8,829 research outputs found
Traffic-Redundancy Aware Network Design
We consider network design problems for information networks where routers
can replicate data but cannot alter it. This functionality allows the network
to eliminate data-redundancy in traffic, thereby saving on routing costs. We
consider two problems within this framework and design approximation
algorithms.
The first problem we study is the traffic-redundancy aware network design
(RAND) problem. We are given a weighted graph over a single server and many
clients. The server owns a number of different data packets and each client
desires a subset of the packets; the client demand sets form a laminar set
system. Our goal is to connect every client to the source via a single path,
such that the collective cost of the resulting network is minimized. Here the
transportation cost over an edge is its weight times times the number of
distinct packets that it carries.
The second problem is a facility location problem that we call RAFL. Here the
goal is to find an assignment from clients to facilities such that the total
cost of routing packets from the facilities to clients (along unshared paths),
plus the total cost of "producing" one copy of each desired packet at each
facility is minimized.
We present a constant factor approximation for the RAFL and an O(log P)
approximation for RAND, where P is the total number of distinct packets. We
remark that P is always at most the number of different demand sets desired or
the number of clients, and is generally much smaller.Comment: 17 pages. To be published in the proceedings of the Twenty-Third
Annual ACM-SIAM Symposium on Discrete Algorithm
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
Current-Mode Techniques for the Implementation of Continuous- and Discrete-Time Cellular Neural Networks
This paper presents a unified, comprehensive approach
to the design of continuous-time (CT) and discrete-time
(DT) cellular neural networks (CNN) using CMOS current-mode
analog techniques. The net input signals are currents instead
of voltages as presented in previous approaches, thus avoiding
the need for current-to-voltage dedicated interfaces in image
processing tasks with photosensor devices. Outputs may be either
currents or voltages. Cell design relies on exploitation of current
mirror properties for the efficient implementation of both linear
and nonlinear analog operators. These cells are simpler and
easier to design than those found in previously reported CT
and DT-CNN devices. Basic design issues are covered, together
with discussions on the influence of nonidealities and advanced
circuit design issues as well as design for manufacturability
considerations associated with statistical analysis. Three prototypes
have been designed for l.6-pm n-well CMOS technologies.
One is discrete-time and can be reconfigured via local logic for
noise removal, feature extraction (borders and edges), shadow
detection, hole filling, and connected component detection (CCD)
on a rectangular grid with unity neighborhood radius. The other
two prototypes are continuous-time and fixed template: one for
CCD and other for noise removal. Experimental results are given
illustrating performance of these prototypes
Game-Theoretic Pricing and Selection with Fading Channels
We consider pricing and selection with fading channels in a Stackelberg game
framework. A channel server decides the channel prices and a client chooses
which channel to use based on the remote estimation quality. We prove the
existence of an optimal deterministic and Markovian policy for the client, and
show that the optimal policies of both the server and the client have threshold
structures when the time horizon is finite. Value iteration algorithm is
applied to obtain the optimal solutions for both the server and client, and
numerical simulations and examples are given to demonstrate the developed
result.Comment: 6 pages, 4 figures, accepted by the 2017 Asian Control Conferenc
Inter-domain router placement and traffic engineering
The Internet is organized as an interconnection of separate administrative domains called Autonomous Systems (AS). The Border Gateway Protocol (BGP) is the de facto standard for controlling the routing of traffic across different ASs. It supports scalable distribution of reachability and routing policy information among different ASs. In this paper, we study a network design problem which determines (1) the optimal placement of border router(s) within a domain and (2) the corresponding inter-and intra-domain traffic patterns within an AS. Practical constraints imposed by BGP and other standard shortest-path-based intra-domain routing protocols are considered. The problem is formulated as a variant of the uncapacitated network design problem (UNDP). While it is feasible to use a brute-force, integer-programming-based approach for tackling small instances of this problem, we have resorted to a dual-ascent approximation approach for mid/large-scale instances. The quality of the approximation approach is evaluated in terms of its computational efficiency and network cost sub-optimality. Sensitivity analysis w.r.t. various network/traffic parameters are also conducted. We then describe how one can apply our optimization results to better configure BGP as well as other intra-domain routing protocols. This serves as a first-step towards the auto-configuration of Internet routing protocols, BGP in particular, which is "well-known" for its tedious and error-prone configuration needs.published_or_final_versio
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