arXiv subjects

George Iosifidis

Publications and source records attributed to George Iosifidis.

51 records · Page 3Linked to original sources

arXiv2019

Learning to Cooperate in D2D Caching Networks

We consider a wireless device-to-device (D2D) cooperative network where memory-endowed nodes store and exchange content. Each node generates random file requests following an unknown and possibly arbitrary spatio-temporal process, and a base station (BS) delivers any file that is not found at its neighbors' cache, at the expense of higher cost. We design an online learning algorithm which minimizes the aggregate delivery cost by assisting each node to decide which files to cache and which files to fetch from the BS and other devices. Our policy relies on the online gradient descent algorithm, is amenable to distributed execution, and achieves asymptotically optimal performance for any request pattern, without prior information.

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arXiv2019

Maximum Lifetime Analytics in IoT Networks

This paper studies the problem of allocating bandwidth and computation resources to data analytics tasks in Internet of Things (IoT) networks. IoT nodes are powered by batteries, can process (some of) the data locally, and the quality grade or performance of how data analytics tasks are carried out depends on where these are executed. The goal is to design a resource allocation algorithm that jointly maximizes the network lifetime and the performance of the data analytics tasks subject to energy constraints. This joint maximization problem is challenging with coupled resource constraints that induce non-convexity. We first show that the problem can be mapped to an equivalent convex problem, and then propose an online algorithm that provably solves the problem and does not require any a priori knowledge of the time-varying wireless link capacities and data analytics arrival process statistics. The algorithm's optimality properties are derived using an analysis which, to the best of our knowledge, proves for the first time the convergence of the dual subgradient method with time-varying sets. Our simulations seeded by real IoT device energy measurements, show that the network connectivity plays a crucial role in network lifetime maximization, that the algorithm can obtain both maximum network lifetime and maximum data analytics performance in addition to maximizing the joint objective, and that the algorithm increases the network lifetime by approximately 50% compared to an algorithm that minimizes the total energy consumption.

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arXiv2019

Learning to Cache With No Regrets

This paper introduces a novel caching analysis that, contrary to prior work, makes no modeling assumptions for the file request sequence. We cast the caching problem in the framework of Online Linear Optimization (OLO), and introduce a class of minimum regret caching policies, which minimize the losses with respect to the best static configuration in hindsight when the request model is unknown. These policies are very important since they are robust to popularity deviations in the sense that they learn to adjust their caching decisions when the popularity model changes. We first prove a novel lower bound for the regret of any caching policy, improving existing OLO bounds for our setting. Then we show that the Online Gradient Ascent (OGA) policy guarantees a regret that matches the lower bound, hence it is universally optimal. Finally, we shift our attention to a network of caches arranged to form a bipartite graph, and show that the Bipartite Subgradient Algorithm (BSA) has no regret

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arXiv2019

Pricing for Collaboration Between Online Apps and Offline Venues

An increasing number of mobile applications (abbrev. apps), like Pokemon Go and Snapchat, reward the users who physically visit some locations tagged as POIs (places-of-interest) by the apps. We study the novel POI-based collaboration between apps and venues (e.g., restaurants). On the one hand, an app charges a venue and tags the venue as a POI. The POI tag motivates users to visit the venue, which potentially increases the venue's sales. On the other hand, the venue can invest in the app-related infrastructure, which enables more users to use the app and further benefits the app's business. The apps' existing POI tariffs cannot fully incentivize the venue's infrastructure investment, and hence cannot lead to the most effective app-venue collaboration. We design an optimal two-part tariff, which charges the venue for becoming a POI, and subsidizes the venue every time a user interacts with the POI. The subsidy design efficiently incentivizes the venue's infrastructure investment, and we prove that our tariff achieves the highest app's revenue among a general class of tariffs. Furthermore, we derive some counter-intuitive guidelines for the POI-based collaboration. For example, a bandwidth-consuming app should collaborate with a low-quality venue (users have low utilities when consuming the venue's products).

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arXiv2018

The Role of Caching in Future Communication Systems and Networks

This paper has the following ambitious goal: to convince the reader that content caching is an exciting research topic for the future communication systems and networks. Caching has been studied for more than 40 years, and has recently received increased attention from industry and academia. Novel caching techniques promise to push the network performance to unprecedented limits, but also pose significant technical challenges. This tutorial provides a brief overview of existing caching solutions, discusses seminal papers that open new directions in caching, and presents the contributions of this Special Issue. We analyze the challenges that caching needs to address today, considering also an industry perspective, and identify bottleneck issues that must be resolved to unleash the full potential of this promising technique.

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arXiv2018

SDN-enabled Tactical Ad Hoc Networks: Extending Programmable Control to the Edge

Modern tactical operations have complex communication and computing requirements, often involving different coalition teams, that cannot be supported by today's mobile ad hoc networks. To this end, the emerging Software Defined Networking (SDN) paradigm has the potential to enable the redesign and successful deployment of these systems. In this paper, we propose a set of novel architecture designs for SDN-enabled mobile ad hoc networks in the tactical field. We discuss in detail the challenges raised by the ad hoc and coalition network environment, and we present specific solutions to address them. The proposed approaches build on evidence from experimental evaluation of such architectures and leverage recent theoretical results from SDN deployments in large backbone networks.

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arXiv2017

Dynamic Policies for Cooperative Networked Systems

A set of economic entities embedded in a network graph collaborate by opportunistically exchanging their resources to satisfy their dynamically generated needs. Under what conditions their collaboration leads to a sustainable economy? Which online policy can ensure a feasible resource exchange point will be attained, and what information is needed to implement it? Furthermore, assuming there are different resources and the entities have diverse production capabilities, which production policy each entity should employ in order to maximize the economy's sustainability? Importantly, can we design such policies that are also incentive compatible even when there is no a priori information about the entities' needs? We introduce a dynamic production scheduling and resource exchange model to capture this fundamental problem and provide answers to the above questions. Applications range from infrastructure sharing, trade and organisation management, to social networks and sharing economy services.

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arXiv2017

On the Efficiency of Sharing Economy Networks

We consider a sharing economy network where agents embedded in a graph share their resources. This is a fundamental model that abstracts numerous emerging applications of collaborative consumption systems. The agents generate a random amount of spare resource that they can exchange with their one-hop neighbours, seeking to maximize the amount of desirable resource items they receive in the long run. We study this system from three different perspectives: a) the central designer who seeks the resource allocation that achieves the most fair endowments after the exchange; b) the game theoretic where the nodes seek to form sharing coalitions within teams, attempting to maximize the benefit of their team only; c) the market where the nodes are engaged in trade with their neighbours trying to improve their own benefit. It is shown that there is a unique family of sharing allocations that are at the same time most fair, stable with respect to continuous coalition formation among the nodes and achieving equilibrium in the market perspective. A dynamic sharing policy is given then where each node observes the sharing rates of its neighbours and allocates its resource accordingly. That policy is shown to achieve long term sharing ratios that are within the family of equilibrium allocations of the static problem. The equilibrium allocations have interesting properties that highlight the dependence of the sharing ratios of each node to the structure of the topology graph and the effect of the isolation of a node on the benefit may extract from his neighbours.

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arXiv2016

Efficient and Fair Collaborative Mobile Internet Access

The surging global mobile data traffic challenges the economic viability of cellular networks and calls for innovative solutions to reduce the network congestion and improve user experience. In this context, user-provided networks (UPNs), where mobile users share their Internet access by exploiting their diverse network resources and needs, turn out to be very promising. Heterogeneous users with advanced handheld devices can form connections in a distributed fashion and unleash dormant network resources at the network edge. However, the success of such services heavily depends on users' willingness to contribute their resources, such as network access and device battery energy. In this paper, we introduce a general framework for UPN services and design a bargaining-based distributed incentive mechanism to ensure users participation. The proposed mechanism determines the resources that each user should contribute in order to maximise the aggregate data rate in UPN, and fairly allocate the benefit among the users. The numerical results verify that the service can always improve performance, and such improvement increases with the diversity of the users' resources. Quantitatively, it can reach an average 30% increase of the total served traffic for a typical scenario even with only 6 mobile users.

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arXiv2016

Auction-Based Coopetition between LTE Unlicensed and Wi-Fi

Motivated by the recent efforts in extending LTE to the unlicensed spectrum, we propose a novel spectrum sharing framework for the coopetition (i.e., cooperation and competition) between LTE and Wi-Fi in the unlicensed band. Basically, the LTE network can choose to work in one of the two modes: in the competition mode, it randomly accesses an unlicensed channel, and interferes with the Wi-Fi access point using the same channel; in the cooperation mode, it delivers traffic for the Wi-Fi users in exchange for the exclusive access of the corresponding channel. Because the LTE network works in an interference-free manner in the cooperation mode, it can achieve a much larger data rate than that in the competition mode, which allows it to effectively serve both its own users and the Wi-Fi users. We design a second-price reverse auction mechanism, which enables the LTE provider and the Wi-Fi access point owners (APOs) to effectively negotiate the operation mode. Specifically, the LTE provider is the auctioneer (buyer), and the APOs are the bidders (sellers) who compete to sell their channel access opportunities to the LTE provider. In Stage I of the auction, the LTE provider announces a reserve rate. In Stage II of the auction, the APOs submit their bids. We show that the auction involves allocative externalities, i.e., the cooperation between the LTE provider and one APO benefits other APOs who are not directly involved in this cooperation. As a result, a particular APO's willingness to cooperate is affected by its belief about other APOs' willingness to cooperate. This makes our analysis much more challenging than that of the conventional second-price auction, where bidding truthfully is a weakly dominant strategy. We show that the APOs have a unique form of the equilibrium bidding strategies in Stage II, based on which we analyze the LTE provider's optimal reserve rate in Stage I.

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arXiv2015

Exchange of Services in Networks: Competition, Cooperation, and Fairness

Exchange of services and resources in, or over, networks is attracting nowadays renewed interest. However, despite the broad applicability and the extensive study of such models, e.g., in the context of P2P networks, many fundamental questions regarding their properties and efficiency remain unanswered. We consider such a service exchange model and analyze the users' interactions under three different approaches. First, we study a centrally designed service allocation policy that yields the fair total service each user should receive based on the service it others to the others. Accordingly, we consider a competitive market where each user determines selfishly its allocation policy so as to maximize the service it receives in return, and a coalitional game model where users are allowed to coordinate their policies. We prove that there is a unique equilibrium exchange allocation for both game theoretic formulations, which also coincides with the central fair service allocation. Furthermore, we characterize its properties in terms of the coalitions that emerge and the equilibrium allocations, and analyze its dependency on the underlying network graph. That servicing policy is the natural reference point to the various mechanisms that are currently proposed to incentivize user participation and improve the efficiency of such networked service (or, resource) exchange markets.

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arXiv2014

Bargaining-based Mobile Data Offloading

The unprecedented growth of mobile data traffic challenges the performance and economic viability of today's cellular networks, and calls for novel network architectures and communication solutions. Data offloading through third-party WiFi or femtocell access points (APs) can effectively alleviate the cellular network congestion in a low operational and capital expenditure. This solution requires the cooperation and agreement of mobile cellular network operators (MNOs) and AP owners (APOs). In this paper, we model and analyze the interaction among one MNO and multiple APOs (for the amount of MNO's offloading data and the respective APOs' compensations) by using the Nash bargaining theory. Specifically, we introduce a one-to-many bargaining game among the MNO and APOs, and analyze the bargaining solution (game equilibrium) systematically under two different bargaining protocols: (i) sequential bargaining, where the MNO bargains with APOs sequentially, with one APO at a time, in a given order, and (ii) concurrent bargaining, where the MNO bargains with all APOs concurrently. We quantify the benefits for APOs when bargaining sequentially and earlier with the MNO, and the losses for APOs when bargaining concurrently with the MNO. We further study the group bargaining scenario where multiple APOs form a group bargaining with the MNO jointly, and quantify the benefits for APOs when forming such a group. Interesting, our analysis indicates that grouping of APOs not only benefits the APOs in the group, but may also benefit some APOs not in the group. Our results shed light on the economic aspects and the possible outcomes of the MNO/APOs interactions, and can be used as a roadmap for designing policies for this promising data offloading solution.

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arXiv2014

Multicast-aware Caching for Small Cell Networks

The deployment of small cells is expected to gain huge momentum in the near future, as a solution for managing the skyrocketing mobile data demand growth. Local caching of popular files at the small cell base stations has been recently proposed, aiming at reducing the traffic incurred when transferring the requested content from the core network to the users. In this paper, we propose and analyze a novel caching approach that can achieve significantly lower traffic compared to the traditional caching schemes. Our cache design policy carefully takes into account the fact that an operator can serve the requests for the same file that happen at nearby times via a single multicast transmission. The latter incurs less traffic as the requested file is transmitted to the users only once, rather than with many unicast transmissions. Systematic experiments demonstrate the effectiveness of our approach, as compared to the existing caching schemes.

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arXiv2012

Competition and Regulation in Wireless Services Markets

We consider a wireless services market where a set of operators compete for a large common pool of users. The latter have a reservation utility of U0 units or, equivalently, an alternative option to satisfy their communication needs. The operators must satisfy these minimum requirements in order to attract the users. We model the users decisions and interaction as an evolutionary game and the competition among the operators as a non cooperative price game which is proved to be a potential game. For each set of prices selected by the operators, the evolutionary game attains a different stationary point. We show that the outcome of both games depend on the reservation utility of the users and the amount of spectrum W the operators have at their disposal. We express the market welfare and the revenue of the operators as functions of these two parameters. Accordingly, we consider the scenario where a regulating agency is able to intervene and change the outcome of the market by tuning W and/or U0. Different regulators may have different objectives and criteria according to which they intervene. We analyze the various possible regulation methods and discuss their requirements, implications and impact on the market.

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arXiv2011

Incentive Mechanisms for Hierarchical Spectrum Markets

In this paper, we study spectrum allocation mechanisms in hierarchical multi-layer markets which are expected to proliferate in the near future based on the current spectrum policy reform proposals. We consider a setting where a state agency sells spectrum channels to Primary Operators (POs) who subsequently resell them to Secondary Operators (SOs) through auctions. We show that these hierarchical markets do not result in a socially efficient spectrum allocation which is aimed by the agency, due to lack of coordination among the entities in different layers and the inherently selfish revenue-maximizing strategy of POs. In order to reconcile these opposing objectives, we propose an incentive mechanism which aligns the strategy and the actions of the POs with the objective of the agency, and thus leads to system performance improvement in terms of social welfare. This pricing-based scheme constitutes a method for hierarchical market regulation. A basic component of the proposed incentive mechanism is a novel auction scheme which enables POs to allocate their spectrum by balancing their derived revenue and the welfare of the SOs.

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