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: "energy aware demand selection and allocation for real time iot data trading"
  Abstract: Personal data is a new economic asset that individuals can trade to generate revenue on the emerging data marketplaces. This paper introduces a decentralized marketplace for trading personal sensing data, generated by resource-constrained IoT devices in real-time. To design such a marketplace, we consider both computing and economic aspects. The computing approach focuses on creating a blockchain-based decentralized marketplace that ensures the integrity of trade agreements. We leverage smart contracts to guarantee that the participants automatically conform to the terms of the agreements without involving a mediator. The economic approach maximizes the marketplace participant's utility to improve the sustainability and usability of the marketplace. To this end, we present a blockchain framework underpinned by an Energy-Aware Demand Selection and Allocation (EDSA) mechanism that optimizes the revenue for the seller and fulfills the buyer's demands. We use a normalized revenue-based greedy algorithm for solving the EDSA problem. Moreover, we present a proof-of-concept implementation of the blockchain framework in Ethereum. Through extensive simulations, we separately evaluate the impact of buyer's demand on the battery drainage of the IoT devices under different scenarios. We observe that increasing battery capacity for IoT devices on the seller end is more strongly related to revenue generation than increasing the number of devices.

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.CR(Cryptography and Security)