9,932 research outputs found
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
An overview of game-theoretic approaches to energy-efficient resource
allocation in wireless networks is presented. Focusing on multiple-access
networks, it is demonstrated that game theory can be used as an effective tool
to study resource allocation in wireless networks with quality-of-service (QoS)
constraints. A family of non-cooperative (distributed) games is presented in
which each user seeks to choose a strategy that maximizes its own utility while
satisfying its QoS requirements. The utility function considered here measures
the number of reliable bits that are transmitted per joule of energy consumed
and, hence, is particulary suitable for energy-constrained networks. The
actions available to each user in trying to maximize its own utility are at
least the choice of the transmit power and, depending on the situation, the
user may also be able to choose its transmission rate, modulation, packet size,
multiuser receiver, multi-antenna processing algorithm, or carrier allocation
strategy. The best-response strategy and Nash equilibrium for each game is
presented. Using this game-theoretic framework, the effects of power control,
rate control, modulation, temporal and spatial signal processing, carrier
allocation strategy and delay QoS constraints on energy efficiency and network
capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on
Resource-Constrained Signal Processing, Communications and Networking, May
200
Efficient and adaptive congestion control for heterogeneous delay-tolerant networks
Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become saturated and unusable. We pro- pose CafRep, an adaptive congestion aware protocol that detects and reacts to congested nodes and congested parts of the network by using implicit hybrid contact and resources congestion heuristics. CafRep exploits localised relative utility based approach to offload the traffic from more to less congested parts of the network, and to replicate at adaptively lower rate in different parts of the network with non-uniform congestion levels. We extensively evaluate our work against benchmark and competitive protocols across a range of metrics over three real connectivity and GPS traces such as Sassy [44], San Francisco Cabs [45] and Infocom 2006 [33]. We show that CafRep performs well, independent of network connectivity and mobility patterns, and consistently outperforms the state-of-the-art DTN forwarding algorithms in the face of increasing rates of congestion. CafRep maintains higher availability and success ratios while keeping low delays, packet loss rates and delivery cost. We test CafRep in the presence of two application scenarios, with fixed rate traffic and with real world Facebook application traffic demands, showing that regardless of the type of traffic CafRep aims to deliver, it reduces congestion and improves forwarding performance
Computer Science and Game Theory: A Brief Survey
There has been a remarkable increase in work at the interface of computer
science and game theory in the past decade. In this article I survey some of
the main themes of work in the area, with a focus on the work in computer
science. Given the length constraints, I make no attempt at being
comprehensive, especially since other surveys are also available, and a
comprehensive survey book will appear shortly.Comment: To appear; Palgrave Dictionary of Economic
Spreading processes in Multilayer Networks
Several systems can be modeled as sets of interconnected networks or networks
with multiple types of connections, here generally called multilayer networks.
Spreading processes such as information propagation among users of an online
social networks, or the diffusion of pathogens among individuals through their
contact network, are fundamental phenomena occurring in these networks.
However, while information diffusion in single networks has received
considerable attention from various disciplines for over a decade, spreading
processes in multilayer networks is still a young research area presenting many
challenging research issues. In this paper we review the main models, results
and applications of multilayer spreading processes and discuss some promising
research directions.Comment: 21 pages, 3 figures, 4 table
A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions
The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network
- …