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is facilitated by the low marginal costs of storage area network (SAN) technology. However, the control and administration of the Data Grid is now spread across multiple organizations, which increases the complexity of a Data Grid deployment. There are now multiple stakeholders networked together in a series of relationships that must agree on every operational detail. The introduction of a DG means stakeholders in various organizations are now linked together over issues such as security, service level agreements, and liability in the event of a security breach. Many other issues should be considered such as human issues on allocating responsibility for managing and operating the hardware and software of the grid, policy issues on to how much storage will be shared and how much bandwidth can be used, and the administrative issues on the allocation of costs and protection against liability. King (2006) has studied the intertwined personnel relationships within a Data Grid linking three clinical sites. Each site is composed of two groups of shareholders, the administrators and the operators shown in Figure 21.21. Before there was a Data Grid, the personnel relationships at the sites were straightforward, as indicated in the gure by the double line and the hexagons labeled 1 1, 2 2, and 3 3 for administrators and operations personnel working side by side. After the Data Grid was added 32 = 9 new primary relationships resulted, as shown in the original three double lines plus six solid lines. In addition there is potential for 3 2 = 6 optional relationships, as marked by the dotted lines. The personnel relationship grows as the number of sites n grows, so there will be n2 new primary relationships, and n 2 = 2n optional relationships. Clearly, Data Grid administration has become a complex issue.

In order to provide survivable policy dissemination, PECAN implements a mechanism that disseminates data using the management hierarchy. Policies are assumed to be created at the GPA and must be disseminated to all the nodes in the network. The rationale behind this is that the entire network must be managed in a coherent fashion and therefore the same policies must be used everywhere. The exception to this is con guration policies, which are usually speci c to a given node and provide con guration directives for that node. The following mechanism is used for policy dissemination:

Monitoring and review: link risk management to other management processes; and facilitate better risk management and continuous improvement.

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Recent years have seen rapid growth in the scienti c understanding of energy balance regulation ( 6), and this has helped identify many new potential targets for anti-obesity drugs. In theory, a drug treatment for obesity may reduce energy intake (decreasing appetite and/or enhancing satiety), reduce nutrient absorption, or increase energy expenditure or substrate utilization; in practice, some agents have effects on more than one aspect of energy balance regulation (Figure 17.3).

The collection of performance statistics from network elements is typically performed via SNMP. For example, the routers that connect a wired LAN and the wireless medium have buffers that can exhibit a sustained over ow, indicating abnormal or unanticipated operational conditions (note that the buffers are normally sized such that they do not over ow under normal operational conditions). An important task of performance management is to monitor the routers to detect such sustained over ows, and report to an integrated fault/ performance/security correlation engine, to help with root cause analysis associated with soft failures. Observe that sustained buffer over ows at a router will result in packet loss, in turn leading to a disruption in service. Another example of a network element in MANETs whose performance needs to be monitored is the device that performs encryption, such as an IPSec

(r) Users redirect mail from ISP to anti-spam service provider (v) Anti-spam service provider visits and cleans user s mailbox

The partial derivative function is called the score function and is given by Score(q) = Score(v) = LL T 2[ yi - q] T [ yi - q] = = , q 2v v i =1 i =1

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