Effective memory reusability based on user distributions in a cloud architecture to support manufacturing ubiquitous computing

Ubiquitous service in manufacturing sites prompts the need for cloud-based infrastructure. However, without proper load balance algorithms, implementation of cloud infrastructure would be very costly. This study proposed an effective load-adjusted-profile-oriented (LAPO) allocation algorithm for enhancing memory reusability and improving the performance of servers by balancing their workloads. The LAPO is an enhanced cluster-based algorithm that can place users with the same usage patterns into the same servers to boost memory efficiency. The current study also presented an incremental update algorithm for monitoring and maintaining the reusability of memory. The experiment was conducted on a manufacturing enterprise resource planning which provided ubiquitous service to managers.

[1]  Rajiv Roy Using Different Encryption Techniques for Load Balancing with Cluster-Based Storage , 2013, IEEE Potentials.

[2]  A. L. Narasimha Reddy,et al.  Evaluation of Data and Request Distribution Policies in Clustered Servers , 1999, HiPC.

[3]  T. Kokilavani,et al.  An Ant Colony Optimization Based Load Sharing Technique for Meta Task Scheduling in Grid Computing , 2012, ACITY.

[4]  Azizkhan F Pathan,et al.  A Load Balancing Model Based on Cloud Partitioning for the Public Cloud , 2014 .

[5]  Ravi Iyer,et al.  Modeling virtual machine performance: challenges and approaches , 2010, PERV.

[6]  Dongfeng Zhao,et al.  A Dynamic Dispatcher-Based Scheduling Algorithm on Load Balancing for Web Server Cluster , 2010, WISM.

[7]  R. Chawla,et al.  The Stealth distributed scheduler , 1991, [1991] Proceedings. 11th International Conference on Distributed Computing Systems.

[8]  Yuqing Zhang,et al.  A Client-Based and Server-Enhanced Defense Mechanism for Cross-Site Request Forgery , 2010, RAID.

[9]  Miron Livny,et al.  Load Balancing in Homogeneous Broadcast Distributed Systems , 1982, SIGMETRICS.

[10]  Ming-Shien Cheng,et al.  User Distributions in N-Tier Platform with Effective Memory Reusability , 2013, MIWAI.

[11]  Ping-Yu Hsu,et al.  Profile Oriented User Distributions in Enterprise Systems with Clustering , 2004, NPC.

[12]  João P. Cachopo,et al.  Exploring Data Locality for Clustered Enterprise Applications , 2013, DEXA.

[13]  Mohammad Kazem Akbari,et al.  A predictive and probabilistic load-balancing algorithm for cluster-based web servers , 2011, Appl. Soft Comput..

[14]  Muhammad El-Taha,et al.  Optimal allocation of servers and processing time in a load balancing system , 2010, Comput. Oper. Res..

[15]  James E. Smith,et al.  Data Cache Prefetching Using a Global History Buffer , 2004, 10th International Symposium on High Performance Computer Architecture (HPCA'04).

[16]  Mukesh Singhal,et al.  Effect of network latency on load sharing in distributed systems , 2006, J. Parallel Distributed Comput..

[17]  L. D. Dhinesh Babu,et al.  Honey bee behavior inspired load balancing of tasks in cloud computing environments , 2013, Appl. Soft Comput..