9,510 research outputs found
Convexity and Robustness of Dynamic Traffic Assignment and Freeway Network Control
We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA)
problem to design optimal traffic flow controls for freeway networks as modeled
by the Cell Transmission Model, using variable speed limit, ramp metering, and
routing. We consider two optimal control problems: the DTA problem, where
turning ratios are part of the control inputs, and the Freeway Network Control
(FNC), where turning ratios are instead assigned exogenous parameters. It is
known that relaxation of the supply and demand constraints in the cell-based
formulations of the DTA problem results in a linear program. However, solutions
to the relaxed problem can be infeasible with respect to traffic dynamics.
Previous work has shown that such solutions can be made feasible by proper
choice of ramp metering and variable speed limit control for specific traffic
networks. We extend this procedure to arbitrary networks and provide insight
into the structure and robustness of the proposed optimal controllers. For a
network consisting only of ordinary, merge, and diverge junctions, where the
cells have linear demand functions and affine supply functions with identical
slopes, and the cost is the total traffic volume, we show, using the maximum
principle, that variable speed limits are not needed in order to achieve
optimality in the FNC problem, and ramp metering is sufficient. We also prove
bounds on perturbation of the controlled system trajectory in terms of
perturbations in initial traffic volume and exogenous inflows. These bounds,
which leverage monotonicity properties of the controlled trajectory, are shown
to be in close agreement with numerical simulation results
Making On-Demand Routing Efficient with Route-Request Aggregation
In theory, on-demand routing is very attractive for mobile ad hoc networks
(MANET), because it induces signaling only for those destinations for which
there is data traffic. However, in practice, the signaling overhead of existing
on-demand routing protocols becomes excessive as the rate of topology changes
increases due to mobility or other causes. We introduce the first on-demand
routing approach that eliminates the main limitation of on-demand routing by
aggregating route requests (RREQ) for the same destinations. The approach can
be applied to any existing on-demand routing protocol, and we introduce the
Ad-hoc Demand-Aggregated Routing with Adaptation (ADARA) as an example of how
RREQ aggregation can be used. ADARA is compared to AODV and OLSR using
discrete-event simulations, and the results show that aggregating RREQs can
make on-demand routing more efficient than existing proactive or on-demand
routing protocols
The price of anarchy in transportation networks by estimating user cost functions from actual traffic data
We have considered a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we converted the speed data to flow data and estimated the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulated appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. In addition, we analyzed the sensitivity of the total user latency cost to important parameters such as road capacities and minimum travel times. Finally, we formulated a system-optimum problem in order to find socially optimal flows for the network. We investigated the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city
Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding
In cloud infrastructure, accommodating multiple virtual networks on a single
physical network reduces power consumed by physical resources and minimizes
cost of operating cloud data centers. However, mapping multiple virtual network
resources to physical network components, called virtual network embedding
(VNE), is known to be NP-hard. With considering energy efficiency, the problem
becomes more complicated. In this paper, we model energy-aware virtual network
embedding, devise metrics for evaluating performance of energy aware virtual
network-embedding algorithms, and propose an energy aware virtual
network-embedding algorithm based on multi-objective particle swarm
optimization augmented with local search to speed up convergence of the
proposed algorithm and improve solutions quality. Performance of the proposed
algorithm is evaluated and compared with existing algorithms using extensive
simulations, which show that the proposed algorithm improves virtual network
embedding by increasing revenue and decreasing energy consumption.Comment: arXiv admin note: text overlap with arXiv:1504.0684
Making Name-Based Content Routing More Efficient than Link-State Routing
The Diffusive Name-based Routing Protocol (DNRP) is introduced for efficient
name-based routing in information-centric networks (ICN). DNRP establishes and
maintains multiple loop-free routes to the nearest instances of a name prefix
using only distance information. DNRP eliminates the need for periodic updates,
maintaining topology information, storing complete paths to content replicas,
or knowing about all the sites storing replicas of named content. DNRP is
suitable for large ICNs with large numbers of prefixes stored at multiple
sites. It is shown that DNRP provides loop-free routes to content independently
of the state of the topology and that it converges within a finite time to
correct routes to name prefixes after arbitrary changes in the network topology
or the placement of prefix instances. The result of simulation experiments
illustrates that DNRP is more efficient than link-state routing approaches
Enabling Correct Interest Forwarding and Retransmissions in a Content Centric Network
We show that the mechanisms used in the name data networking (NDN) and the
original content centric networking (CCN) architectures may not detect Interest
loops, even if the network in which they operate is static and no faults occur.
Furthermore, we show that no correct Interest forwarding strategy can be
defined that allows Interest aggregation and attempts to detect Interest
looping by identifying Interests uniquely. We introduce SIFAH (Strategy for
Interest Forwarding and Aggregation with Hop-Counts), the first Interest
forwarding strategy shown to be correct under any operational conditions of a
content centric network. SIFAH operates by having forwarding information bases
(FIBs) store the next hops and number of hops to named content, and by having
each Interest state the name of the requested content and the hop count from
the router forwarding an Interest to the content. We present the results of
simulation experiments using the ndnSIM simulator comparing CCN and NDN with
SIFAH. The results of these experiments illustrate the negative impact of
undetected Interest looping when Interests are aggregated in CCN and NDN, and
the performance advantages of using SIFAH
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