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.
415324
Mobility information for resource management in wireless ATM networks
User mobility poses a significant technical challenge to network resource management in wireless ATM (Asynchronous Transfer Mode) networks. In order to guarantee quality of service (QoS) to mobile users and to achieve a high efficiency in network resource management, the information of mobile users' handoff at a future moment is essential for statistical multiplexing. This paper develops a novel fuzzy logic inference system to estimate the user mobility information for a wireless ATM network which uses a direct sequence code division multiple access (DS/CDMA) protocol. The estimation is based on measured pilot signal strengths from a number of the nearest base stations by the mobile user. Numerical results are presented to demonstrate the performance of the proposed technique under various path losses and channel shadowing conditions. The proposed technique can achieve simplicity, accuracy and low cost.
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.
41776046
A Node Cooperative ARQ Scheme for Wireless Ad-Hoc Networks
We propose a Node Cooperative Automatic Repeat reQuest (ARQ) scheme for wireless ad-hoc networks to combat the effects of channel fading on the performance of link layer retransmission scheme. The proposed scheme is inspired by the idea of cooperative diversity. Simulation results are given to demonstrate the significant throughput gain, even when the quality of channel between the communicating nodes is poor.
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
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
7243220
Finding multiple routing paths in wide-area WDM networks
In this paper the multiple routing path problem in wide area Wavelength Division Multiplexing (WDM) networks is considered, which is to find K edge-disjoint lightpaths/semi-lightpaths from a source to a destination such that the K paths meet some specified optimization objectives if they exist. Two versions of the problem are studied One is to minimize the total cost of the K paths. Another is to minimize the cost of the maximum cost path among the K paths. An efficient algorithm for the first version is proposed, which takes O (kK (kn + m + n log(kn))) time and delivers an exact solution, where n, m, and k are the number of nodes, links and wavelengths in the network. The second version of the problem is shown to be NP-hard, and an approximate algorithm for it is devised, delivering an approximate solution that is K times the optimum, where K /spl ges/ 2.
33412339
Conservative Algorithms for Parallel and Sequential Integer Sorting
We present a conservative CRCW parallel algorithm for integer sorting. This algorithm sorts n integers from {0, 1, ..., m−1} in time O(n log log min(m,n)/p + log n) using p processors. The simulation of our parallel algorithm on the sequential machine yields a sequential algorithm for integer sorting which sorts n integers from {0, 1, ..., m−1} in time O(n min(log log n, log log m/log n)).
5555998
Finding multiple routing paths in wide-area WDM networks
In this paper a multiple routing path problem in wide area Wavelength Division Multiplexing (WDM) networks is considered, which is to find K edge-disjoint lightpaths/semilightpaths from a source to a destination, if they exist, such that they meet some specified optimization objective. Two versions of the problem are studied. One is to minimize the total cost of the K paths, and the other is to minimize the cost of the maximum cost one among the K paths. An efficient algorithm for the first version is proposed, which takes O(kK(kn+m+nlog(kn))) time and delivers an exact solution, where n, m, and k are the number of nodes, links and wavelengths in the network, respectively. The second version of the problem is shown to be NP-hard, instead an approximation algorithm is devised which delivers a solution within K times of the optimum, where K>=2.
9404152
Learning multi-label scene classification
In classic pattern recognition problems, classes are mutually exclusive by definition. Classification errors occur when the classes overlap in the feature space. We examine a different situation, occurring when the classes are, by definition, not mutually exclusive. Such problems arise in semantic scene and document classification and in medical diagnosis. We present a framework to handle such problems and apply it to the problem of semantic scene classification, where a natural scene may contain multiple objects such that the scene can be described by multiple class labels (e.g., a field scene with a mountain in the background). Such a problem poses challenges to the classic pattern recognition paradigm and demands a different treatment. We discuss approaches for training and testing in this scenario and introduce new metrics for evaluating individual examples, class recall and precision, and overall accuracy. Experiments show that our methods are suitable for scene classification; furthermore, our work appears to generalize to other classification problems of the same nature.
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.