Data processing: artificial intelligence – Fuzzy logic hardware – Analog fuzzy computer
Reexamination Certificate
2000-07-12
2004-07-20
Starks, Jr., Wilbert L. (Department: 2121)
Data processing: artificial intelligence
Fuzzy logic hardware
Analog fuzzy computer
C706S004000, C706S008000, C700S050000
Reexamination Certificate
active
06766309
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to determining at least one type of link in a communication channel by evaluating at least one network statistical parameter using fuzzy logic.
2. Description of the Related Art
Portable computing devices, such as personal digital assistants (PDAs), palmtops, handheld personal computers (PCs), pen-based PCs, and laptops, have become popular in recent years. In addition, with the development of wireless communication technologies, wireless products ranging from local area networks (LAN) to wide area networks (WAN) are available commercially. Accordingly, wireless computing, wireless communication, and wireless networks are becoming common in the daily life. This naturally leads to hybrid communication environments in which both the wired and wireless communication links exist.
The Mobile Internet protocol has been developed as a standard for provisioning the current wired Internet with wireless accessibility, see C. E. Perkins,
Mobile IP: Design Principles and Practice,
Addison-Wesley: Reading, 1997. Mobile ad hoc networks (MANETs) have also been described, see Corson et al., “
Mobile Ad Hoc Networking
(
MANET
):
Routing Protocol Performance Issues and Evaluation Considerations,
” Request for Comments (RFC) 2501, January 1999. Research efforts have focused on IP protocol layer problems such as mobile IP and routing protocols in MANET, as described in Broch et al., “
A Performance Comparison of Multi
-
Hop Wireless Ad Hoc Network Routing Protocols,
” In Proceedings of the Fourth Annual ACM/IEEE International Conference on Mobile Computing and Networking, ACM, Dallas, Tex., October 1998, and on the transport layer, such as TCP performance in wireless networks, see Chandran et al., “
A Feedback Based Scheme for Improving TCP Performance in Ad
-
Hoc Wireless Networks,
” In
Proceedings of the
18
th
International Conference on Distributed Computing Systems
(
ICDCS'
98), Amsterdam, May 26-29, 1998, and Gerla et al., “
TCP Over Wireless Multihop Protocols: Simulation and Experiments,
” In
Proceedings of IEEE ICC'
99, Vancouver, Canada, Jun. 6-10, 1999.
Fuzzy logic was first introduced by L. A. Zadeh in 1965, as described in L. A. Zadeh, “
Fuzzy Sets,
” Information and Control, Vol. 8, pp. 338-353, 1965 and it has since been widely used to construct intelligent systems. Fuzzy logic with its intrinsic nonlinearity has similarity with the reasoning conducted by human beings, such as computing with words, see L. A. Zadeh, “
Fuzzy Logic
-
Computing With Words,
” IEEE Trans. on Fuzzy Systems, Vol. 4, No. 2, pp. 104-111, 1996. A key feature of fuzzy logic is that it can deal with the uncertainties that exist in physical systems.
U.S. Pat. No. 5,687,290 describes an apparatus and method for monitoring and controlling a communications network using fuzzy logic. The apparatus includes a network monitor coupled to the communications network and provides numeric data representative of at least one operating parameter of the communications network. A fuzzifier module is coupled to the network monitor and to convert the numeric data into fuzzy input data. A fuzzy inference engine is coupled to the fuzzifier module and processes the fuzzy input data according to at least one fuzzy rule to provide fuzzy output data representative of control actions to affect a desired state of the communications netowrk. A defuzzifier module is coupled to the fuzzy inference engine and converts the fuzzy output data into numeric data which may be used by a network controller to control at least one network parameter. The apparatus may also include a user interface and a display to allow the fuzzy input data and the fuzzy output data to be displayed to a user.
U.S. Pat. No. 5,822,301 describes a method for evaluating performance of communication links with fuzzy logic. Two possible lines are thereby evaluated with fuzzy logic with respect to their performance, their time behavior and their dependability aspects. The intermediate variables derived therefrom are processed with a principal rule set to form a weighting factor for the respective line. A routing method that is to define the shortest path for a communication connection employs this weighting factor in order to determine the corresponding connection.
Values of round-trip time (RTT) can be used to identify characteristics of communication links. Generally speaking, RTT is the interval between the sending of a packet and receiving its acknowledgement and includes both network propagation delays, such as router-queue delay and link delay, and host-processing delay, such as the time spent at the sender and receiver processing the packet and acknowledgement. Typically, the propagation delay is a significant contributor to the round-trip time. It is described in “
Improving Round
-
Trip Time Estimates in Reliable Transport Protocols,
” ACM Trans. on Computer Systems, Vol. 9, No. 4, pp. 364-373, November 1991 that RTTs via wide area networks with wired links show Poisson distribution characteristics.
Measurements of round trip time (RTT) are used in TCP. TCP dynamically sets an appropriate retransmission timeout value based on the RTT measurement. A conventional method for measuring RTT in TCP is as follows. Every time TCP sends a datagram, it records the time instant. When an acknowledgement (ACK) for that datagram arrives, TCP again gets the time instant and takes the difference between the two times as the current RTT value. This method has the disadvantage referred to as the retransmission ambiguity problem. In the method, an ACK acknowledges the receipt of a datagram instead of a transmission. Accordingly, whenever a datagram is retransmitted and then an ACK is received at the sender, it is impossible to determine if the ACK should be associated with the first or the second transmission of the datagram. One solution to the retransmission ambiguity problem has been described by Karn et al. in “
Improving Round
-
Trip Time Estimates in Reliable Transport Protocols,
” ACM Trans. on Computer Systems, Vol. 9, No. 4, pp. 364-373, November 1991 in which the retransmission ambiguity problem is solved by simply not taking samples of RTT whenever TCP retransmits a datagram. This method only measures RTT for datagrams that have been sent without retransmission.
It is desirable to provide a method for evaluating statistical properties of network quality of service parameters using fuzzy logic for determining if communication links in a communication channel are wired links or include a wireless link which results can be used to adapt network based applications.
SUMMARY OF THE INVENTION
It has been found that wired links and wireless links have different network statistical patterns. The system of the present invention includes a fuzzy reasoning engine which uses quality of service parameters relating to the network statistical patterns as fuzzy inputs, such as a mean value and variance of a round trip time, and determines a confidence about the existence of wireless links in the communication channel as the output. The system can be used for adaptive application scenarios. In a unicast client-server application scenario, the server provides different services to different clients depending on whether a wireless link was detected during the connection establishment phase. In a multicast scenario, a new multicast session is created by a session manager in addition to the original one depending on whether a wireless link was detected during a request to join the multicast session. The new multicast session carries lower data traffic from and to the participants whose communication path includes the wireless link(s).
The invention will be more fully described by reference to the following drawings.
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patent: 5767785 (1998-06-01), Goldberg
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Cheng Liang
Marsic Ivan
Booker Kelvin
Mathews, Collins, Shepherd & Mckay, P.A.
Starks, Jr. Wilbert L.
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