Traffic aided opportunistic scheduling for downlink transmissions: algorithms and performance bounds

Our contribution, in this paper, is two-fold. First, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. Specifically, we present a new expression for the spectral efficiency (SE) of the users and using this expression, we compare the degrees of fairness (DOF) of the TBS scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (CNR) based single-best user scheduling (SBS) and normalized CNR based proportional fair scheduling (PFS) schemes. The second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on our earlier proposed TBS scheme. This HTS scheme selects the first user based on the largest absolute CNR value among all the users while the second user is selected based on the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. The total transmission rate i.e., the constellation size is selected according to the absolute CNR of the first best user. The total transmission rate is then allocated among these selected users by joint consideration of their absolute CNRs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system's fairness without any degradation of the link spectral efficiency (LSE) i.e., the multiuser diversity gain compared to the classical SBS scheme. These results also show that the proposed HTS scheme has a lower fairness in comparison to the PFS scheme which suffers from a considerable degradation in LSE. © 2010 IEEE.

Inventory and total completion time minimization for assembly job-shop scheduling considering material integrity and assembly sequential constraint

This paper considers the multi-criteria scheduling problem with total completion time, maximum lateness, and maximum earliness as the objectives. The problem is a minimisation problem; the total completion time, a MIN-SUM problem, the maximum earliness, a MIN-MAX problem, and the maximum lateness, a MIN-MAX problem. Though, the problem is NP-hard, shortest processing time (SPT) rule, yields optimal for total completion time while early due date rule (EDD) is the optimal solution for maximum lateness and maximum earliness if each criterion were to be considered separately. Two heuristics, named SOL I and SOL II were proposed and the results for each of the criteria were compared to the optimal of the sub-problems. Results of the computational experiment on small job-sizes (5 ≤ n ≤ 30) and large job-sizes (40 ≤ n ≤ 100) show that the two heuristics results are not significantly different from the optimal at 99% significant level for total completion time and maximum lateness performance measures. However, for maximum earliness, the optimal solutions are significantly better than the two proposed heuristics.

Some scheduling problems with deteriorating jobs and learning effects

The paper deals with some single-machine scheduling problems with setup time considerations where the processing time of a job is given as a function of its starting times and position in a sequence. The setup times are proportional to the length of the already processed jobs, i.e., the setup times are past-sequence-dependent (p-s-d). We consider the following objective functions: the makespan, the total completion time, the sum of the δth (\( \delta \geqslant 0 \)) power of job completion times, the total weighted completion time, the maximum lateness and the number of tardy jobs. We show that the makespan minimization problem, the total completion time minimization problem, and the sum of the δth power of job completion times minimization problem can be solved in polynomial time, respectively. We also show that the total weighted completion time minimization problem, the maximum lateness minimization problem and the number of tardy jobs minimization problem can be solved in polynomial time under certain conditions.

A scheme transmitting superposition coding (SC), which superimposes unicast data to multicast data, using opportunistic multicast scheduling (OMS) scheme, is proposed and its performance is evaluated and simulated in this paper. Although the scheme is a little weaker than traditional scheme using QPSK modulation method in bit error rate (BER) performance, its throughput and system time delay promote considerably. Numerical results show that when user channel condition is weak and signal to noise ratio (SNR) is not high, the new scheme can outperform the conventional scheme in terms of system performances.

In this paper, a rate‐based admission control scheme for a single shared wireless base station with opportunistic scheduling and adaptive modulation and coding (AMC) is proposed. The proposed admission scheme maintains minimum average rates of the admitted users, i.e., new users will be admitted if the base station has enough resources to support the required minimum average transmission rates of all users. The proposed scheme relies on an analytical model for the average per‐user rates of an opportunistic scheduling in an unsaturated scenario, where some queues may be empty for certain periods of time. We provide extensive simulation results to demonstrate the accuracy of the base analytical model on which our admission scheme relies. Copyright © 2009 John Wiley & Sons, Ltd.

Although transanal total mesorectal excision (TaTME) is a promising treatment for low rectal cancer, it is considered technically demanding, and the number of cases required to become proficient in TaTME remains unknown. The purpose of this study was to assess the TaTME learning curve based on the total mesorectal excision completion time. This retrospective analysis comprised 128 individuals who received TaTME between September 2016 and December 2021. The cumulative sum method was used to generate the learning curve. The duration of the procedure from the beginning to the end of the circumferential rendezvous was used to define the total mesorectal excision completion time. The learning curve consists of 3 phases: phase I (learning phase: cases 1 to 38), phase II (consolidation phase: cases 39 to 70), and phase III (maturing phase: cases 71 to 128). As the phases varied, both the overall operative time and total mesorectal excision completion time decreased considerably. Through the 3 phases of TaTME, intraoperative adverse events decreased, and in phase III, none occurred. Only 1 instance of local recurrence occurred during phase III, and none occurred during phase I or II. After 70 operations, the surgeon could join the mastery phase of TaTME based on the total mesorectal excision completion time. After the mastering phase began, there were no intraoperative negative occurrences. From the beginning, the oncological safety could be guaranteed.

In this paper, we investigate secure communication for a dual-hop multiuser relay network, where a source communication with N ( N ≥ 1 ) destinations via an untrusted variable gains relay. To exploit multiuser diversity while protecting source’s confidential message, we first propose a joint destination-based jamming and opportunistic scheduling (DJOS) scheme. Then, we derive closed-form approximated and asymptotic expressions of the secrecy outage probability (SOP) for the considered system with DJOS. Furthermore, we determine an asymptotical optimal power allocation (OPA), which minimizes the asymptotic SOP, to further improve the secrecy performance. Our analytical results show that the achievable secrecy diversity order in terms of SOP with fixed power allocation is min ( 1 , N 2 ) , whereas, with OPA, the achievable secrecy diversity order can be improved up to min ( 1 , 2 N N + 2 ) . This interesting result reveals that OPA can improve the secrecy diversity order of the single-user network. This is intuitive since full diversity order of 1 cannot be achieved when N = 1 , thus leaving some space for OPA to improve the diversity order. Nevertheless, for N ≥ 2 , the effect of OPA is to increase the secrecy array gain rather than the secrecy diversity order since full diversity order 1 has been achieved by the OS scheme. Finally, simulation results are presented to validate our analysis.

Diamond relay network model, as a basic transmission model, has recently been attracting considerable attention in wireless ad hoc networks. Node cooperation and opportunistic scheduling scheme are two important techniques to improve the performance in wireless scenarios. In the paper we consider such a problem how to efficiently combine opportunistic scheduling and cooperative modes for the Rayleigh fading scenario in the diamond relay network. To do so, we first compare the throughput of SRP (Spatial Reused Pattern) and AFP (Amplify Forwarding Pattern) in the half‐duplex case with the assumption that channel side information is known to all and then come up with a new scheduling scheme. It will be verified that only switching between SRP and AFP simply does little help to obtain an expected improvement because SRP is always superior to AFP on average due to its efficient spatial reuse. To improve the throughput further, we put forward a new processing strategy in which buffers are employed at both relays in SRP mode. By efficiently utilizing the links with relatively higher gains, the throughput can be greatly improved at a cost of queuing delay. Furthermore, we shall quantitatively evaluate the queuing delay and the tradeoff between the throughput and the additional queuing delay. Finally, to realize our developed strategy and make sure it always run at stable status, we present two criteria and an algorithm on the selection and adjustment of the switching thresholds. Copyright © 2009 John Wiley & Sons, Ltd.

Many cloud applications are data intensive requiring the processing of large data sets and the MapReduce/Hadoop architecture has become the de facto processing framework for these applications. Large data sets are stored in data nodes in the cloud which are typically SAN or NAS devices. Cloud applications process these data sets using a large number of application virtual machines (VMs), with the total completion time being an important performance metric. There are many factors that affect the total completion time of the processing task such as the load on the individual servers, the task scheduling mechanism, communication and data access bottlenecks, etc. One dominating factor that affects completion times for data intensive applications is the access latencies from processing nodes to data nodes. Ideally, one would like to keep all data access local to minimize access latency but this is often not possible due to the size of the data sets, capacity constraints in processing nodes which constrain VMs from being placed in their ideal location and so on. When it is not possible to keep all data access local, one would like to optimize the placement of VMs so that the impact of data access latencies on completion times is minimized. We address this problem of optimized VM placement - given the location of the data sets, we need to determine the locations for placing the VMs so as to minimize data access latencies while satisfying system constraints. We present optimal algorithms for determining the VM locations satisfying various constraints and with objectives that capture natural tradeoffs between minimizing latencies and incurring bandwidth costs. We also consider the problem of incorporating inter-VM latency constraints. In this case, the associated location problem is NP-hard with no effective approximation within a factor of 2 - ϵ for any ϵ > 0. We discuss an effective heuristic for this case and evaluate by simulation the impact of the various tradeoffs in the optimization objectives.

Energy and time constrained scheduling for optimized quality of service

Energy-efficient opportunistic scheduling schemes in wireless networks

Two extensions of the classical scheduling model with two parallel identical machines and a partially ordered set of unit execution time tasks are considered. It is well known that the Coffman—Graham algorithm constructs for this model a so-called ideal schedule: that is, a schedule which is optimal for both makespan and total completion time criteria simultaneously. The question of the existence of such a schedule for the extension of this model, where each task has a release time, has remained open over several decades. The paper gives a positive answer to this question and presents the corresponding polynomial-time algorithm. Another straightforward generalization of the considered classical model is obtained by the introduction of multiprocessor tasks. It is shown that, despite the fact that a slightly modified Coffman-Graham algorithm solves the makespan problem with multiprocessor tasks for arbitrary precedence constraints, generally an ideal schedule does not exist and the problem with the criterion of total completion time turns out to be NP-hard in the strong sense even for in-trees.

Minimizing total completion time with linear deterioration: A new lower bound