Bilateral Shapley Value Based Cooperative Gateway Selection in Congested Wireless Mesh Networks

Javadi, Farshad; Kibria, M.R.; Jamalipour, Abbas

doi:10.1109/glocom.2008.ecp.37

Cited by 9 publications

(9 citation statements)

References 5 publications

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“…For example, calculation numbers have reached to 2 10 − 1 = 1023 as coalition has prosuemrs |N | = 10. In order to solve the problem, bilateral Shapley value (BSV) is proposed by Ketchpel, which solves combinatorial explosion via bilateral-marginalization of coalition [33]. Primarily, bilateral coalition is defined as: assume that S = S 1 ∪ S 2 ⊆ N and S 1 ∩ S 2 = ∅, then S 1 and S 2 are called S's bilateral coalition.…”

Section: Distribution Mechanism Of Energy Costmentioning

confidence: 99%

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Liu

Wang²,

Sun³

2018

Energies

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Integrated energy system (IES) has received increasing attention in micro grid due to the high energy efficiency and low emission of carbon dioxide. Based on the technology of combined heat and power (CHP), this paper develops a novel operation mechanism with community micro turbine and shared energy storage system (ESS) for energy management of prosumers. In the proposed framework, micro-grid operator (MGO) equipped with micro turbine and ESS provides energy selling business and ESS leasing business for prosumers. Prosumers can make energy trading with public grid and MGO, and ESS will be shared among prosumers when they pay for the rent to MGO. Based on such framework, we adopt a cooperative game for prosumers to determine optimal energy trading strategies from MGO and public grid for the next day. Concretely, a cooperative game model is formulated to search the optimal strategies aiming at minimizing the daily cost of coalition, and then a bilateral Shapley value (BSV) is proposed to solve the allocation problem of coalition's cost among prosumers. To verify the effectiveness of proposed energy management framework, a practical example is conducted with a community energy network containing MGO and 10 residential buildings. Simulation results show that the proposed scheme is able to provide financial benefits to all prosumers, while providing peak load leveling for the grid.

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Section: Distribution Mechanism Of Energy Costmentioning

confidence: 99%

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Liu

Wang²,

Sun³

2018

Energies

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“…As the selected paths must satisfy the reliability level required by the client (R r ), thereby among the set of available paths from the gateways to the client, those which can not satisfy the client reliability requirement level are excluded from the set (i.e., selected paths should satisfy R p ≥ R r ). Thereafter, the Game Theory technique used in [5] is utilized to select a set of paths from the remaining available paths. This technique can be implemented in a decentralized fashion which reduces the process complexity.…”

Section: B Deciding Cycle (Dc)mentioning

confidence: 99%

“…Here, utility refers to the relative gain of a path in participating in a coalition and is related to the end-to-end throughput. Note that in [5] instead of normal Shapley Value, Bilateral Shapley Value (BSV) is used to avoid the exponential increase in complexity. Since the data rate contribution of each path must be allocated in a fair manner, a bargaining game theory is incorporated to offer a Pareto efficient equilibrium solution for data rate contribution among the participating paths.…”

Section: Introductionmentioning

confidence: 99%

“…In the proposed work, the utilized optimization technique is stemmed from a Game Theory based technique [4] which was introduced in the authors' previous work [5]. This technique is modeled as the coalition formation among participating paths where the solution is a Shapley Value based selection mechanism, and the main aim is to maximize the individual utility of the members in satisfying the goals.…”

Section: Introductionmentioning

confidence: 99%

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Multi-path routing for a cognitive Wireless Mesh Network

Javadi

Jamalipour

2009

2009 IEEE Radio and Wireless Symposium

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In Wireless Mesh Networks (WMNs), the achievable performance of the nodes depends on the behavior of intermediate routers. Utilizing cognition in the network could result in higher adaptivity to satisfy the end-user requirements. In this paper, we propose a cognitive WMN that utilizes multiple gateways to serve a client through multi-path routing. The injected intellectuality in the network (cognitive process) relieves the capriciousness by adaptively selecting the set of gateways, paths and their data rate contribution. The cognitive technique constantly observes the network through a feedback loop, takes appropriate decision using Game Theory, and applies the decision to the network. For evaluation, extensive simulation is carried out in OMNET discrete event simulator and subsequent results validated the performance of the proposed work.

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“…In the DC, a decision is taken, which results in the satisfaction of the aforementioned goals based on perceived information in the PC and LC. The utilized technique in the DC is an optimization mechanism based on the Game Theory from one of our previous works [4], which facilitates cooperation among neighboring MAPs and MPs for routing. It concurrently selects the best set from the available paths and allocates their data rate contributions.…”

Section: Introductionmentioning

confidence: 99%

A multi-path cognitive resource management mechanism for QoS provisioning in wireless mesh networks

Javadi

Jamalipour

2010

Wireless Netw

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In a Wireless Mesh Network (WMN), achieving acceptable Quality of Service (QoS) levels requires distributed control over network resources and subsequent awareness of the dynamically changing conditions of the WMN. In this paper, for facilitating such control, a cognitive mechanism is introduced, which facilitates cooperation and cognition among multiple Mesh Access Points and edge routers called Mesh Portals for routing client traffic via multiple paths. The aim of the cognition is to reasonably maximize the fulfillment of the clients from the achieved QoS (e.g., end-to-end delay and bandwidth). The cognitive process consists of three cycles. In the first cycle, the Perception Cycle, the current performance status of the WMN is continuously perceived through feedback loops. The perceived information is further processed and fed into the second cycle, the Learning Cycle, in order to understand the network conditions. This results in the prediction of the performance of the paths and estimation of the path delay for various load conditions. The third cycle, the Decision Cycle, is a game theoretic coalition formation algorithm, that results in path selection and data rate assignment. This algorithm is modeled as a cooperative game theory, which incorporates the Bilateral Shapley Value to find the best coalition from available paths, whereupon a bargaining game theory formulates the data rate assignment. Extensive simulations are performed for evaluating the proposed cognitive mechanism under various load conditions and results demonstrate the evident enhancement of the achieved end-to-end QoS of the clients and the network performance compared with non-cognitive scenarios, specifically in congested conditions.

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Bilateral Shapley Value Based Cooperative Gateway Selection in Congested Wireless Mesh Networks

Cited by 9 publications

References 5 publications

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Multi-path routing for a cognitive Wireless Mesh Network

A multi-path cognitive resource management mechanism for QoS provisioning in wireless mesh networks

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