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: "no justified complaints on fair sharing of multiple resources"
  Abstract: Fair allocation has been studied intensively in both economics and computer science, and fair sharing of resources has aroused renewed interest with the advent of virtualization and cloud computing. Prior work has typically focused on mechanisms for fair sharing of a single resource. We provide a new definition for the simultaneous fair allocation of multiple continuously-divisible resources. Roughly speaking, we define fairness as the situation where every user either gets all the resources he wishes for, or else gets at least his entitlement on some bottleneck resource, and therefore cannot complain about not getting more. This definition has the same desirable properties as the recently suggested dominant resource fairness, and also handles the case of multiple bottlenecks. We then prove that a fair allocation according to this definition is guaranteed to exist for any combination of user requests and entitlements (where a user's relative use of the different resources is fixed). The proof, which uses tools from the theory of ordinary differential equations, is constructive and provides a method to compute the allocations numerically.

Connected through hyperedge HE-1 (induced by source paper "efficient multi resource multi unit vcg auction"):
  with members:
    - "non monetary fair scheduling a cooperative game theory approach"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"
    - "fair allocation without trade"
    - "computationally feasible vcg mechanisms"
    - "optimal solutions for multi unit combinatorial auctions branch and bound heuristics"

Connected through hyperedge HE-2 (induced by source paper "on the cluster admission problem for cloud computing"):
  with members:
    - "overcommitment in cloud services bin packing with chance constraints"
    - "era a framework for economic resource allocation for the cloud"
    - "truthful online scheduling with commitments"
    - "fixed and market pricing for cloud services"
    - "fair allocation without trade"
    - "finding approximate pomdp solutions through belief compression"
    - "nonapproximability results for partially observable markov decision processes"

Connected through hyperedge HE-3 (induced by source paper "multi resource fair allocation with bounded number of tasks in cloud computing systems"):
  with members:
    - "enhanced cluster computing performance through proportional fairness"
    - "multi resource fairness objectives algorithms and performance"
    - "dominant resource fairness in cloud computing systems with heterogeneous servers"
    - "fair allocation without trade"

Connected through hyperedge HE-4 (induced by source paper "enhanced cluster computing performance through proportional fairness"):
  with members:
    - "dominant resource fairness in cloud computing systems with heterogeneous servers"
    - "fair allocation without trade"

Connected through hyperedge HE-5 (induced by source paper "multi resource fairness objectives algorithms and performance"):
  with members:
    - "enhanced cluster computing performance through proportional fairness"
    - "fair allocation without trade"

Connected through hyperedge HE-6 (induced by source paper "dominant resource fairness in cloud computing systems with heterogeneous servers"):
  with members:
    - "fair allocation without trade"
    - "an axiomatic theory of fairness in network resource allocation"
    - "understanding fairness and its impact on quality of service in ieee 802 11"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-7 (induced by source paper "polyhedral clinching auctions and the adwords polytope"):
  with members:
    - "clinching auctions beyond hard budget constraints"
    - "efficiency guarantees in auctions with budgets"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"
    - "clinching auctions with online supply"
    - "prior free auctions for budgeted agents"
    - "on multiple round sponsored search auctions with budgets"
    - "bayesian mechanism design for budget constrained agents"
    - "incentive compatible budget elicitation in multi unit auctions"

Connected through hyperedge HE-8 (induced by source paper "mechanism design for fair division"):
  with members:
    - "incentive compatible two player cake cutting"
    - "fair allocation without trade"
    - "truthful fair division"
    - "general auction mechanism for search advertising"

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.DC(Distributed, Parallel, and Cluster Computing)