In this article, we study approximation algorithms for the problem of computing minimum dominating set for a given set S of n unit disks in R2. We first present a simple O(nlogk) time 5-factor approximation algorithm ...
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Let P be a set of n input points in the plane. An algorithm is proposed to place a pair of axis-parallel unit squares, either intersecting with no points in the intersection zone or disjoint, together enclosing the ma...
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In this paper, we address the web service selection problem for linear workflows. Given a linear workflow specifying a set of ordered tasks and a set of candidate services providing different features for each task, t...
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In this paper, we address the web service selection problem for linear workflows. Given a linear workflow specifying a set of ordered tasks and a set of candidate services providing different features for each task, the selection problem deals with the objective of selecting the most eligible service for each task, given the ordering specified. A number of approaches to solving the selection problem have been proposed in literature. With web services growing at an incredible pace, service selection at the Internet scale has resurfaced as a problem of recent research interest. In this work, we present our approach to the selection problem using an abstraction refinement technique to address the scalability limitations of contemporary approaches. Experiments on web service benchmarks show that our approach can add substantial performance benefits in terms of space when compared to an approach without our optimization.
Quantum computers are considered a blessing to the dynamic technological world that promises to solve complex problems much faster than their known classical counterparts. Such computational power imposes critical thr...
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We present two improved algorithms for weighted discrete p-center problem for tree networks with n vertices. One of our proposed algorithms runs in O(n log n + p log2 n log(n/p)) time. For all values of p, our algorit...
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In recent times, Mobile Edge computing (MEC) has emerged as a new paradigm allowing low-latency access to services deployed on edge nodes offering computation, storage and communication facilities. Vendors deploy thei...
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ISBN:
(数字)9781728159430
ISBN:
(纸本)9781728159447
In recent times, Mobile Edge computing (MEC) has emerged as a new paradigm allowing low-latency access to services deployed on edge nodes offering computation, storage and communication facilities. Vendors deploy their services on MEC servers to improve performance and mitigate network latencies often encountered in accessing cloud services. A service placement policy determines which services are deployed on which MEC servers. A number of mechanisms exist in literature to determine the optimal placement of services considering different performance metrics. However, for applications designed as microservice workflow architectures, service placement schemes need to be re-examined through a different lens owing to the inherent interdependencies which exist between microservices. Indeed, the dynamic environment, with stochastic user movement and service invocations, along with a large placement configuration space makes microservice placement in MEC a challenging task. Additionally, owing to user mobility, a placement scheme may need to be recalibrated, triggering service migrations to maintain the advantages offered by MEC. Existing microservice placement and migration schemes consider on-demand strategies. In this work, we take a different route and propose a Reinforcement Learning based proactive mechanism for microservice placement and migration. We use the San Francisco Taxi dataset to validate our approach. Experimental results show the effectiveness of our approach in comparison to other state-of-the-art methods.
This book constitutes the proceedings of the First Indo-Japanese conference on Perception and Machine Intelligence, PerMIn 2012, held in Kolkata, India, in January 2012. The 41 papers, presented together with 1 keynot...
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ISBN:
(数字)9783642273872
ISBN:
(纸本)9783642273865
This book constitutes the proceedings of the First Indo-Japanese conference on Perception and Machine Intelligence, PerMIn 2012, held in Kolkata, India, in January 2012.
The 41 papers, presented together with 1 keynote paper and 3 plenary papers, were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections named perception; human-computer interaction; e-nose and e-tongue; machine intelligence and application; image and video processing; and speech and signal processing.
In recent times, approximate computing is being looked at as a viable alternative for reducing the energy consumption of programs, while marginally compromising on the correctness of their computation. The idea behind...
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Reversible computation, whose special class is quantum computation, arises from the desire to reduce power dissipation, which can be zero under ideal physical circumstances. Nowadays, error correction and fault testin...
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