137,984 research outputs found
Increasing Performances of TCP Data Transfers Through Multiple Parallel Connections
Although Transmission Control Protocol (TCP) is a widely deployed and successful protocol, it shows some limitations in present-day environments. In particular, it is unable to exploit multiple (physical or logical) paths between two hosts. This paper presents PATTHEL, a session-layer solution designed for parallelizing stream data transfers. Parallelization is achieved by striping the data flow among multiple TCP channels. This solution does not require invasive changes to the networking stack and can be implemented entirely in user space. Moreover, it is flexible enough to suit several scenarios - e.g. it can be used to split a data transfer among multiple relays within a peer-to-peer overlay networ
Incentive Design and Market Evolution of Mobile User-Provided Networks
An operator-assisted user-provided network (UPN) has the potential to achieve
a low cost ubiquitous Internet connectivity, without significantly increasing
the network infrastructure investment. In this paper, we consider such a
network where the network operator encourages some of her subscribers to
operate as mobile Wi-Fi hotspots (hosts), providing Internet connectivity for
other subscribers (clients). We formulate the interaction between the operator
and mobile users as a two-stage game. In Stage I, the operator determines the
usage-based pricing and quota-based incentive mechanism for the data usage. In
Stage II, the mobile users make their decisions about whether to be a host, or
a client, or not a subscriber at all. We characterize how the users' membership
choices will affect each other's payoffs in Stage II, and how the operator
optimizes her decision in Stage I to maximize her profit. Our theoretical and
numerical results show that the operator's maximum profit increases with the
user density under the proposed hybrid pricing mechanism, and the profit gain
can be up to 50\% in a dense network comparing with a pricing-only approach
with no incentives.Comment: This manuscript serves as the online technical report of the article
published in IEEE Workshop on Smart Data Pricing (SDP), 201
OSCAR: A Collaborative Bandwidth Aggregation System
The exponential increase in mobile data demand, coupled with growing user
expectation to be connected in all places at all times, have introduced novel
challenges for researchers to address. Fortunately, the wide spread deployment
of various network technologies and the increased adoption of multi-interface
enabled devices have enabled researchers to develop solutions for those
challenges. Such solutions aim to exploit available interfaces on such devices
in both solitary and collaborative forms. These solutions, however, have faced
a steep deployment barrier.
In this paper, we present OSCAR, a multi-objective, incentive-based,
collaborative, and deployable bandwidth aggregation system. We present the
OSCAR architecture that does not introduce any intermediate hardware nor
require changes to current applications or legacy servers. The OSCAR
architecture is designed to automatically estimate the system's context,
dynamically schedule various connections and/or packets to different
interfaces, be backwards compatible with the current Internet architecture, and
provide the user with incentives for collaboration. We also formulate the OSCAR
scheduler as a multi-objective, multi-modal scheduler that maximizes system
throughput while minimizing energy consumption or financial cost. We evaluate
OSCAR via implementation on Linux, as well as via simulation, and compare our
results to the current optimal achievable throughput, cost, and energy
consumption. Our evaluation shows that, in the throughput maximization mode, we
provide up to 150% enhancement in throughput compared to current operating
systems, without any changes to legacy servers. Moreover, this performance gain
further increases with the availability of connection resume-supporting, or
OSCAR-enabled servers, reaching the maximum achievable upper-bound throughput
Analysis of Performance of Dynamic Multicast Routing Algorithms
In this paper, three new dynamic multicast routing algorithms based on the
greedy tree technique are proposed; Source Optimised Tree, Topology Based Tree
and Minimum Diameter Tree. A simulation analysis is presented showing various
performance aspects of the algorithms, in which a comparison is made with the
greedy and core based tree techniques. The effects of the tree source location
on dynamic membership change are also examined. The simulations demonstrate
that the Source Optimised Tree algorithm achieves a significant improvement in
terms of delay and link usage when compared to the Core Based Tree, and greedy
algorithm
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