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the cost f (A) = 1/g(A) and the estimated cost of the route from A to D Node B has knowledge of the cost f (A) of each of its neighbors It is assumed that the cost of the remaining nodes on the path between A and D is proportional to the number of hops between A and D The number of hops is proportional to the distance between A and D and is inversely proportional to radius R Thus, the cost can be represented as ts/R, where different values of t have been investigated The cost definitions, c(A) = f (A)ts/R and c(A) = f (A) + ts/R are suggested for investigation, since it is not clear which will give the best results Then, power and cost factors are merged into a single routing algorithm Merging based on the product or sum of the two metrics is proposed.

What You Can Do Validate data entry If you have form fields on your page, you can make sure they contain the right kind of data before re-submitting them to the server How does this save server processing First, your server doesn t have to do the validation Second, data will only be submitted once, when it is complete, saving your server the trouble of having to serve the same page (with error messages on it) multiple times to the same client Rearrange data on the page This is new to HTML 4! If you are running a page that serves data from a database, you can save your server the trouble of having to serve the same data multiple times, sorted differently, by taking advantage of client-side processing.

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In the first case, the power cost of sending a message from B to a neighbor A is represented as power cost(B, A) = f (A)u(r), where r is equal to the distance between A and B The power cost algorithm can find the optimal power cost by applying the single-source, shortest weighted path Dijkstra s algorithm In the second case, it may be represented as power cost(A, B) = u(r) + f (A), with suitable values for and The power-cost-efficient routing algorithm can be described as follows Let A be the neighbor of B that minimizes pc(B, A) = power cost(B, A) + v(s)f (A), where s = 0 for D, if D is a neighbor of B This algorithm is referred to as power cost 0 when power cost(B, A) = f (A)u(r) Power-cost 1 refers to power cost(B, A) = f (S)u(r) + u(r )f (A).

The packet is delivered to neighbor A The packet does not have to be delivered to D when D is B s neighbor The algorithm keeps running until the destination node is reached, if possible The second term can be modified to compensate for different network conditions A variation, power cost 2, minimizes pc(B, A) = f (A)[u(r) + v(s)], and power cost P switches selection criteria from power cost to the power metric when destination D is a neighbor of current node A Stojmenovic and Lin [22] provide proofs to show that these three routing algorithms are loop-free Simulation Results Experiments are conducted using random 100-node unit graphs, as reported in [22] The average node degree, k = 10, is controlled Disconnected graphs are ignored The distributed power efficient routing algorithm was seen to outperform the GPS-based algorithms for all network sizes.

The Document Object Model and client-side scripting enable you to deliver all the data to the client one time and then give the client the option of seeing it different ways Visitors don t need to know that instead of going out to your server every time they want to see the data rearranged, the processing takes place on their machine This can take a real load off your server What You Can t Do Serve a page You can t serve a page using client processing You can load another page that has already been downloaded with the current page, which can be a clever technique, but at some point all the data you display must come from the server (except for data collected from the visitor and data collected from the client workstation) Deliver data from a database.

The results assume greater significance for a larger network Also, the power-efficient algorithm produced paths close to the optimal ones (obtained by SP) For the evaluation of cost and power-cost-efficient routing algorithms, it is assumed that nodes have different remaining powers An iteration is defined as a routing task specified by a random choice of source and destination nodes Experiments are run to determine the number of iterations until the first node dies The simulations are run for 20 graphs for different network sizes and for HCB models [8] Both cost functions and the different power-cost methods give similar simulation results The performance of the proposed localized cost and power cost methods and the corresponding nonlocalized shortest path cost and power cost algorithms are found to be comparable The cost and power cost algorithms last significantly longer in terms of iterations than the power algorithm.

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