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.
11623385
Resource allocation for multimedia streaming over the Internet
This paper addresses the resource allocation problem for multiple media streaming over the Internet. First, we present an end-to-end transport architecture for multimedia streaming over the Internet. Second, we propose a new multimedia streaming TCP-friendly protocol (MSTFP), which combines forward estimation of network conditions with information feedback control to optimally track the network conditions. Third, we propose a novel resource allocation scheme to adapt media rate to the estimated network bandwidth using each media's rate-distortion function under various network conditions. By dynamically allocating resources according to network status and media characteristics, we improve the end-to-end quality of services (QoS). Simulation results demonstrate the effectiveness of our proposed schemes.
20955787
Cost-based cache replacement and server selection for multimedia proxy across wireless Internet
Multimedia proxy plays an important role in multimedia streaming over wireless Internet. Since wireless network exhibits different characteristics from the Internet, multimedia proxy caching over wireless Internet faces additional challenges. In this paper, we present a study of cache replacement for a single server and server selection for multiple servers across wireless Internet. By considering multiple objectives of multimedia proxy, we design a unified cost metric to measure proxy performance in wireless Internet. Based on the defined unified cost metric, we propose a novel replacement algorithm for single-server and a new server-selection policy for multiple servers to improve the end-to-end performance such as throughput, media quality, and start-up latency. To effectively handle errors occurred on wireless link, channel-adaptive unequal error protection is deployed according to distinct quality of service requirements of layered or scalable media. Simulation results demonstrate that our approaches achieve significantly better performance than the known cache-replacement algorithms and sever selection schemes, respectively.
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.
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.
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.
1722915
A Hybrid Estimation of Distribution Algorithm for CDMA Cellular System Design
While code division multiple access (CDMA) is becoming a promising cellular communication system, the design for a CDMA cellular system configuration has posed a practical challenge in optimisation. The study in this paper proposes a hybrid estimation of distribution algorithm (HyEDA) to optimize the design of a cellular system configuration. HyEDA is a two-stage hybrid approach built on estimation of distribution algorithms (EDAs), coupled with a K-means clustering method and a simple local search algorithm. Compared with the simulated annealing method on some test instances, HyEDA has demonstrated its superiority in terms of both the overall performance in optimisation and the number of fitness evaluations required.
7426259
Modelling the Population Distribution in Multi-objective Optimization by Generative Topographic Mapping
Under mild conditions, the Pareto set of a continuous multi-objective optimization problem exhibits certain regularity. We have recently advocated taking into consideration such regularity in designing multi-objective evolutionary algorithms. Following our previous work on using Local Principal Component Analysis for capturing the regularity, this paper presents a new approach for acquiring and using the regularity of the Pareto set in evolutionary algorithms. The approach is based on the Generative Topographic Mapping and can be regarded as an Estimation of Distribution Algorithm. It builds models of the distribution of promising solutions based on regularity patterns extracted from the previous search, and samples new solutions from the models thus built. The proposed algorithm has been compared with two other state-of-the-art algorithms, NSGA-II and SPEA2 on a set of test problems.
9830436
A Flexible Conversational Dialog System for MP3 Player
In recent years, an increasing number of new devices have found their way into the cars we drive. Speech-operated devices in particular provide a great service to drivers by minimizing distraction, so that they can keep their hands on the wheel and their eyes on the road. This presentation will demonstrate our latest development of an in-car dialog system for an MP3 player designed under a joint research effort from Bosch RTC, VW ERL, Stanford CSLI, and SRI STAR Lab funded by NIST ATP [Weng et al 2004] with this goal in mind. This project has developed a number of new technologies, some of which are already incorporated in the system. These include: end-pointing with prosodic cues, error identification and recovering strategies, flexible multi-threaded, multi-device dialog management, and content optimization and organization strategies. A number of important language phenomena are also covered in the system's functionality. For instance, one may use words relying on context, such as 'this,' 'that,' 'it,' and 'them,' to reference items mentioned in particular use contexts. Different types of verbal revision are also permitted by the system, providing a great convenience to its users. The system supports multi-threaded dialogs so that users can diverge to a different topic before the current one is finished and still come back to the first after the second topic is done. To lower the cognitive load on the drivers, the content optimization component organizes any information given to users based on ontological structures, and may also refine users' queries via various strategies. Domain knowledge is represented using OWL, a web ontology language recommended by W3C, which should greatly facilitate its portability to new domains.The spoken dialog system consists of a number of components (see Fig. 1 for details). Instead of the hub architecture employed by Communicator projects [Senef et al, 1998], it is developed in Java and uses a flexible event-based, message-oriented middleware. This allows for dynamic registration of new components. Among the component modules in Figure 1, we use the Nuance speech recognition engine with class-based ngrams and dynamic grammars, and the Nuance Vocalizer as the TTS engine. The Speech Enhancer removes noises and echo. The Prosody module will provide additional features to the Natural Language Understanding (NLU) and Dialogue Manager (DM) modules to improve their performance.The NLU module takes a sequence of recognized words and tags, performs a deep linguistic analysis with probabilistic models, and produces an XML-based semantic feature structure representation. Parallel to the deep analysis, a topic classifier assigns top n topics to the utterance, which are used in the cases where the dialog manager cannot make any sense of the parsed structure. The NLU module also supports dynamic updates of the knowledge base.The CSLI DM module mediates and manages interaction. It uses the dialogue-move approach to maintain dialogue context, which is then used to interpret incoming utterances (including fragments and revisions), resolve NPs, construct salient responses, track issues, etc. Dialogue states can also be used to bias SR expectation and improve SR performance, as has been performed in previous applications of the DM. Detailed descriptions of the DM can be found in [Lemon et al 2002; Mirkovic & Cavedon 2005].The Knowledge Manager (KM) controls access to knowledge base sources (such as domain knowledge and device information) and their updates. Domain knowledge is structured according to domain-dependent ontologies. The current KM makes use of OWL, a W3C standard, to represent the ontological relationships between domain entities. Protege (http://protege.stanford.edu), a domain-independent ontology tool, is used to maintain the ontology offline. In a typical interaction, the DM converts a user's query into a semantic frame (i.e. a set of semantic constraints) and sends this to the KM via the content optimizer.The Content Optimization module acts as an intermediary between the dialogue management module and the knowledge management module during the query process. It receives semantic frames from the DM, resolves possible ambiguities, and queries the KM. Depending on the items in the query result as well as the configurable properties, the module selects and performs an appropriate optimization strategy.Early evaluation shows that the system has a task completion rate of 80% on 11 tasks of MP3 player domain, ranging from playing requests to music database queries. Porting to a restaurant selection domain is currently under way.
21818900
Trunk Reservation in Multi-service Networks with BPP Traffic
In this paper we develop approximate models for trunk reservation in multi-service systems with BPP (Binomial-Poisson-Pascal) multi-rate traffic streams. The approximation is a generalization of previous work by Tran-Gia & Hubner who assumed Poisson arrival processes. It is based on a generalized algorithm which allows for calculation of individual performance measures for each service, in particular the traffic congestion. The algorithm is numerically robust and requires a minimum of computer memory and computing time. The approximation is good when the services have equal mean service times.
2460253
Approximate processing of massive continuous quantile queries over high-speed data streams
Quantile computation has many applications including data mining and financial data analysis. It has been shown that an /spl epsi/-approximate summary can be maintained so that, given a quantile query (/spl phi/,/spl epsi/), the data item at rank /spl lceil//spl phi/N/spl rceil/ may be approximately obtained within the rank error precision /spl epsi/N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different /spl phi/ and /spl epsi/ poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.