Privacy-Aware Load Balancing in Fog Networks: A Reinforcement Learning Approach

Fog Computing has emerged as a solution to support the growing demands of real-time Internet of Things (IoT) applications, which require high availability of these distributed services. Intelligent workload distribution algorithms are needed to maximize the utilization of such Fog resources while minimizing the time required to process these workloads. These load balancing algorithms are critical in dynamic environments with heterogeneous resources and workload requirements along with unpredictable traffic demands. In this paper, load balancing is provided using a Reinforcement Learning (RL) algorithm, which optimizes the system performance by minimizing the waiting delay of IoT workloads. Unlike previous studies, the proposed solution does not require load and resource information from Fog nodes, which makes the algorithm dynamically adaptable to possible environment changes over time. This also makes the algorithm aware of the privacy requirements of Fog service providers, who might like to hide such information to prevent competing providers from calculating better pricing strategies. The proposed algorithm is interactively evaluated on a Discrete-event Simulator (DES) to mimic a practical deployment of the solution in real environments. In addition, we evaluate the algorithm's generalization ability on simulations longer than what it was trained on, which, to the best of our knowledge, has never been explored before. The results provided in this paper show how our proposed approach outperforms baseline load balancing methods under different workload generation rates.Comment: 9 pages, 9 figures, 1 tabl

A Systematic Approach to the Management of Military Human Resources through the ELECTRE-MOr Multicriteria Method

Personnel selection is increasingly proving to be an essential factor for the success of organizations. These issues almost universally involve multiple conflicting objectives, uncertainties, costs, and benefits in decision-making. In this context, personnel assessment problems, which include several candidates as alternatives, along with several complex evaluation criteria, can be solved by applying Multicriteria Decision Making (MCDM) methods. Uncertainty and subjectivity characterize the choice of personnel for missions or promotions at the military level. In this paper, we evaluated 30 Brazilian Navy officers in the light of four criteria and 34 subcriteria. To support the decision-making process regarding the promotion of officers, we applied the ELECTRE-Mor MCDM method. We categorized the alternatives into three classes in the modeling proposed in this work, namely: Class A (Promotion by deserving), Class B (Promotion by seniority), and Class C (Military not promoted). As a result, the method presented 20% of the officers evaluated with performance corresponding to class A, 53% of the alternatives to class B, and 26.7% with performances attributed to class C. In addition, we presented a sensitivity analysis procedure through variation of the cut-off level λ, allowing decision-making on more flexible or rigorous scenarios at the discretion of the Naval High Administration. This work brings a valuable contribution to academia and society since it represents the application of an MCDM method in state of the art to contribute to solving a real problem.info:eu-repo/semantics/publishedVersio

Application of Partial-Order Methods to Reactive Systems with Event Memorization

International audienceWe are concerned in this paper with the verification of reactive systems with event memorization. The reactive systems are specified with an asynchronous reactive language Electre the main feature of which is the capability of memorizing occurrences of events in order to process them later. This memory capability is quite interesting for specifying reactive systems but leads to a verification model with a dramatically large number of states (due to the stored occurrences of events). In this paper, we show that partial-order methods can be applied successfuly for verification purposes on our model of reactive programs with event memorization. The main points of our work are two-fold: (1) we show that the independance relation which is a key point for applying partial-order methods can be extracted automatically from an \sf Electre program; (2) the partial-order technique turns out to be very efficient and may lead to a drastic reduction in the number of states of the model as demonstrated by a real-life industrial case study

Decision support system for project monitoring portfolio

Vallejo Antich, RA. (2010). Decision support system for project monitoring portfolio. http://hdl.handle.net/10251/8632.Archivo delegad

Using a multi-criteria decision aid methodology to implement sustainable development principles within an Organization

International audienceThe implementation of Sustainable Development (SD) within an Organization is a difficult task. This is due to the fact that it is difficult to deal with conflicting and incommensurable aspects such as environmental, economic and social dimensions. In this paper we have used a Multi-Criteria Decision Aid (MCDA) methodology to cope with these difficulties. MCDA methodology offers the opportunity to avoid monetary valuation of the different dimensions of the SD. These dimensions are not substitutable for one another and all have a role to play. There is an abundance of possible aggregation procedures in MCDA methodology. In this paper we have proposed an innovative method to choose a suitable aggregation procedure for SD problems. Real life case studies of the implementation of an outranking approach (i.e., ELECTRE) and of a mono-criterion synthesis approach (i.e., MAUT approaches based on the Choquet integral) were done to respectively rank 22 SD strategic actions within an expertise Institute and rank 20 practical operational actions to control energy consumption of the Institute's buildings

Permutation based decision making under fuzzy environment using Tabu search

One of the techniques, which are used for Multiple Criteria Decision Making (MCDM) is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS) based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method

Automated Federation Of Virtual Organization In Grid Using Select, Match, Negotiate And Expand (SMNE) Protocol [QA76.9.C58 C518 2008 f rb].

Sekelompok sumber perkomputeran yang teragih dan berlainan jenis dalam persekitaran grid akan membentuk organisasi maya dan berkongsi sumber komputer. A group of distributed and heterogeneous resources in a grid environment may form a Virtual Organization (VO) to enable resource sharing

Komparasi Kinerja ELECTRE dan MOORA dalam Menentukan Konsentrasi Tingkat Kesuburan Sperma

The aim of this research is to test and compare the performance of the ELECTRE method with MOORA in decision making. By using the attribute weighting process, namely the calculation of Information Gain in both methods, the attribute weights are obtained systematically and objectively, therefore they are no longer determined by the assumptions of decision makers. The test data instrument used is a dataset from the UCI Machine Learning Repository, namely the Fertility Dataset which is data on the level of sperm fertility concentration with 100 data records, 9 attributes, 1 class variable and the data set is multivariate. The results of testing the ELECTRE and MOORA methods in this study indicate that the two methods have differences in the results of ranking the best alternative for sperm fertility concentration levels. The ELECTRE method produces A2 as the best alternative, while the MOORA method produces A16 as the best alternative. Then in terms of program execution time, the MOORA method is faster, namely 0.02 seconds, while the ELECTRE method execution time is 1.88 seconds