2128570
Peer-to-peer based multimedia distribution service
Recently, there are many research interests in providing efficient and scalable multimedia distribution service. However, stringent quality-of-service (QoS) requirements for media distribution, as well as dynamically changing and heterogeneous network capacity in today's best effort Internet, bring many challenges. In this paper, we introduce a novel framework for multimedia distribution service based on peer-to-peer (P2P) networks. A topology-aware overlay is proposed in which hosts self-organize into groups. End hosts within the same group have similar network conditions and can easily collaborate with each other to achieve QoS awareness. In order to improve media delivery quality and provide high service availability, we further propose two distributed heuristic replication strategies, intergroup replication and intragroup replication, based on this topology-aware overlay. Specifically, intergroup replication is aimed to improve the efficiency of media content delivery between the group where a request is issued and the group where the content is stored. Also, intragroup replication is targeted at improving the availability of the content. Extensive simulation results show that the latency in our proposed architecture is 20% less than that of the FreeNet and 50% less than that of the randomly replication system. Simulation results also show that the video quality in our system is much better than that in the other two systems. Our P2P-based approach is also distributed, scalable, cost effective, and aware of the performance.
17722556
Network-Adaptive Cache Management Schemes for Mixed Media
For efficently caching mixed-media, this paper discusses several network-adaptive cache management schemes. Considering the characteristics of different types of media, we first proposed a multi-level page-size management scheme. Then, a media-characteristic-weighted replacement policy is presented to improve the hit ratio of mixed media including continuous and noncontinuous media. Lastly, a network-condition- and media-quality-adaptive resource management mechanism is described to dynamically re-allocate cache resource for different types of media according to their request patterns. Simulation results demonstrate effectiveness of our propsoed approaches.
8668229
Bounding the power rate function of wireless ad hoc networks
Given a wireless ad hoc network and an end-to-end traffic pattern, the power rate function refers to the minimum total power required to support different throughput under a layered model of wireless networks. A critical notion of the layered model is the realizable graphs, which describe possible hit-rate supplies on the links by the physical and medium access layers. Under the layered model, the problem of finding the power rate function can he transformed into finding the minimum-power realizable graph that can provide a given throughput. We introduce a usage conflict graph to represent the conflicts among different uses of the wireless medium. Testing the realizability of a given graph can be transformed into finding the (vertex) chromatic number, i.e., the minimum number of colors required in a proper vertex-coloring, of the associated usage conflict graph. Based on an upper bound of the chromatic number, we propose a linear program that outputs an upper bound of the power rate function. A lower bound of the chromatic number is the clique number. We propose a systematic way of identifying cliques based on a geometric analysis of the space sharing among active links. This leads to another linear program, which yields a lower bound of the power rate function. We further apply greedy vertex-coloring to fine tune the bounds. Simulations results demonstrate that the obtained bounds are tight in the low power and low rate regime.
206750751
Error robust scalable audio streaming over wireless IP networks
Streaming high-fidelity audio over wireless Internet protocol (IP) networks is a challenging task because the networks present not only packet losses, but also residual bit errors. These losses and errors have severe adverse effect on the compressed audio bitstream. To solve this problem, this paper introduces error resilience in conjunction with error protection for scalable audio streaming over wireless networks. Specifically, error resilience is achieved by performing bitstream data partitioning and reversible variable length coding in the audio coder. Error protection is provided by layered product channel code to simultaneously handle packet losses and residual bit errors. Both the row and column codes of the product code provide unequal error protection for different layers of the audio bitstream by considering the characteristics of the scalable audio. Rate-distortion optimization is performed to determine the best source-channel coding tradeoff that minimizes the average expected end-to-end distortion. Simulation results demonstrate the effectiveness of our proposed approach.
1741788
A Compound TCP Approach for High-Speed and Long Distance Networks
Many applications require fast data transfer over high speed and long distance networks. However, standard TCP fails to fully utilize the network capacity due to the limitation in its conservative congestion control (CC) algorithm. Some works have been proposed to improve the connection 鈂s throughput by adopt- ing more aggressive loss-based CC algorithms. These algorithms, although can effectively improve the link utilization, have the weakness of poor RTT fairness. Further, they may severely de- crease the performance of regular TCP flows that traverse the same network path. On the other hand, pure delay-based ap- proaches that improve the throughput in high-speed networks may not work well when the traffic is mixed with both delay- based and greedy loss-based flows. In this paper, we propose a novel Compound TCP (CTCP) approach, which is a synergy of delay-based and loss-based approach. Specifically, we add a scal- able delay-based component into the standard TCP Reno conges- tion avoidance algorithm (a.k.a., the loss-based component). The sending rate of CTCP is controlled by both components. This new delay-based component can rapidly increase sending rate when network path is under utilized, but gracefully retreat in a busy network when bottleneck queue is built. Augmented with this delay-based component, CTCP provides very good bandwidth scalability with improved RTT fairness, and at the same time achieves good TCP-fairness, irrelevant to the windows size. We developed an analytical model of CTCP and implemented it on the Windows operating system. Our analysis and experiment results verify the properties of CTCP.
35872608
On the Performance Analysis of Network-Coded Cooperation in Wireless Networks
Cooperative communication is a powerful technology combating fading in wireless medium. In contrast to conventional cooperation (CC) which allows the relay to simply process and forward what it has heard, network-coded cooperation (NCC) endows network coding capability with the relay, i.e., allows the relay to first encode the data it has received from different sources and then forward the network-coded data to corresponding destinations. In this paper we systematically investigate the performance of NCC in terms of diversity-multiplexing tradeoff as well as exact system outage behavior. Under the assumption (denoted as A) that each destination can reliably overhear the data from other sources, we prove the diversity-multiplexing tradeoff of NCC outperforms that of CC. Moreover, we derive the close form of the system outage probability of NCC as a function of signal-to-noise ratio (SNR). The analytical and numerical results show that by requiring less bandwidth cost, NCC offers a similar or even reduced system outage probability compared with CC, and achieves the same full diversity order as CC at high SNR. Finally we discuss the performance of NCC in case the assumption A is removed. For a wireless network composed of N s-d pairs and a single relay, although there is a certain system outage probability increase for NCC, it still provides the same full diversity order of 2 as CC at high SNR, and has a diversity-multiplexing tradeoff superior to CC.
16216432
A Multiobjective Differential Evolution Based on Decomposition for Multiobjective Optimization with Variable Linkages
Although a number of multiobjective evolutionary algorithms have been proposed over the last two decades, not much effort has been made to deal with variable linkages in multiobjective optimization. Recently, we have suggested a general framework of multiobjective evolutionary algorithms based on decomposition (MOEA/D) [1]. MOEA/D decomposes a MOP into a number of scalar optimization subproblems by a conventional decomposition method. The optimal solution to each of these problems is a Pareto optimal solution to the MOP under consideration. An appropriate decomposition could make these individual Pareto solutions evenly distribute along the Pareto optimal front. MOEA/D aims at solving these scalar optimization subproblems simultaneously. In this paper, we propose, under the framework of MOEA/D, a multiobjective differential evolution based decomposition (MODE/D) for tackling variable linkages. Our experimental results show that MODE/D outperforms several other MOEAs on several test problems with variable linkages.
29533358
On the discrete-time dynamics of a PCA learning algorithm
Abstract We propose a principal component analysis algorithm based on our previous work and analyze its deterministic discrete-time (DDT) system. We prove that its DDT system is always bounded for the small constant learning gain and can almost always deliver a principal component. The difference between Oja's algorithm and our proposed algorithm cannot be observed from their corresponding deterministic continuous-time systems.
18316669
On Linear-Spline Based Histograms
Approximation is a very effective paradigm to speed up query processing in large databases. One popular approximation mechanism is data size reduction. There are three reduction techniques: sampling, histograms, and wavelets. Histogram techniques are supported by many commercial database systems, and have been shown very effective for approximately processing aggregation queries. In this paper, we will investigate the optimal models for building histograms based on linear spline techniques. We will firstly propose several novel models. Secondly, we will present efficient algorithms to achieve these proposed optimal models. Our experiment results showed that our new techniques can greatly improve the approximation accuracy comparing to the existing techniques.
27590229
Spectral histogram representations for visual modeling
We present spectral histogram representations for visual modeling. Based on a generative process, the representation is derived by partitioning the frequency domain into small disjoint regions and assuming independence among the regions. This gives rise to a set of filters and a representation consisting of marginal distributions of those filter responses. A distinct advantage of our representation is that it can be effectively used for different classification and recognition tasks, which is demonstrated by experiments and comparisons in texture classification, face recognition, and appearance-based 3D object recognition. The marked improvement over existing methods justifies our principle that effective priori knowledge should be derived from physical generative processes.
15055893
On the convergence of a class of estimation of distribution algorithms
We investigate the global convergence of estimation of distribution algorithms (EDAs). In EDAs, the distribution is estimated from a set of selected elements, i.e., the parent set, and then the estimated distribution model is used to generate new elements. In this paper, we prove that: 1) if the distribution of the new elements matches that of the parent set exactly, the algorithms will converge to the global optimum under three widely used selection schemes and 2) a factorized distribution algorithm converges globally under proportional selection.