Ehab Nabiel Al-Khanak^1,*, Sai Peck Lee², Saif Ur Rehman Khan³, Navid Behboodian⁴, Osamah Ibrahim Khalaf⁵, Alexander Verbraeck⁶, Hans van Lint¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3265-3282, 2021, DOI:10.32604/cmc.2021.015409

Abstract Scientific Workflow Applications (SWFAs) can deliver collaborative tools useful to researchers in executing large and complex scientific processes. Particularly, Scientific Workflow Scheduling (SWFS) accelerates the computational procedures between the available computational resources and the dependent workflow jobs based on the researchers’ requirements. However, cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate (near-optimal) solution within polynomial computational time. Motivated by this, current work proposes a novel SWFS cost optimization model effective in solving this challenge. The proposed model contains three main stages: (i) scientific workflow application, (ii) targeted computational environment,… More >

Nabeela Awan¹, Salman Khan², Mohammad Khalid Imam Rahmani³, Muhammad Tahir³, Nur Alam MD^4,*, Ryan Alturki⁵, Ihsan Ullah⁶

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2449-2462, 2021, DOI:10.32604/cmc.2021.014386

Abstract Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things (IoT). The IoT is the backbone of smart city applications such as smart grids and green energy management. In smart cities, the IoT devices are used for linking power, price, energy, and demand information for smart homes and home energy management (HEM) in the smart grids. In complex smart grid-connected systems, power scheduling and secure dispatch of information are the main research challenge. These challenges can be resolved through various machine learning techniques and data analytics. In this paper, we have proposed a particle… More >

Zhihong Liu¹, Shuo Zhang^2,*, Yaping Liu², Xiangke Wang¹, Dong Yin¹

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 771-790, 2021, DOI:10.32604/cmes.2021.013244

Abstract MapReduce is a widely used programming model for large-scale data processing. However, it still suffers from the skew problem, which refers to the case in which load is imbalanced among tasks. This problem can cause a small number of tasks to consume much more time than other tasks, thereby prolonging the total job completion time. Existing solutions to this problem commonly predict the loads of tasks and then rebalance the load among them. However, solutions of this kind often incur high performance overhead due to the load prediction and rebalancing. Moreover, existing solutions target the partitioning skew for reduce tasks,… More >

Samih M. Mostafa^1,*, Hirofumi Amano²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3253-3270, 2021, DOI:10.32604/cmc.2021.014675

Abstract CPU scheduling is the basic task within any time-shared operating system. One of the main goals of the researchers interested in CPU scheduling is minimizing time cost. Comparing between CPU scheduling algorithms is subject to some scheduling criteria (e.g., turnaround time, waiting time and number of context switches (NCS)). Scheduling policy is divided into preemptive and non-preemptive. Round Robin (RR) algorithm is the most common preemptive scheduling algorithm used in the time-shared operating systems. In this paper, the authors proposed a modified version of the RR algorithm, called dynamic time slice (DTS), to combine the advantageous of the low scheduling… More >

Juan Du^1,*, Peng Dong², Vijayan Sugumaran³

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 715-723, 2020, DOI:10.32604/iasc.2020.010105

Abstract A dynamic optimized production scheduling which takes into account demand fluctuation and uncertainty is very critical for the efficient performance of Prefabricated Component Supply Chain. Previous studies consider only the conditions in the production factory and develop corresponding models, ignoring the dynamic demand fluctuation that often occurs at the construction site and its impact on the entire lifecycle of prefabricated construction project. This paper proposes a dynamic flow shop scheduling model for prefabricated components production, which incorporates demand fluctuation such as the advance of due date, insertion of urgent component and order cancellation. An actual prefabrication construction project has been… More >

Vaibhav Pandey^∗, Poonam Saini^†

Computer Systems Science and Engineering, Vol.34, No.6, pp. 357-376, 2019, DOI:10.32604/csse.2019.34.357

Abstract The cloud computing paradigm facilitates a finite pool of on-demand virtualized resources on a pay-per-use basis. For large-scale heterogeneous distributed systems like a cloud, scheduling is an essential component of resource management at the application layer as well as at the virtualization layer in order to deliver the optimal Quality of Services (QoS). The cloud scheduling, in general, is an NP-hard problem due to large solution space, thus, it is difficult to find an optimal solution within a reasonable time. In application layer scheduling, the tasks are mapped to logical resources (i.e., virtual machines), aiming to optimize one or more… More >

Fengxiang Zhang^∗

Computer Systems Science and Engineering, Vol.34, No.4, pp. 171-178, 2019, DOI:10.32604/csse.2019.34.171

Abstract This paper addresses a number of mathematical issues related to multiprocessor global EDF platforms. We present a deadline-d all busy period and backward interference which are important concepts for multiprocessor EDF systems, and some general schedulability conditions for any studied job are proposed. We formally prove that at most m-1 different tasks’ jobs could contribute their execution time to an interval starting with a P_busy−d, and we propose an approach for computing an exact upper bound of the total deadline-d task load in a given interval. Therefore, the proposed results are important foundations for constructing exact schedulability analyses of global… More >

Sardar Khaliq uz Zaman¹, Tahir Maqsood¹, Mazhar Ali¹, Kashif Bilal¹, Sajjad A. Madani¹, Atta ur Rehman Khan^2,*

Computer Systems Science and Engineering, Vol.34, No.2, pp. 79-90, 2019, DOI:10.32604/csse.2019.34.079

Abstract Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute a predefined number of tasks… More >

Morteza Okhovvat, Mohammad Reza Kangavari^*

Computer Systems Science and Engineering, Vol.34, No.1, pp. 13-21, 2019, DOI:10.32604/csse.2019.34.013

Abstract Existing works on scheduling in Wireless Sensor Actor Networks (WSANs) are mostly concerned with energy savings and ignore time constraints and thus increase the make-span of the network. Moreover, these algorithms usually do not consider balance of workloads on the actor nodes and hence, sometimes some of the actors are busy when some others are idle. These problem causes the actors are not utilized properly and the actors’ lifetime is reduced. In this paper we take both time awareness and balance of workloads on the actor in WSANs into account and propose a convex optimization model (TAMMs) to minimize make-span.… More >

Haisheng Yu¹, Heng Qi¹, Keqiu Li¹, Jianhui Zhang¹,Peng Xiao², Xun Wang¹

Computer Systems Science and Engineering, Vol.33, No.4, pp. 251-258, 2018, DOI:10.32604/csse.2018.33.251

Abstract The routing mechanism in Data Center networks can affect network performance and latency significantly. Hash-based method, such as ECMP (Equal-Cost Multi-Path), has been widely used in Data Center networks to fulfill the requirement of load balance. However, ECMP statically maps one flow to a path by a hash method, which results in some paths overloaded while others remain underutilized. Some dynamic flow scheduling schemes choose the most underutilized link as the next hop to better utilize the network bandwidth, while these schemes lacks of utilizing the global state of the network. To achieve high bandwidth utilization and low latency, we… More >