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By softwarizing traditional dedicated hardware based functions to virtualized network functions (VNFs) that can run on standard commodity servers, network function virtualization (NFV) technology promises high efficiency, flexibility and scalability. To NFV service providers, one primary concern is to maximize network throughput and reduce service time. To reach this goal, two main challenges should be tackled: 1) how to schedule the unpredictable and burst network flows; 2) how to fairly allocate resources between various flows with different resource requirements. In this paper, we are motivated to investigate a throughput maximization problem with joint consideration of fairness between multiple flows using a discrete time queuing model. By taking advantages of Lyapunov optimization techniques, we propose a low-complexity online distributed algorithm that can achieve arbitrary optimal utility with different fairness levels by tuning the fairness bias. The high efficiency of our proposal is validated by both theoretical analysis and extensive simulation studies.

Cluster scheduler serves as a critical component to data-parallel systems in datacenters. Ideally, a scheduler should provide predictable performance with guarantees on the maximal job completion delay, while at the same time ensuring the minimal mean response time. Practically however, performance predictability and optimality are often conflicting with each other. The results often are a plethora of scheduling policies that either achieve predictable performance at the expense of long response times (e.g., max-min fairness), or run the risk of starving some jobs to obtain the minimal mean response time (e.g., Shortest Remaining Processing Time First). To address these problems, we develop a new scheduler, Cluster Fair Queueing (CFQ), which preferentially offers resources to jobs that complete the earliest under a fair sharing policy. We show that CFQ is able to minimize the mean response time while at the same time ensuring jobs to finish within a constant time after their completion under fair sharing. Our Spark deployment on a 100-node EC2 cluster demonstrates that compared to the built-in fair scheduler, CFQ can decrease the mean response time by 40%, which speeds up more than 40% of jobs by over 75% on average.

In this paper, we address the performance analysis of the cooperative communication networks with data packet and energy packet independent arrival but interactive departure which can be profiled as a Coupled Processor Queuing Model. The joint data packet and energy packet assigning problem can achieve its steady state transition probability by Quasi-Birth and Death method and the expressions of throughput, delay and packet drop rate for both data queue and energy queue are also derived. Simulations are demonstrated to verify the accuracy of theoretical derivation results.

This paper studies the fair scheduling problem for dense wireless networks with AP cooperation and MIMO links. The problem is to maximize the aggregate throughput while meeting a specified fairness objective. The proposed scheduling algorithm works with a novel single-slot throughput optimization procedure to first generate a set of candidate communication sets that are both high-performing and have good representation among all users. For a given set of candidate communication sets, our algorithm then produces a communication schedule that achieves near-optimal aggregate throughput among solutions that meet the specified fairness objective. Simulation results show that our proposed scheduling algorithm achieves high aggregate throughput while maintaining very good fairness. We also include a mechanism to relax the fairness constraint by a specified amount, which produces a range of solutions that permit a tradeoff between performance and fairness.

Enhancing Quality of Service (QoS) in mobilenetworks is the key aim for mobile operators. Mobile networkstransport several forms of data traffic for real-time applications(i.e., video monitoring). These applications need to get theadvantage of QoS adaptation. Numerous scheduling techniquesare utilized at the router to assure the QoS of the mobilenetworks. Upcoming 5G mobile networks will be launched, hence, Human-Type-Communication (HTC) and Machine-to-Machine (M2M) data traffic are expected to increasedramatically over mobile networks, which results in growing thecapacity and raising high data rates. These networks areexpected to face challenges in cases of Radio Access Network(RAN) overload and congestion due to the massive smart devicesdata traffic with various QoS requirements. This paper presentsa comparison for data traffic scheduling techniques, which arePriority Queuing (PQ), First-In-First-Out (FIFO) and WeightedFair Queuing (WFQ). We consider to select a suitable data trafficscheduling technique in terms of QoS provisioning and helping5G network, also we propose models and algorithms forefficiently utilized the smallest unit of a RAN in a relay node byaggregating and slicing the data traffic of several M2M devices.

Wireless Sensor Networks (WSN) utilisation is characterised by its dense deployment in order to fulfil the monitoring tasks. This density of communication leads to interference and congestion. In a previous work, a schedule scheme dubbed REFIACC (Reliable, Efficient, Fair and Interference Aware Congestion Control), that takes into account interferences and different links capacities in order to avoid packet loss due congestion, was proposed. REFIACC idea was validated using comparative simulations. In this study, REFIACC scheduling scheme was modelled using Markov chains. The modelling concerns queue length evolution and global system throughput. Different hypothesis details for queue length monitoring, according to application motivation, have led to many variants of models. The evaluation of the model using MATLAB has shown its effectiveness concerning packet reception ratio and reception overhead.

The basic characteristics for the WCDMA system, several typical scheduling algorithms are analyzed, and focused on the proportional fair algorithm, in order to maintain good performance of proportional fair algorithm in terms of throughput and fairness,and make it better adapt to the multi-service environment, this paper proposed a QoS-based proportional fair algorithm, using OPNET network simulation software to build a WCDMA network, respectively in different business environments to verify and compare the algorithm performance.The results show that under the multi-service environment, the performance of QoS-based proportional fair algorithm is better than the basic proportional fair algorithm in terms of throughput and average latency.

Input queuing has become dominant and popular building blocks for high speed crossbar switches with many ports and fast line rates because they require minimum speed-up of memory bandwidth. Input Queued switches with finite Virtual Output Queues guarantees QoS performance in terms of throughput and average delay. A switch performs two functions Queuing and Scheduling. Queue Management algorithm manages the size of the queues and drops packets when necessary or appropriate. Scheduling algorithms determine next packet to transfer and solves conflicts with the switching fabric. Fairness and Starvation are another two properties of IQ switches and it is analyzed in finite VOQ in this works. Fairness performs fair allocation of bandwidth among flows and prevents flows from misbehaving flows. Starvation of VOQ prevents serving High priority queue. The motivation behind this study is to schedule the HoL packets queued in finite VOQs by Framing with Low Latency Queuing (LLQ) and Weighted Fair Queueing (WFQ). This queueing technique of VOQ is measured in terms of throughput and average delay by fair allocation of bandwidth with WFQ and Starvation-free queue with LLQ.

A queue is a line of people or things to be handled in a sequential order. It is a sequence of objects that are waiting to be processed. Queuing theory is the study of queues for managing process and objects. Simulation has been applied successfully for modeling small and large complex systems and understanding queuing behavior. Analysis of the models helps to increases the performance of the system. In this paper we analyze various models of the Single server queuing system with necessaryimplementation using Matlab Software.

Recently, a hybrid disk drive that integrates a small amount of flash memory within a mechanical drive has received significant attention. The hybrid drive extends the storage hierarchy by using flash memory to cache data from the mechanical disk. Unfortunately, current caching architectures fail to fully exploit the potential of the hybrid drive. Furthermore, current disk input/output I/O schedulers are optimized for rotational mechanical disk drives and thus must be re-targeted for the hybrid disk drive. In this paper, we propose a new data caching scheme, called Profit Caching, for hybrid drives. Profit Caching is a self-optimizing caching algorithm. It considers and seamlessly integrates all possible data characteristics that impact the performance of hybrid drives, including read count, write count, sequentiality, randomness, and recency, to determine the caching policy. Moreover, we propose a hybrid disk-aware Completely Fair Queuing HA-CFQ scheduler to avoid unnecessary I/O anticipations of the CFQ scheduler. We have implemented Profit Caching and HA-CFQ scheduler in the Linux kernel. Coupled with a trace-driven simulator, we have also conducted detailed experiments under a variety of workloads. Experimental results show that Profit Caching provides significantly improved performance compared with the previous schemes. In particular, the throughput of Profit Caching outperforms previous Random Access First and FlashCache caching schemes by factors of up to 1.8 and 7.6, respectively. In addition, the HA-CFQ scheduler reduces the total execution time of the CFQ scheduler by up to 1.74%. Finally, the experimental results show that the runtime overhead of Profit Caching is extremely insignificant and can be ignored. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, we address the uplink resource scheduling problem in single carrier frequency-domain multiple access systems. In particular, we focus on the efficiency and fairness trade-offs in scheduling and resource allocation for wireless cellular networks. We present an efficient implementation method that translates these scheduling problems into set partitioning problems that are well-studied in the literature. Then, we discuss a family of utility functions that enable us to investigate the performance of different frequency domain schedulers such as the sum-rate maximization, proportional fair, and max-min fair schedulers. We use the price of fairness as a metric to analytically quantify these trade-offs. Based on the intuition that fairness of resource allocation in cellular radio networks corresponds to the prioritization of cell-edge user rates, we demonstrate that the proportional fair scheduler significantly improves fairness among users, and increases the rates offered to the cell-edge and median users when compared to the sum-rate maximization scheduler. This comes at the cost of reducing the cell-center user rates and the aggregate user rate. We present the steps on how to take into account the practical implementation constraints, in particular, those related with the discrete Fourier transform implementation, in the problem formulation. Simulation results that illustrate these trade-offs are also presented. We conclude that this type of analysis can provide guidelines for the network operators to control the efficiency and fairness trade-off as the data traffic grows.

A recursive and fast construction of an n -element priority queue from exponentially smaller hardware priority queues and size n RAM is presented. All priority queue implementations to date require either O ( log n ) instructions per operation or, exponential (with key size) space or, expensive special hardware whose cost and latency dramatically increases with the priority queue size. Hence constructing a priority queue (PQ) from considerably smaller hardware priority queues (which are also much faster) while maintaining the O ( 1 ) steps per PQ operation is critical. Here we present such an acceleration technique called the Power Priority Queue (PPQ) technique. Specifically, an n -element PPQ is constructed from 2 k - 1 primitive priority queues of size n k ( k = 2 , 3 , … ) and a RAM of size n , where the throughput of the construct beats that of a single, size n primitive hardware priority queue. For example an n -element PQ can be constructed from either three n or five n 3 primitive H/W priority queues. Applying our technique to a TCAM based priority queue, results in TCAM-PPQ, a scalable perfect line rate fair queuing of millions of concurrent connections at speeds of 100 Gbps. This demonstrates the benefits of our scheme; when used with hardware TCAM. We expect similar results with systolic arrays, shift-registers and similar technologies. As a byproduct of our technique we present an O ( n ) time sorting algorithm in a system equipped with a O w n entries TCAM, where here n is the number of items, and w is the maximum number of bits required to represent an item, improving on a previous result that used an Ω ( n ) entries TCAM. Finally, we provide a lower bound on the time complexity of sorting n -element with TCAM of size O ( n ) that matches our TCAM based sorting algorithm.

Exploring theory and methods to analyze the impacts of non real-time services on jitter performance of real-time services is a quite challenging but meaningful job. This article puts forward a general theoretical method to calculate packet jitter in network node bearing mixed services. Based on queuing theory and Markov theory, the network node is modeled as a double-queue single-server and limited-cache queuing system with thresholds. Two-state Markov-modulated Bernoulli process (MMBP-2) and interrupted Bernoulli process (IBP) are used to model the arrival processes of real-time services and small data services respectively in a packet switched network. In order to depict the interaction between real-time services and small data services, a four-dimensional discrete-time Markov chain is implemented to describe the transition of the system states. By solving the system model, expressions for packet jitter are obtained. The results given by the model are then compared with the simulation results obtained by network simulator, version 3 (NS-3).

The application of sliding mode control in wireless network is used for considering the joint congestion control and scheduling. Incorporating dual decomposition enables the joint congestion control and scheduling problem to be considered separately. The communication among these two sub problems is given by the lagrangian price value. Based on the utility optimization of network the congestion control performance for queues can be improved using sliding mode based congestion controller. Buffers on network devices are managed with various queuing techniques. Properly managed queues can minimize dropped packets and network congestion, as well as improve network performance. Thus, the queuing structure of CBWFQ (Class Based Weighted Fair Queuing) and strict Priority is combined so that the packets are classified into different classes and priorities are given to these classes, where the higher priority are given to delay sensitive packets and are scheduled effectively.

This paper provides a concrete implementation and comprehensive assessment of the energy-based fair queuing (EFQ) scheduling algorithm based on the Linux operating system. EFQ is an extended application of the classical fair queuing algorithm in the energy domain. It is designed to provide proportional power sharing as well as effective time-constraint compliance in energy-centric power management (PM) schemes, a type of operating system-level PM schemes that are targeted at providing a battery lifetime guarantee for energy-limited mobile systems. In this paper work, the structure of the Linux completely fair scheduler (CFS) has been effectively utilized to ease the EFQ implementation and reduce the scheduling overhead. Around 150 lines of code have been added to the Linux kernel V3.3 to achieve the EFQ-related functions and to implement the system calls that are required by the Linux user space. To assess the properties of the EFQ scheduler, a test-bench based on the POSIX threads has been developed and the benchmarks of an open-source embedded suite are referred to program the threads under test. The EFQ algorithm is assessed from two aspects, energy management and real-time scheduling. Experimental results on energy management show that EFQ is more effective than the CFS scheduler in managing energy and it can achieve a proportional share of the system power regardless of on which device the energy is spent. Experimental results on real-time scheduling demonstrate that EFQ can achieve strict time-constraint compliance and a robust response time upon the increase of energy estimation error and active tasks.

In view of traffic queuing question, this article has established the dynamic queuing theory model, considered the waiting the traffic flow magnitude and the vehicles density. On this basis, through computer random simulations,we found that traffic conditions can be divided into three statuses,and found out the key conditions of formation for each status. The results can be widely promoted, and can provide advice to government

Summary Computers are indispensable to modern human society. Often, computers host multiple programs running simultaneously. However, among those programs, some maybe more time critical than others to users. Consequently, users would hope those time-critical programs to finish their execution as soon as possible. Generally speaking, the course of program execution includes cooperative operation of CPU, memory, and hard disk. For CPU operation, modern computer systems have the ability to adjust the CPU scheduling sequence according to program priority. Nevertheless, most of them do not have effective ways to provide memory management and disk operation based on program priority. Consequently, it is hard to speed up the execution of prioritized programs as users would expect. The Linux operating system has been widely used in recent years. Even though it still does not support fully-prioritized memory management and disk operation. Previously, based on the default Linux disk scheduler, complete fair queuing (CFQ), we proposed a new disk scheduling algorithm called prioritized CFQ (PCFQ) to provide fully-prioritized disk operation. PCFQ had demonstrated good performance improvement for programs with high priority. In this paper, we report our effort to integrate PCFQ with prioritized memory management as a whole in the Linux operating system. With the cooperation between prioritized memory management and prioritized disk operation, our system further enhanced the performance that PCFQ achieved by up to 62.08%. Experimental results also showed that, compared with the current Linux system, our design can lift the performance of individual prioritized programs by up to 76.63% when there was one prioritized program on the system. The number went up to 82.45% when the system hosted three programs with high priority.Concurrency and Computation: Practice and Experience.Copyright © 2014 John Wiley & Sons, Ltd.

The efficiency of high speed packet access (HSPA) systems is mainly based on Packet Scheduling Scheme which will be the key to influencing on the system performance and ensuring the service quality for the users. In this paper, we introduce a three step packet scheduling scheme to provide quality of services (QoS) guaranteed for high speed uplink packet access. Then, we proposed an improved packet scheduling algorithm based on QoS parameter for mixed service applications in order to meet the actual QoS needs of the different systems. This algorithm calculated the scheduling priority based on the comprehensive factors, including the queuing status of each user, QoS requirements and the sum of speeds on each channel. The simulation results show that the performance efficiency of HSPA systems employed proposed algorithm is superior compared to the conventional PF and M-LWDF algorithm in average packet drop and average cell throughput.

Network devices supporting 100G links are in demand to meet the communication requirements of computing nodes in datacenters and warehouse computers. In this paper, we propose TQ and TQ-Smooth, two light-weight, fair schedulers that accommodate an arbitrarily large number of requestors and are suitable for ultra high-speed links. We show that our first algorithm, TQ, as well its predecessor, DRR, may result in bursty service even in the common case where flow weights are approximately equal, and we find that this can damage the performance of buffer-credit allocation schemes. Our second algorithm, TQ-Smooth, improves short-term fairness to deliver very smooth service when flow weights are approximately equal, while allocating bandwidth in a weighted fair manner. In many practical situations, a scheduler is asked to allocate resources in fixed-size chunks (e.g. buffer units), whose size may exceed that of (small) network packets. In such cases, byte-level fairness will typically be compromised when small-packet flows compete with large-packet ones. We describe and evaluate a scheme that dynamically adjusts the service rates of request/grant buffer reservation to achieve byte-level fairness based on received packet sizes.

Today's operating systems treat GPUs and other computational accelerators as if they were simple devices, with bounded and predictable response times. With accelerators assuming an increasing share of the workload on modern machines, this strategy is already problematic, and likely to become untenable soon. If the operating system is to enforce fair sharing of the machine, it must assume responsibility for accelerator scheduling and resource management. Fair, safe scheduling is a particular challenge on fast accelerators, which allow applications to avoid kernel-crossing overhead by interacting directly with the device. We propose a disengaged scheduling strategy in which the kernel intercedes between applications and the accelerator on an infrequent basis, to monitor their use of accelerator cycles and to determine which applications should be granted access over the next time interval. Our strategy assumes a well defined, narrow interface exported by the accelerator. We build upon such an interface, systematically inferred for the latest Nvidia GPUs. We construct several example schedulers, including Disengaged Timeslice with overuse control that guarantees fairness and Disengaged Fair Queueing that is effective in limiting resource idleness, but probabilistic. Both schedulers ensure fair sharing of the GPU, even among uncooperative or adversarial applications; Disengaged Fair Queueing incurs a 4% overhead on average (max 18%) compared to direct device access across our evaluation scenarios.

In order to solve the limitations of classical packet scheduling architecture in TD-LTE, the TD-LTE downlink packet scheduling was studied and a architecture of downlink packet scheduling for TD-LTE is designed. The packet scheduling architecture was built and three classic scheduling algorithms were simulated in this architecture by Matlab. The simulation results show that the packet scheduling architecture can be applied to scheduling algorithms with different purposes and verify the performances of throughput and fairness of these three scheduling algorithms.

We present an analytical framework for the delay analysis of the distributed coordinated scheduling in the IEEE 802.16 Wireless Network in mesh mode. We designed a queuing model that expresses the network limits accurately. The queuing model is of the type M/G/1/L developed using Linear Algebraic Queuing Theory. After modeling one node, an iterative method is used to calculate the traffic flowing in the whole network. With this model, it is possible to calculate the end-to-end delay and the throughput limit of the link layer. An algorithm is presented that applies a strategy to provide fair resource sharing. The numerical results and simulations for different topologies show that the model is accurate and that the fairness strategy effectively reduces the end-to-end delay.

The scheduling scheme in packet switching networks is one of the most critical features that can affect the performance of the network. Hence, many scheduling algorithms have been suggested and some indices, such as fairness and latency, have been proposed for the comparison of their performances. While the nature of Internet traffic is bursty, traditional scheduling algorithms try to smooth the traffic and serve the users based on this smoothed traffic. As a result, the fairness index mainly considers this smoothed traffic and the service rate as the main parameter to differentiate among different sessions or flows. This work uses burstiness as a differentiating factor to evaluate scheduling algorithms proposed in the literature. To achieve this goal, a new index that evaluates the performance of a scheduler with bursty traffic is introduced. Additionally, this paper introduces a new scheduler that not only uses arrival rates but also considers burstiness parameters in its scheduling algorithms.

paper presented a proposed model for cloud computing scheduling based on multiple queuing models. This allowed us to improve the quality of service by minimize execution time per jobs, waiting time and the cost of resources to satisfy user's requirements. By taking advantage of some useful proprieties of queuing theory scheduling algorithm is proposed to improve scheduling process. Experimental results indicate that our model increases utilization of global scheduler and reduce waiting time. Keywordscomputing; Queuing models; Scheduling process.

Emerging security-aware packet scheduling algorithms can efficiently improve the security measures while forwarding the packets over wireless links. Existing scheduling algorithms for real-time wireless networks are not capable of providing higher level of security. The proposed methodology overcomes the difficulties in the existing scheduling algorithm with the security enhancements. A multilevel queue scheduling algorithm is used to partition the ready queue into several separate queues.For security reasons, the proposed methodology uses the RSA algorithm for encrypting and decrypting the packets. The proposed Security-aware Packet Scheduling (SPS) methodology strives to improve the security levels while achieving high schedulability for real-time packets. The proposed model reduces the congestion occurred during scheduling the packets.The performance of the proposed method results better security than the existing Quality Based Searching algorithm. Also, the system takes lesser time, reduces congestion and traffic also provides higher arrival rate for scheduling the packets. Index Terms: Encryption, Decryption, Multilevel queue scheduling, RSA, Real-time packets, andScheduling algorithms

A home router, or a home gateway, is the node that resides between a public network and a home network for computers to share Internet connections. To insert customized queuing and scheduling codes into the embedded Linux kernel is a way to make the Linux-based home routers support Quality of Service (QoS). It is desirable that the small Linux kernel adopts an efficient queuing and scheduling algorithm to support link sharing, priority and traffic shaping. The algorithm presented in this paper is based on the concept of hierarchical link-sharing and each class in the hierarchy is bound with a token bucket, which can shape the traffic of this class. The analysis and experiment results presented in the paper show that through the novel way of weighted fair token sharing, this proposed algorithm guarantees basic bandwidth service for each class and enables weighted fair sharing of excess bandwidth, with which home computers connected to the network share the Internet service evenly.

The pervasiveness of wireless technology has indeed created massive opportunity to integrate almost everything into the Internet fabric. This can be seen with the advent of Internet of Things and Cyber Physical Systems, which involves cooperation of massive number of intelligent devices to provide intelligent services. Fairness amongst these devices is an important issue that can be analysed from several dimensions, e.g., energy usage, achieving required quality of services, spectrum sharing, and so on. This article focusses on these viewpoints while looking at fairness research. To generalize, mainly wireless networks are considered. First, we present a general view of fairness studies, and pose three core questions that help us delineate the nuances in defining fairness. Then, the existing fairness models are summarized and compared. We also look into the major fairness research domains in wireless networks such as fair energy consumption control, power control, topology control, link and flow scheduling, channel assignment, rate allocation, congestion control and routing protocols. We make a distinction amongst fairness, utility and resource allocation to begin with. Later, we present their inter-relation. At the end of this article, we list the common properties of fairness and give an example of fairness management. Several open research challenges that point to further work on fairness in wireless networks are also discussed. Indeed, the research on fairness is entangled with many other aspects such as performance, utility, optimization and throughput at the network and node levels. While consolidating the contributions in the literature, this article tries to explain the niceties of all these aspects in the domain of wireless networking.

In this article, modeling in queuing systems with heavy traffic customer flows is reviewed. Key areas include their limiting distributions, asymptotic behaviors, modeling issues and applications. Heavy traffic flows are features of queuing in modern communications, transportation and computer systems today. Initially, we reviewed the onset of asymptotic modeling for heavy traffic single server queuing systems and then proceeded to multi server models supporting diffusion approximations developed recently. Our survey shows that queues with heavy traffic customer flows have limiting distributions and extreme value maximum. In addition, the diffusion approximation can conveniently model performance characters such as the queue length or the waiting time distributions in these systems.

In this work, a method is proposed to schedule the resources while considering SNR values along with CQI in a view to provide a better packet scheduling. A threshold based method is also proposed with multiple packet scheduling algorithm. A novel Kalman filter based CQI estimation algorithm is designed using SNR values. Different packet scheduling algorithms are decided for varied CQI levels. Simulation results show that the proposed method would improve the link level performance and average throughput of the system. Furthermore, the effect of improving quality is highlighted on user experience and applications are suggested which might change the way we will use Internet in near or far future.

Static Wireless Mesh Networks (WMN) based on high capacity pencil-beam millimeter wave (mmWave) links offer an attractive solution for small cell backhauling in 5G networks. However, the delay targets in 5G are such that it is quite challenging to develop adequate link scheduling and routing mechanisms especially for a system composed of backhaul nodes with a single TDD radio. We have proposed earlier a scheme that is based on cyclic semipermanent link schedules and multiple spanning tree based multipath routing. This scheme enables multihop backhaul connections with low delays and fast fault recovery. However, so far this scheme has been analyzed only by using end-to-end delay estimates based solely on link schedules. The potential effects of different queueing disciplines have not been studied in detail. In this paper, we will show how common output queueing systems can have a harmful interplay with the cyclic link schedules that contradicts our primary path optimization targets. We will also suggest a few simple modifications to existing queueing solutions that resolve these problems at WMN node level.

Multi-flow carrier aggregation (CA) has recently been considered to meet the increasing demand for high data rates. In this paper, we investigate the cross-layer performance of multi-flow CA for macro user equipments (MUEs) in the expanded range (ER) of small cells. We develop a fork/join (F/J) queuing analytical model that takes into account the time varying channels, the channel scheduling algorithm, partial CQI feedback and the number of component carriers deployed at each tier. Our model also accounts for stochastic packet arrivals and the packet scheduling mechanism. The analytical model developed in this paper can be used to gauge various packet-level performance parameters e.g., packet loss probability (PLP) and queuing delay. For the queuing delay, our model takes out-of-sequence packet delivery into consideration. The developed model can also be used to find the amount of CQI feedback and the packet scheduling of a particular MUE in order to offload as much traffic as possible from the macrocells to the small cells while maintaining the MUE's quality of service (QoS) requirements.

High downlink and uplink speeds are achievable with the aid of LTE. Providing this technology in real life requires scheduling algorithms that will effect the concepts such as throughput and fairness. In this paper some new averaging methods for proportional fair algorithm are proposed. Simulation results show that arithmetic mean method can increase spectral efficiency and fairness performance of proportional fair scheduler.

In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .

The cybernetic approach is used to develop a mathematical model for communicating queuing systems. Conflicting input flows of the first queuing system and one of the input flows of the second queuing system are formed in a synchronous Markov random environment with a finite number of states. Another input flow of the second queuing system consists of retrials arriving from the first queuing system. The transition of a customer from the first queuing system to the second one takes a random amount of time. Servicing is performed by a cyclic algorithm with fixed duration.

The provisioning of quality of service in networks requires a proper scheduling algorithm. The nature of network traffic, especially real-time multimedia applications, is bursty, thus in addition to the service rate (which is commonly used to isolate sessions’ service), other parameters should be involved. In this paper we analyze our proposed scheduling algorithm [Burst Service SCFQ, BSCFQ (Daneshvar et al. in Int J Wirel Mobile Netw 5, 2013)] which attempts to provide a balance between bursty and non-bursty (smooth) traffics. BSCFQ is an improvement of Self-Clock Fair Queueing (SCFQ), a well-known packet scheduling algorithm, in order to be able to compensate for an adjustable amount of missed service to each session. BSCFQ is evaluated by calculating the fairness index, burst service which is defined by the authors and delay bound. Our improvement in the SCFQ does not necessitate any additional computation as regards the implement algorithm.

Efficient utilization of network resources is a key goal for emerging BWAS. This is a complex goal to achieve due to the heterogeneous service nature and diverse QoS requirements of various applications that BWAS support. Packet scheduling is an important activity that affects BWAS QoS outcomes. This paper proposes a new packet scheduling mechanism that improves QoS in mobile wireless networks which exploit IP as a transport technology for data transfer between BWAS base stations and mobile users at the radio transmission layer. In order to improve BWAS QoS the new packet algorithm makes changes at both the IP and the radio layers. The new algorithm exploits handoff priority scheduling principles and takes into account buffer occupancy and channel conditions. The packet scheduling mechanism also incorporates the concept of fairness. The algorithm offers an opportunity to maximize the carriers' revenue at various traffic situations. Simulation results were compared to well-known algorithms which demonstrated the new packet scheduling algorithm is able to provide a low handoff packet drop rate, low packet forwarding rate, low packet delay, ensure fairness amongst the users of different services and generates higher revenue. Furthermore this research proposes a new and novel measure named "Satisfaction Factor" to measure the efficacy of various scheduling schemes and finally proposes four performance metrics for NodeB's of in Next Generation Wireless Networks.

Flow-level bandwidth provisioning (FBP) achieves fine-grained bandwidth assurance for individual flows. It is especially important for virtualization-based computing environments such as data centers. However, existing flow-level bandwidth provisioning solutions suffer from a number of drawbacks, including high implementation complexity, poor performance guarantees, and inefficiency to process variable length packets. In this paper, we study flow-level bandwidth provisioning for Combined Input Crosspoint Queued (CICQ) switches in the OpenFlow context. First, we propose the Flow-level Bandwidth Provisioning algorithm for CICQ switches, which reduces the switch scheduling problem to multiple instances of fair queuing problems, each utilizing a well-studied fair queuing algorithm. We theoretically prove that FBP can closely emulate the ideal Generalized Processing Sharing model, and accurately guarantee the provisioned bandwidth. Furthermore, we implement FBP in the OpenFlow software switch to obtain realistic performance data by a prototype. Leveraging the capability of OpenFlow to define and manipulate flows, we experimentally demonstrate a practical flow-level bandwidth provisioning solution. Finally, we conduct extensive simulations and experiments to evaluate the design. The simulation data verify the correctness of the analytical results, and show that FBP achieves tight performance guarantees. The experiment results demonstrate that our OpenFlow-based prototype can conveniently and accurately provision bandwidth at the flow level.

Currently, the usefulness of many mobile systems is largely limited by the battery lifetime. In this paper, energy-based fair queuing (EFQ) is proposed as a pivotal instrument to maximize the user experience in this type of system. Energy-based fair queuing is a novel class of energy-aware scheduling algorithms that support proportional energy use, effective time-constraint compliance and a flexible trade-off between them. The combination of EFQ with lifetime-oriented power management schemes opens the door to maximize the user experience of battery-limited mobile systems. Moreover, it is suggested to merge traditional energy-efficient algorithms with EFQ to further improve the user experience. The proposed EFQ algorithm is implemented in the Linux kernel V3.3 and verified on a testbench based on an open source Linux scheduler simulator with user-specified energy loads. Simulation results show that EFQ is more effective and flexible than the Linux scheduler in maximizing the user experience of energy-limited mobile systems.

This paper puts forward a new dynamic round-robin (DYRR) packet scheduling algorithm with high efficiency and good fairness. DYRR algorithm introduces dynamic round-robin concept, that is, the allowance given to each of the flows in a given round is not fixed, but is related with the number of bytes sent of this and other flows of the last round scheduling. The time complexity of the DYRR algorithm is O(1). Results from performance simulation analysis shows that DYRR algorithm can effectively smooth output burst, realize fair scheduling, and have a good time delay characteristic.

IEEE 802.16 is standardization for a broadband wireless access in network metropolitan area network (MAN). IEEE 802.16 standard (Wi-Max) defines the concrete quality of service (QoS) requirement, a scheduling scheme and efficient packet scheduling scheme which is necessary to achieve the QoS requirement. In this paper, a novel waiting queue based on downlink bandwidth allocation architecture from a number of rtps schedule has been proposed to improve the performance of nrtPS services without any impaction to other services. This paper proposes an efficient QoS scheduling scheme that satisfies both throughput and delay guarantee to various real and non-real applications corresponding to different scheduling schemes for k=1,2,3,4. Simulation results show that proposed scheduling scheme can provide a tight QoS guarantee in terms of delay for all types of traffic as defined in WiMax standards. This process results in maintaining the fairness of allocation and helps to eliminate starvation of lower priority class services. The authors propose a new efficient and generalized scheduling schemes for IEEE 802.16 broadband wireless access system reflecting the delay requirements.

Packet scheduling, together with classification, is one of the most expensive processing steps in systems providing tight bandwidth and delay guarantees at high packet rates. Schedulers with near-optimal service guarantees and O(1) time complexity have been proposed in the past, using techniques such as timestamp rounding and flow grouping to keep their execution time small. However, even the two best proposals in this family have a per-packet cost component that is linear either in the number of groups or in the length of the packet being transmitted. Furthermore, no studies are available on the actual execution time of these algorithms. In this paper we make two contributions. First, we present Quick Fair Queueing (QFQ), a new O( 1) scheduler that provides near-optimal guarantees and is the first to achieve that goal with a truly constant cost also with respect to the number of groups and the packet length. The QFQ algorithm has no loops and uses very simple instructions and data structures that contribute to its speed of operation. Second, we have developed production-quality implementations of QFQ and of its closest competitors, which we use to present a detailed comparative performance analysis of the various algorithms. Experiments show that QFQ fulfills our expectations, outperforming the other algorithms in the same class. In absolute terms, even on a low-end workstation, QFQ takes about 110 ns for an enqueue()/dequeue() pair (only twice the time of DRR, but with much better service guarantees).

Scheduling real time and non real time packets at network nodes has an important impact by reducing the processing overhead, queuing delay and response time. Most of the existing packet scheduling algorithms used in network based on First-In First-Out (FIFO), non-preemptive priority, and preemptive priority scheduling. However, these algorithms incur a large processing overhead, queuing delay and response time and are not dynamic to the data traffic changes. In this paper, we present a new hierarchical scheduling algorithm to assign priority, Hierarchical Hybrid EDF/FIFO which can not only serve the real time traffic but also provide best effort service to non real time traffic. To examine our approach for scheduling, we realized our analytical study to express the worst case queuing delay and the worst case response time for different traffics. The simulation results showed that the Hierarchical hybrid EDF/FIFO achieved the minimum packet delay and adequate loss packet for non real time traffic when compared with Hierarchical FIFO. In general, the performances of our approach draw near to Hierarchical EDF which confirms the effectiveness of this approach.

Scheduling for flows has been studied before. However, applying the previous schemes directly for LTE networks may not achieve good performance. To have good performance, both frequency domain allocations and time domain allocations for LTE resource blocks are suggested. Our method is suitable for real-time services and it consists of three phases. In frequency domain we design our method to utilize the RBs effectively. In time domain we first manage queues for different applications and propose a mechanism for predicting the packet delays. We introduce the concept of virtual queue to predict the behavior of future incoming packets based on the packets in the current queue. Then based on the calculated results, we introduce a cut-in process to rearrange the transmission order and discard those packets which cannot meet their delay requirements. We compare our scheduling mechanism with maximum throughput, proportional fair, modified largest delay first and exponential proportional fair. Simulation results show our scheduling method can achieve better performance than other schemes.

NAND Flash Memory has been used in several devices by low cost and high capacity, and the demand for mass NAND Flash Memory has increased due to the multimedia extension of mobile devices. The JFFS2, NILFS2, and YAFFS2 file systems are used mainly in NAND Flash Memory. In this paper, the performance of Sequential read/write of the 3 file systems are analyzed for the 4 I/O schedulers : CFQ(Complete Fair Queuing) I/O scheduler, NOOP(No Operation) I/O scheduler, Anticipatory I/O scheduler, and Deadline I/O scheduler. In JFFS2 file system, Anticipatory I/O scheduler has the best performance by 8% decreasing speed in writing time and 1.5% decreasing speed in reading time compared to the other I/O scheduler. In YAFFS2 file system, it results are similar to performance in reading and writing for the 4 I/O schedulers. In NILFS2 file system, NOOP I/O scheduler has 2% faster in writing and Deadline I/O scheduler has 6% faster in reading than other I/O schedulers.

This paper proposed to investigate and evaluate the performance of one of the algorithm used to provide fair bandwidth allocation to the flows. First In First Out (FIFO) queuing is simple but does not protect responsive flows from unresponsive one, flows that are sending more than their fair share. One of FIFO queuing is Random Early Detection which it can effectively avoid congestion at routers, but it also cannot provide fair bandwidth for the flows. On the other hand, per-flow scheduling mechanisms provide max-min fairness but are more complex, it requires keeping state for all flows going through the router; it’s proved that high bandwidth flows at the time of congestion consume most of the bandwidth of the link, so this algorithm (RED-PD) is most candidates to provide fairness to the flows. Simulations with networks demonstrate that there are chances for RED-PD to enhance its work, by means of incorporating the test of unresponsive flows actively in response to changes in the packet drop rate.

Efficient utilization of network resources is a key goal for emerging broadband wireless access systems (BWAS). This is a complex goal to achieve due to the heterogeneous service nature and diverse quality of service (QoS) requirements of various applications that BWAS support. Packet scheduling is an important activity that affects BWAS QoS outcomes. This paper proposes a novel packet scheduling mechanism that improves QoS in mobile wireless networks which exploit IP as a transport technology for data transfer between BWAS base stations and mobile users at the radio transmission layer. In order to improve BWAS QoS the new packet algorithm makes changes at both the IP and the radio layers. The new packet scheduling algorithm exploits handoff priority scheduling principles and takes into account buffer occupancy and channel conditions. The packet scheduling mechanism also incorporates the concept of fairness. Performance results were obtained by computer simulation and compared to the well known algorithms. Results show that by exploiting the new packet scheduling algorithm, the transport system is able to provide a low handoff packet drop rate, low packet forwarding rate, low packet delay and ensure fairness amongst the users of different services.