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5. Developing solutions creating an action-plan to address, as much as possible, the needs of the various stakeholder groups in relation to the other stakeholder groups; and the need to have suf cient information before developing solutions (to avoid the trap of attempting to manage a process with only fragmentary or inadequate information). 6. Testing and re ning solutions the PM and team should realise that solution implementation is an iterative process-making a best guess, testing for stakeholder reactions, and reshaping strategies accordingly. It is important to note that the above six primary areas will bring different results to projects when analysed through the eyes of every procurement system. Since each procurement system has characteristics which make it different from the other, the characteristics will have an in uence on the primary areas and consequently an impact on stakeholder management. In order to have a sound and robust argument on the impact of CPS to stakeholder management, Masterman s (1992) CPS classi cation and characterisation framework is used.

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consider a packet generated at node i and destined for node j; its length is drawn from a particular packet length distribution On its way, the packet passes through a number of links and switching nodes Since the packet length does not change on its way, we observe that the service times over the links are in fact not independent In the queueing network models we have introduced so far, however, the service time at every node is assumed to be independent of the service times at all the other nodes Thus, when we try to model the actual packet flow through the network realistically, we end up with a queueing network model that we cannot solve However, it seems reasonable to assume that in the overall network, packets from many source-destination pairs will be transmitted in an interleaved fashion.

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From this fact it follows that the solution to (1.1 l), (1.12) cannot be constant in time at the endpoints of 0. Hence the problem ( 1.1 1 ), ( 1.12), ( 1.13) has no solution. Some problems are ill-posed because of their very nature, despite their initial and boundary conditions are defined appropriately. This is illustrated in Example 1.5.

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This source of randomness then justifies the assumption that the packet length itself is a random variable with fixed mean, that is regenerated at every queue In a sense, we assume that the queues operate independently from one another This assumption has become known as Kleinrock s independence assumption and has been validated as accurate using extensive simulations We assume that all the packets originating at any of the nodes have the same mean length and obey the same packet length distribution FB(~) (in bits) with mean value l/p (bits per packet) A packet of b bits length will then take b/ci seconds to be transmitted over link i The number of packets that can be transmitted over link i is pci (packets per second) Now that we have established the characteristics of the queueing network nodes, we have to compute the workload per node.

Vs = 120 LQ: V,

We do so by readdressing the traffic matrix I and the actual routes through the network Let R(i, j) be the set of links visited by packets routed from i to j and let N(i, j) be the set of switching nodes in the route from i to j We assume that these sets are uniquely defined and that they are static We do not address the question how these sets, ie, the actual routes through the network, are obtained or established We then can compute the arrival rate of packets to a link 1 as.

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