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1 Introduction Recently there has been much progress on the design of approximation algorithms for a variety of scheduling problems in which the goal is to minimize the average weighted completion time if the jobs scheduled. Many <f theie approximation algorithms have been inspired by polyhedral formulations of the scheduling problems and their use in… (More)

We consider the general problem of scheduling a set of jobs where we may choose not to schedule certain jobs, and thereby incur a penalty for each rejected job. More specifically, we focus on choosing a set of jobs to reject and constructing a schedule for the remaining jobs so as to optimize the sum of the weighted completion times of the jobs scheduled… (More)

Minimizing power consumption is crucial in battery power-limited secure wireless mobile networks. In this paper, we (a) introduce a hardware/software set-up to measure the battery power consumption of encryption algorithms through real-life experimentation, (b) based on the profiled data, propose mathematical models to capture the relationships between… (More)

Enumerative approaches, such as branch-and-bound, to solving optimization problems require a subroutine that produces a lower bound on the value of the optimal solution. In the domain of scheduling problems the requisite lower bound has typically been derived from either the solution to a linear-programming relaxation of the problem or the solution of a… (More)

We consider the problem of scheduling a parallel loop with independent iterations on a network of heterogeneous workstations , and demonstrate the effectiveness of a variant of fa.toring, a scheduling policy originating in the context of shared address-space homogeneous multiprocessors. In the new scheme, weighted factoring, processors are dynamically… (More)

—This paper considers the problem of computing the optimal trajectories of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize data collection latency in wireless sensor networks (WSNs). By relying on slightly different assumption , we define two interesting problems, the k-traveling salesperson problem with neighborhood (k-TSPN) and the… (More)

—This paper investigates the problem of computing the optimal trajectories of multiple data MULEs (e.g. robots, vehicles, etc.) to minimize data collection latency in wireless sensor networks. By relying on slightly different assumption, we define two interesting problems, the k-traveling salesperson problem with neighborhood (k-TSPN) and the k-rooted path… (More)