Dynamic Resource Allocation Scheme Research Articles

A Non-cooperative Differential Game Model for Frequency Reuse Based Channel Allocation in Satellite Networks

In this paper, channel resource allocation problem for LEO mobile satellite systems is investigated and a new dynamic channel resource allocation scheme is proposed based on differential game. Optimal channel resource allocated to each satellite beams are formulated as Nash equilibrium. It is proved that optimal channel resource allocation can be achieved and the differential game based scheme is applicable and acceptable. Numerical results shows that system performance can be improved based on the proposed scheme.

Design a Dynamic Resource Allocation Scheme in Virtual Environment by Implementing a Load Balancer for Session Management

Design a Dynamic Resource Allocation Scheme in Virtual Environment by Implementing a Load Balancer for Session Management

Effects of Accumulated CEO Pay and Relative Performance on Risk Taking and Performance Variance

In this study, we argue that chief executives who have accumulated greater total compensation throughout their tenure at a firm have higher tendency to engage in risky behaviors— manifest in voluminous investments and dynamic resource allocation strategies—and to eventually endanger the firm with volatile performance. Using data on CEOs of large, public U.S. firms, we find that high levels of accumulated total pay indeed increase investment magnitudes and the degree of dynamism in companies’ resource allocation strategies, and that this effect is more salient when the firm’s performance level is greater compared to its aspired level. It is also proposed that underlying this relationship is a cognitive decision-making bias —the CEO’s overconfidence—developed during the process of self-made causal attribution of organizational success. We conclude by discussing implications for theory and future research.

Dynamic Resource Allocation in Hybrid Access Femtocell Network

Intercell interference is one of the most challenging issues in femtocell deployment under the coverage of existing macrocell. Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in dense femtocell networks. Advances in resource management strategies have improved the control mechanism for interference reduction at lower node density, but most of them are ineffective at higher node density. In this paper, a dynamic resource allocation management algorithm (DRAMA) for spectrum shared hybrid access OFDMA femtocell network is proposed. To reduce the macro-femto-tier interference and to improve the quality of service, the proposed algorithm features a dynamic resource allocation scheme by controlling them both centrally and locally. The proposed scheme focuses on Femtocell Access Point (FAP) owners' satisfaction and allows maximum utilization of available resources based on congestion in the network. A simulation environment is developed to study the quantitative performance of DRAMA in hybrid access-control femtocell network and compare it to closed and open access mechanisms. The performance analysis shows that higher number of random users gets connected to the FAP without compromising FAP owners' satisfaction allowing the macrocell to offload a large number of users in a dense heterogeneous network.

The design and implementation of heterogeneous multicore systems for energy-efficient speculative thread execution

With the emergence of multicore processors, various aggressive execution models have been proposed to exploit fine-grained thread-level parallelism, taking advantage of the fast on-chip interconnection communication. However, the aggressive nature of these execution models often leads to excessive energy consumption incommensurate to execution time reduction. In the context of Thread-Level Speculation, we demonstrated that on a same-ISA heterogeneous multicore system, by dynamically deciding how on-chip resources are utilized, speculative threads can achieve performance gain in an energy-efficient way. Through a systematic design space exploration, we built a multicore architecture that integrates heterogeneous components of processing cores and first-level caches. To cope with processor reconfiguration overheads, we introduced runtime mechanisms to mitigate their impacts. To match program execution with the most energy-efficient processor configuration, the system was equipped with a dynamic resource allocation scheme that characterizes program behaviors using novel processor counters. We evaluated the proposed heterogeneous system with a diverse set of benchmark programs from SPEC CPU2000 and CPU20006 suites. Compared to the most efficient homogeneous TLS implementation, we achieved similar performance but consumed 18% less energy. Compared to the most efficient homogeneous uniprocessor running sequential programs, we improved performance by 29% and reduced energy consumption by 3.6%, which is a 42% improvement in energy-delay-squared product.

Survey on Dynamic Resource Allocation Strategy in Cloud Computing Environment

Survey on Dynamic Resource Allocation Strategy in Cloud Computing Environment

A Dynamic Resource Allocation Scheme for the Downlink Heterogeneous Traffic of Internet Protocol (IP) Based OFDM networks

Radio Resource management mechanisms such as physical-centric radio resource allocation and medium access control (MAC)--centric packet scheduling are expected to play a substantial role in the performance of orthogonal frequency division multiplexing (OFDM) based wireless networks. OFDM provide fine granularity for resource allocation since they are capable of dynamically assigning sub-carriers to multiple users and adaptively allocating transmit power. The current layered networking architecture, in which each layer is designed and operated independently, results in inefficient resource use in wireless networks due to the nature of the wireless medium, such as time-varying channel fading. Thus, we need an integrated adaptive design across different layers, allowing for a cross-layer design. In this paper, a scheduling scheme is proposed to dynamically allocate resources for the downlink data transmission of internet protocol based OFDM networks. Generally to maximize the capacity and user satisfaction improvements in packet data admission, scheduling and policing are necessary. Of the three, efficient scheduling has the greatest impact on increased system capacity or effective spectrum usage. In addition, proper scheduling can greatly improve user satisfaction. The contribution of this work is twofold: first we evaluate current allocation schemes by exploiting the knowledge of channel sate information (CSI) and traffic characteristics in terms of queue state information (QSI) to acquire the system performance on a real time network. Second, the resource allocation scheme is extended by incorporating MAC layer information as well as opportunistic packet scheduling in the time-domain-based on minimum weight cost function. The key factors that affect the overall system performance in terms of system average throughput and delay are identified, evaluated and discussed.

Resource Allocation with Incomplete Information for QoE-Driven Multimedia Communications

Most existing Quality of Experience (QoE)-driven multimedia resource allocation methods assume that the QoE model of each user is known to the controller before the start of the multimedia playout. However, this assumption may be invalid in many practical scenarios. In this paper, we address the resource allocation problem with incomplete information where the realized mean opinion score (MOS) can only be observed over time, but the underlying QoE model and playout time are unknown. We consider two variants of this problem: 1) the form of the QoE model is known but the parameters are unknown; 2) both the form and the parameters of the QoE model are unknown. For both cases, we develop dynamic resource allocation schemes based on online test-optimization strategy. Simply speaking, one first spends appropriate time on testing the QoE model, then optimizes the sum of the MOS in the remaining playout time. The highlight of this paper lies in resolving the inherent tension between the test and optimization by jointly considering the uncertainties of QoE model and playout time. Furthermore, we derive tight bounds on the MOS loss incurred by the proposed schemes in comparison with the optimal scheme that knows the QoE model a priori and prove that the performance gap, as the playout time tends to infinity, asymptotically shrinks to zero.

Radio Resource Management Scheme for Multi-Agency TEDS Networks

This paper contributes to the evolution of public safety communication networks by specifying a solution for managing the radio resources of multi-agency Terrestrial Trunked Radio Enhanced Data Services (TEDS) networks. A TEDS network can be securely partitioned so that different public safety agencies such as police, fire, ambulance, etc. can share a single network’s infrastructure including base stations and main switches. This sharing feature offers a cost-effective solution not only for network investment, but it also helps to reduce the costs of network operation, implementation and maintenance. The real implementation of TETRA sharing is not easy because radio resources and other shared resources must be managed among all agencies in an efficient and secure way. Without an efficient radio resource management (RRM) policy, one agency can exhaust the capacity of others. This study proposes a radio resource allocation scheme to provide maximum system throughput and proportional fairness in accordance with agency capacity, which is shared through a dynamic resource allocation scheme. The performance analysis of this scheme in terms of throughput, bounded delay and queue size are obtained. Numerical and simulation results show that the proposed dynamic partitioning-based rate RRM scheme, referred to as DP-RRM, improves both system throughput and average delays.

A Fuzzy-Based Dynamic Load Decision Making Scheme in Cloud Computing

In this paper, a fuzzy-based dynamic resource allocation scheme for load balancing in cloud computing (FDLB) is presented to growth of the service type and user number in the mobile networks of the higher performance is required in service provision and throughput. Besides, the estimation of workload is difficult and time consuming, and the result causes an unstable system and unnecessary message passing overhead. The structure of the FDLB is composed of the design the load distributed agent (LDA). It is observed that the FDLB exhibits better adaptability, robustness, and fault-tolerant capability, thus yielding better performances compared to other existing algorithms.

Survey on Resource Allocation Policy and Job Scheduling Algorithms of Cloud Computing1

Cloud computing is the product of the evolution of calculation. It is a new distributed computing model. As more and more people put into the research and applications on cloud computing, the technology of computing becomes more and more widely used. Cloud computing has a huge user group. It has to deal with a large number of tasks. How to make appropriate decisions when allocating hardware resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. This paper is based on the current situation of resource allocation policy and job scheduling algorithms under cloud circumstance. It summarizes some methods to improve the performance, including dynamic resource allocation strategy based on the law of failure, dynamic resource assignment on the basis of credibility, ant colony optimization algorithm for resource allocation, dynamic scheduling algorithm based on threshold, optimized genetic algorithm with dual fitness and improved ant colony algorithm for job scheduling.

Energy-Efficient Dynamic Resource Allocation for Opportunistic-Relaying-Assisted SC-FDMA Using Turbo-Equalizer-Aided Soft Decode-and-Forward

In this paper, we exploit the benefits of the diversity gains that arise from a cluster of opportunistic relays (ORs) and from the independently fading subcarriers of multiple users. Our goal is to improve the energy efficiency of the decode-and-forward-based OR-assisted single-carrier frequency-division multiple-access (SC-FDMA) uplink, where the direct transmission (DT) link is unavailable. We proposed two joint dynamic resource allocation (JDRA) schemes by assuming that the pilot-aided channel-quality information (CQI) of all the users may be exchanged. Furthermore, we take the following two main aspects into account: 1) “first-hop quality awareness” (FHQA) for JDRA-aided OR and 2) “buffering delay awareness” in the context of interleaver-aided channel-coded systems. In addition, frequency-domain turbo equalizers are employed in both the relay and BS's receivers. Our results demonstrate that, compared to the DT benchmarker, the proposed FHQA JDRA schemes can achieve an energy reduction gain of 91% for a single-antenna base station (BS) receiver and up to 7.4% for a multiantenna BS when considering the energy consumption due to CQI exchange among relays.

Dynamic resource allocation scheme under traffic condition in satellite systems

As the traffic distribution in China mainland is far from uniform, a new traffic model in China mainland is presented on the basis of per-capita Gross Domestic Product (GDP) and density of population. Based on this characteristic traffic model, a new Traffic Dependent Dynamic Channel Allocation and Reservation (TDDCAR) technique is proposed, the simulation model is built, and the strategies’ performance is evaluated through computer simulation. The simulation results show that, compared to the conventional Fixed Channel Allocation (FCA), TDDCAR estimates the traffic conditions in every spot beam and frequently adjusts the traffic according to current traffic conditions. It has achieved a significant improvement in new call blocking probability, handover blocking probability, and fair index, particularly, in heavy traffic conditions. The building of traffic model in China mainland and the analysis of the simulation results has been a key foundation for the study of resource allocation schemes in the future.

AMC-based resource allocation in adaptive frequency reused OFDMA-relay networks

In orthogonal frequency division multiple access (OFDMA) relay system, for supporting relay transmission, the base station (BS)-the relay station (RS) link must consume an extra part of resource, which may result in serious resource shortage. In order to improve resource utilization, this paper proposes a dynamic resource allocation scheme in adaptive frequency reused OFDMA-relay system based on adaptive modulation and coding (AMC) technology. In this scheme, relay nodes have two independent antennas and operate in decode-and-forward (DF) and full-duplex mode. Then the BS and RSs share the same subcarriers by spatial multiplexing by two independent antennas. The resource allocation problem is formulated for system downlink throughput maximization. Since the optimal solution couldn't be obtained easily, a sub-optimal algorithm is proposed. The adaptive frequency reused algorithm with two independent antennas RS improves the system throughput about 24.3 % compared with the orthogonal frequency allocation with single-antenna model, and increases the system throughput 10.4 % compared with adaptive frequency reused algorithms with single-antenna RS. It is proved that both of the RS with two-antenna model and adaptive frequency reused scheme can improve the system throughput significantly.

A Dynamic Resource Allocation Scheme for Inter-Cell Interference Coordination in Cellular OFDMA Systems

This paper presents a novel dynamic subchannel allocation scheme that can improve the cell capacity by coordinating the intercell interference (ICI) in a cellular orthogonal frequency division multiple access (OFDMA) system. The proposed scheme mitigates the ICI by adopting the virtual cell concept and improves the frequency reuse factor through subchannel reuse among different virtual cells. In particular, each virtual cell is assigned a primary and a secondary subchannel group, and each sector base station (BSs) allocates the subchannel resulting in the least ICI in probability out of the candidate subchannels to the mobile stations, dynamically searching from its primary group and then secondary group. In addition, an optional use of pico-cell overlay at the intersection of the virtual cells is also proposed to enhance the fairness of the proposed scheme with the BS-MS distance. Through computer simulation, it is shown that the proposed scheme has the advantages of improved cell capacity and fairness compared to the conventional schemes.

A Threshold-based Dynamic Resource Allocation Scheme for Cloud Computing

Compared to traditional distributed computing paradigms, a major advantage of cloud computing is the ability to provide more reliable, affordable, flexible resources for the applications (or users). The need to manage the applications in cloud computing creates the challenge of on-demand resource provisioning and allocation in response to dynamically changing workloads. Currently most of these existing methods focused on the optimization of allocating physical resources to their associated virtual resources and migrating virtual machines to achieve load balance and increase resource utilization. Unfortunately, these methods require the suspension of the cloud computing applications due to the mandatory shutdown of the associated virtual machines. In this paper, we study the resource allocation at the application level, instead of studying how to map the physical resources to virtual resources for better resource utilization in cloud computing environment. We propose a threshold-based dynamic resource allocation scheme for cloud computing that dynamically allocate the virtual resources (virtual machines) among the cloud computing applications based on their load changes (instead of allocating resources needed to meet peak demands) and can use the threshold method to optimize the decision of resource reallocation. The proposed threshold-based dynamic resource allocation scheme is implemented by using CloudSim, and experimental results show the proposed scheme can improve resource utilization and reduce the user usage cost.

Nonlinear Predictor-Based Dynamic Resource Allocation Over Point-to-Multipoint (P2MP) Networks: A Control Theoretical Approach

Most broadband access networks such as passive optical networks (PONs) adopt the point-to-multipoint (P2MP) topology. One critical issue in such networks is the upstream resource management and allocation mechanism. Nonlinear predictor-based dynamic resource allocation (NLPDRA) schemes for improving the P2MP network upstream transmission efficiency have been investigated in an ad hoc manner. In this paper, we establish a general state space model to analyze the controllability and stability of the NLPDRA schemes from the P2MP network system’s point of view and propose controller design guidelines to maintain the system stability under different scenarios. Analytical results show that NLPDRA maintains the P2MP network system controllability even when the loaded network traffic changes drastically. We further prove that a P2MP network system with NLPDRA is stable by proper pole placements as the traffic changes. Finally, we provide guidelines to design a optimal compensator to achieve system accuracy.

Optimizing Average Performance of OFDM Systems Using Limited-Rate Feedback

Orthogonal frequency-division multiplexing (OFDM) is the most popular modulation in modern wireless communication systems. Among other features, OFDM has been able to successfully exploit channel state information (CSI) at the transmitter, allowing to implement dynamic resource allocation schemes that improve spectral efficiency and error resilience. Nevertheless, in most wireless communication systems achieving a perfect CSI at the transmitter is difficult. For this reason a limited-rate feedback mode has been proposed, in which only quantized CSI at the transmitter is available. In this paper we design joint channel quantization and resource allocation schemes for single-user OFDM systems, that use limited-rate feedback and do not assume any structure on the channel quantizer. The new schemes are obtained by solving an optimization problem that maximizes average ergodic rate subject to average power and bit error rate constraints. Necessary optimality conditions for the quantization and resource allocation schemes are derived and algorithms to find a solution satisfying such conditions are discussed. Since finding the overall global optimal solution is computationally cumbersome, suboptimal yet simple schemes are also explored. Three simplifications are investigated, namely: a worst-case robust design that reduces the dimensionality of the problem; optimal and provably convergent stochastic schemes that catch the average behavior of the system on-the-fly; and schemes that reduce the amount of feedback required from the receiver by exploiting the channel correlation among subcarriers. The signalling and computational costs associated to the implementation of the developed schemes and their extension to multiple user systems are also discussed. Numerical examples corroborate analytical claims and reveal that significant gains result even when suboptimal schemes based on affordable limited-rate feedback are used.

On Uplink Channel Estimation in WiMAX Systems

In this paper, channel estimation algorithms are proposed and compared for uplink WiMAX systems, which are OFDMA based. These algorithms are investigated based on a dynamic resource allocation scheme, and it is shown that each of them is suitable to specific system scenarios. For example, for a system with a bandwidth of 10MHz operating in the low frequency region (2-11GHz), a two-dimensional averaging algorithm outperforms other algorithms, such as a bilinear interpolation algorithm, because the correlations between the pilots and signals are sufficiently high in both the frequency and the time dimensions.

AINE: An IP Network Emulator

AINE is emulation software to build a laboratory environment for real-time performance characterisation of networks and systems, particularly satellite communication systems. Although the AINE emulator was conceived with the specific purpose of satellite networks emulation, it is a generic IP emulation tool that can also emulate link layer algorithms. This tool was developed due to the lack of COTS emulation tools supporting the dynamic radio resource allocation schemes used in DVB-RCS networks. The paper describes the main features and development characteristics of the tool and presents results for complex techniques assessed using the emulator.