Vaggelis G. Douros

Power Control in WLANs for Optimization of Social Fairness

Wide deployment of wireless local area networks (WLANs), especially in modern densely-populated metropolitan areas, constitutes a leap towards ubiquitous wireless network access. This is largely attributable to their low installation and operational cost and mainly their operation in unlicensed bands. Together with the clear benefits of increased WLAN coverage though, new challenges have emerged; dense WLAN deployments lead to significant interference among neighbor networks, making its mitigation a matter of crucial importance for their performance. To this end, transmission power control is a natural choice to limit interference. In this paper, we propose and evaluate two algorithms (FirstMax and BestMax) for WLAN Access Points (APs) to cooperatively control their transmission power levels, leading to more fair and more efficient spectrum usage. Simulations demonstrate that the proposed algorithms (and especially BestMax) are far more profitable and fair choices than transmitting at the maximum feasible power. Consequently, an optimization of the social fairness can be achieved.

On the Nash Equilibria of graphical games for channel access in multihop wireless networks

We study a multihop wireless network with a tree topology where selfish nodes compete for channel access. Firstly, we discuss how this is relevant to future multihop networks focusing on the concept of Device-to-Device communication. We then model this framework as a graphical game, which is a special case of a non-cooperative game in which the payoff of a node is influenced only by a subset of its neighbors. We discuss two payoff models that may be used depending on the application: The first focuses only on transmitters and assigns by default a zero payoff to the receivers and the second models a non-zero payoff to both transmitters and receivers. We then present a distributed scheme that finds an efficient Nash Equilibrium (NE) under both payoff models. We evaluate its performance through extensive simulations showing that the algorithm converges fast to a NE, in a number of rounds that is proportional to the logarithm of the number of nodes. Finally, we find that the number of successful transmissions is almost equal at any NE. This indicates that, under this metric, any NE is practically equally preferable.

On the efficiency of lightweight content placement heuristics for cache-enabled networks

Cache-enabled networks have received increasing attention in both wired and wireless settings. A big challenge for the operator of such networks is to solve efficiently the content placement problem, i.e., to decide how many caches to deploy in the network and in which nodes. We study the content placement problem for two classes of network optimisation objectives, the first focusing on the minimisation of the sum of the shortest paths and the second capturing the cost vs. benefit trade-off to deploy a cache. We know from the state-of-the-art that, even in small networks with few caches, it is unrealistic to find the optimal solution in a reasonable timescale for similar optimisation problems. In order to cope with this challenge, we present an approach under the prism of network analysis. We introduce a family of lightweight heuristic algorithms that use graph-theoretic metrics that identify the most important nodes of the network. We evaluate the performance of the heuristics using real network datasets, showing that the best heuristics are based on the metrics of betweenness centrality and degree centrality. Finally, we provide a randomised version of the heuristics noticing that the same metrics present again the best performance across the different datasets. Moreover, we find out that, in general, the deterministic version of each heuristic outperforms its randomised version.

Caching Games between Content Providers and Internet Service Providers

We consider a scenario where an Internet Service Provider (ISP) serves users that choose digital content among M Content Providers (CP). In the status quo, these users pay both access fees to the ISP and content fees to each chosen CP; however, neither the ISP nor the CPs share their profit. We revisit this model by introducing a different business model where the ISP and the CP may have motivation to collaborate in the framework of caching. The key idea is that the ISP deploys a cache for a CP provided that they share both the deployment cost and the additional profit that arises due to caching. Under the prism of coalitional games, our contributions include the application of the Shap-ley value for a fair splitting of the profit, the stability analysis of the coalition and the derivation of closed-form formulas for the optimal caching policy. Our model captures not only the case of non-overlapping contents among the CPs, but also the more challenging case of overlapping contents; for the latter case, a non-cooperative game among the CPs is introduced and analyzed to capture the negative externality on the demand of a particular CP when caches for other CPs are deployed.

Caching games between Content Providers and Internet Service Providers

Abstract We consider a scenario where an Internet Service Provider (ISP) serves users that choose digital content among M Content Providers (CP). In the status quo, these users pay both access fees to the ISP and content fees to each chosen CP; however, neither the ISP nor the CPs share their profit. We revisit this model by introducing a different business model where the ISP and the CP may have motivation to collaborate in the framework of caching. The key idea is that the ISP deploys a cache for a CP provided that they share both the deployment cost and the additional profit that arises due to caching. Under the prism of coalitional games, our contributions include the application of the Shapley value for a fair splitting of the profit, the stability analysis of the coalition and the derivation of closed-form formulas for the optimal caching policy. Our model captures not only the case of non-overlapping contents among the CPs, but also the more challenging case of overlapping contents; for the latter case, a non-cooperative game among the CPs is introduced and analyzed to capture the negative externality on the demand of a particular CP when caches for other CPs are deployed.

Power Control and Bargaining for Cellular Operator Revenue Increase Under Licensed Spectrum Sharing

Due to the constant need for ever-increasing spectrum efficiency, licensed spectrum sharing approaches, where no exclusive rights are given to any single operator, have recently attracted significant attention. Under this setting, the operators, though still selfish, have motivation to cooperate so as to provide high Quality-of-Service to their respective customers. In this context, we present an approach based on a simple charging model where many operators may coexist efficiently by combining traditional power control with bargaining, using “take it or leave it” offers. We derive conditions for a successful bargain. For the special case of two operators, we show that, through our scheme, each operator always achieves a payoff that is higher than the Nash Equilibrium payoff. We also show analytically when our scheme maximizes the social welfare, i.e., the sum of payoffs. We then compare its performance through simulations with a scheme that maximizes the social welfare and a scheme that applies linear power pricing.

Channel access competition in linear multihop device-to-device networks

We study a linear multihop network that is formed by wireless devices that can directly communicate pairwise whenever two devices are within range of each other. This Device-to-Device communication model is expected to play a significant role in future 5G wireless networks due to its advantages (e.g., cellular offloading, increased throughput and low cost/energy communication). In such networks, devices are typically selfish and compete for channel access aiming at maximizing their own throughput while at the same time avoiding packet collisions. In this setup, we study how an efficient coexistence of these devices may be achieved, using a game-theoretic approach. First, we model the contention for the channel as a game and study the structural properties of the resulting Nash Equilibria (NE). Then, we design a distributed, round-based scheme that is guaranteed to converge to a NE. We compare quantitatively and qualitatively this scheme with previous work. We show that this scheme converges faster to a NE, in a number of rounds that is proportional to the logarithm of the number of nodes of the network. Moreover, the convergence is monotonic, meaning that the percentage of nodes that finalize their strategy is increasing in each round.

Fighting packet storms in mobile networks with information-centrism

Mobile application development for smartphones is a trend in the telecommunications industry. However, their deployment is not seamless since many applications are not “mobile network-friendly.” A key problem that frequently arises is an excessive number of signaling messages, known as signaling storms. This leads to very high overhead and a decrease in operator income. We focus on this problem and propose an approach that is based on an information-centric networking deployment at the access network. We compute the number of signaling messages and derive the conditions under which our approach leads to fewer messages than the approach that is used in current networks. We also argue about the network and application layer modifications that are needed for the adoption of our method.