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3) Suppose the information portion of a packet (D in Figure 52-1 contains 10 bytes consisting of the 8bit unsigned binary representation of the integers 0 through 9 Compute the Internet checksum for this ata 4) Consider the 4-bit generator, G shown in Figure 52-5, and suppose that D has the value 10101010 What is the value of R 5) Consider the single sender CDMA example in Figure 53-4 What would be the sender's output (for the two data bits shown) if the senders CDMA code were (1, -1, 1, -1, 1, -1, 1, -1) 6) Consider sender 2 in Figure 53-5 What is the sender's output to the channel (before it is added to the signal from sender 1), Zi,m 2 7) Suppose that the receiver in Figure 53-5 wanted to receive the data being sent by sender 2 Show (by calculation), that the receiver is indeed able to recover sender 2's data from the aggregate channel signalby using sender 2's code 8) In section 53, we provided an outline of the derivation of the efficiency of slotted ALOHA In this problem we''ll complete the derivation a) Recall that when there are N active nodes the efficiency of slotted ALOHA is Np(1-p)N-1 Find the value of p that maximizes this expression b) Using the value of p found in part (a), find the efficiency of slotted ALOHA by letting N approach infinity Hint: (1 - 1/N)N approches 1/e as N approaches infinity 9) Show that the maximum efficiency of pure Aloha is 1/(2e) Note: this problem is easy if you have completed the problem above! 10) Graph the efficiency of slotted ALOHA and pure ALOHA as a function of p for N=100 11) Consider a broadcast channel with N nodes and a transmission rate of R bps Suppose the broacast channel uses polling (with an additional polling node) for multiple access Suppose the amount of time from when a node completes transmission until the subsequent node is permitted to transmit (ie, the polling delay) is tpoll Suppose that within a polling round, a given node is allowed to transmit at most Q bits What is the maximum throughput of the broadcast channel 12) Consider three LANs interconnected by two routers, as shown in the diagram below a) Redraw the diagram to include adapters b) Assign IP addresses to all of the interfaces For LAN 1 use addresses of the form 111111111.

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the piece by a new one and letting the piece operate for the present day A preventive replacement takes one day A new piece has working condition i = 1 A piece whose present working condition is i has the next day working condition j with known probability qij where qij = 0 for j < i The following replacement rule is used The current piece is only replaced by a new one when ts working condition is greater than the critical value m, where m is a given integer with 1 m < N (a) De ne an appropriate Markov chain and specify its one-step transition probabilities (b) Explain how to calculate the long-run fraction of days the equipment is inoperative and the fraction of replacements occurring in the failure state N 315 Consider a stochastically failing piece of equipment with two identical components that operate independently of each other The lifetime in days of each component has a discrete probability distribution {pj , j = 1, , M} A component in the failure state at the beginning of a day is replaced instantaneously It may be economical to preventively replace the other working component at the same time the failed component has to be replaced The cost of replacing only one component is K1 , while the cost of replacing simultaneously both components equals K2 with 0 < K2 < 2K1 The control rule is as follows Replace a component upon failure or upon reaching the age of R days, whichever occurs rst If a component is replaced and the other component is still working, the other component is preventively replaced when it has been in use for r or more days The parameters r and R are given integers with 1 r < R (a) De ne an appropriate Markov chain and specify its one-step transition probabilities (b) How can you calculate the long-run average cost per day 316 A transmission channel transmits messages one at a time, and transmission of a message can only start at the beginning of a time slot The time slots have unit length and the transmission time of a message is one time slot However, each transmission can fail with some probability f A failed transmission is tried again at the beginning of the next time slot The numbers of new messages arriving during the time slots are independent random variables with a common discrete distribution {ak , k = 0, 1, } Newly arriving messages are temporarily stored in a buffer of ample capacity It is assumed that the average arrival rate of new messages is smaller than the average number of attempts needed to transmit a message successfully, that is, k kak < 1/f The goal is to nd the long-run average throughput per time unit (a) De ne an appropriate Markov chain with a one-dimensional state space and specify its one-step transition probabilities (b) Can you give a recursive algorithm for the computation of the state probabilities Express the average throughput in terms of the state probabilities 317 Messages arrive at a transmission channel according to a Poisson process with rate The channel can transmit only one message at a time and a new transmission can only start at the beginnings of the time slots t = 1, 2, The transmission time of a message is one time slot The following access-control rule is used The gate is closed for newly arriving messages when the number of messages awaiting transmission has reached the level R and is opened again when the number of messages awaiting transmission has dropped to the level r, where the parameters r and R are given integers with 0 r < R The goal is to study the long-run fraction of lost messages as function of r and R (a) De ne an appropriate Markov chain and specify its one-step transition probabilities (b) Show how to calculate the long-run fraction of lost messages 318 In Example 351 we have determined for the GI /M/1 queue the customer-average probability j denoting the long-run fraction of customers who nd j other customers present upon arrival Denote by the time-average probability pj the long-run fraction of time that j customers are present for j = 0, 1, Use Theorem 333 and Lemma 114.

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Earlier in this chapter we discussed image shearing It can be thought of as anchoring one corner of a rectangular region and stretching the opposite corner horizontally, vertically, or in both directions Shearing colors is the same process, but here the object is the color instead of the image Color shearing increases or decreases a color component by an amount proportional to another color component For example, consider the transformation in which the red component is increased by one half the value of the blue component Under such a transformation, the color (02, 05, 1) would become ( 07, 05, 1) The new red component is 02 (05)(1) = 07 The following color matrix is used to shear image colors.float[][] ptsArray = { new float[] {1, 0, 0, 0, 0}, new float[] {0, 1, 0, 0, 0}, new float[] {50f, 0, 1, 0, 0}, new float[] {0, 0, 0, 1, 0}, new float[] {0, 0, 0, 0, 1}}; ColorMatrix clrMatrix = new ColorMatrix(ptsArray . Drawing Data Matrix In Java Using Barcode printer for Java .Related: VB.NET UPC-E Generating , Generate Code 128 Java , Generate Code 128 .NET WinForms

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