human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "reca an efficient reconfigurable cache architecture for storage systems with online workload characterization"
  Abstract: In recent years,  Solid-State Drives  (SSDs) have gained tremendous attention in computing and storage systems due to significant performance improvement over  Hard Disk Drives  (HDDs). The cost per capacity of SSDs, however, prevents them from entirely replacing HDDs in such systems. One approach to effectively take advantage of SSDs is to use them as a caching layer to store performance critical data blocks in order to reduce the number of accesses to HDD-based disk subsystem. Due to characteristics of Flash-based SSDs such as limited write endurance and long latency on write operations, employing caching algorithms at the  Operating System  (OS) level necessitates to take such characteristics into consideration. Previous OS-level caching techniques are optimized towards only one type of application, which affects both generality and applicability. In addition, they are not adaptive when the workload pattern changes over time. This paper presents an efficient  Reconfigurable Cache Architecture  (ReCA) for storage systems using a comprehensive workload characterization to find an optimal cache configuration for I/O intensive applications. For this purpose, we first investigate various types of I/O workloads and classify them into five major classes. Based on this characterization, an optimal cache configuration is presented for each class of workloads. Then, using the main features of each class, we continuously monitor the characteristics of an application during system runtime and the cache organization is reconfigured if the application changes from one class to another class of workloads. The cache reconfiguration is done online and workload classes can be extended to emerging I/O workloads in order to maintain its efficiency with the characteristics of I/O requests. Experimental results obtained by implementing ReCA in a 4U rackmount server with SATA 6Gb/s disk interfaces running Linux 3.17.0 show that the proposed architecture improves performance and lifetime up to 24 and 33 percent, respectively.

Connected through hyperedge HE-1 (induced by source paper "automating distributed tiered storage management in cluster computing"):
  with members:
    - "competitive caching with machine learned advice"
    - "a unified approach to interpreting model predictions"
    - "xgboost a scalable tree boosting system"
    - "why should i trust you explaining the predictions of any classifier"
    - "compacting transactional data in hybrid oltp olap databases"
    - "interactive analytical processing in big data systems a cross industry study of mapreduce workloads"
    - "competitive paging algorithms"

Connected through hyperedge HE-2 (induced by source paper "evaluating reliability of ssd based i o caches in enterprise storage systems"):
  with members:
    - "architectural techniques for improving nand flash memory reliability"
    - "investigating power outage effects on reliability of solid state drives"
    - "lbica a load balancer for i o cache architectures"
    - "eci cache a high endurance and cost efficient i o caching scheme for virtualized platforms"
    - "errors in flash memory based solid state drives analysis mitigation and recovery"
    - "error characterization mitigation and recovery in flash memory based solid state drives"

Connected through hyperedge HE-3 (induced by source paper "modeling impact of human errors on the data unavailability and data loss of storage systems"):
  with members:
    - "evaluating impact of human errors on the availability of data storage systems"
    - "investigating power outage effects on reliability of solid state drives"
    - "eci cache a high endurance and cost efficient i o caching scheme for virtualized platforms"
    - "partial mds codes and their application to raid type of architectures"
    - "threats of human error in a high performance storage system problem statement and case study"

Connected through hyperedge HE-4 (induced by source paper "eci cache a high endurance and cost efficient i o caching scheme for virtualized platforms"):
  with members:
    - "investigating power outage effects on reliability of solid state drives"
    - "error characterization mitigation and recovery in flash memory based solid state drives"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.PF(Performance)