Abstract
This paper proposes a hierarchical control system in grid virtual organization. The hierarchical system can be decomposed into multiple application groups, which can be further decomposed into multiple applications. At the top of the hierarchy, the global controller controls the gross allocation of resources to the groups. At the next level down, the group controller coordinates the local deployments of all applications that consume the local allocation of resources. At the lowest level, the local controllers adjust the local resource usages to optimize the utility of single application. The hierarchical control system considers all applications and coordinates all layers of grid architecture upon any changes. According to different time granularity, we adopt a different control scheme. The global control considers all applications and coordinates three layers of grid architecture in response to large system changes at coarse time granularity, while local control adapts a single application to small changes at fine granularity. This paper adopts utility-driven cross layer optimization for grid applications to find a system wide optimization and solves the cross-layer optimization by using pricing based decomposition. A set of hierarchical utility functions is used to measure the performance of the grid system that follows the system, group and application hierarchy. This paper uses total utility to measure the overall quality of grid system. The experiments are conducted to test the performance of the hierarchical control algorithms.
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References
Foster I (2006) Globus toolkit version 4: software for service-oriented systems. In: IFIP international conference on network and parallel computing. LNCS, vol 3779. Springer, Berlin, pp 2–13
Yuan W, Nahrstedt K, Adve S, Jones D, Kravets R (2006) GRACE-1: cross-layer adaptation for multimedia quality and battery energy. IEEE Trans Mobile Comput 5(7):799–815
Sachs D, Yuan W, Hughes C, Harris A, Adve S, Jones D, Kravets R, Nahrstedt K (2003) GRACE: a cross-layer adaptation framework for saving energy. IEEE Comput 36(12):50–51
Yuan W, Nahrstedt K, Adve S, Jones D, Kravets R (2003) Design and evaluation of a cross-layer adaptation framework for mobile multimedia systems. In: Proc of SPIE/ACM multimedia computing and networking conference (MMCN’03), Santa Clara, CA, 2003, pp 1–13
Rohloff K, Gabay Y, Ye J, Schantz RE (2007) Scalable, distributed, dynamic resource management for the ARMS distributed real-time embedded system. In: IEEE IPDPS 2007, pp 1–7
Rohloff K, Ye J, Loyall J, Schantz R (2006) A hierarchical control system for dynamic resource management, In: 2006 IEEE real-time and embedded technology and applications symposium (RTAS 2006), Work in progress symposium, San Jose, CA, April 7 2006
Al-Ali R, Rana O, Walker D, Jha S, Sohail S (2002) G-QoSM: grid service discovery using QoS properties. Comput Inf J 21(4):363–382, Special issue on grid computing
Al-Ali R, ShaikhAli A, Rana O, Walker D (2003) Supporting QoS-based discovery in service-oriented grids. In: Proceedings of IEEE heterogeneous computing workshop (HCW’03), Nice, France, 2003
Nam DS, Youn C-H (2004) QoS-constrained resource allocation for a grid-based multiple source electrocardiogram application. In: ICCSA 2004, LNCS 3043, 2004, pp 352–359
Foster I, Fidler M, Roy A, Sander V, Winkler L (2004) End-to-end quality of service for high-end applications. Elsevier Comput Commun J 27(14):1375–1388
Ghosh S, Rajkumar R, Hansen J, Lehoczky J (2003) Scalable resource allocation for multi-processor QoS optimization. In: Proceedings of 23rd international conference on distributed computing systems, May 2003, pp 174–183
Ghosh S, Rajkumar R, Hansen J, Lehoczky J (2004) Integrated resource management and scheduling with multi-resource constraints. In: Proceedings of 25th IEEE real-time systems symposium, 2004
Lee C, Lehoczky J, Rajkumar R, Siewiorek D (1999) On quality of service optimization with discrete QoS options. In: Proceedings of the IEEE real-time technology and applications symposium, June 1995
Dŏgan A, Ozguner F (2002) Scheduling independent tasks with QoS requirements in grid computing with time-varying resource prices. In: Proceedings of GRID 2002. LNCS, vol 2536. Springer, Berlin, pp 58–69
Buyya R, Murshed R, Abramson D (2002) A deadline and budget constrained cost-time optimization algorithm for scheduling task farming applications on global grids. In: Int conf on parallel and distributed processing techniques and applications, Las Vegas, NV, USA, June 2002
Li C, Li L (2005) A distributed utility-based two level market solution for optimal resource scheduling. Comput Grid, Parallel Comput 31(3–4):332–351
Li C, Li L (2004) The use of economic agents under price driven mechanism in grid resource management. J Syst Archit 50(9):521–535
Li C, Li L (2003) Applying agents to build grid service management. J Netw Comput Appl 26(4):323–340
Li C, Li L (2004) Competitive proportional resource allocation policy for computational grid. Future Gen Comput Syst 20(6):1041–1054
Li C, Li L (2004) Agent framework to support computational grid. J Syst Softw 70(1–2):177–187
Li C, Li L (2006) Multi economic agent interaction for optimizing the aggregate utility of grid users. Comput Grid, Appl Intell 25(2):147–158
BRITE. http://www.cs.bu.edu/brite
Luh PB, Hoitomt DJ (1993) Scheduling of manufacturing systems using the Lagrangian relaxation technique. IEEE Trans Autom Control 38(7):1066–1079
Luh PB, Zhao YW, Thakur LS (2000) Lagrangian relaxation neural networks for job shop scheduling. IEEE Trans Robot Autom 16(1):78–88
Lai K, Rasmusson L, Adar E, Sorkin S, Zhang L, Huberman BA (2005) Tycoon: An implementation of a distributed, market-based resource allocation system. Multiagent Grid Syst 1(3):169–182
Roy N, Das SK, Basu K, Kumar (2005). Enhancing availability of grid computational services to ubiquitous computing applications. In: Proceedings of 19th IEEE International parallel and distributed processing symposium, 2005
Patriksson M (2008) A survey on the continuous resource allocation problem. Eur J Oper Res 185:1–46
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Li, C., Li, L. Hierarchical control policy for dynamic resource management in grid virtual organization. J Supercomput 49, 190–218 (2009). https://doi.org/10.1007/s11227-008-0231-z
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DOI: https://doi.org/10.1007/s11227-008-0231-z