Optimize the Server Provisioning and Request Dispatching in Distributed Memory Cache Services

The distributed cache system contains a group of servers caching different contents based on consistent hashing. The dynamic provisioning of servers helps to improve the system efficiency, which leads to a reduction of energy cost. We first measure the cache hit rate, request batching effect and cache warm-up time of the system through experiments, considering that they can affect the system performance and efficiency. Then we formulate a stochastic network optimization problem, which aims at achieving objectives on the queue stability, energy cost and cache hit rate simultaneously, through the dynamic control of server activeness and request dispatching. The problem is transformed into a minimization problem in each time slot, which is further addressed through the proposed efficient online algorithm based on dynamic programming. Moreover, we improve the scheme with several practical considerations in the scheme implementation. Finally, the proposed algorithm and the improvements are evaluated through extensive experiments.

[1]  Hai Jin,et al.  Carbon-Aware Load Balancing for Geo-distributed Cloud Services , 2013, 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems.

[2]  M. Tech,et al.  Dynamic Heterogeneity-Aware Resource Provisioning in the Cloud , 2015 .

[3]  Ulas C. Kozat,et al.  Dynamic resource allocation and power management in virtualized data centers , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[4]  Jeffrey Considine,et al.  Simple Load Balancing for Distributed Hash Tables , 2003, IPTPS.

[5]  J. Stuart Hunter,et al.  The exponentially weighted moving average , 1986 .

[6]  Eitan Frachtenberg,et al.  Many-core key-value store , 2011, 2011 International Green Computing Conference and Workshops.

[7]  Yitzhak Birk,et al.  Replicate and Bundle (RnB) -- A Mechanism for Relieving Bottlenecks in Data Centers , 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.

[8]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[9]  Cho-Li Wang,et al.  Optimization and stabilization of composite service processing in a cloud system , 2013, 2013 IEEE/ACM 21st International Symposium on Quality of Service (IWQoS).

[10]  Prashant J. Shenoy,et al.  Dynamic Provisioning of Multi-tier Internet Applications , 2005, Second International Conference on Autonomic Computing (ICAC'05).

[11]  Lei Ying,et al.  Map task scheduling in MapReduce with data locality: Throughput and heavy-traffic optimality , 2013, INFOCOM.

[12]  Minghua Chen,et al.  Simple and effective dynamic provisioning for power-proportional data centers , 2011, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[13]  Jianping Pan,et al.  Resource allocation and request handling for user-aware content retrieval in the cloud , 2014, 39th Annual IEEE Conference on Local Computer Networks.

[14]  Xiaomin Zhu,et al.  Real-Time Tasks Oriented Energy-Aware Scheduling in Virtualized Clouds , 2014, IEEE Transactions on Cloud Computing.

[15]  Joseph Issa,et al.  Hadoop and memcached: Performance and power characterization and analysis , 2012, Journal of Cloud Computing: Advances, Systems and Applications.

[16]  Amar Phanishayee,et al.  FAWN: a fast array of wimpy nodes , 2009, SOSP '09.

[17]  David R. Karger,et al.  Web Caching with Consistent Hashing , 1999, Comput. Networks.

[18]  Guillaume Pierre,et al.  Wikipedia workload analysis for decentralized hosting , 2009, Comput. Networks.

[19]  Veljko M. Milutinovic,et al.  Distributed shared memory: concepts and systems , 1997, IEEE Parallel Distributed Technol. Syst. Appl..

[20]  Ming Mao,et al.  A Performance Study on the VM Startup Time in the Cloud , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[21]  Bo Li,et al.  On Arbitrating the Power-Performance Tradeoff , 2013 .

[22]  R. Srikant,et al.  Stochastic models of load balancing and scheduling in cloud computing clusters , 2012, 2012 Proceedings IEEE INFOCOM.

[23]  Jianping Pan,et al.  Optimize the dynamic provisioning and request dispatching in distributed memory cache services , 2014, 2014 IEEE 22nd International Symposium of Quality of Service (IWQoS).

[24]  Tony Tung,et al.  Scaling Memcache at Facebook , 2013, NSDI.

[25]  Jignesh M. Patel,et al.  Wimpy node clusters: what about non-wimpy workloads? , 2010, DaMoN '10.

[26]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.

[27]  Bo Li,et al.  On arbitrating the power-performance tradeoff in SaaS clouds , 2013, 2013 Proceedings IEEE INFOCOM.

[28]  Wolf-Dietrich Weber,et al.  Power provisioning for a warehouse-sized computer , 2007, ISCA '07.