Adaptive Scheduling Scheme Research Articles

Priority Based Call Admission Control Protocol for Videoconference Traffic in Wireless/Cellular Networks

In this paper, we propose a new CAC protocol which provides videoconference traffic taking multiple services like voice, text and multimedia at a time for multiclass users. In this proposed protocol we use priority on basis of account balance of customers and serve the calls with higher priority first. The higher the account balance higher is the priority. The call continues until the user closes the call or the balance is zero or the user is taking considerable amount of resources causing starvation. Video packet delay requirements are strict because delays are annoying to a viewer. An adaptive scheduling scheme to allocate optimum rate for each traffic queue is proposed to minimize the scheduling delay. By simulation experiments, we show that the proposed protocol achieves optimum rate with reduced delay, maximum use of bandwidth and maximum Quality of Service (QoS).

Enhanced MAC protocol to support multimedia traffic in cognitive wireless mesh networks

With the advanced physical layer techniques such as multiple-input and multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM), transmission real-time 2D/3D contents and applications becomes more and more necessary in wireless networks for the amazing growing in demand of customers. However, the low efficiency of medium access control (MAC) protocol degrades the performance of real-time traffic greatly in multihop, wireless and mobile environment. Focusing on supporting real-time multimedia traffic in cognitive wireless mesh networks (WMNs), an enhanced MAC protocol is proposed. And the contribution of this paper is twofold: (1) An efficient carrier sense multiple access with collision avoidance (CSMA/CA) compatible time division multiple access (TDMA)-like MAC protocol called T-MAC is proposed, which aims to improve the system performance by allocating more channel access time in centralized manner and decreasing overhead. (2) An optimal adaptive scheduling scheme is proposed to support real-time multimedia applications and guarantee QoS for different priority traffic, which aims to find the optimized schedule among all possible sequences of concurrent transmissions by minimizing the occupied resources. Detailed simulation results and comparison with IEEE 802.11e MAC scheme show that the proposed T-MAC can effectively improve quality of service (QoS) for multimedia traffic in terms of throughput, end-to-end delay and packet loss rate, which also manifests that T-MAC is an efficient multimedia applications transmission scheme for mobile terminals and MAPs in cognitive WMNs.

Fuzzy scheduling with swarm intelligence-based knowledge acquisition for grid computing

In spite of the existence of a large diversity in literature related to scheduling algorithms in computational grids, there are only a few efficiently dealing with the inherent uncertainty and dynamism of resources and applications of these systems. Further, the need to meet both users and providers QoS requirements, such as tardiness or resource utilization, calls for new adaptive scheduling strategies that consider current and future status of the grid. Fuzzy Rule-Based Systems (FRBSs) are knowledge based systems that are recently emerging as an alternative for the development of grid scheduling middleware. Their main strength resides in their adaptability to changes in environment and their ability to model vagueness. However, since their performance strongly depends on the quality of their acquired knowledge, new automatic learning strategies are pursued. In this work, a FRBS meta-scheduler for scheduling jobs in computational grids is suggested which incorporates a novel knowledge acquisition method based on Swarm Intelligence. Simulations results show that the fuzzy meta-scheduler improves six classical queued-based and scheduled-based approaches present in today's production systems and it is able to easily adapt to changes in the grid conditions.

Adaptive Packet Scheduling Scheme to Support Real-time Traffic in WLAN Mesh Networks

Due to multiple hops, mobility and time-varying channel, supporting delay sensitive real-time traffic in wireless local area network-based (WLAN) mesh networks is a challenging task. In particular for real-time traffic subject to medium access control (MAC) layer control overhead, such as preamble, carrier sense waiting time and the random backoff period, the performance of real-time flows will be degraded greatly. In order to support real-time traffic, an efficient adaptive packet scheduling (APS) scheme is proposed, which aims to improve the system performance by guaranteeing inter-class, intra-class service differentiation and adaptively adjusting the packet length. APS classifies incoming packets by the IEEE 802.11e access class and then queued into a suitable buffer queue. APS employs strict priority service discipline for resource allocation among different service classes to achieve inter-class fairness. By estimating the received signal to interference plus noise ratio (SINR) per bit and current link condition, APS is able to calculate the optimized packet length with bi-dimensional markov MAC model to improve system performance. To achieve the fairness of intra-class, APS also takes maximum tolerable packet delay, transmission requests, and average allocation transmission into consideration to allocate transmission opportunity to the corresponding traffic. Detailed simulation results and comparison with IEEE 802.11e enhanced distributed channel access (EDCA) scheme show that the proposed APS scheme is able to effectively provide inter-class and intra-class differentiate services and improve QoS for real-time traffic in terms of throughput, end-to-end delay, packet loss rate and fairness.

Packet loss-ratio based scheduler: an adaptive scheduling scheme to increase the number of multimedia applications in WLAN

The reference scheduler in IEEE 802.11e fails to maintain the goal of quality of service (QoS) support and high network efficiency simultaneously. In this paper we investigate channel access schemes to increase the number of multimedia applications in wireless local area network (WLAN) while maintaining the QoS requirements. We have developed a scheduling scheme, named as packet loss-ratio based scheduler (PLS) that takes into account the packet losses occurred while allotting the transmission time to a multimedia stream. To implement this scheme the access point (AP) requires only the queue size information and can be implemented within the format of IEEE 802.11e. The simulation results show that the PLS can accommodate more number of traffic streams and can also randomise the packet loss from a traffic stream, which is a requirement for multimedia coder-decoders (CODECs) to conceal the distortion.

비안정적인 Rework 확률이 존재하는 제조공정을 위한 적응형 스케줄링 알고리즘

본 논문은 비안정적인 재작업 발생확률이 존재하는 제조공정을 위한 적응형 스케줄링 알고리즘을 제시한다. 본 논문에서 제안하는 하이브리드 Q-학습 알고리즘은 강화학습 기반의 Q-학습과 인공신경망을 결합한 알고리즘으로써 재작업확률이 불안정한 상황의 제조공정에 대해 학습을 통해 적응력을 가질 수 있도록 고안되었다. 제안 알고리즘은 평균지연시간을 척도로 그 성능을 평가하였고, 기존의 작업할당 알고리즘들과 다양한 실험 시나리오를 기반으로 비교함으로써 그 우수성을 보이도록 한다. This paper presents an adaptive scheduling algorithm for manufacturing processes with non-stationary rework probabilities. The adaptive scheduling scheme named by hybrid Q-learning algorithm is proposed in this paper making use of the non-stationary rework probability and coupling with artificial neural networks. The proposed algorithm is measured by mean tardiness and the extensive computational results show that the presented algorithm gives very efficient schedules superior to the existing dispatching algorithms.

A Practical Layer 3 Admission Control and Adaptive Scheduling (L3-ACAS) for COTS WLANs

We propose a practical approach to provide QoS over the existing best-effort Commercial On The Shelf (COTS) IEEE802.11 WLANs using Layer 3 Admission Control and Adaptive Scheduling (L3-ACAS) scheme. This approach enables operators with existing large-scale WLAN deployments to offer QoS control over their networks with minimal disruption, capital expenditure (CAPEX) or infrastructure upgrade. Extensive simulation studies show that with this scheme, the total goodput, flows throughput ratio, packets delay and jitter of the real-time applications such as VoIP and real-time video can be improved significantly. We have also successfully implemented a testbed to evaluate our architecture using the existing COTS hardware and the open source Linux components.

A holistic sensor network design for energy conservation and efficient data dissemination

One important application of wireless sensor networks is to track mobile elements in the field, where the sensor network generally consists of a large number of sensor nodes deployed in an unattended environment and the sensor nodes are unlikely to be recharged. Redundant sensor nodes are often deployed to increase network robustness and extend network lifetime. There is a big challenge to distribute information and conserve energy in resource-constrained, densely populated sensor networks. Target and inquirer mobility brings further challenges to large-scale sensor networks. Frequent location updates for multiple inquirers and targets can drain the limited on-board energy excessively. We propose a holistic system design across media access control, network and application layers to optimize the performance of large-scale sensor networks by taking into account the interactions and tradeoffs between different design objectives. Our system includes a two-level node activity scheduling scheme for energy conservation and a scenario-aware data dissemination scheme to efficiently distribute query and event data and handle inquirer and target mobility. Furthermore, we analyze the system delay and introduce an adaptive scheduling scheme to reduce the initial sensing delay. The simulation results show that our system can save more than six times of the energy with reduced transmission delay and increased data delivery ratio.

Adaptive Mixed Scheduling for Correcting Errors in Trapping Sets of LDPC Codes

Trapping sets of low-density parity-check codes are the problematic substructures that contribute to the error floor behavior under iterative decoding. Adoption of mixed scheduling for belief propagation decoding has shown to be very effective in solving some of the trapping sets. In this letter, we propose an adaptive mixed scheduling scheme that provides significantly improved code performance compared to existing mixed scheduling schemes.

Development & Comparative Analysis of an Adaptive Fuzzy Logic LFC control model for Gain Scheduling using Fuzzy Logic & Adaptive Fuzzy Techniques

In this paper, the recent data based artificially intelligent techniques like fuzzy and neural network have been customized and used .The application/case study has been taken. Fuzzy provides a robust inference mechanism with no learning and adaptability and artificial neural network provides learning and adaptability. Artificial neural networks and fuzzy systems have been successfully applied to the LFC problem with rather promising results. In this paper, an adaptive fuzzy gain scheduling scheme for conventional PI controllers has been simulated and tested for off-nominal operating conditions. From the simulation and the result obtained in this paper, it has been shown that the proposed adaptive fuzzy logic controller offers better performance than fixed gain controllers& fuzzy gain controller. Comparative analysis of percentage error of gain using fuzzy& adaptive fuzzy has also been done in this paper. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org Er. Ashish Kumar Mechanical Engg. Deptt RIET, Rail Majra Er.Inderpal Singh Electrical Engg. Deptt BBSBEC, Fatehgarh

Utility-based resource allocation in orthogonal frequency division multiple access networks

The authors consider network utility maximisation problem in orthogonal frequency division multiple access (OFDMA) networks to study cross-layer, fair and efficient resource allocation. Assuming knowledge of the instantaneous channel gains, this problem is decomposed into rate control and scheduling problems at the transport and medium access control/physical layers, respectively. In contrast to the rate control problem that is solved using subgradient method, the scheduling problem has high computational complexity owing to optimising integer and continuous variables simultaneously. Based on the results from analysing the integer relaxed scheduling problem, computationally efficient adaptive scheduling (CEAS) and opportunistic time division multiple access (Opp-TDMA) scheduling schemes are proposed to joint subcarrier assignment and power allocation. Simulation results demonstrate that aggregate utility achieved in the network with the cooperation between rate control and proposed scheduling schemes outperforms those of previously proposed joint channel-aware and queue-aware scheduling schemes. Also, through comparison with the optimal solution, the authors conclude that CEAS is applicable for OFDMA real-time scheduling due to low computational complexity and high performance.

Adaptive Scheduling of Data Paths using Uppaal Tiga

We apply Uppaal Tiga to automatically compute adaptive scheduling strategies for an industrial casestudy dealing with a state-of-the-art image processing pipeline of a printer. As far as we know,this is the first application of timed automata technology to an industrial scheduling problem withuncertainty in job arrivals.

An adaptive job scheduling scheme for mesh-connected multicomputers

Allocating submeshes to jobs in mesh-connected multicomputers in an FCFS fashion leads to poor system performance because a large job at the head of the waiting queue can prevent the allocation of free submeshes to other smaller waiting jobs. However, serving jobs aggressively out-of-order can lead to excessive waiting delays for large jobs located at the head of the waiting queue. In this paper, we show that the ability of the job scheduling algorithm to bypass the head of the waiting queue should increase with the load, and we propose a scheduling scheme that can bypass the waiting queue head in a load-dependent adaptive fashion. Also, giving priority to large jobs because they are more difficult to accommodate is investigated. The performance of the proposed scheme has been compared to that of FCFS, aggressive out-of-order scheduling, and other previous job scheduling schemes. Extensive simulation results based on synthetic workloads and real workload traces indicate that our scheduling strategy is a good strategy when both average and maximum job waiting delays are considered. In particular, it is substantially superior to FCFS in terms of mean turnaround times, and to aggressive out-of-order scheduling in terms of maximum waiting delays.

Adaptive scheduling scheme to support real-time traffic in wireless local area networks

To overcome the defect of IEEE 802.11e reference scheduler allocating fixed Transmission Opportunity(TXOP) duration,an adaptive scheduling scheme was proposed to support real-time traffic.The proposed scheduler dynamically allocated variable TXOP duration based on the traffic load information of the amount of buffered frames in each traffic stream queue sent by stations,to satisfy the requirements of different traffic under different load.By guaranteeing minimum delay of traffic,the scheduler tried to allocate TXOP for the new arrival traffic with proportional request reduction and linear programming.Detailed simulation results and comparison with IEEE 802.11e reference scheduler prove that the proposed scheduling scheme not only improves system throughput,but also decreases delay of real-time traffic.

Applying reinforcement learning to scheduling strategies in an actual grid environment

Grid environments are dynamic and heterogeneous by nature, therefore requiring adaptive scheduling strategies. Reinforcement learning is an interesting and simple adaptive approach that may work well in actual grid environments. In this work, we employ reinforcement learning to classify available resources in a grid environment, giving support to two scheduling algorithms, AG and MQD. We study the makespan optimisation and load balancing. An algorithm known as RR is used for normalising purposes.

Ring of Masters (ROM): A new ring structure for Bluetooth scatternets with dynamic routing and adaptive scheduling schemes

This paper attempts to address the scatternet problem in Bluetooth through a comprehensive approach. We propose a new decentralized ring structure to combat the formation of traffic bottlenecks. The adopted construction protocol ensures flexibility of node selection and a good level of fault tolerance. The routing protocol combines both simplicity and robustness by taking advantage of the ring structure and relying on the collective memory of piconets to make forwarding and discarding decisions. The intra- and inter-piconet scheduling algorithm, called ROM adaptive scheduling (RAS), dynamically allocates time slots and is responsive to the varying workload conditions. We demonstrate, through analysis and simulations, that the various components of ROM yield a system that has good performance in terms of throughput, latency, delivery, and link utilization.

Predictive Congestion Control Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel estimator algorithm in DPC that predicts the channel quality. Then, an adaptive flow control scheme selects suitable rate which is enforced by the newly proposed adaptive backoff interval selection scheme. An optional adaptive scheduling scheme updates weights associated with each packet to guarantee the weighted fairness during congestion. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the DPCC reduces congestion and improves performance over congestion detection and avoidance (CODA) [3] and IEEE 802.11 protocols.

A method of genetic algorithm based multiobjective optimization via cooperative coevolution

The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

Scheduling with timed automata

In this work, we present timed automata as a natural tool for posing and solving scheduling problems. We show how efficient shortest path algorithms for timed automata can find optimal schedules for the classical job-shop problem. We then extend these results to synthesize adaptive scheduling strategies for problems with uncertainty in task durations.

Adaptive scheduling for differentiated services in an Ethernet passive optical network

Feature Issue on Optical Access Networks (OAN) The Ethernet passive optical network (EPON) is a technology viewed as an attractive solution to the last mile problem. The interleaved polling with adaptive cycle time (IPACT) is a remarkable medium access control (MAC) protocol for EPONs. The IPACT scheme supports two stages of scheduling. One is inter-optical network unit (ONU) scheduling. The other is intra-ONU scheduling. In this paper, we propose a systematic adaptive scheduling scheme to enhance the functions of the IPACT on both types of scheduling in order to achieve efficient bandwidth utilization of EPONs under unbalanced traffic and to provide class-of-service (COS) or differentiated services within an ONU. The simulation results show that our proposed scheduling scheme can improve the performance of the EPON system under unbalanced traffic loads and provide fair bandwidth allocation of the uplink to different types of traffic.