1446823
An FDD wideband CDMA MAC protocol for wireless multimedia networks
A medium access control (MAC) protocol is developed for wireless multimedia networks based on frequency division duplex (FDD) wideband code division multiple access (CDMA). In this protocol, the received power levels of simultaneously transmitting users are controlled by a minimum-power allocation algorithm such that the heterogeneous bit error rates (BERs) of multimedia traffic are guaranteed. With minimum-power allocation, a multimedia wideband CDMA generalized processor sharing (GPS) scheduling scheme is proposed. It provides fair queueing to multimedia traffic with different QoS constraints. It also takes into account the limited number of code channels for each user and the variable system capacity due to interference experienced by users in a CDMA network. The admission of real-time connections is determined by a new effective bandwidth connection admission control (CAC) algorithm in which the minimum-power allocation is also considered. Simulation results show that the new MAC protocol guarantees QoS requirements of both real-time and nonreal-time traffic in an FDD wideband CDMA network.
9104202
Rate-Adaptive Framing for Interfered Wireless Networks
The majority of existing wireless rate controls are based on the implicit assumption that frames are corrupted due to the random, arbitrary environmental and thermal noises. They generally reduce the channel rate on frame losses, trading lower efficiency in frequency band utilization for more robust modulation so that the current noise level may be tolerable. In highly interfered wireless networks where frames are lost mainly due to interference from other wireless transceivers, simply reducing the channel rate prolongs the frame transmission time and therefore aggravates frame loss ratio. This positive feedback in the rate control loop quickly diverges the interfered transceivers into a suboptimal channel rate and drives the network into a state with high interference. In the worst case, interfered transceivers can be starved. In this paper we present RAF, the rate-adaptive framing that jointly controls the channel rate and frame size according to the observed interference patterns and noise level at the receiver. Based on the inputs from physical layer carrier sense, the receiver derives the optimal channel rate and frame size that maximize throughput, and informs the transmitter of such optimal configuration in a few bits in the per-frame acknowledgement. Through intensive simulations we show that RAF consistently outperforms ARF, RBAR, and OAR in all simulated scenarios.
11332751
A capacity acquisition protocol for channel reservation in CDMA networks
In this paper, a capacity acquisition protocol is proposed for channel reservation in CDMA networks. Under this protocol, a cell is virtually divided into three regions (i.e., inner region, forced handoff region, and active handoff region). A new call in the active handoff region works in soft handoff mode upon its admission, while a new call in the inner and forced handoff regions works in single mode. However, in the forced handoff region, calls working in single mode can be forced into soft handoff mode, when extra capacity is needed by soft handoff calls. As a result, no explicit channel reservation is required before a call enters soft handoff. By adjusting the size of the forced handoff region, the capacity acquisition can adapt to traffic load and guarantee a desired call dropping probability. To evaluate the capacity acquisition protocol, an analytical model is derived and is also validated through computer simulations. Numeric results illustrate that the capacity acquisition protocol significantly reduces the call dropping probability.
3114897
Multi-graph enabled active learning for multimodal web image retrieval
In this paper, we propose a multimodal Web image retrieval technique based on multi-graph enabled active learning. The main goal is to leverage the heterogeneous data on the Web to improve retrieval precision. Three graphs are constructed on images' content features, textual annotations and hyperlinks respectively, namely Content-Graph, Text-Graph and Link-Graph, which provide complimentary information on the images. By analyzing the three graphs, a training dataset is automatically created and transductive learning is enabled. The transductive learner is a multi-graph based classifier, which simultaneously solves the learning problem and the problem of combining heterogeneous data. This proposed approach, overall, tackles the problem of unsupervised active learning on Web graph. Although the proposed approach is discussed in the context of WWW image retrieval, it can be applied to other domains. The experimental results show the effectiveness of our approach.
1347401
Decentralized utilization control in distributed real-time systems
Many real-time systems must control their CPU utilizations in order to meet end-to-end deadlines and prevent overload. Utilization control is particularly challenging in distributed real-time systems with highly unpredictable workloads and a large number of end-to-end tasks and processors. This paper presents the decentralized end-to-end utilization control (DEUCON) algorithm that can dynamically enforce desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier work, DEUCON features a novel decentralized control structure that only requires localized coordination among neighbor processors. DEUCON is systematically designed based on recent advances in distributed model predictive control theory. Both control-theoretic analysis and simulations show that DEUCON can provide robust utilization guarantees and maintain global system stability despite severe variations in task execution times. Furthermore, DEUCON can effectively distribute the computation and communication cost to different processors and tolerate considerable communication delay between local controllers. Our results indicate that DEUCON can provide scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments
3433910
Residual-Based Measurement of Peer and Link Lifetimes in Gnutella Networks
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent tradeoff between overhead and accuracy, which does not allow any fundamental improvement to the method. Instead, we propose a completely different approach for sampling user dynamics that keeps track of only residual lifetimes of peers and uses a simple renewal-process model to recover the actual lifetimes from the observed residuals. Our analysis indicates that for reasonably large systems, the proposed method can reduce bandwidth consumption by several orders of magnitude compared to prior approaches while simultaneously achieving higher accuracy. We finish the paper by implementing a two-tier Gnutella network crawler equipped with the proposed sampling method and obtain the distribution of ultrapeer lifetimes in a network of 6.4 million users and 60 million links. Our experimental results show that ultrapeer lifetimes are Pareto with shape a alpha ap 1.1; however, link lifetimes exhibit much lighter tails with alpha ap 1.9.
6284709
Satisfiability of Quantitative Temporal Constraints with Multiple Granularities
Most work on temporal constraints has ignored the subtleties involved in dealing with multiple time granularities. This paper considers a constraint satisfaction problem (CSP) where binary quantitative constraints in terms of different time granularities can be specified on a set of variables, and unary constraints are allowed to limit the domain of variables. Such a CSP cannot be trivially reduced to one of the known CSP problems. The main result of the paper is a complete algorithm for checking consistency and finding a solution. The complexity of the algorithm is studied in the paper under different assumptions about the granularities involved in the CSP, and a second algorithm is proposed to improve the efficiency of the backtracking process needed to obtain all the solutions of the CSP. 
 
The work of Wang and Jajodia was partially supported by the National Science Foundation under the grant IRI-9633541.
631362
DEUCON: Decentralized End-to-End Utilization Control for Distributed Real-Time Systems
Many real-time systems must control their CPU utilizations in order to meet end-to-end deadlines and prevent overload. Utilization control is particularly challenging in distributed real-time systems with highly unpredictable workloads and a large number of end-to-end tasks and processors. This paper presents the decentralized end-to-end utilization control (DEUCON) algorithm, which can dynamically enforce the desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier works, DEUCON features a novel decentralized control structure that requires only localized coordination among neighbor processors. DEUCON is systematically designed based on advances in distributed model predictive control theory. Both control-theoretic analysis and simulations show that DEUCON can provide robust utilization guarantees and maintain global system stability despite severe variations in task execution times. Furthermore, DEUCON can effectively distribute the computation and communication cost to different processors and tolerate considerable communication delay between local controllers. Our results indicate that DEUCON can provide a scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments.