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obtained results are not acceptable, the analysis process has to be repeated several times, until the goal is achieved. Modern cellular networks are large and many of their key parameters are interdependent. This is the main reason of an increased demand for automated optimisation solutions, since an engineer usually cannot cope with this level of complexity (traditionally involving an examination of coverage plots as colour images together with some statistical analysis). The computer, together with specialised software, becomes the decision module in this case. Consequently, the whole optimisation process can be performed automatically through iterative trimming of network parameters with only small assistance of a human. This process should correctly be referred to as optimisation. In the book, however, it is purposely called automated optimisation to emphasise this idea. Several works and projects were carried on optimising wireless networks, specifically UMTS networks. The IST Momentum project, finalised in 2003, was the most extensive one [1]. Earlier example projects are ARNO [2] and STORMS [3], completed in 2000 and 1999 respectively. These projects focused in solving the optimisation problem solely based on planning data, because UMTS networks were not yet commercial. Currently, there are several commercial products available in the market that are offering optimisation solutions to UMTS and other cellular technologies.

A similar procedure is often useful when you are developing an intensive data system. If you are uncertain of your ability to manipulate the required volume of data, construct a prototype to test it. I found this invaluable when asked to investigate whether some of the early PC networks could work fast enough to replace the predominant mini-computer-based systems for equity trades. We thought they could but some members of the client s team were highly skeptical, especially the managing director (MD). The solution was to build a prototype with a server that generated several hundred of thousands of changing numbers per minute (mimicking the

Figure 4.4). I couldn t figure it out until my mother pointed out that I had typed in Food Dog by mistake. Darn!

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if ((new = _malloc_unlocked(size)) != NULL) { CLRBITS01(ts); if (ts > size) ts = size; MEMCOPY(new, old, ts); _free_unlocked(old); (void) _mutex_unlock(&__malloc_lock); return (new); } /* * Attempt special case recovery allocations since malloc() failed: * * 1. size <= SIZE(tp) < MINSIZE * Simply return the existing block * 2. SIZE(tp) < size < MINSIZE * malloc() may have failed to allocate the chunk of * small blocks. Try asking for MINSIZE bytes. * 3. size < MINSIZE <= SIZE(tp) * malloc() may have failed as with 2. Change to * MINSIZE allocation which is taken from the beginning * of the current block. * 4. MINSIZE <= SIZE(tp) < size * If the previous block is free and the combination of * these two blocks has at least size bytes, then merge * the two blocks copying the existing contents backwards. */ CLRBITS01(SIZE(tp)); if (SIZE(tp) < MINSIZE) { if (size < SIZE(tp)) { /* case 1. */ SETOLD01(SIZE(tp), ts); (void) _mutex_unlock(&__malloc_lock); return (old); } else if (size < MINSIZE) { /* case 2. */ size = MINSIZE; goto call_malloc; } } else if (size < MINSIZE) { /* case 3. */ size = MINSIZE; goto chop_big; } else if (ISBIT1(ts) && (SIZE(np = LAST(tp)) + SIZE(tp) + WORDSIZE) >= size) { ASSERT(!ISBIT0(SIZE(np))); t_delete(np); SIZE(np) += SIZE(tp) + WORDSIZE; /* * Since the copy may overlap, use memmove() if available. * Otherwise, copy by hand. */ (void) memmove(DATA(np), old, SIZE(tp)); old = DATA(np);

Over the next couple of years, Einstein contacted other professors in attempts to secure an academic position for Kaluza In one such letter, he wrote glowingly to the Austrian migr physicist Karl Herzfeld of Johns Hopkins: The internal relationship between gravitation and electricity I believe to have found now after long erring travels, in close connection to an idea of Kaluza, which appeared some years ago (1921) in our academy reports One should try to provide for him favorable possibilities for employment 26 Alas, Herzfeld couldn t hire Kaluza He had just joined the Hopkins faculty himself and was not in the best position to promote an unknown instructor Finally, Einstein learned about an opening at the University of Kiel The director there was Adolf Fraenkel, a mathematician specializing in set theory Trusting Einstein s judgment, he gladly appointed Kaluza to be professor at Kiel.

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