Proof Test of Chaos-Based Hierarchical Network Control Using Packet-Level Network Simulation

Computer networks require sophisticated control mechanisms to realize fair resource allocation among users in conjunction with efficient resource usage. To successfully realize fair resource allocation in a network, someone should control the behavior of each user by considering fairness. To provide efficient resource utilization, someone should control the behavior of all users by considering efficiency. To realize both control goals with different granularities at the same time, a hierarchical network control mechanism that combines microscopic control (i.e., fairness control) and macroscopic control (i.e., efficiency control) is required. In previous works, Aida proposed the concept of chaos-based hierarchical network control. Next, as an application of the chaos-based concept, Aida designed a fundamental framework of hierarchical transmission rate control based on the chaos of coupled relaxation oscillators. To clarify the realization of the chaos-based concept, one should specify the chaos-based hierarchical transmission rate control in enough detail to work in an actual network, and confirm that it works as intended. In this study, we implement the chaos-based hierarchical transmission rate control in a popular network simulator, ns-2, and confirm its operation through our experimentation. Results verify that the chaos-based concept can be successfully realized in TCP/IP networks. key words: chaos, hierarchical network architecture, congestion control, TCP global synchronization, TCP (transmission control protocol), RED (random early detection)

[1]  Aaron Falk,et al.  Specification for the Explicit Control Protocol (XCP) , 2007 .

[2]  Yin Zhang,et al.  On individual and aggregate TCP performance , 1999, Proceedings. Seventh International Conference on Network Protocols.

[3]  Masaki Aida Concept of Chaos-Based Hierarchical Network Control and Its Application to Transmission Rate Control , 2015, IEICE Trans. Commun..

[4]  Ness B. Shroff,et al.  The impact of imperfect scheduling on cross-Layer congestion control in wireless networks , 2006, IEEE/ACM Transactions on Networking.

[5]  Masaki Aida,et al.  Diffusion-Type Autonomous Decentralized Flow Control for End-to-End Flow in High-Speed Networks , 2005, IEICE Trans. Commun..

[6]  Mohammad Javad Yazdanpanah,et al.  IDFC: A new approach to control bifurcation in TCP/RED , 2011, J. Netw. Comput. Appl..

[7]  Tamer A. ElBatt,et al.  Joint scheduling and power control for wireless ad hoc networks , 2002, IEEE Transactions on Wireless Communications.

[8]  Cheng Jin,et al.  FAST TCP: Motivation, Architecture, Algorithms, Performance , 2006, IEEE/ACM Transactions on Networking.

[9]  Mario Gerla,et al.  Enhancing TCP fairness in ad hoc wireless networks using neighborhood RED , 2003, MobiCom '03.

[10]  V. Jacobson,et al.  Congestion avoidance and control , 1988, CCRV.

[11]  Masayuki Murata,et al.  Proposal for Autonomous Decentralized Structure Formation Based on Local Interaction and Back-Diffusion Potential , 2012, IEICE Trans. Commun..

[12]  QUTdN QeO,et al.  Random early detection gateways for congestion avoidance , 1993, TNET.

[13]  Mark Handley,et al.  Congestion control for high bandwidth-delay product networks , 2002, SIGCOMM '02.

[14]  Larry Peterson,et al.  TCP Vegas: new techniques for congestion detection and avoidance , 1994, SIGCOMM 1994.

[15]  Masaki Aida,et al.  An autonomous decentralized control for indirectly controlling system performance variable in large-scale and wide-area network , 2014, 2014 16th International Telecommunications Network Strategy and Planning Symposium (Networks).

[16]  Theodore S. Rappaport,et al.  Cross-layer design for wireless networks , 2003, IEEE Commun. Mag..

[17]  Keisuke Ito,et al.  Chaotic Behavior in Great Earthquakes –Coupled Relaxation Oscillator Model, Billiard Model and Electronic Circuit Model– , 1980 .

[18]  Mohammad Haeri,et al.  Characterization of complex behaviors of TCP/RED computer networks based on nonlinear time series analysis methods , 2007 .

[19]  Masaki Aida Using a Renormalization Group to Create Ideal Hierarchical Network Architecture with Time Scale Dependency , 2012, IEICE Trans. Commun..

[20]  Xinming Zhang,et al.  TCP Congestion Window Adaptation Through Contention Detection in Ad Hoc Networks , 2010, IEEE Transactions on Vehicular Technology.

[21]  Mung Chiang,et al.  Cross-Layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[22]  Liang Chen,et al.  Controlling chaos in Internet congestion control model , 2004 .