Abstract-Improving the performance of the transmission control protocol (TCP) in wireless Internet protocol (IP) communications has been an active research area. The performance degradation of TCP in wireless and wired-wireless hybrid networks is mainly due to its lack of the ability to differentiate the packet losses caused by network congestions from the losses caused by wireless link errors. In this paper, we propose a new TCP scheme, called TCP-Jersey, which is capable of distinguishing the wireless packet losses from the congestion packet losses, and reacting accordingly. TCP-Jersey consists of two key components, the available bandwidth estimation (ABE) algorithm and the congestion warning (CW) router configuration. ABE is a TCP sender side addition that continuously estimates the bandwidth available to the connection and guides the sender to adjust its transmission rate when the network becomes congested. CW is a configuration of network routers such that routers alert end stations by marking all packets when there is a sign of an incipient congestion. The marking of packets by the CW configured routers helps the sender of the TCP connection to effectively differentiate packet losses caused by network congestion from those caused by wireless link errors. This paper describes the design of TCP-Jersey, and presents results from experiments using the NS-2 network simulator. Results from simulations show that in a congestion free network with 1% of random wireless packet loss rate, TCP-Jersey achieves 17% and 85% improvements in goodput over TCP-Westwood and TCP-Reno, respectively; in a congested network where TCP flow competes with VoIP flows, with 1% of random wireless packet loss rate, TCP-Jersey achieves 9% and 76% improvements in goodput over TCP-Westwood and TCP-Reno, respectively. Our experiments of multiple TCP flows show that TCP-Jersey maintains the fair and friendly behavior with respect to other TCP flows.
In this paper, a simple mathematical model is presented for studying the performance of the BitTorrent [1] file sharing system. We are especially interested in the distribution of the peers with different states of the download job completedness. With the model we find that in the stable state the distribution of the download peers follows a U-shaped curve, and the parameters such as the departure rate of the seeds and the abort rate of the download peers will influence the peer distribution in different ways notably. We also analyze the file availability and the dying process of the BitTorrent file sharing system. We find that the system's stability deteriorates with the clustering of the peers, and BitTorrent's built-in "tit-for-tat" unchoking strategy could not help to preserve the integrity of the file among the download peers when the size of the community is small. An innovative peer selection strategy which enables more peers to finish the download job and prolongs the system's lifetime is proposed, in which the peers cooperate to improve the stability of the system by making a tradeoff between the current download rate and the future service availability. Finally, experimental results are presented to validate our analysis and findings.
Full quantum state tomography (FQST) plays a unique role in the estimation of the state of a quantum system without a priori knowledge or assumptions. Unfortunately, since FQST requires informationally (over)complete measurements, both the number of measurement bases and the computational complexity of data processing suffer an exponential growth with the size of the quantum system. A 14-qubit entangled state has already been experimentally prepared in an ion trap, and the data processing capability for FQST of a 14-qubit state seems to be far away from practical applications. In this paper, the computational capability of FQST is pushed forward to reconstruct a 14-qubit state with a run time of only 3.35 hours using the linear regression estimation (LRE) algorithm, even when informationally overcomplete Pauli measurements are employed. The computational complexity of the LRE algorithm is first reduced from ∼10 19 to ∼10 15 for a 14-qubit state, by dropping all the zero elements, and its computational efficiency is further sped up by fully exploiting the parallelism of the LRE algorithm with parallel Graphic Processing Unit (GPU) programming. Our result demonstrates the effectiveness of using parallel computation to speed up the postprocessing for FQST, and can play an important role in quantum information technologies with large quantum systems.
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