Minimum Delay Scheduling Research Articles

Minimum Length Minimum Delay Scheduling Using Artificial Butterfly Optimization (ABO) Algorithm in Manet

Recently, the requirement for various real-time applications over Mobile ad-hoc networks (MANETs) has been increasing tremandously. Packet scheduling and routing algorithms are the important factors for improving the Quality of service (QoS) parameters over the MANETs. Still, it is not easy to proficiently aid multimedia broadcast with its stringent delay constraints over MANETs. Moreover, there are several problems in assisting QoS over MANETs owing to interference amid nodes in the network. In this paper, Minimum Length Minimum Delay Scheduling (MLMDS) using Artificial Butterfly Optimization (ABO) algorithm is proposed. A fitness function for ABO is derived in terms of the round trip scheduling delay, the conflict graph and the amount of slots in the data sub-frame. A slot selection algorithm is proposed such that the selected slot is supposed to yield lesser delay and spatial reuse. By simulation results, it has been shown that MLMDS achieves minimum delay with higher throughput.

Delay, Throughput and Emission Tradeoffs in Airport Runway Scheduling with Uncertainty Considerations

Runway systems are among the most stringent bottlenecks at global hub airports, which have been identified as a major source of airport inefficiency. Runway system inefficiencies are manifested in multiple dimensions such as delay, throughput reduction and excessive emission, whose tradeoffs are investigated in this paper as part of an airport runway scheduling problem in the presence of uncertainty. We formulate a multi-objective optimization model aiming to minimize flight delays, maximize airport throughput, and minimize aircraft emissions, subject to a variety of constraints such as minimum separation, time window, runway occupancy and flight turnaround. The computational performance is enhanced with an efficient multi-objective evolutionary algorithm, with two mechanisms of adaptive and controllable time-coding and objective-guided individual selection. The proposed method is flexible in adjusting conservatism when it comes to optimization with uncertainty, and offers a set of Pareto optimal solutions for different stakeholders without using scalarization of different objectives. A real-world case study is carried out for one of the world’s buiest airports, Shanghai Pudong, under the case of 2 runways, 2 operation types, 12 uncertain conditions and 4 tradeoff scenarios. The computational results show that the proposed optimized method has overall advantages in improving the runway scheduling performance over some meta-heuristics and the First Come First Served strategy. The tradeoff analysis reveals that the minimum delay schedule is preferable for balancing delay, throughtput and emission. The findings provide managerial insights regarding traffic management measures for different stakeholders at high-density airports.

Scheduling Policies for Wireless Downlink With Correlated Random Connectivity and Multislot Reconfiguration Delay

Stable and minimum delay scheduling of wireless downlinks, with time correlated random connectivity between the base station and each associated user, is an important problem in modern communication systems. We assume that the base station of the wireless downlink dynamically switches between the users to transmit packets to each user. The dynamic switching of the base station incurs a reconfiguration delay. We find that as the reconfiguration delay increases the stability region of the wireless downlink with correlated channel connectivity shrinks to that achieved by time sharing among the users over large time periods. Since existing scheduling policies are designed either for single slot reconfiguration delay and correlated random connectivity, or multislot reconfiguration delay but without correlated connectivity, we propose scheduling policies which explicitly takes into account the correlated channel connectivity and multislot reconfiguration delay and show using simulations that the average delay is reduced compared to existing policies.

Operational Schedule Flexibility and Infrastructure Investment: Capacity Trade-Off on Single-Track Railways

To minimize costs, railways carefully match route infrastructure investment to projected traffic levels. Under structured operations according to a rigid timetable, the optimal amount of infrastructure for a given traffic volume can be determined with various models. However, North American railways use flexible operations for which planned train departure times can vary. Schedule flexibility increases the number of possible meet locations on a single track, which can lead to a combination of increased delays and infrastructure investment. When industry practitioners plan rail line capacity for flexible operations, they rarely optimize schedule flexibility and infrastructure investment simultaneously for a given level of service. To increase knowledge of the relationship between these factors, the research reported in this paper simulated operations on two representative single-track routes with rail traffic controller software. A baseline minimum-delay schedule was developed for each route under an initial infrastructure. The experiment design introduced schedule flexibility and infrastructure expansion to examine the interaction between these factors and train delay response. The results suggested that, for a given infrastructure configuration, an immediate increase in train delay occurred with small amounts of schedule flexibility. After this increase, routes became insensitive to further increases in schedule flexibility. Similarly, to maintain a level of service required substantial infrastructure investment for small amounts of schedule flexibility.

Cross-Layer Minimum-Delay Scheduling and Maximum-Throughput Resource Allocation for Multiuser Cognitive Networks

A cognitive network is considered that consists of a base station (BS) communicating with multiple primary and secondary users. Each secondary user can access only one of the orthogonal primary channels. A model is considered in which the primary users can tolerate a certain average delay. A special case is also considered in which the primary users do not suffer from any delay. A novel cross-layer scheme is proposed in which the BS performs successive interference cancellation and thus a secondary user can coexist with an active primary user without adversely affecting its transmission. A scheduling algorithm is proposed that minimizes the average packet delay of the secondary user under constraints on the average power transmitted by the secondary user and the average packet delay of the primary user. A resource allocation algorithm is also proposed to assign the secondary users' channels such that the total throughput of the network is maximized. Our results indicate that the network throughput increases significantly by increasing the number of transmitted packets of the secondary users and/or by allowing a small delay for the primary user packets.

An Optimal Energy Efficient and Minimum Delay Scheduling for Periodic WSN Applications

Wireless Sensor Network (WSN) enables pervasive, ubiquitous, and seamless communication with the physical world. This paper investigates an optimal cross-layer joint routing and scheduling problem for WSN with periodic data collection. The problem is formulated as an Integer Linear Program (ILP) model such that a joint scheduling and routing is developed to maximize network lifetime and minimize delay. In this paper, an ILP model with multi objective cost function is proposed. The proposed ILP model represents the operation of Energy-Efficient Distributed Schedule-Based (EEDS) protocol. The ILP model is solved for different network configurations. The optimal solutions assuming different objectives are compared.

Conditionally Optimal Minimum-Delay Scheduling for Bursty Traffic Over Fading Channels

Next-generation wireless networks for personal communication services should be designed to transfer delay-sensitive bursty-traffic flows over energy-limited buffer-equipped faded connections. In this application scenario, a still-open question concerns the closed-form design of scheduling policies minimizing the average transfer delay under constraints on both average and peak energies. Since, in this paper, both queue and link states may assume finite, countable infinite, or even uncountable infinite values, we cannot resort to dynamic programming to solve the aforementioned minimization problem. The key point of the (somewhat) novel approach that we follow consists of the minimization (on a per-step basis) of the queue length averaged over the fading statistics and conditioned on the queue occupancy at the previous step when two energy constraints are considered. The first one is on the allowed peak energy, and the second one is on the available average energy conditioned on the current queue occupancy. The resulting optimal scheduler operates cross layer, meaning that it allocates step-by-step energy on the basis of both current queue and link states. We prove that, under the considered energy constraints, the scheduler retains two optimality properties. First, its stability region is the maximal admissible one. Second, the scheduler also minimizes the unconditional average queue length. The numerical tests that have been carried out corroborate these optimality properties and give insight about scheduler performance under heavy-tailed distributed input traffic, such as that generated by variable-bit-rate (VBR) media encoders.

Minimum Delay Scheduling for Performance Guaranteed Switches With Optical Fabrics

We consider traffic scheduling in performance guaranteed switches with optical fabrics to ensure 100% throughput and bounded packet delay. Each switch reconfiguration consumes a constant period of time called reconfiguration overhead, during which no packet can be transmitted across the switch. To minimize the packet delay bound for an arbitrary traffic matrix, the number of switch configurations in the schedule should be no larger than the switch size N . This is called minimum delay scheduling, where the ideal minimum packet delay bound is determined solely by the total overhead of the N switch reconfigurations. A speedup in the switch determines the actual packet delay bound, which decreases toward the ideal bound as the speedup increases. Our objective is to minimize the required speedup S schedule under a given actual packet delay bound. We propose a novel minimum delay scheduling algorithm quasi largest-entry-first (QLEF) to solve this problem. Compared with the existing minimum delay scheduling algorithms MIN and alphai-SCALE, QLEF dramatically cuts down the required S schedule bound. For example, QLEF only requires S schedule=17.89 for N=450, whereas MIN and alphai -SCALE require S schedule=37.13 and 27.82, respectively. This gives a significant performance gain of 52% over MIN and 36% over alphai-SCALE.

A periodic scheduling problem in flow control for data communication networks

The scheduling of user-session transmission-priority time slots in time-periodic frames on links in a network is considered from an algorithmic standpoint. Priority slot schedules with low schedule delays can be used in a flow control scheme to lower limits on packet intranetwork delay. An NP-completeness result is proved, showing that for general networks the scheduling of priority slots to obtain a minimum sum of schedule delays is algorithmically hard. Minimum-delay scheduling algorithms for special classes and a scheduling heuristic for general networks are presented. >