• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1770-1780
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• 1997

Our problem is improvement of image quality because it is inevitable cell loss of image data when traffic congestion occurs. If cells are discarded indiscriminately in transmission of MPEG video data, it occurs severe degradation in quality of service(QOS). In this paper, to solve this problem, we propose two method. The first, we analyze the traffic characteristics of an MPEG encoder and generate high priority and low priority data stream. During network congestion, only the least low priority cells are dropped, and this ensures that the high priority cells are successfully transmitted, which, in turn, guarantees satisfactory QoS. In this case, the prioritization scheme for the encoder assigns components of the data stream to each priority level based on the value of a parameter ${\beta}$. The second, Number of high priority cells are increased when value of ${\beta}$ is large. It occurs the loss of high priority cell in the congestion. To prevent it, this paper is regulated to data stream rate as buffer occupancy with UPC controller. Therefore, encoder's bandwidth can be calculated renegotiation of the encoder and networks. In this paper, the encoder's bandwidth requirements are characterized by a usage parameter control (UPC) set consisting of peak rate, burstness, and sustained rate. An adaptive encoder rate control algorithm at the Networks Interface Card(NIC) computes the necessary UPC parameter to maintain the user specified quality of service. Simulation results are given for a rate-controlled VBR video encoder operating through an ATM network interface which supports dynamic UPC. These results show that dynamic bandwidth renegotiation of prioritized data stream could provided bandwidth saving and significant quality gains which guarantee high priority data stream.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.39-47
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• 2005

The range of hardware implementation increases in communication systems as high-speed processing is required for high data rate. In the broadband wireless access (BWA) system based on IEEE standard 802.16 the functions of higher part in the MAC layer to Provide data needed for generating MAC PDU are implemented in software, and the tasks from formatting MAC PDUs by using those data to transmitting the messages in a modem are implemented in hardware. In this paper, the interface hardware for efficient message exchange between MAC and PHY layers in the BWA system is designed. The hardware performs the following functions including those of the transmission convergence(TC) sublayer; (1) formatting TC PDU(Protocol data unit) from/to MAC PDU, (2) Reed-solomon(RS) encoding/decoding, and (3) resolving DL MAP and UL MAP, so that it controls transmission slot and uplink and downlink traffic according to the modulation scheme of burst profile. Also, it provides various control signal for PHY modem. In addition, the truncated binary exponential backoff (TBEB) algorithm is implemented in a subscriber station to avoid collision on contention-based transmission of messages. The VLSI architecture performing all these functions is implemented and verified in VHDL.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.532-543
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• 2004

Mobile Ad hoc NETworks (MANET) consist of mobile nodes which are usually powered by battery Approaches for minimizing power consumption have been proposed for all network layers and devices. IEEE 802.11 DCF (Distributed Coordination Function), a well-known medium access control protocol for MANETS, also defines a power save mode operation. The nodes in power save mode periodically repeat the awake state and the doze state in synchronized fashion. When all nodes are in the awake state, the exchange the announcements for the subsequent message transmission with neighbors. The nodes that send or receive the announcements stay awake for data transmission, and others go into the dole state. The previous works for enhancing the power save mode operation have focused on shortening the duration of the awake state. We observed that the longer sleeping period results in seriously long delivery latency and the consequent unnecessary power consumption as well, because the packets can move forward only one hop for a fixed interval. In this paper, we propose an improved protocol for the power save mode of IEEE 802.11 DCF, which allows the flooding packets to be forwarded several hops in a transmission period. Our approach does not reduce the duration of compulsory awake period, but maximizes its utilization. Each node propagates the announcements for next flooding to nodes of several hops away, thus the packets can travel multiple hops during one interval. Simulation results of comparison between our scheme and the standard show a reduction in flooding delay maximum 80%, and the unicasting latency with accompanying flooding flows near 50%, with slight increase of energy consumption.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.