A mobile ad hoc network is an autonomous system of infrastructureless, multihop wireless mobile nodes. Reactive routing protocols perform well in such an environment due to their ability to cope quickly against topological changes. In this paper, we propose a new routing protocol called Caching and Multipath (CHAMP) Routing Protocol. CHAMP uses cooperative packet caching and shortest multipath routing to reduce packet loss due to frequent route breakdowns. Simulation results reveal that by using a five-packet data cache, CHAMP exhibits excellent improvement in packet delivery, outperforming AODV and DSR by at most 30% in stressful scenarios. Furthermore, end-to-end delay is significantly reduced while routing overhead is lower at high mobility rates. 0-7803-7753-2/03/$17.00 (C) 2003 IEEE

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When organizing the operating theatre and scheduling surgeries, hospitals face a trade-off between the need to be responsive to emergency cases and to conduct scheduled elective surgeries efficiently. We develop a simulation model to compare a flexible and a focused resource-allocation policy. We evaluate these two policies on patient and provider outcome measures, including patient wait time and physician overtime. We find that the focused policy results in lower elective wait time and lower overtime, which leads to the conclusion that electives benefit more from the elimination of emergency disruptions than what they lose from the reduced access to operating rooms. Emergency patient wait time, however, increases significantly as we shift from the flexible to the focused policy. The sensitivity analysis showed that average emergency wait time can decrease as the processing time variability increases. The trade-off between efficiency and responsiveness calls for additional research on other operating-room-allocation policies.

Abstract-We address the problem of efficient online computation of the speeds of different cores of a multi-core processor to maximize the throughput (which is expressed as a weighted sum of the speeds), subject to an upper bound on the core temperatures. We first compute the solution for steady-state thermal conditions by solving a linear program. We then present two approaches to computing the transient speed curves for each core: (i) a local solution, which involves solving a linear program every time step (of about 10 ms), and (ii) a global solution, which computes the optimal speed curve over a large time window (of about 100 s) by solving a non-linear program. We showed that the local solution is insensitive to the weights assigned in the performance objective (hence the need for the global solution). This is because a reduction in the speed of a core can only reduce the temperature of the other cores over much larger time periods (of the order of several seconds). The local solution is then completely determined by the temperature constraint equations. We show that the constraint matrix exhibits a special property -it can be expressed as the sum of a diagonal matrix and a matrix with identical rows. This allows us to solve the multi-core thermal constraint equations analytically to determine the (temporally) local optimum speeds. Further, we showed that due to this property, the steady-state speed solution selects a set of threads to operate at maximum temperature, and turns off all unused cores. Hence, to ensure that all available threads are scheduled, we impose a "fairness" constraint. Finally, we show how the open-loop speed control methods proposed above could be used together with a feedback controller to achieve robustness to model uncertainty.

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