On the self-similar nature of Ethernet traffic
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Communications of the ACM
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
A practical approach for multimedia traffic modeling
Broadband communications
Dynamical behavior of rate-based flow control mechanisms
ACM SIGCOMM Computer Communication Review
An Active Network Approach to Efficient Network Management
IWAN '99 Proceedings of the First International Working Conference on Active Networks
Application of the M/Pareto Process to Modeling Broadband Traffic Streams
ICON '99 Proceedings of the 7th IEEE International Conference on Networks
Broadband traffic modeling: simple solutions to hard problems
IEEE Communications Magazine
Active distributed management for IP networks
IEEE Communications Magazine
Programmable agents for flexible QoS management in IP networks
IEEE Journal on Selected Areas in Communications
The SwitchWare active network architecture
IEEE Network: The Magazine of Global Internetworking
ACC: using active networking to enhance feedback congestion control mechanisms
IEEE Network: The Magazine of Global Internetworking
A taxonomy for congestion control algorithms in packet switching networks
IEEE Network: The Magazine of Global Internetworking
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Recent measurements of local and wide-area network traffic have proven that the widely used Markovian process models cannot be applied for today's network traffic. If the traffic were Markovian process, the traffic's burst length would be smoothed by averaging over a long time scale contradicting with the observations of today's traffic characteristics. Measurements of real traffic also prove that traffic burstiness is present on a wide range of time scales. Traffic that is bursty on many or all time scales can be characterized statistically using the concept of long-range dependency. Long-range dependent traffic has noticeable bursts, long periods with extremely high values on all time creating traffic congestions. Several conventional methods have been implemented to avoid congestion, but they are not responsive enough to the varying transmission capacity and network delay in high-speed networks. A new research direction, programmable networking, offers a more promising solution for congestion control. Traditional packet networks perform only the processing necessary to forward packets toward their destination. As computing power becomes cheaper, more and more functionality can be deployed inside the network. Programmable networks support dynamic modification of the network software and hardware to manipulate the network's behavior. A special way of network programmability is when special programs called mobile or software agents are carried in the packets to the routers. Software agents are loaded, executed, migrated, and suspended in order to implement some network functions. Software agents provide the highest possible degree of flexibility in congestion control. They can carry congestion-specific knowledge into the network at locations where it is needed, rather than transferring information to the sending hosts as it happens in traditional flow control solutions. In our paper, we propose a new programmable network architecture using software agents that can reduce the harmful consequences of congestions due to aggregated bursty traffic, such as packet losses, extremely long response times, etc.