33166016
Indirect RSVP for Virtual Cluster Cellular Mobile IP Networks
Mobile IP (MIP) could be deployed in a wireless cellular network so that the integrated Cellular Mobile IP (CMIP) network can be used to support datagram delivery to mobile users. In order to provide QoS for realtime traffic in IP network, Resource reSerVation Protocol (RSVP) is needed to reserve network resources along the route which the datagrams follow. However, current RSVP fails to operate through the MIP tunnel. Moreover, the high registration rate in a CMIP network greatly degrades RSVP performance. In this paper, an Indirect RSVP (IRSVP) over Virtual Cluster Cellular Mobile IP (VCCMIP) is proposed in which an assistant RSVP connection is introduced to assist the end-to-end major RSVP operation over the MIP tunnel. IRSVP signaling costs and packet loss rates are evaluated. Simulation results show that the proposed scheme can greatly increase RSVP performance in terms of packet loss and RSVP connection active percentage.
11389576
Ultra-wideband wireless communications
Summary Ultra-wideband (UWB) communication techniques have attracted a great interest in both academia and industry in the past few years for applications in short-range wireless mobile systems. This is due to the potential advantages of UWB transmissions such as low power, high rate, immunity to multipath propagation, less complex transceiver hardware, and low interference. However, tremendous R&D efforts are required to face various technical challenges in developing UWB wireless systems, including UWB channel characterization, transceiver design, coexistence and interworking with other narrowband wireless systems, design of the link and network layers to benefit from UWB transmission characteristics. This paper is to provide an overview of UWB communications, summarize the previous research results, and identify further research issues that need to be tackled. The emphasis is placed on the commercial wireless communications. Copyright # 2003 John Wiley & Sons, Ltd.
7313627
Voice capacity analysis of WLAN with unbalanced traffic
An analytical model to study the performance of wireless local area networks (WLANs) supporting asymmetric nonpersistent traffic using the IEEE 802.11 distributed coordination function mode for medium access control (MAC) is developed. Given the parameters of the MAC protocol and voice codecs, the voice capacity of an infrastructure-based WLAN, in terms of the maximum number of voice connections that can be supported with satisfactory user-perceived quality, is obtained. In addition, voice capacity analysis reveals how the overheads from different layers, codec rate, and voice packetization interval affect voice traffic performance in WLANs, which provides an important guideline for network planning and management. The analytical results can be used for effective call admission control to guarantee the quality of voice connections. Extensive simulations have been performed to validate the analytical results
768133
Performance analysis of TCP-friendly AIMD algorithms for multimedia applications
In this paper, the performance of TCP-friendly generic AIMD (Additive Increase and Multiplicative Decrease) algorithms for Web-based playback and multirate multimedia applications is investigated. The necessary and sufficient TCP-friendly condition is derived, and the effectiveness and responsiveness of AIMD are studied. Due to practical implications, a Dynamic TCP-friendly AIMD (DTAIMD) algorithm is proposed. Extensive simulation results are given to verify the derived necessary and sufficient condition, and to demonstrate the performance of the proposed DTAIMD algorithm.
9894542
Reliability optimization of distributed access networks with constrained total cost
In this paper, we study the system reliability optimization of distributed access networks subject to a constraint on the total cost. We first formulate the cost-constrained system reliability optimization problem as a searching process in a combinatorial tree, which enumerates all the possible solutions to the problem. Because the calculation of each possible solution for the reliability problem is extremely time-consuming, a novel algorithm, the Shrinking & Searching Algorithm (SSA), is proposed to speed up the searching process. SSA jointly considers the upper bound of the system reliability for each branch in the combinatorial tree, and the cost constraint on the possible solutions. It avoids most of the redundant calculations in the searching process by gradually shrinking the difference between lower & upper bounds of the length of a path in the corresponding combinatorial tree, which represents a feasible solution. Case study & simulation results are presented to demonstrate the performance of the SSA.
16600319
Update-Based Cache Access and Replacement in Wireless Data Access
Cache has been applied for wireless data access with different replacement policies in wireless networks. Most of the current cache replacement schemes are access-based replacement policies since they are based on object access frequency/recency information. Access-based replacement policies either ignore or do not focus on update information. However, update information is extremely important since it can make access information almost useless. In this paper, we consider two fundamental and strongly consistent access algorithms: poll-per-read (PER) and call-back (CB). We propose a server-based PER (SB-PER) cache access mechanism in which the server makes replacement decisions and a client-based CB cache access mechanism in which clients make replacement decisions. Both mechanisms have been designed to be suitable for using both update frequency and access frequency. We further propose two update-based replacement policies, least access-to-update ratio (LA2U) and least access-to-update difference (LAUD). We provide a thorough performance analysis via extensive simulations for evaluating these algorithms in terms of access rate, update rate, cache size, database size, object size, etc. Our study shows that although effective hit ratio is a better metric than cache hit ratio, it is a worse metric than transmission cost, and a higher effective hit ratio does not always mean a lower cost. In addition, the proposed SB-PER mechanism is better than the original PER algorithm in terms of effective hit ratio and cost, and the update-based policies outperform access-based policies in most cases
6579321
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (ie, frequent patterns) has already been mined. Our goal is to help a particular user effectively discover interesting patterns according to his specific interest. Without requiring a user to explicitly construct a prior knowledge to measure the interestingness of patterns, we learn the user's prior knowledge from his interactive feedback. We propose two models to represent a user's prior: the log linear model and biased belief model. The former is designed for item-set patterns, whereas the latter is also applicable to sequential and structural patterns. To learn these models, we present a two-stage approach, progressive shrinking and clustering, to select sample patterns for feedback. The experimental results on real and synthetic data sets demonstrate the effectiveness of our approach.
14429022
Mining long-term search history to improve search accuracy
Long-term search history contains rich information about a user's search preferences, which can be used as search context to improve retrieval performance. In this paper, we study statistical language modeling based methods to mine contextual information from long-term search history and exploit it for a more accurate estimate of the query language model. Experiments on real web search data show that the algorithms are effective in improving search accuracy for both fresh and recurring queries. The best performance is achieved when using clickthrough data of past searches that are related to the current query.
410513
Active Feedback - UIUC TREC-2003 HARD Experiments
In this paper, we report our experiments on the HARD (High Accuracy Retrieval from Documents) Track in TREC 2003. We focus on active feedback, i.e., how to intelligently propose questions for relevance feedback in order to maximize accuracy improvement in the second run. We proposed and empirically evaluated three different methods, i.e., top-k, gapped top-k, and k-cluster centroid, to extract a fixed number of text units (e.g. passage or document) for feedback. The results show that presenting the top k documents for user feedback is often not as beneficial for learning as presenting more diversified documents.
1982629
Efficient embedding K-ary complete trees into hypercubes
Dilated embedding and precise embedding of K-ary complete trees into hypercubes are studied. For dilated embedding, a nearly optimal algorithm is proposed which embeds a K-ary complete tree of height h, T/sub K/(h), into an (h/spl minus/1)/spl lsqb/logK/spl rsqb/+/spl lsqb/log(K+2)/spl rsqb/ dimensional hypercube with dilation max(2, /spl phi/(K)*), /spl phi/(K+2). For precise embedding, we show a (K/spl minus/1)h+1 dimensional hypercube is large enough to contain T/sub K/(h) as its subgraph for K/spl ges/3.<<ETX>>
302118
A Hierarchical Model of Reference Affinity
To improve performance, data reorganization needs locality models to identify groups of data that have reference affinity. Much past work is based on access frequency and does not consider accessing time directly. In this paper, we propose a new model of reference affinity. This model considers the distance between data accesses in addition to the frequency. Affinity groups defined by this model are consistent and have a hierarchical structure. The former property ensures the profitability of data packing, while the latter supports data packing for storage units of different sizes. We then present a statistical clustering method that identifies affinity groups among structure fields and data arrays by analyzing training runs of a program. When used by structure splitting and array regrouping, the new method improves the performance of two test programs by up to 31%. The new data layout is significantly better than that produced by the programmer or by static compiler analysis.