Heuristic Algorithm for Proportional Fair Scheduling in D2D-Cellular Systems

Resource allocation (RA) for OFDMA has been extensively researched with the objective of maximizing capacity while serving users in a fair manner. However, most of the previous works have focused on achieving these requirements per symbol (instantaneously). On the other hand proportional fair (PF) scheduling which is widely deployed in 3G data networks achieves the system objectives over a certain time, thus adding flexibility and increasing the system throughput. PF scheduling has been modified to work in OFDMA in a few studies, but they have extended the scheme without making use of the additional capacity increase that can be achieved by considering individual relative subcarrier responses. In this paper we propose a simple subcarrier opportunistic proportional fair (SOPF) scheduling scheme specifically suited to OFDMA. It includes a measure that makes the allocation assign the subcarrier to the user who has the best response relative to the average response of that subcarrier with the rest of the users. The result is that our SOPF scheme achieves a capacity-fairness measure above the traditional PF scheme.

In this paper, we provide expressions for the secrecy outage probability (SOP) for suboptimal and optimal opportunistic scheduling schemes in a reconfigurable intelligent surface (RIS) aided single antenna system with multiple eavesdroppers in approximate closed form. A suboptimal scheduling (SS) scheme is analyzed, which is used when the channel state information (CSI) of the eavesdropping links is unavailable, and the optimal scheduling (OS) scheme is also analyzed, which is used when the global CSI is available. For each scheme, we provide a simplified expression for the SOP in the high signal-to-noise ratio (SNR) regime to demonstrate its behavior as a function of the key system parameters. At high SNR, the SOP saturates to a constant level which decreases exponentially with the number of RIS elements in the SS scheme and with the product of the number of RIS elements and the number of users in the OS scheme. We also show that the derived SOP of the SS scheme can directly provide the SOP for the best antenna-user pair scheduling scheme in a multiple antenna system. We compare the performance of the opportunistic user scheduling schemes with that of a non-orthogonal multiple access (NOMA) based scheduling scheme which chooses a pair of users in each time slot for scheduling and we show that the opportunistic schemes outperform the NOMA-based scheme. We also derive a closed-form expression for the SOP of a decode-and-forward (DF) relay-aided scheduling scheme in order to compare it with that of the RIS-aided system. It is found that the RIS-aided system outperforms the relay-aided system when the number of RIS elements is sufficiently large. An increased number of RIS elements is required to outperform the relay-aided system at higher operating frequencies.

Emerging systems like OFDMA and MIMO systems require multichannel scheduling over a wireless link. In this paper, we focus on the case that the number of channels to be assigned to a mobile terminal is limited, which we call limited matching. This case often occurs over a MIMO downlink when the number of receive antennas at a mobile user is smaller than that of transmit antennas at the base station. When the system exploits channel-aware opportunistic scheduling based on the channel feedback, finding the sum of channel gains by the limited matching is an NP-complete problem. To solve it easily, we can use the Hungarian algorithm, but its complexity is still too high and not amenable to performance analysis. Hence, we develop a heuristic algorithm, and analyze its cell throughput. Also, we investigate its performance when the channel feedback information is partially available. For analytic simplicity, we consider proportionally fair (PF) scheduling that is widely accepted as an opportunistic scheduler. Numerical results demonstrate that our heuristic limited-matching scheduling algorithm works well with partial channel feedback.

Directed acyclic graph (DAG) scheduling is a well-known problem, because a DAG can be used to describe a wide range of complex applications, including scientific applications and parallel computing jobs. Most DAG scheduling algorithms were proposed to minimize the job makespan (i.e., execution time) on a multiprocessor computer or cluster. However, as the cost-driven public cloud services have become an attractive and popular platform for providing computing resources, cost minimization emerges as a new critical issue. Therefore, the objective of this work is to propose and solve the cost optimization problem for scheduling DAGs on an IaaS cloud platform where task scheduling must cope with resource provisioning to achieve the optimal solution. In this paper, we proposed both optimal and heuristic scheduling algorithms, and we evaluated them across a variety of DAGs using the price model from EC2. Comparing to other cost-oblivious DAG schedules that aim to minimize makespan or resource usage, the results show that our cost-aware heuristic algorithm can reduce cost by 20---50 % and achieve a cost within x1.16 of the optimal one.

Long Term Evolution(LTE) 시스템은 멀티미디어 서비스와 같은 다양한 서비스를 이동 사용자에게 제공할 수 있다. 실제로 HSPA+(High Speed Packet Access plus)는 다운링크의 비트 율(bit rate)을 크게 향상 시켰으나, 다양한 멀티미디어 서비스에서 요구하는 서비스 품질을 어떻게 만족시킬 것인가에 대한 연구는 매우 미비한 상태이다. 본 논문에서는 proportional fair(PF) 알고리즘을 기반으로 하여 LTE를 위한 효율적인 패킷 스케쥴링 알고리즘을 제안하였다. 제안된 알고리즘에서는 패킷 스케쥴링을 할 때 패킷의 우선순위를 결정하는 가장 중요한 요소인 트래픽 클래스의 가중치와 순간 사용자 데이터 전송율을 최적화 하였다. 또한 다중 셀(multi-cell) 환경에서 LTE를 통해서 사용자에게 전송되는 멀티미디어 트래픽을 시뮬레이션 함으로써 제안된 알고리즘의 성능이 향상되었음을 보였다. The Long Term Evolution (LTE) system is already able to provide a background of variety services for mobile users with multimedia services such as audio, video, and data. In fact, the High Speed Packet Access plus (HSPA+) solution can greatly enhance bit rates on down-link. However, the supporting for multimedia applications with different QoS (Quality of Service) requirements is not devised yet. Hence, in this paper we propose an effective packet scheduling algorithm based on Proportional Fairness (PF) scheduling algorithms for the LTE. In this proposed packet scheduling scheme, we optimized instantaneous user data rates and the traffic class weight which prioritize user's packets. Finally, we evaluated and showed the performance of the proposed scheduling algorithm through simulations of multimedia traffics being transmitted to users over LTE links in a multi-cell environment.

A modified proportional fairness (PF) scheduling scheme for OFDMA systems with imperfect channel quality indicator is suggested. It is based on user grouping, and in system level simulations, the proposed scheme improves average user throughput considerably when compared to conventional PF scheduling without grouping.

Secrecy outage analysis of multi-user multi-eavesdropper cellular networks in the face of cochannel interference

Radio-frequency (RF) energy harvesting presents a viable solution to prolong the lifetime of wireless communication devices. In this paper, we study downlink multiuser scheduling for a time-slotted system with simultaneous wireless information and power transfer. In particular, in each time slot, a single user is scheduled to receive information, whereas the remaining users opportunistically harvest the ambient RF energy. We devise novel online scheduling schemes in which the tradeoff between the users' ergodic rates and their average amount of harvested energy can be controlled. In particular, we modify the well-known maximum signal-to-noise ratio (SNR) and maximum normalized-SNR (N-SNR) schedulers by scheduling the user whose SNR/N-SNR has a certain ascending order (selection order) rather than the maximum one. We refer to these new schemes as order-based SNR/N-SNR scheduling and show that the lower the selection order, the higher the average amount of harvested energy in the system at the expense of a reduced ergodic sum rate. The order-based N-SNR scheduling scheme provides proportional fairness among the users in terms of both the ergodic achievable rate and the average harvested energy. Furthermore, we propose an order-based equal throughput (ET) fair scheduler, which schedules the user having the minimum moving average throughput out of the users whose N-SNR orders fall into a given set of allowed orders. We show that this scheme provides the users with proportionally fair average harvested energy values. In this context, we also derive feasibility conditions for achieving ET with the order-based ET scheduler. Using the theory of order statistics, the average per-user harvested energy and ergodic achievable rate of all proposed scheduling schemes are analyzed and obtained in closed form for independent and nonidentically distributed Rayleigh, Rician, Nakagami- $m$, and Weibull fading channels. Our closed-form analytical results are corroborated by simulations.

In the wireless sensor networks, sensor deployment and coverage are the vital parameter that impacts the network lifetime. Network lifetime can be increased by optimal placement of sensor nodes and optimizing the coverage with the scheduling approach. For sensor deployment, heuristic algorithm is proposed which automatically adjusts the sensing range with overlapping sensing area without affecting the high degree of coverage. In order to demonstrate the network lifetime, we propose a new heuristic algorithm for scheduling which increases the network lifetime in the wireless sensor network. Further, the proposed heuristic algorithm is compared with the existing algorithms such as ant colony optimization, artificial bee colony algorithm and particle swarm optimization. The result reveals that the proposed heuristic algorithm with adjustable sensing range for sensor deployment and scheduling algorithm significantly increases the network lifetime.

Fair scheduling or Fair Queueing (FQ) algorithms have received much attention in recent years because of their ability to provide a wide range of Quality-ofService (QoS) guarantees to end users. In this paper, we present a new analysis method that can statistically model such fair scheduling algorithms under Poisson arrivals and a general packet length distribution. We coin the new term M/G/FQ to describe this analysis method, which fits a broad range of scheduling policies including WFQ, SCFQ, SFQ and SPFQ.

When the traditional heterogeneous multi-core scheduling algorithm performs tasks with high resource density, a large amount of idle time often occurs on the processor core. Therefore, based on the environment of heterogeneous multi-core processors, this paper studies the static heuristic table scheduling algorithm, and proposes an optimization approach for the problem of single priority assignment and too simple task assignment. We design optimization in the static heuristic scheduling algorithm list generation phase and task allocation phase, and propose a hybrid task allocation method with three strategies to improve the standby time utilization of processor core. Then, DVFS technology is used to optimize the scheduling results, so that the task can run with lower energy consumption without increasing makespan. Finally, the new algorithm is compared with three traditional scheduling algorithms through design experiments, and it is proved that the new algorithm has better performance when executing more tasks.

Analysis of temporal and throughput fair scheduling in multirate WLANs

We present a jointly optimal selection and scheduling scheme for the lossy transmission of frames governed by a dependency relation and a delay constraint over a link with limited capacity. A main application for this is scalable video streaming. Our objective is to select a subset of frames and decide their transmission schedule such that the overall video quality at the receiver is maximized. The problem is solved for two of the most common classes of dependency structures for video encoding, which include as a special case the popular hierarchical dyadic structure. We formally characterize the structural properties of an optimal transmission schedule in terms of frame dependency. It is shown that regardless of the subset of frames selected for transmission, any optimal schedule has an equivalent canonical form that is a subsequence of a unique universal sequence containing all frames. The canonical form can be computed efficiently through the construction of a dependency tree. This leads to separable but jointly optimal frame selection and scheduling algorithms that have quadratic computational complexity in the number of frames. Simulation with video traces demonstrates that the optimal scheme can substantially outperform existing suboptimal alternatives.

In this paper, we investigate the proportional fair scheduling (PFS) problem for multiuser OFDM systems, considering the impact of packet length. Packet length influences scheduling schemes in a way that each scheduled packet should be ensured to be completely transmitted within scheduled frames. We formulate the PFS problem into an optimization problem. Based on the observations on the structure of optimal solutions, we propose a heuristic scheduling algorithm. The scheme firstly allocates subcarriers among users without considering the packet length constraint. Then subcarrier readjustment is done in a way that surplus subcarriers from length-satisfied users are released and allocated among length-unsatisfied users. The objective is to provide proportional fairness among users while guaranteeing complete transmission of each scheduled packet. Simulation results show that the proposed scheme has quite close performance to the optimal scheme in terms of multi-carrier proportional fairness measure (MCPFM) and average throughput.

In order to allocate elastic resource to the application of PaaS platform, the authors analyze the key technologies and the particularity of resource scheduling in PaaS platform, and design an application-oriented resource allocation model and heuristic scheduling algorithm based on an ant colony algorithm. Different from the existing resource allocation methods based on virtual machines in IaaS, the scheduling strategy is based on Application in PaaS platform. According to the analysis of the application layout, the heuristic algorithm is used to minimize the number of application migration and reduce the waiting time of the task. In order to avoid falling into the loop or local optimal solution, the authors also used a tabu search technique. The results of comparative experiments show that, this strategy has higher resource utilization and shorter task waiting time.