Optimal Resource Allocation and Relay Selection in Bandwidth Exchange Based Cooperative Forwarding

In this paper, we investigate joint optimal relay selection and resource allocation under bandwidth exchange (BE) enabled incentivized cooperative forwarding in wireless networks. We consider an autonomous network where N nodes transmit data in the uplink to an access point (AP) / base station (BS). We consider the scenario where each node gets an initial amount (equal, optimal based on direct path or arbitrary) of bandwidth, and uses this bandwidth as a flexible incentive for two hop relaying. We focus on alpha-fair network utility maximization (NUM) and outage reduction in this environment. Our contribution is two-fold. First, we propose an incentivized forwarding based resource allocation algorithm which maximizes the global utility while preserving the initial utility of each cooperative node. Second, defining the link weight of each relay pair as the utility gain due to cooperation (over noncooperation), we show that the optimal relay selection in alpha-fair NUM reduces to the maximum weighted matching (MWM) problem in a non-bipartite graph. Numerical results show that the proposed algorithms provide 20- 25% gain in spectral efficiency and 90-98% reduction in outage probability.Comment: 8 pages, 7 figure

Adaptive Energy Aware Cooperation Strategy in Heterogeneous Multi-domain Sensor Networks

AbstractIn some applications of sensor networks, multi-domain exists and cooperation among domains could lead to longer lifetime. In this paper, we consider heterogeneous multi-domain sensor networks. It means that different networks belong to different domains and sensors are deployed at the same physical location and their topology is heterogonous. Apparently, domains life time can be increased by means of cooperation in packet forwarding; however selfishness is inevitable from rational perspective. We investigate this problem to find out cooperation of authorities while their sensors are energy aware. When sensors are energy aware, spontaneous cooperation cannot take place. Therefore we presented the Adaptive Energy Aware strategy, a novel algorithm that is based on TIT-FOR-TAT, starts with generosity and ends up with conservative behaviour. Our simulation results showed that this algorithm could prolong its network lifetime in competition with other networks

Game theory for collaboration in future networks

Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio

Energy Efficiency in Multi-hop CDMA Networks: A Game Theoretic Analysis

A game-theoretic analysis is used to study the effects of receiver choice on the energy efficiency of multi-hop networks in which the nodes communicate using Direct-Sequence Code Division Multiple Access (DS-CDMA). A Nash equilibrium of the game in which the network nodes can choose their receivers as well as their transmit powers to maximize the total number of bits they transmit per unit of energy is derived. The energy efficiencies resulting from the use of different linear multiuser receivers in this context are compared, looking at both the non-cooperative game and the Pareto optimal solution. For analytical ease, particular attention is paid to asymptotically large networks. Significant gains in energy efficiency are observed when multiuser receivers, particularly the linear minimum mean-square error (MMSE) receiver, are used instead of conventional matched filter receivers.Comment: To appear in the Proceedings of the Workshop on Multi-Layer Modelling and Design of Multi-Hop Wireless Networks (MLMD 06), Minneapolis, MN, July 12 - 15, 200

Scalable Data Management in Mobile Environments: protocol design in MANETs and data management in mobile sensors

My presentation addressed with two areas of my current research interests: (1) Protocol design in Mobile Ad-hoc Networks, and (2) Sensor data management. It describes briefly the motivating challenges and our approach to dealing with them

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio