We propose an asynchronous iterative scheme that allows a set of interconnected nodes to distributively reach agreement within pre-specified bound in finite number steps. While this could be adopted wide variety applications, we discuss it the context task scheduling for data centers. In context, algorithm is guaranteed approximately converge optimal plan, given available resources, Furthermore...

My dissertation examines algorithms for optimal spatial reuse TDMA scheduling with reconfigurable directional antennas. I present and solve the joint beam steering and scheduling problem for spatial reuse TDMA and describe a prototype implemented system based on the algorithms developed. The current prototype achieves up to a 600% speedup over TDMA with a mean of 234% in the experiments to date...

We propose the use of formal languages of infinite words over the alphabet of task identifiers as an interface between control designs and software implementations. We argue that this approach is more flexible than the classical real-time scheduling framework based on periodic tasks, and allows composition of interfaces by language-theoretic operations. We show that finite automata over infinit...

In this work we propose a scheduling and control formulation for simultaneously addressing scheduling and control problems by explicitly incorporating process dynamics in the form of system constraints that ought to be met. The formulation takes into account the interactions between such problems and is able to cope with nonlinearities embedded into the processing system. The simultaneous sched...

Data science and data processing are very popular topics nowadays. Un- like a few years ago, everything is connected to now we have handle these kinds of large well. Therefore the distributed heterogeneous resources networks e.g. computational grid, attracted great interest. It has become challenge schedule jobs in order utilize available effectively. The allocation arriving impact on efficienc...

A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The he...

This paper presents a hybrid backward scheduling method, referred to as HBS, which mainly addresses discrete manufacturing environments. It operates under the framework of hierarchical finite capacity shop floor modelling and discrete event simulation. HBS applies a set of transformation relations in order to convert a finite capacity forward scheduling method (FS) that can employ different ass...

We propose a new efficient serial architecture to implement the Berlekamp–Massey algorithm, which is frequently used in BCH and Reed–Solomon decoders. An inversionless Berlekamp–Massey algorithm is adopted which not only eliminates the finite-field inverter but also introduces additional parallelism. We discover a clever scheduling of three finite-field multipliers to implement the algorithm ve...

We consider a generalized switch model, which includes as special cases the model of multiuser data scheduling over a wireless medium, the inputqueued cross-bar switch model and a discrete time version of a parallel server queueing system. Input flows n = 1, . . . ,N are served in discrete time by a switch. The switch state follows a finite state, discrete time Markov chain. In each state m, th...