1,354,791 research outputs found
Massive Opportunistic Sensing with Limited Collaboration for Age of Information
No full textWe consider an Internet of thing scenario, where a set of sensors collect data and exchange them with a common receiver. We analyze their interaction, considering a shared goal to minimize Age of information at the receiver's side. We argue that a fully collaborative setup, albeit generally succeeding in this task at first, often leads to resource wastage in the long run. We try to achieve a similar level of cooperation through a purely opportunistic mechanism, in which nodes are driven by selfish objectives, but still aware of the ultimate goal of maximizing information freshness. We show how our proposed approach, allowing fewer nodes to participate in the task (up to one order of magnitude), results in a better resource management, still improving the long-term average age of information. At the same time, a target number of participating nodes can be set, e.g., to a given fraction of the network, by properly tuning the individual objectives and the communication costs
An online approach for the scheduling of treatment modalities in a rehabilitation department
No full textWorking pape
Analysis of Age of Information in Slotted ALOHA Networks With Different Strategic Backoff Schemes
No full textStatus update freshness in slotted ALOHA networks is an important issue for Internet of things scenarios with large number of nodes and uncoordinated access. We compare the age of information of three different implementations of a backoff to counteract collisions due to uncoordinated medium access, where the transmission probability is (i) gradually decreased, (ii) turned to 0 after a collision, or (iii) turned to 0 proactively. We discuss whether these strategies decrease the average AoI of the nodes, and highlight how their efficiency changes with a distributed application in a game theoretic fashion. As a result, the gradual backoff scheme is not recommended, whereas the reactive scheme has an optimal performance inferior to the proactive one, but obtains analogous results at the Nash equilibrium, and can be a candidate for practical implementations
DCP: a TCP-Inspired Method for Online Domain Adaptation under Dynamic Data Drift
No full textMobile computing faces challenges due to the resource constraints of mobile devices, such as limited computing power, energy, and connectivity. These limitations hinder the use of high-complexity classifiers and wireless transmissions. To address this issue, we propose a novel collaboration paradigm between mobile devices and edge servers, where the edge server assists the mobile devices by dynamically retraining a low-complexity classifier to adapt to temporal changes in data distribution. We propose a novel approach called drift control protocol (DCP) which is inspired by TCP congestion control mechanism. DCP aims to strike a balance between low-complexity classifier retraining frequency and communication costs with the edge server. It adjusts the update rate of the classifier on the mobile device based on distribution drift characteristics and controls the number of input samples sent to the edge server to improve accuracy. We evaluate and study different versions of DCP using synthetic and real datasets We demonstrate that DCP keeps the error bound, while reducing the burden of the communication cost by 90% for the mobile nodes, which makes our proposal suitable for online domain adaptation
Are Retailers’ Private Labels Always Detrimental to National Brand Manufacturers? A Differential Game Perspective
No full textWe study the competition between national and private brands (or private labels) in a vertical channel structure. Our main objective is to analyze the impacts of the private label’s existence on strategies, sales, and profits of the members and the whole channel. We use a differential game, where the control variables are price and non-price marketing decisions, and investigate two scenarios. The first one, used as a benchmark, considers an exclusive retailer that distributes only a national brand provided by a manufacturer. The latter invests in national advertising to build its brand’s goodwill. In the second scenario, the retailer owns a private label that competes with the national brand. By computing the results under both scenarios, we provide answers to the following research questions: (1) What should the price and the non-price marketing strategies be, with and without the private label? (2) How do they compare? (3) Is the presence of a private label always profitable for the retailer and harmful to the manufacturer? One of our main results indicates that the manufacturer is not necessarily always hurt by the private label, as the existing literature suggests
When does a royalty clause with a guarantee lead to a no-equilibrium situation in a licensing contract?
No full textWe consider a licensing agreement where a brand owner grants to a manufacturer the rights to use his own brand on the goods she produces. The ‘royalty’ clause requires that the licensee pays a monetary compensation for having such property and it generally consists of a percentage of the licensee's sales. Furthermore, a guaranteed minimum royalty, the so-called guarantee, is also required, and it has to be paid even in the face of total failure of the property.
We take into account such clause by considering a non-differentiable term—the maximum between the guarantee and the percentage of the sales—in the payoffs of the involved parts. A Stackelberg game constituted by two non-differentiable optimal control problems is formulated in order to find the Stackelberg equilibrium open-loop advertising strategies for the licensor and the licensee. We discuss the existence conditions for such an equilibrium with respect to feasible guarantee levels, and we highlight that particular guarantee values lead to a no-equilibrium situations
Strategic Backoff of Slotted ALOHA for Minimal Age of Information
No full textRandom access protocols are usually adopted in the Internet of Things to enable uncoordinated medium sharing. Tackling this setting, we explore the statistics of the packet inter-delivery times under slotted ALOHA contention, considering two backoff schemes (reactive vs. proactive). We further discuss the efficiency of these schemes in minimizing the average age of information. Finally, we investigate age minimization both as a centralized optimization and via game theory, obtaining numerical solutions for both cases. A reactive scheme applied in a centralized manner is found to be the most suitable to systems that require a bounded age, whereas a proactive solution applied distributedly is best used to minimize the average age
Cybersecurity Analysis Through Shapley Values for a Network Traffic Dataset of Android Malware
No full textWe explore the use of machine learning, specifically Random Forest classifiers, combined with SHapley Additive exPlanations values, to detect Android malware. We leverage diverse datasets, including the Android Genome Project and Drebin, to distinguish between benign and malicious applications. Emphasizing feature importance through SHAP analysis, we aim to enhance model interpretability and effectiveness in cybersecurity. This approach not only improves threat detection accuracy, but also contributes to the broader field of explainable AI in cybersecurity. The paper is structured to cover theoretical foundations, methodology, results, and future directions in this evolving area of study. Also, based on practical findings, we highlight the importance of the data source and transmission patterns as a way to identify malware
Advertising and Price to Sustain The Brand Value in a Licensing Contract
No full textOne of the reasons that induce a brand owner to issue a licensing contract is that of improving the value of his brand. In this paper, we look at a fashion licensing agreement where the licensee produces and sells a product in a complementary business. The value of a fashion brand is sustained by both the advertising efforts of the licensor and the licensee. We assume that demand is proportional to the brand value and decreases with the price. The licensor wants to maximize his revenue coming from the royalties and to minimize his advertising costs. Moreover, he does not want his brand to be devalued at the end of the selling season. On the other hand, the licensee plans her advertising campaign in order to invest in the brand value and maximize the sales revenue. The aim of this paper is to analyze the different strategies the licensor can adopt to sustain his brand. To this end, we determine the optimal advertising policies by solving a Stackelberg differential game, where the owner of the brand acts as the leader and the licensee as the follower. We determine the equilibrium policies of the two players assuming that advertising varies over time and price is constant. We also determine a minimum selling price which guarantees brand sustainability without advertising too much
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