The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
Sidi-mohammed Senouci - One of the best experts on this subject based on the ideXlab platform.
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TCP Computational Energy Cost within Wireless Mobile Ad Hoc Network
2009 IEEE/ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, VOLS 1 AND 2, 2009Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results from a detailed Energy measurement\nstudy of different TCP variants when used in Mobile Ad hoc Network\nenvironments. More precisely, we focus on the node-level Cost of the TCP\nprotocol; also know as the computational Energy Cost. In fact, the\ncomputational Energy consumption is the most important part of TCP\nEnergy consumption. This is already proven in previous work and our\nresults confirm this fact. Sometimes, the computational Energy Cost is\nthree times that of the communication Energy Cost The studied TCP\nvariants, in this work, are TCP New-Reno, Vegas, SACK, and Westwood. In\nour analysis, we draw a breakdown of the Energy Cost of the main\ncongestion control algorithm (i.e. slow start, fast retransmit/fast\nrecovery, and congestion avoidance) used by these TCP variants. The\ncomputational Energy Cost is studied using a hybrid approach,\nsimulation/emulation, using the SEDLANE emulation tool. This study takes\ninto consideration different data packet loss models (congestion, link\nloss, wireless signal loss, interference) within such environments when\ndifferent ad-hoc routing protocols (reactive and proactive) are used.\nThe performed study gives a set of results that are of high interest for\nfuture improvements of TCP in MANETs. Among the obtained results, we\nshow that the computational Energy Cost of TCP varies according to the\ntype of data packet loss model it comes through: network congestion,\ninterference, link loss, or signal loss. The results demonstrate that\nthe link loss scenario is the most severe situation for TCP connections\nto face. In addition to that, we show that the Fast Retransmit/Fast\nRecovery phase has much less Energy Cost than both Slow Start and\nCongestion Avoidance phases, due to the fact that it sends more TCP data\nbytes in a shorter period of time. Finally, the computational Energy\nCost is quantified and compared to the TCP end to end performance for\neach TCP variant showing the link between both.
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TCP computational Energy Cost within wireless Mobile Ad Hoc Network
2008 33rd IEEE Conference on Local Computer Networks (LCN), 2008Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results of a detailed measurement study of the computational Energy Cost of different TCP variants when used in mobile ad hoc networks. The studied TCP variants are TCP New-Reno, Vegas, SACK, and Westwood. We used a hybrid approach using simulation and emulation, through SEDLANE emulation tool. This study investigates different packet loss models (congestion, link loss, signal loss, interference) with different ad hoc routing protocols (reactive and proactive). The study demonstrates that the fast retransmit/fast recovery phase has a mush lower Energy Cost than both slow start and congestion avoidance phases, sending more TCP data bytes in a shorter period of time.
Alaa Seddik-Ghaleb - One of the best experts on this subject based on the ideXlab platform.
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TCP Computational Energy Cost within Wireless Mobile Ad Hoc Network
2009 IEEE/ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, VOLS 1 AND 2, 2009Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results from a detailed Energy measurement\nstudy of different TCP variants when used in Mobile Ad hoc Network\nenvironments. More precisely, we focus on the node-level Cost of the TCP\nprotocol; also know as the computational Energy Cost. In fact, the\ncomputational Energy consumption is the most important part of TCP\nEnergy consumption. This is already proven in previous work and our\nresults confirm this fact. Sometimes, the computational Energy Cost is\nthree times that of the communication Energy Cost The studied TCP\nvariants, in this work, are TCP New-Reno, Vegas, SACK, and Westwood. In\nour analysis, we draw a breakdown of the Energy Cost of the main\ncongestion control algorithm (i.e. slow start, fast retransmit/fast\nrecovery, and congestion avoidance) used by these TCP variants. The\ncomputational Energy Cost is studied using a hybrid approach,\nsimulation/emulation, using the SEDLANE emulation tool. This study takes\ninto consideration different data packet loss models (congestion, link\nloss, wireless signal loss, interference) within such environments when\ndifferent ad-hoc routing protocols (reactive and proactive) are used.\nThe performed study gives a set of results that are of high interest for\nfuture improvements of TCP in MANETs. Among the obtained results, we\nshow that the computational Energy Cost of TCP varies according to the\ntype of data packet loss model it comes through: network congestion,\ninterference, link loss, or signal loss. The results demonstrate that\nthe link loss scenario is the most severe situation for TCP connections\nto face. In addition to that, we show that the Fast Retransmit/Fast\nRecovery phase has much less Energy Cost than both Slow Start and\nCongestion Avoidance phases, due to the fact that it sends more TCP data\nbytes in a shorter period of time. Finally, the computational Energy\nCost is quantified and compared to the TCP end to end performance for\neach TCP variant showing the link between both.
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TCP computational Energy Cost within wireless Mobile Ad Hoc Network
2008 33rd IEEE Conference on Local Computer Networks (LCN), 2008Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results of a detailed measurement study of the computational Energy Cost of different TCP variants when used in mobile ad hoc networks. The studied TCP variants are TCP New-Reno, Vegas, SACK, and Westwood. We used a hybrid approach using simulation and emulation, through SEDLANE emulation tool. This study investigates different packet loss models (congestion, link loss, signal loss, interference) with different ad hoc routing protocols (reactive and proactive). The study demonstrates that the fast retransmit/fast recovery phase has a mush lower Energy Cost than both slow start and congestion avoidance phases, sending more TCP data bytes in a shorter period of time.
Yacine Ghamri-doudane - One of the best experts on this subject based on the ideXlab platform.
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TCP Computational Energy Cost within Wireless Mobile Ad Hoc Network
2009 IEEE/ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, VOLS 1 AND 2, 2009Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results from a detailed Energy measurement\nstudy of different TCP variants when used in Mobile Ad hoc Network\nenvironments. More precisely, we focus on the node-level Cost of the TCP\nprotocol; also know as the computational Energy Cost. In fact, the\ncomputational Energy consumption is the most important part of TCP\nEnergy consumption. This is already proven in previous work and our\nresults confirm this fact. Sometimes, the computational Energy Cost is\nthree times that of the communication Energy Cost The studied TCP\nvariants, in this work, are TCP New-Reno, Vegas, SACK, and Westwood. In\nour analysis, we draw a breakdown of the Energy Cost of the main\ncongestion control algorithm (i.e. slow start, fast retransmit/fast\nrecovery, and congestion avoidance) used by these TCP variants. The\ncomputational Energy Cost is studied using a hybrid approach,\nsimulation/emulation, using the SEDLANE emulation tool. This study takes\ninto consideration different data packet loss models (congestion, link\nloss, wireless signal loss, interference) within such environments when\ndifferent ad-hoc routing protocols (reactive and proactive) are used.\nThe performed study gives a set of results that are of high interest for\nfuture improvements of TCP in MANETs. Among the obtained results, we\nshow that the computational Energy Cost of TCP varies according to the\ntype of data packet loss model it comes through: network congestion,\ninterference, link loss, or signal loss. The results demonstrate that\nthe link loss scenario is the most severe situation for TCP connections\nto face. In addition to that, we show that the Fast Retransmit/Fast\nRecovery phase has much less Energy Cost than both Slow Start and\nCongestion Avoidance phases, due to the fact that it sends more TCP data\nbytes in a shorter period of time. Finally, the computational Energy\nCost is quantified and compared to the TCP end to end performance for\neach TCP variant showing the link between both.
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TCP computational Energy Cost within wireless Mobile Ad Hoc Network
2008 33rd IEEE Conference on Local Computer Networks (LCN), 2008Co-Authors: Alaa Seddik-Ghaleb, Yacine Ghamri-doudane, Sidi-mohammed SenouciAbstract:In this paper, we present the results of a detailed measurement study of the computational Energy Cost of different TCP variants when used in mobile ad hoc networks. The studied TCP variants are TCP New-Reno, Vegas, SACK, and Westwood. We used a hybrid approach using simulation and emulation, through SEDLANE emulation tool. This study investigates different packet loss models (congestion, link loss, signal loss, interference) with different ad hoc routing protocols (reactive and proactive). The study demonstrates that the fast retransmit/fast recovery phase has a mush lower Energy Cost than both slow start and congestion avoidance phases, sending more TCP data bytes in a shorter period of time.
Lena Hulthén - One of the best experts on this subject based on the ideXlab platform.
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Energy Cost in children assessed by multisensor activity monitors.
Medicine and Science in Sports and Exercise, 2009Co-Authors: Daniel Arvidsson, Frode Slinde, Sven Larsson, Lena HulthénAbstract:PURPOSE: The SenseWear Pro2 Armband (SWA; BodyMedia, Inc., Pittsburg, PA), the Intelligent Device for Energy Expenditure and Activity (IDEEA; Minisun LLC, Fresno, CA), and the ActiReg (AR; PreMed AS, Oslo, Norway) were compared with indirect calorimetry to determine the ability of these devices to assess Energy Cost in children during resting and different physical activities. METHODS: Fourteen children, 11-13 yr old, wore the SWA, the IDEEA, and the AR during resting, sitting, stationary bicycling, jumping on a trampoline, playing basketball, stair walking, and walking/running along a 50-m track. The Oxycon Mobile portable metabolic system (VIASYS Healthcare, Conshohocken, PA) was used as the criterion method for Energy Cost. RESULTS: For resting and sitting, the three activity monitors showed comparable results, but none of them accurately assessed Energy Cost for stationary bicycling, jumping on a trampoline, or playing basketball. The IDEEA was the only activity monitor that accurately assessed Energy Cost for stair walking. Also, the IDEEA showed a close estimate of Energy Cost across the walking and the running intensities, whereas the SWA accurately assessed Energy Cost for slow to normal walking but showed increased underestimation of Energy Cost with increasing speed. The AR overestimated Energy Cost during walking and during slow running but did not respond to increasing running speed. CONCLUSIONS: To be able to capture children's physical activity, all three activity monitors need to be further developed. Overall, the IDEEA showed the highest ability to assess Energy Cost in this study, but SWA may be more feasible for use in children under free-living conditions.
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Energy Cost of physical activities in children: Validation of SenseWear Armband
Medicine and Science in Sports and Exercise, 2007Co-Authors: Daniel Arvidsson, Frode Slinde, Sven Larsson, Lena HulthénAbstract:PURPOSE: To examine the validity of SenseWear Pro2 Armband in assessing Energy Cost of physical activities in children, and to contribute with values of Energy Costs in an overview of physical activities in children. METHODS: Energy Cost was assessed by SenseWear Pro2 Armband in 20 healthy children, 11-13 yr, while lying down resting, sitting playing games on mobile phone, stepping up and down on a step board, bicycling on a stationary bike, jumping on a trampoline, playing basketball, and walking/running on a treadmill at the speeds 2, 3, 4, 5, 6, 7, 8, and 10 km x h(-1). During these activities, Energy Cost was also assessed from VO2 and VCO2 measured by Oxycon Mobile portable metabolic system, which was used as criterion method. RESULTS: The difference in Energy Cost between SenseWear Pro2 Armband and Oxycon Mobile was -0.7 (0.5) (P < 0.001) for resting, -2.0 (0.9) (P < 0.001) for playing games on mobile phone, -6.6 (2.3) (P < 0.001) for stepping on the step board, -12.0 (3.7) (P < 0.001) for bicycling, -2.7 (11.9) (P = 0.34) for jumping on the trampoline, and -14.8 (6.4) kJ x min(-1) (P < 0.001) for playing basketball. The difference in Energy Cost between SenseWear Pro2 Armband and Oxycon Mobile for increasing treadmill speed was 1.3 (3.1) (P = 0.048), 0.1 (2.9) (P = 0.82), -1.2 (2.6) (P = 0.049), -1.6 (3.2) (P = 0.044), -3.1 (3.7) (P = 0.0013), -4.9 (3.7) (P < 0.001), -5.3 (3.7) (P < 0.001), and -11.1 (3.5) kJ x min(-1) (P < 0.001). CONCLUSIONS: SenseWear Pro2 Armband underestimated Energy Cost of most activities in this study, an underestimation that increased with increased physical activity intensity. A table of Energy Costs (MET values) of physical activities in children measured by indirect calorimetry is presented as an initiation of the creation of a compendium of physical activities in children.
Yi Huang - One of the best experts on this subject based on the ideXlab platform.
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Energy Cost for estimation in multihop wireless sensor networks
2010 IEEE International Conference on Acoustics Speech and Signal Processing, 2010Co-Authors: Yi HuangAbstract:This paper addresses a transmission Energy problem for estimation in multihop wireless sensor networks. We consider two very different schemes of estimation: progressive estimation and consensus estimation. Progressive estimation is designed for networks about which a central planner knows a routing tree and all channel state information. Consensus estimation is commonly known for more dynamic networks. In this paper, we develop Energy planning algorithms to minimize the transmission Energy Cost for both schemes, and compare their Energy Costs. This study shows that the total Energy Cost for consensus estimation can be much higher than that for progressive estimation, but the peak Energy for the former is less than that for the latter.
