scholarly journals Game-based cache allocation strategy for ICN slicing

2021 ◽  
Vol 336 ◽  
pp. 05030
Author(s):  
Liping Ge ◽  
Jinhe Zhou
Keyword(s):  
Equilibrium Solution ◽  
Base Station ◽  
Virtual Network ◽  
Game Model ◽  
Allocation Strategy ◽  
Newton Iterative Method ◽  
Content Acquisition ◽  
Simulation Results ◽  
Cache Allocation ◽  
Cooperative Game Model

To reduce the delay of content acquisition, this paper proposes a game-based cache allocation strategy in the Information-Centric Network (ICN) slice. The cache resource allocation of different mobile virtual network operators (MVNOs) is modeled as a non-cooperative game model. The Newton iterative method is used to solve this problem, and the cache space allocated by the base station for each MVNO is obtained. Finally, the Nash equilibrium solution is obtained. Simulation results show that the proposed algorithm can reduce the delay.

scholarly journals Massive MIMO: Achievable Energy Efficiency for 5G systems with Multi-user Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 6527-6534
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Path Loss ◽  
Antenna System ◽  
Base Station ◽  
Small Cells ◽  
Limiting Factors ◽  
Improve Energy Efficiency ◽  
User Terminal ◽  
Simulation Results

Massive Multi-Input and Multi-Output (MIMO) antenna system potentially provides a promising solution to improve energy efficiency (EE) for 5G wireless systems. The aim of this paper is to enhance EE and its limiting factors are explored. The maximum EE of 48 Mbit/Joule was achieved with 15 user terminal (UT)s. This problem is related to the uplink spectral efficiency with upper bound for future wireless networks. The maximal EE is obtained by optimizing a number of base station (BS) antennas, pilot reuse factor, and BSs density. We presented a power consumption model by deriving Shannon capacity calculations with closed-form expressions. The simulation result highlights the EE maximization with optimizing variables of circuit power consumption, hardware impairments, and path-loss exponent. Small cells achieve high EE and saturate to a constant value with BSs density. The MRC scheme achieves maximum EE of 36 Mbit/Joule with 12 UTs. The simulation results show that peak EE is obtained by deploying massive BS antennas, where the interference and pilot contamination are mitigated by coherent processing. The simulation results were implemented by using MATLAB 2018b.

scholarly journals SoftPSN: Software-Defined Resource Slicing for Low-Latency Reliable Public Safety Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Anteneh A. Gebremariam ◽  
Muhammad Usman ◽  
Riccardo Bassoli ◽  
Fabrizio Granelli
Keyword(s):  
Public Safety ◽  
First Responders ◽  
Base Station ◽  
Low Latency ◽  
Radio Resource ◽  
Life Saving ◽  
Before And After ◽  
Simulation Results ◽  
Emergency Scenarios ◽  
Safety Applications

Achieving the low-latency constraints of public safety applications during disaster could be life-saving. In the context of public safety scenarios, in this paper, we propose an efficient radio resource slicing algorithm that enables first responders to deliver their life-saving activities effectively. We used the tool of stochastic geometry to model the base station distribution before and after a disaster. In addition, under this umbrella, we also proposed an example of public safety scenario, ultrareliable low-latency file sharing, via in-band device-to-device (D2D) communication. The example scenario is implemented in NS-3. The simulation results show that radio resource slicing and prioritization of first responders resources can ensure ultrareliable low-latency communication (URLLC) in emergency scenarios.

Two-Stage Non-Cooperative Game Model for Vertical Handoffs in Heterogeneous Wireless Networks

2021 ◽  
pp. 90-114
Author(s):  
Pramod Kumar Goyal ◽  
Pawan Singh
Keyword(s):  
Game Theory ◽  
Wireless Networks ◽  
Cooperative Game ◽  
Heterogeneous Wireless Networks ◽  
Substantial Reduction ◽  
Game Model ◽  
Two Stage ◽  
Vertical Handoffs ◽  
Cooperative Game Model ◽  
Selection Of

In a heterogeneous wireless network (HWN) environment, performing an efficient vertical handoff requires the efficient qualitative evaluation of all stakeholders like wireless networks (WN) and mobile users (MU) and mutual selection of best WN-MU. In the literature, most of the work deals with both these requirements jointly in the techniques proposed by them for the vertical handoffs (VHO) in HWNs, leaving very little scope to manipulate the above requirements independently. This may result in inefficient vertical handoffs. Hence, this chapter proposed a generalized two-stage two players, iterative non-cooperative game model. This model presents a modular framework that separates the quantitative evaluation of WNs and MUs (at Stage 1) from the game formulation and solution (at Stage 2) for mutual selection of best WN-MU pair for VHO. The simulation results show a substantial reduction in the number of vertical handoffs with the proposed game theory-based two-stage model as compared to a single-stage non-game theory method like multiple attribute decision making.

A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

2020 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Dimitris N. Kanellopoulos ◽  
Pratik Gite
Keyword(s):  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Signal Power ◽  
Aggregated Data ◽  
Simulation Results ◽  
Buffer Length ◽  
Energy Buffer

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH.

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