11,421 research outputs found
Optimal Joint Routing and Scheduling in Millimeter-Wave Cellular Networks
Millimeter-wave (mmWave) communication is a promising technology to cope with
the expected exponential increase in data traffic in 5G networks. mmWave
networks typically require a very dense deployment of mmWave base stations
(mmBS). To reduce cost and increase flexibility, wireless backhauling is needed
to connect the mmBSs. The characteristics of mmWave communication, and
specifically its high directional- ity, imply new requirements for efficient
routing and scheduling paradigms. We propose an efficient scheduling method,
so-called schedule-oriented optimization, based on matching theory that
optimizes QoS metrics jointly with routing. It is capable of solving any
scheduling problem that can be formulated as a linear program whose variables
are link times and QoS metrics. As an example of the schedule-oriented
optimization, we show the optimal solution of the maximum throughput fair
scheduling (MTFS). Practically, the optimal scheduling can be obtained even for
networks with over 200 mmBSs. To further increase the runtime performance, we
propose an efficient edge-coloring based approximation algorithm with provable
performance bound. It achieves over 80% of the optimal max-min throughput and
runs 5 to 100 times faster than the optimal algorithm in practice. Finally, we
extend the optimal and approximation algorithms for the cases of multi-RF-chain
mmBSs and integrated backhaul and access networks.Comment: To appear in Proceedings of INFOCOM '1
Optimal Time-dependent Sequenced Route Queries in Road Networks
In this paper we present an algorithm for optimal processing of
time-dependent sequenced route queries in road networks, i.e., given a road
network where the travel time over an edge is time-dependent and a given
ordered list of categories of interest, we find the fastest route between an
origin and destination that passes through a sequence of points of interest
belonging to each of the specified categories of interest. For instance,
considering a city road network at a given departure time, one can find the
fastest route between one's work and his/her home, passing through a bank, a
supermarket and a restaurant, in this order. The main contribution of our work
is the consideration of the time dependency of the network, a realistic
characteristic of urban road networks, which has not been considered previously
when addressing the optimal sequenced route query. Our approach uses the A*
search paradigm that is equipped with an admissible heuristic function, thus
guaranteed to yield the optimal solution, along with a pruning scheme for
further reducing the search space. In order to compare our proposal we extended
a previously proposed solution aimed at non-time dependent sequenced route
queries, enabling it to deal with the time-dependency. Our experiments using
real and synthetic data sets have shown our proposed solution to be up to two
orders of magnitude faster than the temporally extended previous solution.Comment: 10 pages, 12 figures To be published as a short paper in the 23rd ACM
SIGSPATIA
Cross-layer design of multi-hop wireless networks
MULTI -hop wireless networks are usually defined as a collection of nodes
equipped with radio transmitters, which not only have the capability to
communicate each other in a multi-hop fashion, but also to route each others’ data
packets. The distributed nature of such networks makes them suitable for a variety of
applications where there are no assumed reliable central entities, or controllers, and
may significantly improve the scalability issues of conventional single-hop wireless
networks.
This Ph.D. dissertation mainly investigates two aspects of the research issues
related to the efficient multi-hop wireless networks design, namely: (a) network
protocols and (b) network management, both in cross-layer design paradigms to
ensure the notion of service quality, such as quality of service (QoS) in wireless mesh
networks (WMNs) for backhaul applications and quality of information (QoI) in
wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of
this Ph.D. dissertation, different network settings are used as illustrative examples,
however the proposed algorithms, methodologies, protocols, and models are not
restricted in the considered networks, but rather have wide applicability.
First, this dissertation proposes a cross-layer design framework integrating
a distributed proportional-fair scheduler and a QoS routing algorithm, while using
WMNs as an illustrative example. The proposed approach has significant performance
gain compared with other network protocols. Second, this dissertation proposes
a generic admission control methodology for any packet network, wired and
wireless, by modeling the network as a black box, and using a generic mathematical
0. Abstract 3
function and Taylor expansion to capture the admission impact. Third, this dissertation
further enhances the previous designs by proposing a negotiation process,
to bridge the applications’ service quality demands and the resource management,
while using WSNs as an illustrative example. This approach allows the negotiation
among different service classes and WSN resource allocations to reach the optimal
operational status. Finally, the guarantees of the service quality are extended to
the environment of multiple, disconnected, mobile subnetworks, where the question
of how to maintain communications using dynamically controlled, unmanned data
ferries is investigated
Optimal Scaling of a Gradient Method for Distributed Resource Allocation
We consider a class of weighted gradient methods for distributed resource allocation over a network. Each node of the network is associated with a local variable and a convex cost function; the sum of the variables (resources) across the network is fixed. Starting with a feasible allocation, each node updates its local variable in proportion to the differences between the marginal costs of itself and its neighbors. We focus on how to choose the proportional weights on the edges (scaling factors for the gradient method) to make this distributed algorithm converge and on how to make the convergence as fast as possible.
We give sufficient conditions on the edge weights for the algorithm to converge monotonically to the optimal solution; these conditions have the form of a linear matrix inequality. We give some simple, explicit methods to choose the weights that satisfy these conditions. We derive a guaranteed convergence rate for the algorithm and find the weights that minimize this rate by solving a semidefinite program. Finally, we extend the main results to problems with general equality constraints and problems with block separable objective function
Efficient Wireless Security Through Jamming, Coding and Routing
There is a rich recent literature on how to assist secure communication
between a single transmitter and receiver at the physical layer of wireless
networks through techniques such as cooperative jamming. In this paper, we
consider how these single-hop physical layer security techniques can be
extended to multi-hop wireless networks and show how to augment physical layer
security techniques with higher layer network mechanisms such as coding and
routing. Specifically, we consider the secure minimum energy routing problem,
in which the objective is to compute a minimum energy path between two network
nodes subject to constraints on the end-to-end communication secrecy and
goodput over the path. This problem is formulated as a constrained optimization
of transmission power and link selection, which is proved to be NP-hard.
Nevertheless, we show that efficient algorithms exist to compute both exact and
approximate solutions for the problem. In particular, we develop an exact
solution of pseudo-polynomial complexity, as well as an epsilon-optimal
approximation of polynomial complexity. Simulation results are also provided to
show the utility of our algorithms and quantify their energy savings compared
to a combination of (standard) security-agnostic minimum energy routing and
physical layer security. In the simulated scenarios, we observe that, by
jointly optimizing link selection at the network layer and cooperative jamming
at the physical layer, our algorithms reduce the network energy consumption by
half
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