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 competitiveness power control in relay assisted interference body networks"
  Abstract: Recent advances in microelectronics have enabled the realization of Wireless Body Area Networks (WBANs). Increasing the transmission power of WBAN's nodes improves the Signal to Interference plus Noise Ratio (SINR), and hence decreases the bit error probability. However, this increase may impose interference on nodes within the same WBAN or on other nodes of nearby coexisting WBANs, as these WBANs may use similar frequencies. Due to co-channel interference, packet collisions and retransmissions are increased and consequently, the power consumption of the individual WBANs may increase correspondingly. To address this problem, we adopt the approach of two-hop cooperative communication due to its efficiency in power savings. In this paper, we propose a cooperative power control-based algorithm, namely, IMA, for interference mitigation among the individual sensors of a single WBAN. Basically, our approach selects an optimal set of relays from the nodes within each WBAN to mitigate the interference. Thus, IMA selection criterion relies on the best channel, namely, SINR and power conditions to select the set of best relays. The experimental results illustrate that IMA improves the SINR, the power efficiency and extends WBAN lifetime. In addition, the results illustrate that IMA lowers the bit error probability and improves the throughput.

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.NI(Networking and Internet Architecture)