scheduling in cloud computing is an essential requirement to execute the tasks given as per the requirements. The scheduler orders the tasks according to the steps mentioned under the scheduling algorithms. The schedu...
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ISBN:
(纸本)9781509030385
scheduling in cloud computing is an essential requirement to execute the tasks given as per the requirements. The scheduler orders the tasks according to the steps mentioned under the scheduling algorithms. The scheduling algorithms need to ensure that the cloud is functioning to the optimum efficiency as well as the tasks are given equal weightage. The way of execution of a scheduling algorithm differs from one another and hence a system, if established, to compare these scheduling algorithms will help the cloud service providers to work better and in a more efficient way as per the user requirements. In fact, it is very important to have a standard comparison system amongst the scheduling algorithms, as per now, there is no particular research done to compare and contrast the scheduling algorithm. This paper develops a set of environments and scenarios in order to differentiate the functioning of the scheduling algorithms. The following scheduling algorithms are studied: First Come First Serve, Shortest Job First, Opportunistic Load Balancing, and Generalized Priority Algorithm. They were put to test under the various environment and scenarios and were evaluated based on parameters such as Cost and Makespan. Based on these studies, an intelligent tool was developed which takes in the user preferences, such as the number of jobs, their preference of time metrics and cost metrics and suggests the scheduler about the number of VMs, and the scheduling algorithm which should be used to accommodate the user requirements.
In this paper, the carrier aggregation (CA) is applied to Heterogeneous Networks (HetNets) consisting of a macro base station (MBS) and low-power pico base stations (PBSs). The PBSs are distributed in the outer space ...
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ISBN:
(纸本)9781509041831
In this paper, the carrier aggregation (CA) is applied to Heterogeneous Networks (HetNets) consisting of a macro base station (MBS) and low-power pico base stations (PBSs). The PBSs are distributed in the outer space of the disk centered at the MBS and the closed-form solution of the radius of the disk is analyzed. In the CA based HetNet, firstly, a practical user association scheme is proposed to classify the users into macrocell user (MUs) and pico-cell users (PUs). Secondly, a PU-centric cooperative transmission strategy is proposed to increase the data rate of PUs. Then, in order to eliminate the cross-tier interference in HetNet, the MUs and PUs schedule different component carriers (CCs) according to different algorithms. For the MUs, an improved simulated annealing (SA) scheduling algorithm is proposed to maximize the sum rate of the MUs. Compared with the existing SA, the inner loop of the proposed SA is redesigned. Consequently, the best value can be obtained more quickly. For PUs, a location information based low-complexity maximize minimum distance (MMD) algorithm is proposed to reduce the interference from PBSs to PUs as much as possible. Overall, an integrated scheme is proposed to improve the performance. At last, numerical results demonstrate the performance of the proposed schemes.
The use of orthogonal frequency division multiple access (OFDMA) in Long Term Evolution (LTE) and LTE-Advanced systems facilitates the potential for scheduling cell users on orthogonal time-frequency resource blocks s...
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ISBN:
(纸本)9781479944484
The use of orthogonal frequency division multiple access (OFDMA) in Long Term Evolution (LTE) and LTE-Advanced systems facilitates the potential for scheduling cell users on orthogonal time-frequency resource blocks selectively. This paper identifies several frequency selective scheduling (FSS) algorithms and studies their performance and optimality under certain identified constraints in practice. The performance is studied under the limiting factors of cell load, user mobility, the number of users per cell, data traffic characteristics, and the LTE standards constraint of using a single modulation and coding scheme (MCS) across assigned resource blocks. To address the single MCS restriction, a dynamic Proportional Fair (PF) scheduling algorithm is developed to achieve optimal allocation under this constraint. The gain either in signal-to-interference-plus-noise ratio (SINR) or cell throughput achieved from these algorithms is statistically quantified using detailed LTE system level simulations.
作者:
Ram PratapTaskeen ZaidiAssistant Professor
Department of MCA ShriRamswaroop Memorial Group of Professional Colleges Lucknow India Associate Professor
Faculty of Computer Science &Engineering ShriRamswaroopMemorial University Barabanki India
Delivery of reliable services in cloud environment is a major issue. Reliability may be achieved by implementing the fault tolerance. Due to the abundant growth of traffic and service request on cloud datacenters, bal...
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ISBN:
(纸本)9781538646939
Delivery of reliable services in cloud environment is a major issue. Reliability may be achieved by implementing the fault tolerance. Due to the abundant growth of traffic and service request on cloud datacenters, balancing the load in cloud environment is one of the serious challenges as failure may occur due to increase in power consumption, node failure, machine failure etc. Therefore there is a need of a policy for balancing the load among the datacenters and various solutions to balance the load have been proposed by researchers. Load distribution is the mechanism of dispersal the load between different nodes based on certain parameters such as underloaded(node) and overloaded (node). In this research article we have discussed the concept of dispersal of load and then perform a comparative analysis of various task-scheduling policies such as First Come First Serve, Shortest Job First and Round Robin on *** simulation results on Cloudsim depicted that RR task-scheduling is much better than the FCFS and SJF whether we are using the Time shared policy or Space shared policy for execution of cloudlet.
The paper gives an insight and overview of Cloud Computing, Fog computing and Task scheduling methods. When we require scalable along with on demand access for computing resources while using internet then Cloud Compu...
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ISBN:
(数字)9798331506452
ISBN:
(纸本)9798331506469
The paper gives an insight and overview of Cloud Computing, Fog computing and Task scheduling methods. When we require scalable along with on demand access for computing resources while using internet then Cloud Computing comes into the picture. It has the capability to deliver on request, Self-service, wider network access, resource pooling, swift elasticity and deliberate services. Fog computing can processes data at the edge of the network, because of which faster processing and the storage of data nearer to the data sources happens which in fact can enhance the capabilities. In cloud and fog computing environment task scheduling has an essential role as it has the capabilities to optimize the allocation of resources, enhancing the efficiency and it can guarantee the performance in latency-sensitive based applications. Here in this paper various challenges faced are discussed and it describes about variety of algorithms designed to enhance the scheduling efficiency.
With ever-increasing demands for bandwidth optical packet/burst switching is used to utilise more of the available capacity of optical networks. In current prototypes of optical switches time and wavelength multiplexi...
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With ever-increasing demands for bandwidth optical packet/burst switching is used to utilise more of the available capacity of optical networks. In current prototypes of optical switches time and wavelength multiplexing are combined to resolve packet contentions by means of Fiber Delay Lines and wavelength converters in the switching elements. Although optical switches have lower energy consumption than their electronic counterparts, it remains substantial. Since wavelength converters contribute significantly to the switches overall energy consumption, they should be used sparingly, rather than continuously. Current scheduling algorithms however do not take the usage of wavelength converters (and the related energy consumption) into account. To this end, we developed and evaluated new cost-based scheduling algorithms, which take both gap and delay into account to schedule an incoming packet. The performance improvement of these algorithms over existing algorithms can be traded off for a significant reduction in up-time of the wavelength converters by introducing a conversion cost in the involved cost function. This is backed by Monte Carlo simulation results, in which the algorithms are applied both in a void-filling and non-void-filling setting. The algorithms are of the same implementation complexity as current algorithms, and thus of immediate value to switch designers.
Many big data systems are in the rise to handle the high volume of data that need to be stored and processed in the current world scenarios. One of the key features of the big data system is an efficient job schedulin...
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Many big data systems are in the rise to handle the high volume of data that need to be stored and processed in the current world scenarios. One of the key features of the big data system is an efficient job scheduling using a robust scheduling algorithm. This paper will do a survey of some of the big data scheduling algorithms in terms of fairness, speed of processing, efficiency etc. This paper describes briefly about how a big data system works and then go deep in to some of the scheduling algorithms used in the big data systems.
High-Level Synthesis (HLS) is a process of designing digital circuit from high-level language descriptions and thus is applied for shorten time to market. Operation scheduling is one of the critical step in HLS. It de...
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Industrial Internet-of-Things, automation, and process control applications require communication networks with a high degree of reliability, low energy expenditure, and low latency. Convergecast communication wherein...
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ISBN:
(数字)9781728191270
ISBN:
(纸本)9781728191287
Industrial Internet-of-Things, automation, and process control applications require communication networks with a high degree of reliability, low energy expenditure, and low latency. Convergecast communication wherein all nodes in the network transmit data to a common base station is a common paradigm for such applications. Time slotted networks which support deterministic scheduling, such as 802.15.4e Time Slotted Channel Hopping (TSCH) multiple access (MAC) protocol, are well suited for such applications. In this paper, we consider a joint relay selection and scheduling problem for convergecast on a multihop wireless network using single channel TSCH MAC protocol. The objective of the problem is to reduce both the number of relay nodes required for network connectivity as well as the slot-frame duration for a periodic deterministic convergecast schedule. For tree networks with half-duplex constraints we obtain a lower bound on the minimum slot-frame duration and show that the relay selection and scheduling problem can be decoupled. We propose a heuristic scheduling algorithm which is shown to achieve the above lower bound using simulations. For the NP-hard relay selection problem, we propose a polynomial time relay selection algorithm with an improved approximation ratio. The performance of our relay selection and scheduling algorithms are studied via simulations on randomly generated graphs.
In this paper, the performance of Proportional Fair (PF), Maximum-Largest Weighted Delay First (M-LWDF) and Exponential/Proportional Fair (EXP/PF) packet scheduling algorithms has been investigated in the downlink Lon...
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In this paper, the performance of Proportional Fair (PF), Maximum-Largest Weighted Delay First (M-LWDF) and Exponential/Proportional Fair (EXP/PF) packet scheduling algorithms has been investigated in the downlink Long Term Evolution (LTE) system. The performance evaluation is conducted in single cell with interference environment while increasing number of users in the range of 10 to 80 (Case 1) and varying users' speed in the range [3, 120] km/h (Case 2). Results show that in Case 1, M-LWDF outperforms other two algorithms in terms of average throughput, spectral efficiency, packet delay, packet loss ratio (PLR), and fairness index, and in Case 2, the performance of simulated scheduling algorithms drops noticeably with increased users' speed and M-LWDF outperforms other two algorithms in terms of average throughput, spectral efficiency, PLR, and delay.
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