Autonomic swarms for regenerative and collaborative networking

The exponential growth of web services have necessitate the evolution of network infrastructures to meet this challenge. We envision the myriad of Internet connected devices coming together to provide a robust and reliable service network. We propose an Autonomous Swarm Network to provide autonomic capabilities to achieve our service quality goals while coping with complex and changing requirements of today's web services particularly cost-effectiveness versus service assurance. To create a high-resilient network, we incorporated features of self-management, self-configuration, self-optimization and self-healing strategies. Using a combination of fast-flux service networks, autonomic management and swarm algorithms, it becomes possible to build cost effective assurance for existing web services. We demonstrate the feasibility of our solution using the Nanyang Analytics Supercomputer with more than 20,000 agents against varying loads. We've also simulated algorithms and reconfiguration strategies. We subsequently developed a prototype swarm network of up to 500 machines.

[1]  Jeffrey O. Kephart,et al.  An architectural approach to autonomic computing , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[2]  Nora Cuppens-Boulahia,et al.  Data Privacy Management and Autonomous Spontaneous Security , 2014, Lecture Notes in Computer Science.

[3]  Hamed Shah-Hosseini,et al.  Problem solving by intelligent water drops , 2007, 2007 IEEE Congress on Evolutionary Computation.

[4]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[5]  Kamil Saraç,et al.  A survey on the design, applications, and enhancements of application-layer overlay networks , 2010, CSUR.

[6]  Ravinder Bahl,et al.  Comparative Study and Analysis of Different Types of Buffering in Go-Back-2 Network in NS2 , 2011, 2011 UkSim 13th International Conference on Computer Modelling and Simulation.

[7]  Thomas E. Anderson,et al.  Phalanx: Withstanding Multimillion-Node Botnets , 2008, NSDI.

[8]  Noria Foukia,et al.  DDoS Defense Mechanisms: A New Taxonomy , 2009, DPM/SETOP.

[9]  Sheela Ganesh Thorenoor,et al.  Analysis of IP Network for different Quality of Service , 2011 .

[10]  J. G. Wardrop,et al.  Some Theoretical Aspects of Road Traffic Research , 1952 .

[11]  M. Kodialam,et al.  Oblivious Routing of Highly Variable Traffic in Service Overlays and IP Backbones , 2009, IEEE/ACM Transactions on Networking.

[12]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[13]  Murat Kantarcioglu,et al.  A Game-Theoretical Approach for Finding Optimal Strategies in a Botnet Defense Model , 2010, GameSec.

[14]  Brij B. Gupta,et al.  A Recent Survey on DDoS Attacks and Defense Mechanisms , 2011 .

[15]  Roch Guérin,et al.  On the robustness of router-based denial-of-service (DoS) defense systems , 2005, CCRV.

[16]  Thorsten Holz,et al.  As the net churns: Fast-flux botnet observations , 2008, 2008 3rd International Conference on Malicious and Unwanted Software (MALWARE).