• Journal of Communications and Networks
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• v.6 no.1
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• pp.78-87
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• 2004

This paper presents deterministic, worst-case analysis of a queueing system whose multiple homogeneous input streams are regulated by the associated leaky buckets and the queueing system that has a single stream regulated by the jumping-window. Queueing delay averaged over all items is used for performance measure, and the worst-case input traffic and the worst-case performance are identified for both queueing systems. For the former queueing system, the analysis explores different phase relations among leaky-bucket token generations. This paper observes how the phase differences among the leaky buckets affect the worst-case queueing performance. Then, this paper relates the worst-case performance of the former queueing system with that of the latter (the single stream case, as in the aggregate streams from many users, whose item arrivals are regulated by one jumping-window). It is shown that the worst-case performance of the latter is identical to that of the former in which all leaky buckets have the same phase and have particular leaky bucket parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1116-1125
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• 1997

In this paper, the modified UPC(Usage Parameter Control) algorithm is proposed. The proposed UPC algorithm is based on Leakey Bucket algorithm and adds the characteristics of the jumping window algorithm for monitoring the average bit rate. The proposed algorithm let a cell, which is tagged by Leaky Bucket algorithm, pass through the network, if the network does not violate the average bit rate. The measuring method of window mechanism like jumping window. This paper supposes On/Off traffic source model of rthe performance evaluation and analysis of the proposed algorithm. Therefore, as simulation results, the proposed algorithm acquires more reduced results of the cell loss rate and bucket size than the Leaky Bucket algorithm.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.41-49
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• 2012

Wireless network support and extended mobile network environment with exponential growth of smart phone users allow us to utilize the network anytime or anywhere. Malicious attacks such as distributed DOS, internet worm, e-mail virus and so on through high-speed networks increase and the number of patterns is dramatically increasing accordingly by increasing network traffic due to this internet technology development. To detect the patterns in intrusion detection systems, an existing research proposed an efficient algorithm called the jumping window algorithm and analyzed approximately 2,000 patterns in Snort 2.1.0, the most famous intrusion detection system. using the algorithm. However, it is inappropriate from the number of TCAM lookups and TCAM memory efficiency to use the result proposed in the research in current environment (Snort 2.9.0) that has longer patterns and a lot of patterns because the jumping window algorithm is affected by the number of patterns and pattern length. In this paper, we simulate the number of TCAM lookups and the required TCAM size in the jumping window with approximately 8,100 patterns from Snort-2.9.0 rules, and then analyse the simulation result. While Snort 2.1.0 requires 16-byte window and 9Mb TCAM size to show the most effective performance as proposed in the previous research, in this paper we suggest 16-byte window and 4 18Mb-TCAMs which are cascaded in Snort 2.9.0 environment.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3150-3158
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• 1997

In the ATM networks, there are two method in traffic control as schemes to improve the quality of service; one is the reactive control after congestion and the other is the preventive control before congestion. The preventive control include the CAC(Connection Admission Control), the UPC(Usage Parameter Control), the NPC(Network Parameter Control) and the PC(Priority co ntrol). In this paper, we propose an efficient UPC algorithm that has a complex structure using the Jumping window algorithm within the Leaky Bucket algorithm. The proposed algorithm controls peak hit rate by the Leaky Bucket algorithm, then it does the traffic control to evaluate by the Jumping Window whether violates mean bit rate or not. As we assume On/Off traffic source model, our simulation results showed cell loss rate less than the pre-existential Leaky Bucket algorithm method, and it could decrease the demanded Bucket size.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.833-841
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• 1997

In this paper, the hybrid LB-TJW(Leaky Bucket-Triggered Jumping Window) algorithm for multimedia traffic control is proposed and its performance is evaluated and analyzed. Its architecture is composed of the peak bit rate controller and the average bit rate controller. Generally, the cell which violates the peak bit rate is discraded in LBalgorithm, and the average bit rate of JW or TJW algorithm is better than that of LB algorithm. However, the hybrid LB-TJW algorithm passes it though the network if the cell does not violate the peak bit rate. If the cell violates the peak bit rate, the hybrid LB-TJW algorithm passes it to the average bit rate controller which perforithm to monitor the average bit rate of input traffic. The TJW algorithm monitors the cell that violates the average bit rate. If the cell does not violate the average bit rare, the LB-TJW algorithm passes it through the network. As simulation results, the cell loss rate and the buffer size of the LB-TJW algorithm is reduced to half as much as those of LB algortihm.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.503-510
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• 2005

With the increasing importance of network protection from cyber threats, it is requested to develop a multi-gigabit rate pattern matching method for protecting against malicious attacks in high-speed network. This paper devises a high-speed pattern matching algorithm with TCAM by using an m-byte jumping window pattern matching scheme. The proposed algorithm significantly reduces the number of TCAM lookups per payload by m times with the marginally enlarged TCAM size which can be implemented by cascading multiple TCAMs. Due to the reduced number of TCAM lookups, we can easily achieve multi-gigabit rate for scanning the packet payload. It is shown by simulation that for the Snort nile with 2,247 patterns, our proposed algorithm supports more than 10 Gbps rate with a 9Mbit TCAM.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.1
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• pp.33-41
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• 1996

In order to obtain the most favourable classification system for fishing gears, the problems in the existing systems were investigated and a new system in which the fishing method was adopted as the criterion of classification and the kinds of fishing gears were obtained by exchanging the word method into gear in the fishing methods classified newly for eliminating the problems was established. The new system to which the actual gears are arranged is as follows ; (1)Harvesting gear \circled1Plucking gears : Clamp, Tong, Wrench, etc. \circled2Sweeping gears : Push net, Coral sweep net, etc. \circled3Dredging gears : Hand dredge net, Boat dredge net, etc. (2)Sticking gears \circled1Shot sticking gears : Spear, Sharp plummet, Harpoon, etc. \circled2Pulled sticking gears : Gaff, Comb, Rake, Hook harrow, Jerking hook, etc. \circled3Left sticking gears : Rip - hook set line. (3)Angling gears \circled1Jerky angling gears (a)Single - jerky angling gears : Hand line, Pole line, etc. (b)Multiple - jerky angling gears : squid hook. \circled2Idly angling gears (a)Set angling gears : Set long line. (b)Drifted angling gears : Drift long line, Drift vertical line, etc. \circled3Dragged angling gears : Troll line. (4)Shelter gears : Eel tube, Webfoot - octopus pot, Octopus pot, etc. (5)Attracting gears : Fishing basket. (6)Cutoff gears : Wall, Screen net, Window net, etc. (7)Guiding gears \circled1Horizontally guiding gears : Triangular set net, Elliptic set net, Rectangular set net, Fish weir, etc. \circled2Vertically guiding gears : Pound net. \circled3Deeply guiding gears : Funnel net. (8)Receiving gears \circled1Jumping - fish receiving gears : Fish - receiving scoop net, Fish - receiving raft, etc. \circled2Drifting - fish receiving gears (a)Set drifting - fish receiving gears : Bamboo screen, Pillar stow net, Long stow net, etc. (b)Movable drifting - fish receiving gears : Stow net. (9)Bagging gears \circled1Drag - bagging gears (a)Bottom - drag bagging gears : Bottom otter trawl, Bottom beam trawl, Bottom pair trawl, etc. (b)Midwater - drag gagging gears : Midwater otter trawl, Midwater pair trawl, etc. (c)Surface - drag gagging gears : Anchovy drag net. \circled2Seine - bagging gears (a)Beach - seine bagging gears : Skimming scoop net, Beach seine, etc. (b)Boat - seine bagging gears : Boat seine, Danish seine, etc. \circled3Drive - bagging gears : Drive - in dustpan net, Inner drive - in net, etc. (10)Surrounding gears \circled1Incomplete surrounding gears : Lampara net, Ring net, etc. \circled2Complete surrounding gears : Purse seine, Round haul net, etc. (11)Covering gears \circled1Drop - type covering gears : Wooden cover, Lantern net, etc. \circled2Spread - type covering gears : Cast net. (12)Lifting gears \circled1Wait - lifting gears : Scoop net, Scrape net, etc. \circled2Gatherable lifting gears : Saury lift net, Anchovy lift net, etc. (13)Adherent gears \circled1Gilling gears (a)Set gilling gears : Bottom gill net, Floating gill net. (b)Drifted gilling gears : Drift gill net. (c)Encircled gilling gears : Encircled gill net. (d)Seine - gilling gears : Seining gill net. (e)Dragged gilling gears : Dragged gill net. \circled2Tangling gears (a)Set tangling gears : Double trammel net, Triple trammel net, etc. (b)Encircled tangling gears : Encircled tangle net. (c)Dragged tangling gears : Dragged tangle net. \circled3Restrainting gears (a)Drifted restrainting gears : Pocket net(Gen - type net). (b)Dragged restrainting gears : Dragged pocket net. (14)Sucking gears : Fish pumps.

• Journal of the Korea Computer Graphics Society
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• v.3 no.1
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• pp.57-67
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• 1997

The navigation of virtual space comes down to the manipulation of the virtual camera. The movement of the virtual cameras has 6 degrees of freedom. However, input devices such as mouses and joysticks are 2D. So, the movement of the camera that corresponds to the input device is 2D movement at the given moment. Therefore, the 3D movement of the camera can be implemented by means of the combination of 2D and 1D movements of the camera. Many of the virtual space navigation browser use several navigation modes to solve this problem. But, the criteria for distinguishing different modes are not clear, somed of the manipulations in each mode are repeated in other modes, and the kinesthetic correspondence of the input devices is often confusing. Hence the user has difficulty in making correct decisions when navigating the virtual space. To solve this problem, we use a single navigation metaphore in which different modes are organically integrated. In this paper we propose a helicopter pilot metaphor. Using the helicopter pilot metaphore means that the user navigates the virtual space like a pilot of a helicopter flying in space. In this paper, we distinguished six 2D movement spaces of the helicopter: (1) the movement on the horizontal plane, (2) the movement on the vertical plane,k (3) the pitch and yaw rotations about the current position, (4) the roll and pitch rotations about the current position, (5) the horizontal and vertical turning, and (6) the rotation about the target object. The six 3D movement spaces are visualized and displayed as a sequence of auxiliary windows. The user can select the desired movement space simply by jumping from one window to another. The user can select the desired movement by looking at the displaced 2D movement spaces. The movement of the camera in each movement space is controlled by the usual movements of the joystick.