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only a small subset of all available paths is in use at any one time The reduction of routing control overhead remains the key motivation behind the design of on-demand protocols because a high overhead usually has a signi cant performance impact in low-bandwidth wireless links However, setting up a path on demand introduces route acquisition latency because a route discovery process must be performed to set up a new path before a packet can be transmitted The route acquisition latency may lead to a large delay for the initial packets awaiting to be sent when the route is being set up Examples of reactive routing protocols are the temporally ordered routing algorithm (TORA) [36], AODV, and DSR In a multihop wireless network with low mobility, proactive routing protocols may perform better than reactive routing protocols because there will be little link breakage.

15

Thus, routing control updates can be sent less frequently while retaining the advantage of minimum route acquisition latency As illustrated in Figure 64, the bene t of proactive routing protocol is especially obvious with a high new traf c ow arrival rate, where each new ow may cause reactive routing protocols to initiate a separate on-demand path setup Hybrid routing protocols try to combine the advantages of both proactive and reactive routing protocols In one concept, called multiscoping, information from a nearby node will be used more frequently and be more valuable compared to information from a distant node As such, a hybrid routing protocol may proactively maintain a routing table at each node for all paths within a limited-size local neighborhood while setting up routes reactively for destination nodes outside the local neighborhood An example of a hybrid protocol is the zone routing protocol (ZRP) [38].

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for (Enumeration e = htablekeys(); ehasMoreElements();) 212 { 213 /* The enetElement() returns an Object with which hkey is initialized */ 214 Object hkey = enextElement(); 215 /* The vitemindexOf() method returns an integer value which is the index of the 216 Object in this vectorThe argument to this method is a String value which is the 217 item code and indexitem is initialized with this integer value */ 218 int indexitem = vitemindexOf((String)hkey); 219 /* htableget(hkey) method returns the object associated with this key 220 in the hashtable So, it returns the quantity ordered for this item code */ 221 int quan = IntegerparseInt((String)htableget(hkey)); 222 /* vrateelementAt() returns an Object This object is the rate of the item whose index 223 value is indexitem This is typecast to String parseInt method parses this string 224.

In ZRP, each node proactively maintains all paths for a neighborhood of k hops Within the neighborhood, a path is readily available when a node wants to send a packet When a node wants to send a packet to a destination outside the k-hop neighborhood, it sends a route request to its border nodes, which are nodes at the edge of the neighborhood These border nodes will know if the destination node is within their own k-hop neighborhood and decide either to reply to the route request or forward.

2.3.3.1 Channel Capacity of the CSI-Known Case The channel matrix H can be decomposed by using singular-value decomposition (SVD [9]) as follows:

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into int value and initializes to rate */ 225 int rate = IntegerparseInt((String)vrateelementAt(indexitem)); 226 /* The total will contain the amount of the each item ordered which is quan*rate 227 (Quantity*Rate) */ 228 String total = new String(); 229 total = totalvalueOf(quan*rate);.

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