زمان‌بندی

Open Access Article

1 - Scheduling tasks in cloud environments using mapping framework - reduction and genetic algorithm
nima khezr nima jafari novimipour

Task scheduling is a vital component of any distributed system such as grids, clouds, and peer-to-peer networks that refer tasks to appropriate resources for execution. Common scheduling methods have disadvantages such as high time complexity, inconsistent execution of More

Task scheduling is a vital component of any distributed system such as grids, clouds, and peer-to-peer networks that refer tasks to appropriate resources for execution. Common scheduling methods have disadvantages such as high time complexity, inconsistent execution of input tasks, and increased program execution time. Exploration-based scheduling algorithms to prioritize tasks from Manuscript profile

Open Access Article

2 - A Task Mapping and Scheduling Algorithm based on Genetic Algorithm for Embedded System Design
mohadese nikseresht Mohsen Raji

Embedded system designers face numerous design requirements and objectives (such as runtime, power consumption and reliability). Since meeting one of these requirements mostly contradicts other design requirements, it seem to be inevitable to apply multi-objective appr More

Embedded system designers face numerous design requirements and objectives (such as runtime, power consumption and reliability). Since meeting one of these requirements mostly contradicts other design requirements, it seem to be inevitable to apply multi-objective approaches in various stages of designing embedded systems, including task scheduling step. In this paper, a multi-objective task mapping and scheduling in the design stage of the embedded system is presented. In this method, tasks are represented by task graphs assuming that the hardware architecture platform is given and determined. In order to manage the dependencies between tasks in the task graph, a segmentation method is used, in which the tasks that can be executed simultaneously are specified in a segment and is considered in the scheduling process. In the proposed method, the task mapping and scheduling problem is modeled as a genetic algorithm-based multi-objective optimization problem considering execution time, energy consumption, and reliability. In comparison to similar previous works, the proposed scheduling method respectively provides 21.4%, 19.2%, and 20% improvement in execution time, energy consumption, and reliability. Applying a multi-objective helps the designer to pick out the best outcome according to different considerations. Manuscript profile

Open Access Article

3 - An Approach to Increase Internet Traffic Transmission Rate in All-Optical OPS Networks
اکبر غفارپور رهبر

Consider an all-optical time-slotted OPS network in which Internet protocol has been used at upper layers. Contention is a major problem for such a network. It is shown in this paper that optical packet retransmission at the optical domain can improve Internet throughpu More

Consider an all-optical time-slotted OPS network in which Internet protocol has been used at upper layers. Contention is a major problem for such a network. It is shown in this paper that optical packet retransmission at the optical domain can improve Internet throughput and can even reduce cost of OPS network implementation. In this technique, a copy of transmitted optical packets are saved in ingress switches and retransmitted when required, independent of TCP layer retransmission. In other words, retransmission may happen both at the optical layer and at the TCP layer. In this paper, an approach is proposed to reduce cost of OPS network implementation. In addition, Internet throughput is studied in slotted OPS network and an approach is proposed to increase Internet throughput and to improve throughput of long-hop connections. Manuscript profile

Open Access Article

4 - Semi-Partitioning Multiprocessor Real-Time Scheduling in Data Stream Management Systems
M. Alemi M. Haghjoo

In data stream management systems as long as streams of data arrive to the system, stored queries are executed on these data. Regarding high workload, high processing capacity is required, leading to consider multiple processors to cope with it. Partitioning approach, o More

In data stream management systems as long as streams of data arrive to the system, stored queries are executed on these data. Regarding high workload, high processing capacity is required, leading to consider multiple processors to cope with it. Partitioning approach, one of the main methods in multiprocessor real-time scheduling, bind each query to one of processors based on its utilization, ratio of estimated execution time to period, and instances of each query which should be completed under defined deadline can only be executed on specified processor. Each query which could not be assigned to any processor can be split based on utilization of processors and spread among them, causing to get closer to optimum result. This system has been examined with real network data, showing lower miss ratio and higher utilization in comparison to simple partitioning approach. Manuscript profile

Open Access Article

5 - Lifetime Improvement of Real-Time Embedded Systems by Battery-Aware Scheduling
S. Manoochehri kargahi kargahi

Many embedded systems and mobile devices use batteries as their energy suppliers. The lifetime of these devices is thus dependent on the battery behavior. Accordingly, battery management besides reducing the energy consumption of the respective system helps to increase More

Many embedded systems and mobile devices use batteries as their energy suppliers. The lifetime of these devices is thus dependent on the battery behavior. Accordingly, battery management besides reducing the energy consumption of the respective system helps to increase the efficiency of such systems. Maximizing the battery lifetime is a quiet challenging problem due to the nonlinear behavior of batteries and its dependence on the characteristics of the discharge profile. This paper employs dynamic voltage scaling (DVS) to extend the lifetime of battery-operated real-time embedded systems. We propose a battery-aware scheduling algorithm to maximize the lifetime and efficiency of the battery. The proposed algorithm is based on greedy heuristics suggested by battery characteristic and power consumption of tasks to employs DVS. Two methods are used to evaluate the mentioned algorithms; the first one is based on the cost function derived from a high-level analytical model of battery, and the second one is based on Dualfoil, a low-level li-ion battery simulator. Experimental results show that the system lifetime can be increased about 4.3% to 19.6%in various situations (in terms of system workload and tasks power consumption). Manuscript profile

Open Access Article

6 - Coordinated Fair Scheduling in LTE-Advanced Multi-Sector Cells
M. Abiri Mehri Mehrjoo R. Abaspour Ghadi

In this paper, we propose a coordinated fair scheduling (CFS) scheme for LTE-Advanced networks where the cells are equipped with multiple sector antennas. To enhance the network spectral efficiency and throughput, the sectors use the same frequency bands. However, to re More

In this paper, we propose a coordinated fair scheduling (CFS) scheme for LTE-Advanced networks where the cells are equipped with multiple sector antennas. To enhance the network spectral efficiency and throughput, the sectors use the same frequency bands. However, to reduce the co-channel interference, the transmissions from the sectors to the users are coordinated. In other words, multiple sectors are allowed to transmit simultaneously, if the occurred co-channel interference is less than a threshold value. The scheduling scheme takes advantage of the user's diversity in space to transmit to the users with good channel conditions while maintaining fairness among the users using the alpha-fair criterion. Furthermore, a heuristic approach is proposed to reduce the computational complexity of the scheduling scheme. The performance of the proposed CFS scheme and the heuristic approach are evaluated using simulation results. The simulation results show that using coordinated fair scheduling improves system performance and increases cell throughput. Manuscript profile

Open Access Article

7 - Scheduling of Modules in Fog Computing by Knapsack-Based Symbiotic Organisms Search
D. Rahbari M. Nickray

Wireless sensor networks have limitations such as processing power, storage resources, and time delay in data transfer to the cloud. The cloud computing by the development of cloud-based services to the edge of the network reduces traffic and delays, so these types of n More

Wireless sensor networks have limitations such as processing power, storage resources, and time delay in data transfer to the cloud. The cloud computing by the development of cloud-based services to the edge of the network reduces traffic and delays, so these types of networks are used in many systems, such as medical care, wearable devices, transportation systems and smart cities. Task scheduling techniques in fog computing are considered to be NP-hard issues. Applications require resources to run. Network fog devices are close to the sensors and the cloud and have the required processing power to run the applications. Each fog device can be used to run resource allocation policies. In this paper, we present an optimized Knapsack-based method optimized by symbiotic organism search to allocate resources appropriately to tasks in fog network. The proposed method is simulated in the iFogsim as a developed library from Cloudsim for fog computing. The results indicate improvement in energy consumption, resource consumption, and execution cost of the network. The proposed method is better than FCFS and Knapsack methods. Manuscript profile

Open Access Article

8 - Sustainable Tree-Based Scheduling in Solar Powered Wireless Mesh Networks
H. Barghi S. V. Azhari

In many applications of wireless mesh networks, due to the lack of access to a permanent source of energy and the use of battery and energy harvesting equipment, energy sustainable design is very important. Duty-cycle adjustment, putting the node into sleep mode in some More

In many applications of wireless mesh networks, due to the lack of access to a permanent source of energy and the use of battery and energy harvesting equipment, energy sustainable design is very important. Duty-cycle adjustment, putting the node into sleep mode in some parts of the working period, is a method for energy saving and sustainability assurance. In this case, to exchange data between neighboring nodes, protocols for sleep scheduling are needed. In some applications of these networks, such as video surveillance applications, it is necessary to collect data from different parts of the network. Tree topology is a good option for these applications. A simple method for coordinating sleep in a tree topology is the TIME-SPLIT algorithm, at which the working time of each node is evenly divided among its children. The proposed TIME-SPLIT scheduling algorithm does not consider the node energy limitations. In this paper, we have added the nodes duty-cycle constraint in the TIME-SPLIT algorithm to guarantee energy sustainability in tree-based wireless mesh networks. In situations where the energy status of the children is different, equal division of time leads to network inefficiency. To improve network efficiency and throughput, we provide two scheduling algorithms that take into account the conditions of the children's energy and traffic. In the first proposed algorithm, the time division is performed in relation to the duty-cycle of the children of each node. In the second algorithm, the time division is dynamically and in proportion to the traffic of the children, and the connection acceptance is more precisely performed based on its energy consumption during its lifespan. The simulation results performed by the NS3 network simulator show that in energy and tree structure imbalance conditions, where children of a node have different energy or sub tree, the proposed methods significantly (more than about 60%) increase the network’s total delivered traffic. Manuscript profile

Open Access Article

9 - Energy-Aware Scheduling for Real-Time Unicore Mixed-Criticality Systems
S. H. Sadeghzadeh yasser sedaghat

Integrated modular avionics (IMA) has significantly evolved avionic industry. In this architecture, tasks with different criticality have been integrated into a share hardware in order to reduce the size, weight, power consumption and cost so they commonly use the resou More

Integrated modular avionics (IMA) has significantly evolved avionic industry. In this architecture, tasks with different criticality have been integrated into a share hardware in order to reduce the size, weight, power consumption and cost so they commonly use the resources. The industry’s interest in integrating tasks has resulted in introducing mixed-criticality systems. Real time and assurance of executing critical tasks are considered of the two basic needs for these kinds of systems. However, integration of critical and non-critical tasks makes some problems for scheduling executing tasks. On the other hand, reducing energy consumption is another important need as these devices run by batteries. Therefore, the present study aims at satisfying the above mentions needs (real time scheduling and reducing energy consumption) by introducing an innovative energy- aware scheduling approach. The proposed algorithm guarantees executing critical tasks as well as reducing energy consumption by dynamic voltage and frequency scaling (DVFS). The results of simulation showed that energy consumption of the proposed algorithm improved up to 14% in comparison with the similar approaches. Manuscript profile

Open Access Article

10 - Priority-Based Task Scheduling Using Fuzzy System in Mobile Edge Computing
Entesar Hosseini Mohsen Nickray SH. GH.

Mobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are i More

Mobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are important issue in MEC. In this paper, we use a standard three-level system model of mobile devices, edge and cloud, and propose two offloading and scheduling algorithms. A decision-making algorithm for offloading tasks is based on the greedy Knapsack offloading algorithm (GKOA) on the mobile device side, which selects tasks with high power consumption for offloading and it saves energy consumption of the device. On the MEC side, we also present a dynamic scheduling algorithm with fuzzy-based priority task scheduling (FPTS) for prioritizing and scheduling tasks based on two criteria. Numerical results show that our proposed work compared to other methods and reduces the waiting time, latency and system overhead. Also, provides the balance of the system with the least number of resources. And the proposed system reduces battery consumption in the smart device by up to 90%. The results show that more than 92% of tasks are executed successfully in the edge environment. Manuscript profile

Open Access Article

11 - Scheduling of Scientific Workflow Applications in Multi-Cloud Environment Using Cuckoo Search Algorithm
S. Mohammad Latif PourKarimi Somayeh Abdi

Multi-cloud environments consist of the considerable variety of resources where the cost of scheduling workflow applications can be significantly reduced in such environments and the resource limitationsimposed by commercial cloud providers can bealso overcome. Accordin More

Multi-cloud environments consist of the considerable variety of resources where the cost of scheduling workflow applications can be significantly reduced in such environments and the resource limitationsimposed by commercial cloud providers can bealso overcome. Accordingly, this study addresses the scheduling of scientific workflowapplications in a multi-cloud environment under a deadline with the aim of minimizing costs. In this paper,an algorithm for scheduling of workflow applications in multi-cloud environment is presented using the cuckoo search algorithm which is one of the most popular meta-heuristic methods. The Cuckoo Search Algorithm is able to search the solution space in a short time and find solutions in the vicinity of the optimal global solution that is close to it. The results show that the proposed approach of this research has better performance in comparison with other meta- heuristic approach in terms of cost reduction. Moreover, the obtained solutions of the proposed meta- heuristic algorithm are in a desirable degree close to the global optimal solutions of mathematical model. Manuscript profile

Open Access Article

12 - A Task Scheduling and Mapping Approach to Enhance the Main Design Challenges of Multiprocessor Systems on Chip
حمیدرضا زرندی

In this paper, a static task scheduling and mapping heuristic approach to optimize execution time, reliability, power and temperature of multiprocessor systems on chip is presented. This method is proposed based on the list scheduling approach and utilized task replicat More

In this paper, a static task scheduling and mapping heuristic approach to optimize execution time, reliability, power and temperature of multiprocessor systems on chip is presented. This method is proposed based on the list scheduling approach and utilized task replication, dynamic voltage and frequency scaling, and adding cooling slacks to improve reliability, power consumption and temperature to expand the design space and explore the solution set more efficiently. Due to the existing trade-offs among the considered parameters and their optimization, the optimization process is complicated and our proposed method is used the Pareto front generation technique. Moreover, our proposed method, models the objectives comprehensively to consider their dependency. Several experiments are performed to demonstrate the performance and capability of the proposed method in joint optimization of the parameters and extracting the proper solution set. Compared to the previous research, our proposed method outperforms them in optimizing the considered design parameters and its results is 19% better averagely than an efficient studied heuristic method. Manuscript profile

Open Access Article

13 - An Efficient Approach for Resource Allocation in Fog Computing Considering Request Congestion Conditions
Samira Ansari Moghaddam سميرا نوفرستي مهري رجايي

Cloud data centers often fail to cope with the millions of delay-sensitive storage and computational requests due to their long distance from end users. A delay-sensitive request requires a response before its predefined deadline expires, even when the network has a hig More

Cloud data centers often fail to cope with the millions of delay-sensitive storage and computational requests due to their long distance from end users. A delay-sensitive request requires a response before its predefined deadline expires, even when the network has a high load of requests. Fog computing architecture, which provides computation, storage and communication services at the edge of the network, has been proposed to solve these problems. One of the fog computing challenges is how to allocate cloud and fog nodes resources to user requests in congestion conditions to achieve a higher acceptance rate of user requests and minimize their response time. Fog nodes have limited storage and computational power, and hence their performance is significantly reduced due to high load of user requests. This paper proposes an efficient resource allocation method in fog computing that decides where (fog or cloud) to process the requests considering the available resources of fog nodes and congestion conditions. According to the experimental results, the performance of the proposed method is better compared with existing methods in terms of average response time and percentage of failed requests. Manuscript profile

Open Access Article

14 - Energy-Aware Data Gathering in Rechargeable Wireless Sensor Networks Using Particle Swarm Optimization Algorithm
Vahideh Farahani Leili Farzinvash Mina Zolfy Lighvan Rahim Abri Lighvan

This paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine t More

This paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine the important aspects of energy-aware data gathering including sleep scheduling, and energy-aware clustering and routing. Additionally, most of them proposed greedy algorithms with poor performance. As a result, nodes run out of energy intermittently and temporary disconnections occur throughout the network. In this paper, we propose an energy-efficient data gathering algorithm namely Energy-aware Data Gathering in Rechargeable wireless sensor networks (EDGR). The proposed algorithm divides the original problem into three phases namely sleep scheduling, clustering, and routing, and solves them successively using particle swarm optimization algorithm. As derived from the simulation results, the EDGR algorithm improves the average and standard deviation of the energy stored in the nodes by 17% and 5.6 times, respectively, compared to the previous methods. Also, the packet loss ratio and energy consumption for delivering data to the sink of this scheme is very small and almost zero Manuscript profile

Open Access Article

15 - A review on hoof trimming timing in cows
Marzieh Faezi Alireza Bahonar Ahmadreza Mohamadnia

Hoof trimming as a part of hoof health management is one of the important parts of herd health management system. Timing of hoof trimming and its method are the main subjects that must be known for an efficient hoof trimming program. In the current study, the different More

Hoof trimming as a part of hoof health management is one of the important parts of herd health management system. Timing of hoof trimming and its method are the main subjects that must be known for an efficient hoof trimming program. In the current study, the different suggested timings of trimming (around drying, early, middle and end of lactation) have been reviewed. Although the need for more research to find the best time for hoof trimming is yet necessary, an appropriate timing is suggested based on the current literature. Also the unique role of accurate data recording system in time management of trimming is mentioned. Manuscript profile

Open Access Article

16 - WSTMOS: A Method For Optimizing Throughput, Energy, And Latency In Cloud Workflow Scheduling
Arash Ghorbannia Delavar Reza Akraminejad sahar mozafari

Application of cloud computing in different datacenters around the world has led to generation of more co2 gas. In addition, energy and throughput are the two most important issues in this field. This paper has presented an energy and throughput-aware algorithm for sche More

Application of cloud computing in different datacenters around the world has led to generation of more co2 gas. In addition, energy and throughput are the two most important issues in this field. This paper has presented an energy and throughput-aware algorithm for scheduling of compressed-instance workflows in things-internet by cluster processing in cloud. A method is presented for scheduling cloud workflows with aim of optimizing energy, throughput, and latency. In the proposed method, time and energy consumption has been improved in comparison to previous methods by creating distance parameters, clustering inputs, and considering real execution time. In WSTMOS method by considering special parameters and real execution time, we managed to reach the optimized objective function. Moreover, in the proposed method parameter of time distance of tasks to virtual machines for reduction of number of migration in virtual machines was applied. In WSTMOS method by organizing the workflow inputs to low, medium and heavy groups and also by distributing appropriate load on more suitable servers for processors threshold, we accomplished to optimize energy and cost. Energy consumption was reduced by 4.8 percent while the cost was cut down by 4.4 percent using this method in comparison to studied method. Finally, average delay time, power and workload are optimized in comparison to previous methods. Manuscript profile

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