Sharif Digital Repository

Large scale Internet services are expected to only increase in complexity and popularity. Their energy consumption is also a major concern in data centers. Smart scheduling of their sub-services on data center Physical Machines (PM) can effectively improve their energy as well as performance. Since today servers are not energy-proportional yet, a major and traditionally neglected source of inefficiency in them is the utilization level of PMs. We present two scheduling algorithms for precedence-constrained parallel Virtual Machines (VM) in a virtualized data center where each VM represents a sub-service of the Internet-scale service. Our algorithms use virtualization technology to increase... 

Process variation has already emerged as a major concern in design of multi-processor system on chips (MPSoC). In recent years, there have been several attempts to bring variability awareness into the task scheduling process of embedded MPSoCs to improve performance yield. This study attempts to provide a comparative study of the current variation-aware design-time task and communication scheduling techniques that target embedded MPSoCs. To this end, the authors first use a sign-off variability modelling framework to accurately estimate the frequency distribution of MPSoC components. The task scheduling methods are then compared in terms of both the quality of the final solution and the... 

This paper presented a combined scheduling and bidding algorithm for constructing the bidding curve of an electric utility that participated in the day-ahead energy markets. Day-ahead market price uncertainty was modeled using non-probabilistic information gap decision theory (IGDT). The considered utility consisted of generation units and a retailer part; the retailer part of the utility and its demand response program (DRP) could affect the utility's profit, which should be considered in the bidding strategy problem. The bidding strategy algorithm proposed in this paper dispatched units by optimizing the demand response programs of the retailer part. In addition, non-decreasing bidding... 

This paper deals with the resource-constrained project scheduling problem with flexible work profiles. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero. In many real-life projects, however, it often occurs that only one renewable bottleneck resource is available and that activities do not have, a fixed prespecified duration and associated resource requirement, but a total work content, which essentially indicates how much work has to be performed on them. Based on this work content, all feasible work profiles have to be specified for the activities, each characterized by a, fixed duration and a resource... 

The utilization of the limited resources of a multiprocessor or multicomputer system is a primary performance issue which is crucial for the design of many scheduling algorithms. While many of the existing parallel machines benefit from a regular product network topology, almost none of the previous resource placement techniques have come to recognize and exploit this inherent regularity. This paper introduces several novel algorithms for deriving resource placement schemes in product networks based on the assumption of perfect resource placement in their underling basic graphs. Our techniques use known schemes for the basic networks as their building blocks for deploying the resource... 

The focus of this research is on the flexible flow shop sequence dependent group scheduling problem (FFSDGS) with minimization of makespan as the criterion (FFm|fmls, Splk|Cmax). Since the research problem is shown to be NP-hard, a meta-heuristic algorithms based on memetic algorithm is developed to efficiently solve the problem. The performance of the proposed algorithm is compared with the only available meta-heuristic algorithm in the literature, i.e., tabu search (TS). The comparison is performed based on paired t-test and the result shows that the memetic algorithm has a superior performance compared to the TS  

The NP-hard single machine sequence-dependent group scheduling problem with minimization of total weighted earliness and tardiness is investigated. An arc-time-indexed formulation is presented and a Lagrangian-based branch-and-bound algorithm is proposed. The Lagrangian relaxation of the arc-time-indexed formulation is solved as a shortest path problem. The results of an extensive computational study demonstrate the efficacy of the proposed algorithm and establish characteristics of some hard to solve instances  

We have developed a mathematical programming model for minimizing total flow time of the flow shop sequence dependent group scheduling (FSDGS) problem, typically classified as Fm|fmls, Splk, prmu|∑Cj. As the problem is shown to be strongly NP-hard, a tabu search (TS) algorithm as well as a hybrid ant colony optimization (HACO) algorithm have been developed to heuristically solve the problem. A lower bounding (LB) method based on the Branch-and-Price algorithm is also developed to evaluate the quality of the metaheuristic algorithms. In order to compare the performance of metaheuristic algorithms, random test problems, ranging in size from small, medium, to large are created and solved by... 

Scheduling projects incorporated with materials ordering results in a more realistic problem. This paper deals with the combined problem of project scheduling and material ordering. The purpose of this paper is to minimize the total cost of this problem by determining the optimal values of activity duration, activity finish time and the material ordering schedule subject to constraints. We employ a genetic algorithm approach to solve it. Elements of the algorithm, such as chromosome structure, unfitness function, crossover, mutation and local search operations are explained. The results of the experimentation are quite satisfactory  

Considering the collection of all networks with independent set interference model, Shah, Tse, and Tsitsiklis showed that there exist scheduling algorithms with polynomial complexity and delay, only if the maximum independent set problem can be solved in polynomial time (equivalently, P=NP). In this paper, we extend this result to arbitrary collections of networks and present a clear-cut criterion for the existence of polynomial complexity and delay scheduling algorithms relative to a given collection of networks with arbitrary interference models, not confined to independent set interference or SINR models, and not necessarily encompassing all network topologies. This amounts to the... 

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and... 

Most of the research works conducted on Project Scheduling Problem (PSP) especially Resource Constrain Project Scheduling Problem (RCPSP) either ignore equipment planning or schedule the activities first, and then plan for the required equipment. Moreover, little works that consider simultaneous PSP and Equipment Planning (EP) are based on the assumption that the equipment is continuously available. However, in reality, equipment is subject to either random breakdowns or deterministic maintenance programs that make it not being available all the time. In this paper, the PSP and EP problems are simultaneously considered in closer to reality situations in which the equipment is not always... 

Feature selection is a fundamental problem in machine learning and data mining. The majority of feature selection algorithms are designed for running on a single machine (centralized setting) and they are less applicable to very large datasets. Although there are some distributed methods to tackle this problem, most of them are distributing the data horizontally which are not suitable for datasets with a large number of features and few number of instances. Thus, in this paper, we introduce a novel vertically distributable feature selection method in order to speed up this process and be able to handle very large datasets in a scalable manner. In general, feature selection methods aim at... 

Cost optimization for workflow scheduling while meeting deadline is one of the fundamental problems in utility computing. In this paper, a two-phase cost-efficient scheduling algorithm called critical chain is presented. The proposed algorithm uses the concept of slack time in both phases. The first phase is deadline distribution over all tasks existing in the workflow which is done considering critical path properties of workflow graphs. Critical chain uses slack time to iteratively select most critical sequence of tasks and then assigns sub-deadlines to those tasks. In the second phase named mapping step, it tries to allocate a server to each task considering task's sub-deadline. In the... 

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and... 

In this paper we show that Biham's chosen key attack can be generalized to include any block cipher and we give a low complexity chosen key attack on any Feistel type ci-pher. Then we show that the irregularities in the shift pattern of DES key schedule algorithm is not sufficient for the cryptosystem to resist against related key attacks. We have realized our proposition by a counter example in which the E-box of DES is slightly modified whiles other components and among those, the shift pattern in key schedule algorithm is kept unchanged. We have ap-plied a new related key attack on the resulting DES-like cryptosystem and demonstrated that the security of the system decreases drastically  

Scheduling of the maintenance activities is considered, in which the duration of activities is uncertain, delivery date of the maintenance shutdown is predefined, and activities are multi-mode. The problem is a multi-mode time-constrained project scheduling problem (MTCPSP). The glycol regeneration unit in a gas refinery is as the case study. Based on the effect of equipment or sub-equipment on the system reliability, the importance value of equipment and sub-equipment within the system is determined, and these values are used in a heuristic algorithm as a priority rule for choosing activities in the schedule. Outcomes demonstrate the performance of the algorithm in early or on time delivery... 

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved  

Cloud computing technology, which is a new model of service provisioning in distributed systems, has been raised as a way to execute workflow applications. To profit from this technology for executing workflow applications, it is necessary to develop workflow scheduling algorithms that consider different QoS parameters such as execution time and cost. Therefore, in this paper, we focus on two criteria: makespan (completion time) and execution cost of workflow application and propose a scheduling algorithm named CB-DT (Constrained Budget-Decreased Time) which aims to create a schedule that decreases the makespan while satisfying the budget constraint of the workflow application. In the... 

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved