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 >

Tingting Yang¹, Hailong Feng¹, Chengming Yang², Ge Guo³, Tieshan Li¹

Computer Systems Science and Engineering, Vol.33, No.2, pp. 157-164, 2018, DOI:10.32604/csse.2018.33.157

Abstract In this paper, the online and offline scheduling schemes towards maritime Cyber Physical Systems (CPSs), to transmit video packets generating from the interior of vessel. During the sailing from the origin port to destination port, the video packets could be delivered via the infostations shoreside. The video packets have their respective release times, deadlines, weights and processing time. The video packets only could be successfully transmitted before their deadlines. A mathematic job-machine problem is mapped. Facing distinguished challenges with unique characteristics imposed in maritime scenario, we focus on the heterogeneous networking and resource optimal scheduling technology to provide valuable insights… More >

Vidblain Amaro-Ortega^1,∗, Arnoldo Díaz-Ramírez², Brenda Leticia Flores-Ríos¹, Félix Fernando González-Navarro¹, Frank Werner³, Larysa Burtseva¹

Computer Systems Science and Engineering, Vol.33, No.1, pp. 31-40, 2018, DOI:10.32604/csse.2018.33.031

Abstract The Linux operating system has been employed to execute numerous real-time applications. However, it is limited to support soft real-time systems by two scheduling policies: First-In-First-Out and Round Robin. For real-time systems with critical constraints, the soft real-time support and these scheduling policies are still insufficient. In this work, the Earliest Deadline First scheduling policy, which has been shown in theory to be an optimal one in uniprocessor systems, is introduced as an extension of the Linux kernel. This policy is implemented into the real-time class, without the necessity of defining an additional class. The Linux kernel affords capabilities of… More >

Win-Chin Lin^a, Chin-Chia Wu^a, Kejian Yu^b, Yong-Han Zhuang^a, Shang-Chia Liu^c

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 671-681, 2018, DOI:10.1080/10798587.2017.1302711

Abstract Most research studies on scheduling problems assume that a job visits certain machines only one time. However, this assumption is invalid in some real-life situations. For example, a job may be processed by the same machine more than once in semiconductor wafer manufacturing or in a printed circuit board manufacturing machine. Such a setting is known as the “re-entrant flowshop”. On the other hand, the importance of learning effect present in many practical situations such as machine shop, in different branches of industry and for a variety of corporate activities, in shortening life cycles, and in an increasing diversity of… More >

Imed Kacem, Ahmed Kadri, Pierre Laroche

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 421-430, 2018, DOI:10.31209/2018.100000016

Abstract This paper addresses an inventory regulation problem in bicycle sharingsystems. The problem is to balance a network consisting of a set of stations by using a single vehicle, with the aim of minimizing the weighted sum of the waiting times during which some stations remain imbalanced. Motivated by the complexity of this problem, we propose a two-stage procedure based on decomposition. First, the network is divided into multiple zones by using two different clustering strategies. Then, the balancing problem is solved in each zone. Finally, the order in which the zones must be visited is defined. To solve these problems,… More >

S. M. Mousavi^a, M. Zandieh^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 9-16, 2018, DOI:10.1080/10798587.2016.1261956

Abstract This paper considers the problem of scheduling n independent jobs in g-stage hybrid flow shop environment. To address the realistic assumptions of the proposed problem, two additional traits were added to the scheduling problem. These include setup times, and the consideration of maximum completion time together with total tardiness as objective function. The problem is to determine a schedule that minimizes a convex combination of objectives. A procedure based on hybrid the simulated annealing; genetic algorithm and local search so-called HSA-GA-LS are proposed to handle this problem approximately. The performance of the proposed algorithm is compared with a genetic algorithm… More >

Tongmao Ma^1,2, Shanchen Pang¹, Weiguang Zhang¹, Shaohua Hao¹

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115

Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >