End-to-end maxmin fairness in multihop wireless networks: Theory and protocol

To promote commercial deployment of multihop wireless networks, the research/industry communities must develop new theories and protocols for flexible traffic engineering in these networks in order to support diverse user applications. This paper studies an important traffic engineering problem–how to support fair bandwidth allocation among all end-to-end flows in a multihop wireless network–which, in a more precise term, is to achieve the global maxmin fairness objective in bandwidth allocation. There exists no distributed algorithm for this problem in multihop wireless networks using IEEE 802.11 DCF. We have two major contributions. The first contribution is to develop a novel theory that maps the global maxmin objective to four local conditions and prove their equivalence. The second contribution is to design a distributed rate adjustment protocol based on those local conditions to achieve the global maxmin objective through fully distributed operations. Comparing with the prior art, our protocol has a number of advantages. It is designed for the popular IEEE 802.11 DCF. It replaces per-flow queueing with per-destination queueing. It achieves far better fairness (or weighted fairness) among end-to-end flows.     

A comparative analysis of video codecs for multihop wireless video sensor networks

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video coding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video codecs based on emerging video coding paradigms such as distributed video coding and distributed compressive video sensing for multihop WVSNs. The main objective of this work was to provide an insight into the computational (encoding/decoding) complexity, energy consumption, node and network lifetime, processing and memory requirements, and the quality of reconstruction of these video codecs. Based on the findings, this paper also provides some guidelines for the selection of appropriate video codecs for a given WVSN application.     

Game Theoretic subcarrier and power allocation for wireless OFDMA networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.     

Interference aware resource allocation for hybrid hierarchical wireless networks

This paper addresses the problem of interference aware resource allocation for OFDMA based hybrid hierarchical wireless networks. We develop two resource allocation algorithms considering the impact of wireless interference constraints using a weighted SINR conflict graph to quantify the interference among the various nodes: (1) interference aware routing using maximum concurrent flow optimization; and (2) rate adaptive joint subcarrier and power allocation algorithm under interference and QoS constraints. We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution.     

多媒体系统多资源分配中效率与公平性的权衡

针对多媒体系统多资源分配问题,提出了一种权衡效率与公平性的有效方法。分析 -公平性与系统效用及公平性指标的关系,提出利用 -公平性来实现两者之间的权衡,并验证其合理性。为了获得满足 -公平性的资源分配,提出了一种基于定价机制的多资源分配算法。仿真结果表明,所提出的多资源分配算法能够在较短时间内获得近似最优的资源分配;通过调整 值能够实现效率与公平性之间的权衡, 值越大,越强调公平性。     

Similarity based image selection with frame rate adaptation and local event detection in wireless video sensor networks

Wireless Video Sensor Networks (WVSNs7unding environmental information. Those sensor nodes can locally process the information and then wirelessly transmit it to the coordinator and to the sink to be further processed. As a consequence, more abundant video and image data are collected. In such densely deployed networks, the problem of data redundancy arises when information are gathered from neighboring nodes. To overcome this problem, one important enabling technology for WVSN is data aggregation, which is essential to be cost-efficient. In this paper, we propose a new approach for data aggregation in WVSN based on images and shot similarity functions. It is deployed on two levels: the video-sensor node level and the coordinator level. At the sensor node level the proposed algorithms aim at reducing the number of frames sensed by the sensor nodes and sent to the coordinator. At the coordinator level, after receiving shots from different neighbouring sensor nodes, the similarity between these shots is computed to eliminate redundancies and to only send the frames which meet a certain condition to the sink. The similarity between shots is evaluated based on their color, edge and motion information. We evaluate our approach on a live scenario and compare the results with another approach from the literature in terms of data reduction and energy consumption. The results show that the two approaches have a significant data reduction to reduce the energy consumption, thus our approach tends to overcome the other one in terms of reducing the energy consumption related to the sensing process, and to the transmitting process while guaranteeing the detection of all the critical events at the node and the coordinator levels.

     

A QoE-based jointly subcarrier and power allocation for multiuser multiservice networks在多业务多用户网络场景下的基于QoE的联合子载波和功率资源分配

Quality of experience (QoE) is widely applied to reflect user’s satisfaction of the network service, which exactly conforms to the user-centric concept in 5G. In this paper, we propose a QoE-based subcarrier and power allocation algorithm for the downlink transmission of a multiuser multiservice system. For the subcarrier allocation algorithm, the rate proportional fairness factor is defined to ensure the fairness between users. Based on different QoE models of three services, i.e., file down (FD), video streaming and voice over internet protocol (VOIP), a multi-objective optimization method is exploited to allocate the power resource by minimizing the total power consumption and maximizing the mean opinion score (MOS) value of users simultaneously. Simulation results indicate that the proposed algorithm has less power consumption and higher QoE performance than the traditional proportional fairness (PF) algorithm. In addition, the proposed algorithm can achieve nearly the same fairness performance as the PF algorithm. Moreover, when the number of subcarriers becomes larger, the power assumption will be less but with little influence on both the QoE and fairness performances.     

Balancing energy efficiency and throughput fairness in IEEE 802.11 WLANs

The proliferation of wireless networks based on IEEE 802.11 has resulted in a heterogenous set of devices using a variety of applications to compete for the desired service performance. Most notably, the class of highly mobile and energy constrained devices is showing high growth rates. Yet, fairness of resource allocation is still only considered in terms of achievable throughput and without considering energy efficiency. In this paper we first show that performing an energy efficient and fair resource allocation in current IEEE 802.11 WLANs is challenging, given the diversity of power consumption figures among mobile devices. We then propose a criterion to objectively balance between the most energy-efficient configuration (where all resources are given to one station) and the throughput-fair allocation (where the power consumption is not considered). We derive a closed-form expression for the optimal configuration of 802.11 with respect to this criterion. Our analysis is validated through simulations, showing that our approach betters the prevalent allocation schemes discussed in literature in terms of energy efficiency, while maintaining the notion of fairness among devices. Experimental results obtained in a real-world testbed confirm the main results derived from our analysis and simulations.     

Joint Source Coding and Network-Supported Distributed Error Control for Video Streaming in Wireless Multihop Networks

Real-time video communication over wireless multihop networks has gained significant interest in the last few years. In this paper, we focus our attentions on the problem of source coding and link adaptation for packetized video streaming in wireless multihop networks when network nodes are media-aware. We consider a system where source coding is employed at the video encoder by selecting the encoding mode of each individual macro-block, while error control is exercised through application-layer retransmissions at each media-aware network node. For this system model, the contribution of each communication link on the end-to-end video distortion is considered separately in order to achieve globally optimal source coding and ARQ error control. To reach the globally optimal solution, we formulate the problem of joint source and distributed error control (JSDEC) and devise a low-complexity solution algorithm based on dynamic programming. Extensive experiments have been carried out on the basis of H.264/AVC codec to demonstrate the effectiveness of the proposed algorithm over the existing joint source and channel coding (JSCC) algorithm in terms of PSNR perceived at the decoder under time-varying multihop wireless links.     

改进的解码转发多跳中继系统及最优功率分配

多跳信道的中断性能较差,且节点接收设备上的多跳分集信道较为复杂。为此,基于解码转发多跳信道和多跳分集信道,提出一种改进的解码转发多跳中继系统,解决上述2种信道性能和复杂度的矛盾。推导中断概率的计算公式,以最小化系统中断概率为目标,利用拉格朗日乘子优化各节点的功率分配。仿真结果表明,改进系统能获得比传统多跳中继系统更低的中断概率,最优功率分配方案下系统的中断性能优于均匀功率分配方案,并且性能优势随跳数增加更为明显。     

Jointly optimal congestion control, channel allocation and power control in multi-channel wireless multihop networks

In this paper, to increase end-to-end throughput and energy efficiency of the multi-channel wireless multihop networks, a framework of jointly optimize congestion control in the transport layer, channel allocation in the data link layer and power control in the physical layer is proposed. It models the network by a generalized network utility maximization (NUM) problem with elastic link data rate constraints. Through binary linearization and log-transformation, and after relaxing the binary constraints on channel allocation matrix, the NUM problem becomes a convex optimization problem, which can be solved by the gateway centralized through branch and bound algorithm with exponential time complexity. Then, a partially distributed near-optimal jointly congestion control, channel allocation and power control (DCCCAPC) algorithm based on Lagrangian dual decomposition technique is proposed. Performance is assessed through simulations in terms of network utility, energy efficiency and fairness index. Convergence of both centralized and distributed algorithms is proved through theoretic analysis and simulations. As the available network resources increase, the performance gain on network utility increases.     

Toward end-to-end fairness: a framework for the allocation of multiple prioritized resources in switches and routers

As flows of traffic traverse a network, they share with other flows a variety of resources such as links, buffers and router CPUs in their path. Fairness is an intuitively desirable property in the allocation of resources in a network shared among flows of traffic from different users. While fairness in bandwidth allocation over a shared link has been extensively studied, overall end-to-end fairness in the use of all the resources in the network is ultimately the desired goal. End-to-end fairness becomes especially critical when fair allocation algorithms are used as a component of the mechanisms used to provide end-to-end quality-of-service guarantees. This paper seeks to answer the question of what is fair when a set of traffic flows share multiple resources in the network with a shared order of preference for the opportunity to use these resources. We present the Principle of Fair Prioritized Resource Allocation or the FPRA principle, a powerful extension of any of the classic notions of fairness such as max–min fairness, proportional fairness and utility max–min fairness defined over a single resource. We illustrate this principle by applying it to a system model with a buffer and an output link shared among competing flows of traffic. To complete our illustration of the applicability of the FPRA principle, we propose a measure of fairness and evaluate representative buffer allocation algorithms based on this measure. Besides buffer allocation, the FPRA principle may also be used in other contexts in data communication networks and operating system design.     

Resource allocation algorithm with limited feedback for multicast single frequency networks

The single frequency network (SFN) can provide a multimedia broadcast multicast service over a large coverage area. However, the application of SFN is still restricted by a large amount of feedback. Therefore, we propose a multicast resource allocation scheme based on limited feedback to maximize the total rate while guaranteeing the quality of service (QoS) requirement of real-time services. In this scheme, we design a user feedback control algorithm to effectively reduce feedback load. The algorithm determines to which base stations the users should report channel state information. We then formulate a joint subcarrier and power allocation issue and find that it has high complexity. Hence, we first distribute subcarriers under the assumption of equal power and develop a proportional allocation strategy to achieve a tradeoff between fairness and QoS. Next, an iterative water-filling power allocation is proposed to fully utilize the limited power. To further decrease complexity, a power iterative scheme is introduced. Simulation results show that the proposed scheme significantly improves system performance while reducing 68% of the feedback overhead. In addition, the power iterative strategy is suitable in practice due to low complexity.     

认知OFDM无线电系统基于公平度门限的资源分配

根据认知无线电的特点和正交频分复用(OFDM)的传输特性,提出了一种针对认知OFDM无线电系统的自适应资源分配算法。在传统的子载波分配过程中,具有优先权的用户将优先选择载波,但信道增益最大的载波并不一定会被其使用,这将导致载波利用效率下降。针对这一问题,该算法在载波分配过程中,通过公平度门限来决定载波分配的优先级,从而实现容量和公平度的折中。同时,在子载波和功率分配中使次用户对主用户的干扰功率限制在主用户可容忍的干扰极限内,保证了每个用户的通信要求。仿真结果表明,该算法在满足公平性的同时还提升了系统的容量。     

无线充电体域网基于边际效用的网络资源分配方法

射频能量采集技术可以从根本上解决电池容量对无线体域网生存期的限制,为了提高网络资源分配的效率以及公平性,提出一种基于边际效用理论的网络资源分配方法。首先,设计传感器节点的效用函数,将节点所能获得的吞吐量映射成QoS满意的等级;然后,以最大化网络中全部传感器节点整体效用为目标,将多高效、公平的网络资源分配问题构建成效用最大化问题;最后,通过对偶分解方法求得该问题的最优解。仿真结果表明,与总吞吐量最大化和sigmoid效用最大化方法相比,所提出的方法在获得较高系统整体吞吐量的同时,确保了传感器节点个体获得吞吐量的公平性。     

云计算资源调度研究综述

资源调度是云计算的一个主要研究方向.首先对云计算资源调度的相关研究现状进行深入调查和分析;然后重点讨论以降低云计算数据中心能耗为目标的资源调度方法、以提高系统资源利用率为目标的资源管理方法、基于经济学的云资源管理模型,给出最小能耗的云计算资源调度模型和最小服务器数量的云计算资源调度模型,并深入分析和比较现有的云资源调度方法;最后指出云计算资源管理的未来重要研究方向:基于预测的资源调度、能耗与性能折衷的调度、面向不同应用负载的资源管理策略与机制、面向计算能力(CPU、内存)和网络带宽的综合资源分配、多目标优化的资源调度,以便为云计算研究提供有益的参考.     

基于合作博弈的数据中心骨干网带宽分配策略

数据中心(data center, DC)之间通过部署流量工程来提高连接各个数据中心骨干网的利用率,虽然效率提升显著,但对不同类型汇聚流的带宽分配的公平性没有考虑.将多个汇聚流对带宽分配的竞争行为建模为一个合作博弈,通过寻求此博弈的纳什谈判解(Nash bargaining solution, NBS)来确定优化的带宽分配策略CGBA(cooperation game based bandwidth allocation),权衡各汇聚流的最小带宽保证与带宽分配的公平性.在Mininet平台上进行实验仿真并和典型的带宽分配策略对比,结果表明CGBA不但可保证各汇聚流的最小带宽需求,还确保了各类流对带宽资源竞争的公平性.     

Efficient compressed sensing based object detection system for video surveillance application in WMSN

Limited memory, energy and bandwidth are the major constraints in wireless visual sensor network (WVSN). Video surveillance applications in WVSN attracts a lot of attention in recent years which requires high detection accuracy and increased network lifetime that can be achieved by reducing the energy consumption in the sensor nodes. Compressed sensing (CS) based background subtraction plays a significant role in video surveillance application for detecting the presence of anomaly with reduced complexity and energy. This paper presents a system based on CS for single and multi object detection that can detect the presence of an anomaly with higher detection accuracy and minimum energy. A novel and efficient mean measurement differencing approach with adaptive threshold strategy is proposed for detection of the objects with less number of measurements, thereby reducing transmission energy. The performance of the system is evaluated in terms of detection accuracy, transmission energy and network lifetime. Furthermore, the proposed approach is compared with the conventional background subtraction approach. The simulation results show that the proposed approach yields better detection accuracy with 90% reduction in samples compared to conventional approach.     

Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid

A mobile ad hoc computational grid is a distributed computing infrastructure that allows mobile nodes to share computing resources in a mobile ad hoc environment. Compared to traditional distributed systems such as grids and clouds, resource allocation in mobile ad hoc computational grids is not straightforward because of node mobility, limited battery power and an infrastructure‐less network environment. The existing schemes are either based on a decentralized architecture that results in poor allocation decisions or assume independent tasks. This paper presents a scheme that allocates interdependent tasks and aims to reduce task completion time and the amount of energy consumed in transmission of data. This scheme comprises two key algorithms: resource selection and resource allocation. The resource selection algorithm is designed to select nodes that remain connected for a longer period, whereas the resource assignment or allocation algorithm is developed to allocate interdependent tasks to the nodes that are accessible at the minimum transmission power. The scheme is based on a hybrid architecture that results in effective allocation decisions, reduces the communication cost associated with the exchange of control information, and distributes the processing burden among the nodes. The paper also investigates the relationship between the data transfer time and transmission energy consumption and presents a power‐based routing protocol to reduce data transfer costs and transmission energy consumption. Copyright © 2014 John Wiley & Sons, Ltd.