Sequential Scheduling Algorithm Research Articles

Sequential clinical scheduling with stochastic patient re-entrance: Case of Mohs Micrographic Surgery

We study the problem of appointment scheduling for outpatient clinics with stochastic patient re-entrance. It is motivated by the scheduling problem for Mohs Micrographic Surgery, which is a popular technique for the excision of skin cancers. Re-entrance occurs when a patient repeats upstream processes during the single-day outpatient appointment, usually after a medical test. In some surgical procedures, the number of re-entrances for each patient is unknown until medical test results become available, causing long patient waiting time and clinic overtime. To address these challenges, we develop a stochastic slot model, SMART, that captures the key characteristics of the appointment processes and stochastic re-entrance, utilizing a delay before possible re-entrance. We then design a sequential scheduling algorithm that balances patient waiting, clinic overtime and patient throughput while considering stochastic complications such as no-shows, processing time variability, and the number of re-entrances per patient. We establish several theoretical properties of the algorithm, including the optimality of the resulting schedules for the sequential scheduling setting. We apply SMART to appointment scheduling for Mohs clinics, where patients may have same-day re-entrance due to repetitive skin excisions. We compare SMART schedules to others that ignore re-entrance and to current scheduling practices via simulation studies under a more realistic setting. Numerical experiments show that SMART schedules dominate other schedules, and ignoring re-entrance can cost huge loss in efficiency. Furthermore, SMART schedules exhibit a special ‘stair-stepping’ pattern for the number of appointments, with most patients assigned to the early slots and many empty slots at the end.

Research on Particle Swarm Optimization Algorithm Based on Cloud Computing Task Scheduling

Whether home or abroad, both resource allocation and task scheduling is one of the popular problems in the cloud computing environment, and swarm intelligence algorithm is a hot topic. Particle swarm optimization (PSO) is an important swarm intelligent algorithm in solving the task scheduling optimization problem. Based on the research of the basic PSO algorithm, this paper proposes the next improvement strategies: (1) The calculation method of the success value of single particle is improved, and the progressive speed of individual particles is improved; (2) Integrated the correlation between random factors, that improved the global optimization ability of PSO algorithm in the process of optimization, and avoided the particle trapping into the local best. The simulation results show that under the same conditions, the improved algorithm’s execution time is better than the sequential scheduling algorithm, the greedy algorithm, the basic PSO algorithm, the correlation PSO algorithm and the adaptive PSO algorithm for inertia weights.

OFDMA Based QoS-Oriented Guarantee Novelty Multiple Access Protocol

The next generation wireless local area network (WLAN) 802.11ax standards committee takes high quality of service(QoS) guarantee as one of important technology goals of the next generation WLAN. As a result of a variety of wireless traffics, so the requirements of the QoS must also be varied. However, the existing media access control(MAC) protocol based on orthogonal frequency division multiple access(OFDMA) can’t support QoS diversification and high requirement well. To solve this problem, this paper presents a QoS-oriented OFDMA MAC for the next generation WLAN. On one hand, for backward compatibility consideration, continue to use four priority traffics of 802.11e in this protocol; on the other hand, the introduction of QoS-oriented priority scheduling algorithm to support future wireless traffic feature which is QoS of diversification and high requirements. Finally, through the simulation, the system effective throughput of the proposed QoS-OFDMA MAC is 57.8% and 59% higher than the OFDMA MAC of the sequential scheduling algorithm and the OFDMA MAC of the proportional fairness algorithm.

Sequential ship traffic scheduling model for restricted two-way waterway transportation

A good ship traffic scheduling mode can enhance traffic efficiency to a large degree, especially in restricted waterways such as approach channel of ports and straits. A ship scheduling model for restricted two-way waterways is proposed in this article. The assumption is made in the model that two-way transportation is not allowed for cases in which there is at least one large ship. Based on this assumption, a mathematical model is proposed to minimize the weighted average of the mean and the maximum waiting time given several safety restrictions. A sequential scheduling algorithm is proposed to solve such problem, in which the ships are divided into rounds. The ships in each round are scheduled simultaneously to enhance traffic efficiency by the trade-off between the priorities of small and large ships. Experiments are carried out by comparing sequential scheduling method with first-come-first-serve model. The results indicate that the proposed algorithm can reduce ships’ waiting time, whereas a lot of ships need to wait for long time with first come first serve. The distinctions are more evident with a higher proportion of large ships, and the proposed algorithm can keep ships’ waiting time to an acceptable level.

고급 언어에서 ASIP을 위한 전용 부호 생성 기술 연구

In this paper, we discuss a code generation technique for custom transport triggered architecture (TTA) from a high-level language structure. This methodology is implemented by using TTA-based Co-design Environment (TCE) tool. The results show how the scheduler exploits instruction level parallelism in the custom target architecture and source program. Thus, the scheduler generates parallel TTA instructions using lower cycle counts than the sequential scheduling algorithm. Moreover, we take Tensilica tool to make a comparison with TCE. Because of the efficiency of TTA, TCE takes less execution cycles compared to Tensilica configurations. Finally, this paper shows that it requires only 7 cycles to generate the parallel TTA instruction set for implementing Cyclic Redundancy Check (CRC) applications as an input design, and presents the code generation technique to move complexity from the processor software to hardware architecture. This method can be applicable lots of channel Codecs like CRC and source Codecs like High Efficiency Video Coding (HEVC).

Weighted-Bit-Flipping-Based Sequential Scheduling Decoding Algorithms for LDPC Codes

Low-density parity-check (LDPC) codes can be applied in a lot of different scenarios such as video broadcasting and satellite communications. LDPC codes are commonly decoded by an iterative algorithm called belief propagation (BP) over the corresponding Tanner graph. The original BP updates all the variable-nodes simultaneously, followed by all the check-nodes simultaneously as well. We propose a sequential scheduling algorithm based on weighted bit-flipping (WBF) algorithm for the sake of improving the convergence speed. Notoriously, WBF is a low-complexity and simple algorithm. We combine it with BP to obtain advantages of these two algorithms. Flipping function used in WBF is borrowed to determine the priority of scheduling. Simulation results show that it can provide a good tradeoff between FER performance and computation complexity for short-length LDPC codes.

Sequential clinical scheduling with patient no-show: The impact of pre-defined slot structures

This paper develops a sequential scheduling algorithm for consultation periods not divided into slots. Patients call a scheduler and request appointments with a specified provider. The scheduler provides the patient with an appointment time before the call terminates. In making the appointment, the scheduler cannot alter the appointments of previously scheduled patients. Service times are random and each scheduled patient has a probability of “no-showing” for the appointment. Each arriving patient generates a given amount of revenue, and costs are incurred from patient waiting and provider overtime. The scheduling method selects the calling patient's appointment time by minimizing the total expected cost. We prove that total expected cost is a convex function of appointment times and that the expected profit of the schedule is unimodal, which provides a unique stopping criterion for the scheduling algorithm. Computational studies compare this approach with no-show based sequential scheduling methods for out-patient clinics where a predefined slot structure is assumed. The new method yields higher expected profit and less overtime than when service periods are pre-divided into slots. Because slot scheduling is ingrained in healthcare, we use the model to design slot structures that account for no-show and service time variation.

Sequential clinical scheduling with service criteria

This study investigates sequential appointment scheduling with service criteria. It uses a constraint-based approach with service criteria bounded in a constraint set in contrast to the more typical weighted linear objective function. Properties are derived and a sequential scheduling algorithm is developed. Fairness properties of generated schedules are considered in detail, where fairness is the uniformity of performance across patients. New unfairness measures are proposed and used to capture the inequity among patients assigned to different slots. Other criteria such as expectation and variance of patient waiting time, queue length, and overtime are also considered. The fairness/revenue tradeoff is investigated as is the flexibility of the constraint-based approach in handling unavailable time periods.

Downlink data transmission scheduling algorithms in wireless networks

The problem of downlink data transmission scheduling in wireless networks is studied. It is pointed out that every downlink data transmission scheduling algorithm must have two components to solve the two subproblems of power assignment and transmission scheduling. Two types of downlink data transmission scheduling algorithms are proposed. In the first type, power assignment is performed before transmission scheduling. In the second type, power assignment is performed after transmission scheduling. The performance of two algorithms of the first type which use the equal power allocation method are analyzed. It is shown that both algorithms exhibit excellent worst-case performance and asymptotically optimal average-case performance under the condition that the total transmission power is equally allocated to the channels. In general, both algorithms exhibit excellent average-case performance. It is demonstrated that two algorithms of the second type perform better than the two algorithms of the first type due to the equal time power allocation method. Furthermore, the performance of our algorithms are very close to the optimal and the room for further performance improvement is very limited. It is shown that all the above algorithms can be extended to schedule downlink data transmissions with parallel channels. It is also shown that the simple sequential scheduling algorithm is optimal if the total transmission power is equally allocated to the channels. As an extra contribution, an M/G/1 queueing model for the FCFS queueing discipline is established, and it is observed that increasing the number of channels has more impact on the reduction of the average response time than increasing the total transmission power.

Design and performance analysis of scheduling algorithms for WDM-PON under SUCCESS-HPON architecture

Results of the design and performance analysis of two new algorithms for efficient and fair scheduling of variable-length frames in a wavelength division multiplexing (WDM)-passive optical network (PON) under the Stanford University aCCESS-Hybrid PON (SUCCESS-HPON) architecture are reported. The WDM-PON under the SUCCESS-HPON architecture has unique features that have direct impacts on the design of scheduling algorithms. First, an optical line terminal (OLT) uses tunable transmitters and receivers that are shared by all the optical network units (ONUs) served by the OLT to reduce the number of expensive dense WDM (DWDM) transceivers. Second, also for cost reduction, ONUs have no local DWDM light sources but use optical modulators to modulate optical continuous wave (CW) bursts provided by the OLT for upstream transmissions. Therefore, the tunable transmitters at the OLT are used for both upstream and downstream transmissions. To provide efficient bidirectional communications between the OLT and the ONUs and guarantee fairness between upstream and downstream traffic, two scheduling algorithms have been designed: 1) batching earliest departure first (BEDF); and 2) sequential scheduling with schedule-time framing (S/sup 3/F). The BEDF is based on the batch scheduling mode where frames arriving at the OLT during a batch period are stored in virtual output queues (VOQs) and scheduled at the end of the batch period. It improves transmission efficiency by selecting the frame with the earliest departure time from a batch of multiple frames, which optimizes the usage of tunable transmitters in scheduling. Considering the high complexity of the optimization process in BEDF, the S/sup 3/F based on the sequential scheduling mode has also been designed as in the original sequential scheduling algorithm proposed earlier. In S/sup 3/F, the authors use VOQs to provide memory space protection among traffic flows and a granting scheme together with schedule-time framing for both upstream and downstream traffic to reduce framing and guard band overhead. Through extensive simulations under various configurations of the tunable transmitters and receivers, it has been demonstrated that both the BEDF and S/sup 3/F substantially improve the throughput and delay performances over the original sequential scheduling algorithm, while guaranteeing better fairness between upstream and downstream traffic.

Scheduling Algorithms for Star-Coupled WDM Networks with Tunable Transmitter and Tunable Receiver Architecture

This paper presents the design and analysis of two scheduling algorithms for a reservation-based medium access control (MAC) protocol for wavelength division multiplexed (WDM) multi-channel optical networks. The network architecture is based on a passive star topology with one tunable transmitter and receiver (TT-TR) per node. The main objective of scheduling algorithm design is to reduce the computation time while maximizing the utilization of the network resources. In this paper, we propose two scheduling schemes called SEQSAM (SEQuential Scheduling AlgorithM) and BALSAM (BALanced Scheduling AlgorithM). Let M denote the number of nodes, C the number of channels, and K the maximum number of packets transmitted by one node to another. SEQSAM uses the M × M traffic demand matrix--obtained during the reservation phase of the MAC protocol--to compute a collision-free schedule for the nodes of the network. BALSAM uses the modified MULTI-FIT algorithm (MMFT) [1] to convert the M × M matrix into a corresponding M × C matrix, which is input to the IBS (Interval Based Scheduling) algorithm [2] that schedules the requests of the nodes. The overall time complexity of SEQSAM is O(M3) compared to BALSAM algorithm's time complexity of O(M2CK + M2 + MlogM). Note that the lower bound for any scheduling algorithm operating on a M × M matrix is O(M2). A simulation-based performance study that considers network utilization, computation time, tuning latency, average packet latency and throughput for 1.2 Gbps and 2.4 Gbps data streams is presented.

An Approximation Algorithm for Diagnostic Test Scheduling in Multicomputer Systems

The problem of diagnostic test scheduling (DTS) is to assign to each edge e of a diagnostic graph G a time interval of length l(e) so that intervals corresponding to edges at any given vertex do not overlap and the overall finishing time is minimum. In this correspondence we show that the DTS problem is NP-complete. Then we present a longest, first sequential scheduling algorithm which runs in worst case time O(dm log n) and uses O(m) space to produce a solution of length less than four times optimal. Then we show that the general performance bound can be strengthened to 3 * OPT(G) for low-degree graphs and to 2 ·OPT(G) in some special cases of binomial diagnostic graphs.