We study algorithmic problems that are motivated by bandwidth trading in next generation networks. Typically, bandwidth trading involves sellers (e.g., network operators) interested in selling bandwidth pipes that offer to buyers a guaranteed level of service for a specified time interval. The buyers (e.g., bandwidth brokers) are looking to procure bandwidth pipes to satisfy the reservation requests of end-users (e.g., Internet subscribers). Depending on what is available in the bandwidth exchange, the goal of a buyer is to either spend the least amount of money to satisfy all the reservations made by its customers, or to maximize its revenue from whatever reservations can be satisfied. We model the above as a real-time non-preemptive scheduling problem in which machine types correspond to bandwidth pipes and jobs correspond to the end-user reservation requests. Each job specifies a time interval during which it must be processed and a set of machine types on which it can be executed...