human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "design and analysis of optimal threshold offloading oto algorithm for lte femtocell macrocell networks"):
  Abstract: LTE femtocells have been widely deployed to increase network capacity and to offload mobile data traffic from macrocells. While cellular users' mobility behaviors are taken into consideration, a dilemma is formed: Should a User Equipment (UE) either handover into a femtocell or keep the current connection with a macrocell? Indeed, various user mobility behaviors may incur significant signaling overhead and degrade femtocell offloading capability due to frequent handover in/out femtocells. To address this dilemma, in this paper we propose an Optimal Threshold Offloading (OTO) algorithm considering the tradeoff between the signaling overhead and femtocell offloading capability. We develop an analytical model and define two performance metrics to quantify the tradeoff. The proposed model not only models user mobility behaviors but also captures femtocell offloading benefits, and shed light on their fundamental relationship. The correctness of analytical model and simulation model are cross-validated by extensive ns2 simulations. Both analytical and simulation results demonstrate that the OTO algorithm can significantly reduce signaling overhead at the minor cost of femtocell offloading capability. The results enable wide applicability in various scenarios, and therefore, have important theoretical significance. Moreover, the analytical results provide a quick way to evaluate signaling overhead and offloading capability in LTE networks without wide deployment, saving on cost and time.

Includes members:
  Member "handover between macrocell and femtocell for umts based networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adaptive resource management for multimedia applications in femtocellular and macrocellular networks")
  Member "femtocell networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")

Question: Please tell me which class the source paper 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)