Titlebook: Wired/Wireless Internet Communications; 15th IFIP WG 6.2 Int Yevgeni Koucheryavy,Lefteris Mamatas,Panagiotis Pa Conference proceedings 2017

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Distributed Sleep Mode Power Control in 5G Ultra Dense Networks which utilizes sleep mode strategies and spectrum sharing among users. The mechanism exhibits increased throughput for the femtocell subscribers, preserving non-subscribers performance and increasing the network’s energy efficiency.

Asperity

Bargaining over Fair Channel Sharing Between Wi-Fi and LTE-U Networksh bargaining approach. In particular, we show that such a time-sharing bargaining protocol, in spite of the interference between signals, can lead to a gain for both networks under an increase of the transmission power to one of them.

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Bargaining over Fair Channel Sharing Between Wi-Fi and LTE-U Networksnologies. Sharing wireless resources between different wireless technologies requires protocols that share spectrum in an equitable manner. In this paper, we examine the time-sharing of wireless channels by Wi-Fi and LTE-U networks. To design fair access protocol for the networks we use . fairness c

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Analysis and Performance Evaluation of SDN Queue Model examine how networks’ performance will be affected as the traffic loads and network utilization change. To achieve the aimed goal, as a research method, we used AnyLogic Multimethod simulation tool. This is a first of its kind where SDN performance evaluation is based on queuing model simulation to

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Analysis of a Retrial Queue with Limited Processor Sharing Operating in the Random Environmentf the arrival rate, capacity of the server, i.e., the number of customers than can share the server simultaneously, the service intensity, the impatience rate, etc.) depend on the state of the random environment. Customers arriving when the server capacity is exhausted join orbit and retry for servi

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Stationary Distribution of Waiting Time in , Queueing System with LIFO Service Disciplineare selected for the service in accordance with the LIFO (Last In – First Out) service discipline. It is well known that stationary distribution of the number of customers in such a system coincides with the corresponding distribution in the system with FIFO (First In – First Out) discipline which h