1919911
Robust rate adaptation for 802.11 wireless networks
Rate adaptation is a mechanism unspecified by the 802.11 standards, yet critical to the system performance by exploiting the multi-rate capability at the physical layer.I n this paper, we conduct a systematic and experimental study on rate adaptation over 802.11 wireless networks. Our main contributions are two-fold. First, we critique five design guidelines adopted by most existing algorithms. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incur significant performance penalty in certain scenarios. The fundamental challenge is that rate adaptation must accurately estimate the channel condition despite the presence of various dynamics caused by fading, mobility and hidden terminals. Second, we design and implement a new Robust Rate Adaptation Algorithm (RRAA)that addresses the above challenge. RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, and an adaptive RTS filter to prevent collision losses from triggering rate decrease. Our extensive experiments have shown that RRAA outperforms three well-known rate adaptation solutions (ARF, AARF, and SampleRate) in all tested scenarios, with throughput improvement up to 143%.
16187298
DIRAC: a software-based wireless router system
Routers are expected to play an important role in the IP-based wireless data network. Although a substantial number of techniques have been proposed to improve wireless network performance under dynamic wireless channel conditions and host mobility, a system support framework is still missing. In this paper, we describe DIRAC, a software-based router system that is designed for wireless networks to facilitate the implementation and evaluation of various channel-adaptive and mobility-aware protocols. DIRAC adopts a distributed architecture that is composed of two parts: a Router Core (RC) shared by the wireless subnets, and a Router Agent (RA) at each access point/base station. RAs expose wireless link-layer information to the RC and enforce the control commands issued by the RC. This approach allows the router to make adaptive decisions based on link-layer information feedback. It also permits the router to enforce its policies (e.g., policing) more effectively through underlying link-layer mechanisms. As showcases, we implement under DIRAC the prototypes of three wireless network services: link-layer assisted fast handover, channel-adaptive scheduling, and link-layer enforced policing. Our implementation and experiments show that our distributed wireless router provides a flexible framework, which enables advanced network-layer wireless services that are adaptive to channel conditions and host mobility.
619246
The impact of multihop wireless channel on TCP performance
This paper studies TCP performance in a stationary multihop wireless network using IEEE 802.11 for channel access control. We first show that, given a specific network topology and flow patterns, there exists an optimal window size W* at which TCP achieves the highest throughput via maximum spatial reuse of the shared wireless channel. However, TCP grows its window size much larger than W* leading to throughput reduction. We then explain the TCP throughput decrease using our observations and analysis of the packet loss in an overloaded multihop wireless network. We find out that the network overload is typically first signified by packet drops due to wireless link-layer contention, rather than buffer overflow-induced losses observed in the wired Internet. As the offered load increases, the probability of packet drops due to link contention also increases, and eventually saturates. Unfortunately the link-layer drop probability is insufficient to keep the TCP window size around W'*. We model and analyze the link contention behavior, based on which we propose link RED that fine-tunes the link-layer packet dropping probability to stabilize the TCP window size around W*. We further devise adaptive pacing to better coordinate channel access along the packet forwarding path. Our simulations demonstrate 5 to 30 percent improvement of TCP throughput using the proposed two techniques.
23906830
PEAS: a robust energy conserving protocol for long-lived sensor networks
Small, inexpensive sensors with limited memory, computing power and short battery lifetimes are turning into reality. Due to adverse conditions such as high noise levels, extreme humidity or temperatures, or even destructions from unfriendly entities, sensor node failures may become norms rather than exceptions in real environments. To be practical, sensor networks must last for much longer times than that of individual nodes, and have yet to be robust against potentially frequent node failures. This paper presents the design of PEAS, a simple protocol that can build a long-lived sensor network and maintain robust operations using large quantities of economical, short-lived sensor nodes. PEAS extends system functioning time by keeping only a necessary set of sensors working and putting the rest into sleep mode. Sleeping ones wake up now and then, probing the local environment and replacing failed ones. The sleeping periods are self-adjusted dynamically, so as to keep the sensors' wakeup rate roughly constant, thus adapting to high node densities.
11410811
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair-scheduling algorithms because of two unique characteristics of wireless media: (1) bursty channel errors and (2) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however, a base station has only a limited knowledge of the arrival processes of uplink flows. We propose a new model for wireless fair-scheduling based on an adaptation of fluid fair queueing (FFQ) to handle location-dependent error bursts. We describe an ideal wireless fair-scheduling algorithm which provides a packetized implementation of the fluid mode, while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless FFQ model.
1236934
A Packet Scheduling Approach to QoS Support in Multihop Wireless Networks
Providing packet-level quality of service (QoS) is critical to support both rate-sensitive and delay-sensitive applications in bandwidth-constrained, shared-channel, multihop wireless networks. Packet scheduling has been a very popular paradigm to ensure minimum throughput and bounded delay access for packet flows. This work describes a packet scheduling approach to QoS provisioning in multihop wireless networks. Besides minimum throughput and delay bounds for each flow, our scheduling disciplines seek to achieve fair and maximum allocation of the shared wireless channel bandwidth. However, these two criteria can potentially be in conflict in a generic-topology multihop wireless network where a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth is possible. In this paper, we propose a new scheduling model that addresses this conflict. The main results of this paper are the following: (a) a two-tier service model that provides a minimum “fair” allocation of the channel bandwidth for each packet flow and additionally maximizes spatial reuse of bandwidth, (b) an ideal centralized packet scheduling algorithm that realizes the above service model, and (c) a practical distributed backoff-based channel contention mechanism that approximates the ideal service within the framework of the CSMA/CA protocol.
321115
Compressed pattern matching in DNA sequences
We propose derivative Boyer-Moore (d-BM), a new compressed pattern matching algorithm in DNA sequences. This algorithm is based on the Boyer-Moore method, which is one of the most popular string matching algorithms. In this approach, we compress both DNA sequences and patterns by using two bits to represent each A, T, C, G character. Experiments indicate that this compressed pattern matching algorithm searches long DNA patterns (length > 50) more than 10 times faster than the exact match routine of the software package Agrep, which is known as the fastest pattern matching tool. Moreover, compression of DNA sequences by this method gives a guaranteed space saving of 75%. In part the enhanced speed of the algorithm is due to the increased efficiency of the Boyer-Moore method resulting from an increase in alphabet size from 4 to 256.
11276211
PDC: Pattern discovery with confidence in DNA sequences
Pattern discovery in DNA sequences is one of the most challenging tasks in molecular biology and computer science. The main goal of pattern discovery in DNA sequences is to identify sequences of important biological function hidden in the huge amounts of genomic sequences. Several methods and techniques have been proposed and implemented in this field. However, in order to reduce computational time and complexity, most of them either focus on finding short DNA patterns or require explicit specification of pattern lengths in advance. Scientists need to find longer patterns without specifying pattern lengths in advance and still have good performance.In this paper, we propose a pattern discovery algorithm called Pattern Discovery with Confidence (PDC). Based on biological studies, we propose a new measurement system that can identify overrepresented patterns inside DNA sequences. Using this measurement, PDC algorithm can narrow the search space by checking dependency along the pattern, thus extending the pattern as long as possible without the need to restrict or specify the length of a pattern in advance. Experimental tests demonstrate that this approach can find long, interesting patterns within a reasonable computation time.
35964038
Learning Engineering Models with the Minimum Description Length Principle
This paper discusses discovery of mathematical models from engineering data sets. KEDS, a Knowledge-based Equation Discovery System, identifies several potentially overlapping regions in the problem space, each associated with an equation of different complexity and accuracy. The minimum description length principle, together with the KEDS algorithm, is used to guide the partitioning of the problem space. The KEDSMDL algorithm has been tested on discovering models for predicting the performance efficiencies of an internal combustion engine.
7682350
Incremental genetic K-means algorithm and its application in gene expression data analysis
BackgroundIn recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.ResultsIn this paper, we propose a new clustering algorithm, Incremental Genetic K-means Algorithm (IGKA). IGKA is an extension to our previously proposed clustering algorithm, the Fast Genetic K-means Algorithm (FGKA). IGKA outperforms FGKA when the mutation probability is small. The main idea of IGKA is to calculate the objective value Total Within-Cluster Variation (TWCV) and to cluster centroids incrementally whenever the mutation probability is small. IGKA inherits the salient feature of FGKA of always converging to the global optimum. C program is freely available at http://database.cs.wayne.edu/proj/FGKA/index.htm.ConclusionsOur experiments indicate that, while the IGKA algorithm has a convergence pattern similar to FGKA, it has a better time performance when the mutation probability decreases to some point. Finally, we used IGKA to cluster a yeast dataset and found that it increased the enrichment of genes of similar function within the cluster.
11393308
Computational Methods for Analysis of Cryptic Recombination in the Performance of Genomic Recombination Detection Software
The detection of recombination from DNA sequences is relevant to the understanding of evolutionary and molecular genetics. While programs such as GENECONV have been identified as detecting recombination more reliably than others, previous studies have not analyzed how many recombinations they fail to detect. We develop a method for testing how often such programs fail to identify recombinations and how detectability is affected by pairwise differences among the parental sequences. Recombination of sequences having a range of average pairwise differences (APD) is simulated by a stochastic method, and then the history of recombinations is compared to the recombinations identified by GENECONV. With high APD, GENECONV fails to detect ~50% of recombinations; while at a more typical intraspecies APD of 1% to 2%, >70% of recombinations are undetected. Quantitative results suggest corrections for estimating recombination rates more accurately and methods to detect evidence of recombination more consistently.