New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

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118 CHAPTER 5. COMPUTER SCIENCE GRID STRATEGIES Figure 5.3.5: Comparing basic FTP to GridFTP. Shown is the time needed for the transfer of a 1GB file over the internet at different times of a day. GridFTP solves most of these problems and extends the FTP approach by many useful features. E.g., by using parallel connections it is able to speed up transmission throughput as shown in Figure 5.3.5. But in order to use it all machines have to install the GlobusToolkit - which is definitively not desirable (see section 5.1.3). To circumvent these problems we have developed an Internet-socked based client/server approach that allows to exchange files between two machines within the QAD Grid obeying the authentication and authorization schemas described above. A socket is one software endpoint of a bidirectional communication link between two programs in a network. Typically this would be a server program and one or more client programs communicating via a dedicated port (channel). In the QAD Grid each platform server runs at least one data service that accepts client connections and sends or receives data. For a worker to get a file the following process must be successfully finished: 1. The worker queries the platform server by a database query to get IP addresses of available data services hosting the requested file (identified by the unique file ID) ordered by their local machine load level. 2. The worker measures the round-trip time (RTT) of the first five IP addresses of this list. The RTT is the time a data packet needs to travel from the worker to the service and back. 3. The worker establishes a secure socket connection (see section Secure Communication below) to the data service with the smallest RTT value and requests the file. 4. The data service checks the authentication and authorization of the worker and rejects the query if one fails. Authentication is done in the following way: the worker sends its account information (user id and password) and certificate to the data service. The data service logs into the platform server’s database using the worker’s credentials and requests the certificate of this worker. Authorization is successful if the database login is successful and both certificate are identical. 5. If the previous step succeeds the file is send to the worker. If the file is not marked as sensitive the connection is no longer encrypted to avoid encryption overhead. If sensitive data is to be send, first a 256bit key is sent to the worker and then encryption is changed from RSA (asymmetric) to Rijndael AES-256 (symmetric Advanced Encryption Standard, see
5.3. QAD GRID PLATFORM SERVER 119 (Daemen and Rijmen, 1999, 2002)) encryption which is about 1000fold faster with respect to encryption and decryption. The latter step - the fast transfer of large volumes of data - mainly relies on the network transport protocol used. However, the dominant network transport protocol of today, TCP (Transmission Control Protocol), is tuned for yesterdays wide area networks (WAN). The slow response of TCP in fast long distance networks leaves sizeable unused bandwidth in such networks. As an example, if one copies a big file (bigger than 100MB say) between two computers in a country-wide 100Mbit network the transfer rate would be about 5Mbit/s (Megabyte per second, meaning that about 95% of the bandwidth are unused. To understand this, one has to know that TCP sends data in small packages. At the start of a connection, TCP determines the size of a so-called congestion window to determine how many packets are send at one time. The maximum congestion window is related to the amount of buffer space that the OS allocates for the connection. To achieve maximum throughput, it is critical to use an optimal buffer size for each individual connection. Obviously, the larger the size of this congestion window, the higher the throughput. However, if set too large, the sender can overrun the receiver, which will cause packets drop on the receiver side which have to be re-sent. For the following example to the calculation of optimal TCP buffer size we assume that there is no network congestion (no packet loss) and the connection quality stays the same over connection life-time. Then, network throughput is directly related to TCP buffer size (BS) and the network latency (NL), which is the amount of time for a packet to traverse the network. Let us further assume that network latency in a typical connection between two computers over a 100Mbit WAN in, say, Berlin is about 40ms. We know that Windows XP has a default TCP buffer size of 17.520 bytes. The maximum possible throughput (T P ) is calculated by T P = BS = 17520bytes/0.04sec = 0.44MByte = 3.5Mbit NL sec sec If you would increase the TCP buffer size to 65KByte (as e.g. Mac OS does) it would get a bit better but still not close to the optimal value of 100Mbit: T P = BS = 65936bytes/0.04sec = 1.6MByte = 13Mbit NL sec sec It is a rule of thumb that a near optimal TCP buffer size (BSopt) for a particular connection is double the value for delay (D) times bandwidth (BW ). By using a program like “ping” one can measure the round trip time (RT T ) a data package needs to travel to the destination computer. The RT T is twice the delay, so we have BSopt = 2 · D · BW = RT T · BW If we assume a RTT of 80ms for the above connection this means that the TCP buffer should be Figure 5.3.6: This graph shows how the quality of a particular connection changes between 8am and 2pm. The y-axis shows “Bandwidth · delay”, sampled every 20 seconds. (Taken from (Thulasidasan et al., 2003).)
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New Statistical Algorithms for the
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Contents Acknowledgments . . . . .
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New Statistical Algorithms for the
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Extended Abstract English Version M
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German Version Das Gebiet der Prote
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Chapter 1 Introduction and Survey 1
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1.2. GOALS, OBJECTIVES AND TASKS 7
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1.2. GOALS, OBJECTIVES AND TASKS 9
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Chapter 2 Preliminaries 2.1 Topic O
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2.1. TOPIC OVERVIEW 13 Figure 2.1.1
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2.1. TOPIC OVERVIEW 15 completeness
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2.2. AN EXAMPLE 17 (a) Opera A (b)
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2.2. AN EXAMPLE 19 Figure 2.2.6: Tw
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2.2. AN EXAMPLE 21 successes. We ca
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Chapter 3 Mathematical Modeling and
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3.2. INTRODUCTION TO MALDI TOF MS 2
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3.3. PREPROCESSING 31 mix (external
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3.3. PREPROCESSING 33 Figure 3.3.5:
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3.3. PREPROCESSING 35 Figure 3.3.7:
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3.4. HIGHLY SENSITIVE PEAK DETECTIO
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3.5. PEAK DETECTION IN 2D MAPS 43
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3.6. PEAK REGISTRATION (ALIGNMENT)
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3.7. IDENTIFYING POTENTIAL FEATURES
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3.8. EXTRACTING FINGERPRINTS 57 Fig
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3.8. EXTRACTING FINGERPRINTS 59 FID
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3.8. EXTRACTING FINGERPRINTS 61 Dim
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3.9. COMPLEXITY ANALYSIS 63 3.9 Com
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Chapter 4 (Bio-)Medical Application
Page 73 and 74: 4.1. DATA USED 67 4.1.2 Serum Data
Page 75 and 76: 4.2. STATISTICAL REMARKS 69 1. Vali
Page 77 and 78: 4.2. STATISTICAL REMARKS 71 Molar v
Page 79 and 80: 4.2. STATISTICAL REMARKS 73 � Fir
Page 81 and 82: 4.2. STATISTICAL REMARKS 75 Let ˆ
Page 83 and 84: 4.2. STATISTICAL REMARKS 77 the boo
Page 85 and 86: 4.3. STUDY RESULTS 79 Figure 4.3.3:
Page 87 and 88: 4.3. STUDY RESULTS 81 Figure 4.3.4:
Page 89 and 90: 4.3. STUDY RESULTS 83 � kNN (gen.
Page 91 and 92: 4.3. STUDY RESULTS 85 d(x, θi) =
Page 93 and 94: 4.3. STUDY RESULTS 87 pairs of obje
Page 95 and 96: 4.3. STUDY RESULTS 89 � “Peptid
Page 97 and 98: 4.4. IDENTIFICATION OF PROTEOMIC FI
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Page 109 and 110: Chapter 5 Computer Science Grid Str
Page 111 and 112: 5.1. INTRODUCTION 105 � A node is
Page 113 and 114: 5.1. INTRODUCTION 107 of and config
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Page 117 and 118: 5.2. THE QUASI AD-HOC (QAD) GRID 11
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Page 141 and 142: 5.4. QAD GRID WORKER 135 Checkpoint
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Page 165 and 166: 6.2. CASE STUDIES 159 The peak pick
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Page 169 and 170: 6.2. CASE STUDIES 163 Approach Base
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Page 173 and 174: Chapter 7 Related Work In this chap
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Chapter 8 Conclusion and Future Dir
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8.3. FROM BIOMARKERS TO BIOPRINTS 1
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Appendix A Implementation Details T
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Appendix B Curriculum Vitae Name Ti
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References Aebersold, R. and Mann,
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REFERENCES 179 Breiman, L. (2001).
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REFERENCES 181 Downard, K. M. and M
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REFERENCES 183 Gillette, M. A., Man
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REFERENCES 185 Huyghe, E., Muller,
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REFERENCES 187 Kuijpens, J. L. P.,
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REFERENCES 189 McLachlan, S. M. and
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REFERENCES 191 Platt, J. C. (1999).
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REFERENCES 193 Stone, M. (1974). Cr
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REFERENCES 195 Washburn, M. P., Wol
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