QoS requirement improves the video quality for secondary MT significantly.

QoS-oriented packet scheduling scheme for opportunistic networks

The unique characteristics of opportunistic networks (ONs), such as intermittent connectivity and limited network resources, makes it difficult to support quality of service (QoS) provisioning, particularly to guarantee delivery ratio and delivery delay. In this paper, we propose a QoS-oriented packet scheduling scheme (QPSS) to make decisions for bundle transmissions to satisfy the needs for the delivery ratio and delivery delay constraints of bundles. Different from prior works, a novel bundle classification method based on the reliability and latency requirements is utilized to decide the traffic class of bundles. A scheduling algorithm of traffic class and bundle redundancy is used to maintain a forwarding and dropping priority queue and allocate network resources in QPSS. Simulation results indicate that our scheme not only achieves a higher overall delivery ratio but also obtains an approximate 14% increase in terms of the amount of eligible bundles.

Quality of Service Analysis for the Real-Time Secondary Users in Cognitive Radio Cellular Networks

Cognitive radio technology can improve the spectrum utilization in wireless networks by providing the capability for the secondary users to opportunistically use the frequency spectrum which is originally dedicated to the licensed users. In this paper the quality of service parameters for the real-time (RT) secondary users are analyzed in an overlay cognitive radio cellular network. RT packets are delay sensitive and can tolerate a limited amount of waiting time. Otherwise they will be useless and hence will be dropped. On the other hand, the availability of the frequency channels for SUs in cognitive radio networks (CRNs) depends on the activity of licensed users. Therefore, the support of RT services in CRNs requires elaborate considerations in various functionalities of the network. Here a practical cellular structure for the network is considered. Furthermore, a packet scheduling scheme is proposed and an analytical framework is developed for the performance analysis of RT secondary users. The effect of errors of spectrum sensing is also taken into account in the performed analysis. The analytical results are verified by simulations. The obtained results are very helpful for the support of RT traffic in cellular CRNs.

QoE driven cross-layer scheme for DASH-based scalable video transmission over LTE

Recently using Scalable Video Coding (SVC) in Dynamic Adaptive Streaming of over HTTP (DASH) has attracted more and more attention. In this paper, we present a Quality-of-Experience (QoE) driven Cross-Layer Scheme (QCLS) for DASH-based scalable video transmission over LTE. Specifically, assuming the priority-based extraction be exploited for bitstream adaption, we first propose a new continuous Rate-Distortion (RD) model for scalable video stream. Then to guarantee continuous playback, a two-level rate adaption algorithm is presented: a novel throughput-based algorithm is implemented for dynamic selection of segment bitrate on the DASH client side at the first level, and the second level applies the rate adaption by designing a suitable packet scheduling strategy at the Base Station. The packets of each segment with lower priority that are still left in the packet queues when their playback deadline is missed, would be considered as the ones that are beyond the actual transmission ability and discarded by the second-level rate adaption. Furthermore, in order to reasonably utilize the wireless resources in LTE (Long-Term Evolution) system, a cross-layer optimization problem that maximizes the total weighted received quality of the currently transmitted segments for all clients is formulated. In view of its high complexity of obtaining the optimal solution, we develop an approach of the suboptimal solution, which can determine a locally optimal transmission strategy in resource allocation as well as the corresponding Modulation and Coding Scheme. Accordingly, the transmission rate of each client can be obtained. Simulation results show that our proposed cross-layer scheme can provide better performance than the existing ones for DASH-based scalable video transmission over LTE.