REVIEW AND COMPARISON OF TASKS SCHEDULING IN CLOUD COMPUTING

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1 REVIEW AND COMPARISON OF TASKS SCHEDULING IN CLOUD COMPUTING Yousef Tohidirad 1, Zahed Soltai aliabadi 2, Abdolsalam Azizi 3, Siamak Abdezadeh 4 ad Mohammad Moradi 5 1 Departmet of Computer Egieerig, Electroic Brach, Islamic Azad Uiversity, Tehra, Ira 2,3 Departmet of Computer Egieerig, Urmia Brach, Islamic Azad Uiversity, Urmia, Ira 4 Departmet of Computer, Bouka Brach, Islamic Azad Uiversity, Bouka, Ira 5 Departmet of Computer, Baeh Brach, Islamic Azad Uiversity, Baeh, Ira ABSTRACT Recetly, there has bee a dramatic icrease i the popularity of cloud computig systems that ret computig resources o-demad, bill o a pay-as-you-go basis, ad multiplex may users o the same physical ifrastructure. It is a virtual pool of resources which are provided to users via Iteret. It gives users virtually ulimited pay-per-use computig resources without the burde of maagig the uderlyig ifrastructure. Oe of the goals is to use the resources efficietly ad gai maximum profit. Schedulig is a critical problem i Cloud computig, because a cloud provider has to serve may users i Cloud computig system. So schedulig is the maor issue i establishig Cloud computig systems. The schedulig algorithms should order the obs i a way where balace betwee improvig the performace ad quality of service ad at the same time maitaiig the efficiecy ad fairess amog the obs. This paper itroduces ad explores some of the methods provided for i cloud computig has bee scheduled. Fially the waitig time ad time to implemet some of the proposed algorithm is evaluated. KEYWORDS Cloud Computig, schedulig algorithms, Schedulig Maagemet, Virtual Machie (VM), CloudSim. 1. INTRODUCTION Moder commuicatio has bee termed as viral exchage of iformatio. This follows to the effect that the cotemporary world is subect to iteret commuicatio, which sees people share iformatio i a ghostly maer. I the actual sese, the people who commuicate durig this process are the machies ivolved, mostly the computers ad servers [1]. Users of the iteret have see cotiuous maipulatio of data that they share. This aspect is cotrolled by the fact that users are may, thereby makig the computers to be subect to heavy task schedulig protocols. This aims to have may people access the iteret with ease ad i the required badwidth. The itercoectio of these processes, despite the differece i the computer processors, is termed as Cloud Computig. Cloud computig is a techique that uses the most elemetal issues of iformatio sharig. I this maer, there is a rightly developed ifrastructure as well as the iterrelatig services. Differet relatig cocepts are described withi the aspects of the process. A umber of computers are always coected i the etwork i real-time [2]. Users have the ability to reach the GUI features without kowig the applied expertise o the same. This is well laid uder the priciple of DOI: /ifcst

2 visualizatio. Visualizatio is the mai itetio of the techology with the itetio of ruig umerous VMs o a sigle machie with the required specificatios of load balacig. I this way, a good task scheme is used to expad the ability for the load balacig uder task schedulig withi the specified distributio system. There is a ABC presece ispired by the life of the hoeybee. To improve the performace of the process, there are created set of behaviours ad techiques desiged by the required persoel to utilize the give desigs uder the desigs of the ABC algorithm [3]. 2. MATERIALS AND METHODS 2.1. Basics of ABC As a cocer of VM schedulig, ABC algorithm has stood as the ideal measure for its success for most special implemetatios [4].While beig used from time to time, the algorithm has bee effective for the establishmet of the right value. While workig uder the priciple of the hoeybees, iformatio sharig o machies is based o source details, destiatio, etwork quality, player of the etwork, threats ad desig tricks of the etwork. This ca be describes by the ABC pseudo code show i Figure 1 [1]. Figure 1. ABC pseudo code/ basic algorithm of ABC aimed at havig tasks scheduled [1] 2.2. ABC i applicatio The maor itetio of Cloud Computig is the existece of self-motivated a pool of VM resources [5]. The VM requiremets are defied accordig to the system s users. This is doe i accordace with the expected desig specificatios. Usig the acceptable Cloud Maagemet policies, possibility for routig specificatios is established. This aspect is doe withi the limits of the available servers while lookig at the cloud maagemet. Uder the same specificatios, it is possible have differet degrees of schedulig maagemet while cosiderig the load levels withi VMs. The balacig alog this lie should leave the best room for the reductio of maskespa ad respose time. 88

3 Sice the machies have the geeral outlook of virtual presece, it is good to represet them uder a set of umbers for the resultat or overall virtuosity as show i the equatio (1) [1]. VM = {VM 1, VM 2, VM 3,,VM N } (1) These machies are subect to idividual tasks that result ito a overall system task as show i the equatio (2) [1]. Tack = {tack 1, tack 2, tack 3,,tack K } (2) The machies work i tadem (parallel) usig differet processors. I this way, the schedulig ability is o-prevetive. As a result, figure 2 shows the diagram a flowchart of the task schedulig uder the ABC istructios [1]. Figure 2. ABC istructio ad the schedulig modality [1] 89

4 I the secod process, evaluatio of the populatio s fitess is a calculatio based o the formula (3) [1]. fit i = evalutio of i= 1 task _ legth the i capacity I this case, the fitess of the process umbers are show by fit withi the capacity of VM withi the tasks of descriptios task legth. To obtai the overall capacity, equatio (4) is applicable [1]. of VM capacity = pe _ um * pe _ mips + vm _ bw (4) (3) I this case, the umber of processors i the system is idicated by _withi the istructio limits show by_ i the required badwidth of _ as per the ability of the virtual machies. The idetificatio ad the allocatio of these elemets lead to the fitess selectio of the required eighbourhood VMs. Whe the process recruitmet reaches, the boudig elemet is defiable by the formula (5) [1]. fit i task _ legthi + iputfile_ legth i= 1 = evalutio of the capacity of VM (5) I this case, the iput File legth becomes the size of the task with pedig executio details. Oce this is doe, the overshadowig fitess is chose i lie with the assig task VM. This allows the calculatio of load balace withi the workload VMs as per the iformatio obtaied from the datacetre [6]. It becomes easier to get the stadard deviatio with respect to the actual load VMs as formula (6) [1]. 1 S. D. = ( X X )^2 (6) Ay VM ow has a processig time idicated by the equatio (7) [1]. = 0 X k task _ i= = 1 capacity legth i (7) The mea processig time for all the VMs is also idicated as formula (8) [1]. X = X = 1 (8) From the above coclusive equatios, it ca be stated that wheever S.D. of the full VM becomes less or equal to mea, a balaced state of the system is experieced. I case S.D. is higher tha the mea, the imbalace state prevails [7]. 90

5 2.3. Results ad discussio By the use of a CloudSim tool (ay versio from 3.0.1); the simulatio platform is subect to the table 1 [1]. TABLE 1. Parameters for the CloudSim settig [1] For settig the ABC algorithm, the parameters are show i TABLE 2 [1]. TABLE 2. Parameters for improved ABC settig [1] 91

6 As possible to establish, the assessmet of the procedure is describable uder three algorithmic istructios. There is the presece of First Come First Served (FCFS) that works o the chroological reach of the give task. There is the Shortest Job First (SJF) that cosiders the sequecig by makig the selectio of the first ob i short terms stated [8]. The Logest Job First (LJF) esures that the heavy ob is selected first. The results of the first ad the secod experimets are show i Figures 3 ad 4[1, 5]. Figure 3. Compariso of makespa ad the tasks Figure 4. Compariso of makespa ad the umber of VMs 92

7 As show i figure 3, there are a umber of icreasig requests. As a result, the average umbers of requests beig made are progressig uder the same desig specificatios [9, 10, 11, ad 12]. Cosequetly, ABC_LJF ca be said to be effective withi the required schedulig o the full system [12, 13]. As for the secod experimet, there is a expoetial decay of makespa with the umber of VMs. I the same desig show, the previous coclusio still prevails. 3. CONCLUSION As the paper idicates, ABC cotrolled algorithm is see to be suitable for solutios surroudig VM schedulig maagemet so that the tasks are scheduled i the right maer ad eeds. This goes uder the adustable features i Cloud Computig. As these parameters are optimized, the stability of the system still prevails. This allows the system to operate with optimum utility. It is the imperative to state that ABC algorithm is good for Cloud Computig ad its eviromet uder the utility of the required parameters i a maer that the tasks are hadled with utmost utility. This stability makes the system to works without crashig i the maers of ABC_LJF eeds ad desigs. REFERENCES [1] B. Kruekaew, W. Kimpa, Virtual Machie Schedulig Maagemet o Cloud Computig Usig Artificial Bee Coloy, Proceedigs of the Iteratioal MultiCoferece of Egieers ad Computer Scietists, pp , [2] D.H. Kha, D. Kapgate, P.S. Prasad, A Review o Virtual Machie Maagemet Techiques ad Schedulig i Cloud Computig Iteratioal Joural of Advaced Research i Computer Sciece ad Software Egieerig, 3(12), pp , [3] S. Hadi, Advatages, Challeges ad Optimizatios of Virtual Machie Schedulig i Cloud Computig Eviromets, Iteratioal Joural of Computer Theory ad Egieerig, 4(2), [4] G. TARUN, Host Schedulig Algorithm Usig Geetic Algorithm I Cloud Computig Eviromet, Iteratioal Joural of Research i Egieerig & Techology, 1(1), [5] K. Kira, A Adaptive Algorithm For Dyamic Priority Based Virtual Machie Schedulig I Cloud, Iteratioal Joural of Computer Sciece Issues, 9(6), [6] I. Moschakis, H. Karatza, Performace ad Cost evaluatio of Gag Schedulig i a Cloud Computig System with Job Migratios ad Starvatio Hadlig, Thessaloiki: Aristotle Uiversity of Thessaloiki, 2013 [7] N. Ramkumar, Efficiet Resource Utilizatio Algorithm (ERUA) for Service Request Schedulig i Cloud, Iteratioal Joural of Egieerig ad Techology, 5(2), [8] V. Vigesh, K.K. Sedhil, N. Jaisakar, Resource maagemet ad schedulig i cloud eviromet, Iteratioal Joural of Scietific ad Research Publicatios, 3(6), [9] K. Rasmi, V. Vive, Resource Maagemet Techiques i Cloud Eviromet - A Brief Survey, Iteratioal Joural of Iovatio ad Applied Studies, 2(4), [10] S.P. Abirami, R. Shalii, Liear Schedulig Strategy for Resource allocatio i Cloud Eviromet, Iteratioal Joural o Cloud Computig ad Architecture, 2(1), [11] S. Paulus, U. Riema, A Approach for a Busiess-drive Cloud-compliace Aalysis Coverig Public Sector Process Improvemet Requiremets, Iteratioal Joural of Maagig Public Sector Iformatio ad Commuicatio Techologies (IJMPICT), Vol. 4, No. 3, pp. 1-13, [12] R. Saii, Idu, EFFICIENT JOB SCHEDULING OF VIRTUAL MACHINES IN CLOUD COMPUTING, Iteratioal Joural of Advaced Research i Computer ad Commuicatio Egieerig, pp , [13] S. Hashemi, Cloud computig techology for E-govermet architecture, Iteratioal Joural i Foudatios of Computer Sciece & Techology (IJFCST), Vol. 3, No.6, pp ,