On Randomized Memoryless Algorithms for the Weighted kk-server Problem

The weighted $k$-server problem is a generalization of the $k$-server problem in which the cost of moving a server of weight $\beta_i$ through a distance $d$ is $\beta_i\cdot d$. The weighted server problem on uniform spaces models caching where caches have different write costs. We prove tight bounds on the performance of randomized memoryless algorithms for this problem on uniform metric spaces. We prove that there is an $\alpha_k$-competitive memoryless algorithm for this problem, where $\alpha_k=\alpha_{k-1}^2+3\alpha_{k-1}+1$; $\alpha_1=1$. On the other hand we also prove that no randomized memoryless algorithm can have competitive ratio better than $\alpha_k$. To prove the upper bound of $\alpha_k$ we develop a framework to bound from above the competitive ratio of any randomized memoryless algorithm for this problem. The key technical contribution is a method for working with potential functions defined implicitly as the solution of a linear system. The result is robust in the sense that a small change in the probabilities used by the algorithm results in a small change in the upper bound on the competitive ratio. The above result has two important implications. Firstly this yields an $\alpha_k$-competitive memoryless algorithm for the weighted $k$-server problem on uniform spaces. This is the first competitive algorithm for $k>2$ which is memoryless. Secondly, this helps us prove that the Harmonic algorithm, which chooses probabilities in inverse proportion to weights, has a competitive ratio of $k\alpha_k$.Comment: Published at the 54th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2013

Construction and commissioning of a technological prototype of a high-granularity semi-digital hadronic calorimeter

A large prototype of 1.3m3 was designed and built as a demonstrator of the semi-digital hadronic calorimeter (SDHCAL) concept proposed for the future ILC experiments. The prototype is a sampling hadronic calorimeter of 48 units. Each unit is built of an active layer made of 1m2 Glass Resistive Plate Chamber(GRPC) detector placed inside a cassette whose walls are made of stainless steel. The cassette contains also the electronics used to read out the GRPC detector. The lateral granularity of the active layer is provided by the electronics pick-up pads of 1cm2 each. The cassettes are inserted into a self-supporting mechanical structure built also of stainless steel plates which, with the cassettes walls, play the role of the absorber. The prototype was designed to be very compact and important efforts were made to minimize the number of services cables to optimize the efficiency of the Particle Flow Algorithm techniques to be used in the future ILC experiments. The different components of the SDHCAL prototype were studied individually and strict criteria were applied for the final selection of these components. Basic calibration procedures were performed after the prototype assembling. The prototype is the first of a series of new-generation detectors equipped with a power-pulsing mode intended to reduce the power consumption of this highly granular detector. A dedicated acquisition system was developed to deal with the output of more than 440000 electronics channels in both trigger and triggerless modes. After its completion in 2011, the prototype was commissioned using cosmic rays and particles beams at CERN.Comment: 49 pages, 41 figure

Signal Processing for Caching Networks and Non-volatile Memories

The recent information explosion has created a pressing need for faster and more reliable data storage and transmission schemes. This thesis focuses on two systems: caching networks and non-volatile storage systems. It proposes network protocols to improve the efficiency of information delivery and signal processing schemes to reduce errors at the physical layer as well. This thesis first investigates caching and delivery strategies for content delivery networks. Caching has been investigated as a useful technique to reduce the network burden by prefetching some contents during o˙-peak hours. Coded caching [1] proposed by Maddah-Ali and Niesen is the foundation of our algorithms and it has been shown to be a useful technique which can reduce peak traffic rates by encoding transmissions so that different users can extract different information from the same packet. Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. On one hand, distributed storage limits the capability of combining content from different servers into a single message, causing performance losses in coded caching schemes. But, on the other hand, the inherent redundancy existing in distributed storage systems can be used to improve the performance of those schemes through parallelism. This thesis proposes a scheme combining distributed storage of the content in multiple servers and an efficient coded caching algorithm for delivery to the users. This scheme is shown to reduce the peak transmission rate below that of state-of-the-art algorithms

Memoryless Algorithms for the Generalized kk-server Problem on Uniform Metrics

We consider the generalized $k$-server problem on uniform metrics. We study the power of memoryless algorithms and show tight bounds of $\Theta(k!)$ on their competitive ratio. In particular we show that the \textit{Harmonic Algorithm} achieves this competitive ratio and provide matching lower bounds. This improves the $\approx 2^{2^k}$ doubly-exponential bound of Chiplunkar and Vishwanathan for the more general setting of uniform metrics with different weights

Ad hoc IoT approach for monitoring parking control process

The purpose of this research is to develop a collaborative approach to control the parking in a city using IoT (Internet of Things). This approach is based on Bluetooth Low Energy (BLE) beacons to control the parking process without having to investment in sensors. Parking violations can be easily detected through the proposed collaborative process among user's mobile devices. A reward mechanism incentives users' participation. This approach uses an ad hoc network of users who send information to a central system regarding georeferenced beacon information. Comparing with previous payments associated with a vehicle, the approach can identify parking violations, e.g. parking without associated payment.info:eu-repo/semantics/publishedVersio

The Incremental Constraint of k-Server

Online algorithms are characterized by operating on an input sequence revealed over time versus a single static input. Instead of generating a single solution, they produce a sequence of incremental solutions corresponding to the input seen so far. An online algorithm's ignorance of future inputs limits its ability to produce optimal solutions. The incremental nature of its solutions is also an obstacle. The two factors can be differentiated by examining the corresponding incremental algorithm, which has knowledge of future inputs, but must still provide a competitive solution at each step. In this thesis, the lower bound of the incremental constraint of k-server is shown to be to 2