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In order to prevent erroneous ACK responses due to delay variation, the receiver waits for a time before returning an ACK response if dwin < ack count. As per RFC 2581 [19], in the case of out-of-order segments an ACK response is immediately prompted, but otherwise the receiver waits for a time period Ti before responding with an ACK. This effective timeout interval is calculated with a timeout tolerance factor, , > 0 as follows, where i is calculated by Eq. (10.1): Ti = (2 + ) i (10.2)

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After the assignment has been calculated, the leader MULE communicates to all the other MULEs the nodes they have been given to serve r Data Collection In the data collection phase the MULEs start their journey along their routes, looking for data At this time the nodes do not know the MULE to which they are assigned; and hence when they hear the MULE beacon, they respond with their packet They will receive an acknowledgment only from the MULE that is supposed to collect their packets A node records this information, and in the future it will respond only to its assigned MULE Simulation results are shown in reference 33 that demonstrate how effective this algorithm is in distributing nodes to MULEs 105.

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By identifying the five-month cycle low count and looking at the historical price record, I was able to make a keen observation and share it with my fellow investors A good plan based on good analysis does pay off! This book was not intended to go much into cycle studies However, the amazing repetitiveness of another timing cycle is worth mentioning The equities market seems to respond to what I identified as an 11-week cycle low back in late 2001 The relevance of the 11-week cycle is that it is approximately 55 trading days the number 55 is a Fibonacci series number, and it is approximately half or 50 percent of the five-month cycle The 50 percent Fibonacci ratio number also interacts as a reference with the 11-week cycle So there is a connection with the Fibonacci series and ratio numbers.

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There is also a mechanism in the DAA method to account for variable, instead of xed, increases in the dynamic window. The speed increase factor, , with 0 < < 1. If the maxdwin is a status indicator that turns true when the maximum possible value for the dynamic ACK window has been reached (by default set to 4 segments), then the dynamic ACK window s growth is set to dwin = dwin + dwin + 1 if maxdwin=false, otherwise (10.3)

2 Multihop Routing and Controlled Sink Mobility We consider here the case of a mobile sink traveling through the network and receiving data at its current location via multihop routing We start by describing in detail a solution where the sink moves according to the current network condition (controlled mobility), with the aim of balancing energy consumption among the network nodes and thus prolonging the network lifetime This solution, presented in references 9 and 10, illustrates two fundamental research steps: mathematical modeling (for the centralized determination of an optimal solution) and the de nition of distributed heuristics A mathematical model is de ned as follows: Taking as input realistic parameters such as the cost of route setup,.

Equation (10.3) allows the receiver to respond immediately with ACKs in the case when the TCP sender is in the Slowstart phase and each ACK increases its congestion window by a single segment. If ACKs were delayed during this phase the sender would not receive enough ACKs to increase its sending rate effectively. Essentially, the maxdwin parameter signi es (at the receiver) when the Slowstart phase (at the sender) is over. Once the maxdwin is reached once, then this mechanism is not activated again for the same connection. Hence, this facility is intended for short le transfers. The DAA method has been evaluated on chain and grid topologies of varying length and different number of ows [7]. On chain topologies of up to 8 hops and 20 ows, the method increases TCP NewReno throughput up to 50% over its regular version and 30% over the DDA method described in Section 10.4.2. In particular, it is noted that as the number of concurrent ows increases, the DAA method becomes increasingly effective. On grid topologies, taking into account 3 and 6 cross traf c sources, the performance improvement is of the same magnitude, but the difference diminishes against optimized (with respect to maximum congestion window size) Vegas and SACK agents. The method does not lead to a discernible performance advantage in the case of short-lived ows. From an implementation perspective the DAA method is an end-to-end sender/receiver modi cation. The sender needs to be tweaked with respect to initial cwnd size, and the receiver needs to implement the ACK dynamic window.

java ean 13 reader

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java ean 13 reader

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java ean 13 reader